Showing papers by "University of Minnesota published in 2018"
Clotilde Théry1, Kenneth W. Witwer2, Elena Aikawa3, María José Alcaraz4 +414 more•Institutions (209)
TL;DR: The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV-associated functional activities, and a checklist is provided with summaries of key points.
Abstract: The last decade has seen a sharp increase in the number of scientific publications describing physiological and pathological functions of extracellular vesicles (EVs), a collective term covering various subtypes of cell-released, membranous structures, called exosomes, microvesicles, microparticles, ectosomes, oncosomes, apoptotic bodies, and many other names. However, specific issues arise when working with these entities, whose size and amount often make them difficult to obtain as relatively pure preparations, and to characterize properly. The International Society for Extracellular Vesicles (ISEV) proposed Minimal Information for Studies of Extracellular Vesicles (“MISEV”) guidelines for the field in 2014. We now update these “MISEV2014” guidelines based on evolution of the collective knowledge in the last four years. An important point to consider is that ascribing a specific function to EVs in general, or to subtypes of EVs, requires reporting of specific information beyond mere description of function in a crude, potentially contaminated, and heterogeneous preparation. For example, claims that exosomes are endowed with exquisite and specific activities remain difficult to support experimentally, given our still limited knowledge of their specific molecular machineries of biogenesis and release, as compared with other biophysically similar EVs. The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV-associated functional activities. Finally, a checklist is provided with summaries of key points.
5,988 citations
Centers for Disease Control and Prevention1, University of North Carolina at Chapel Hill2, Vanderbilt University3, University of Arizona4, Rutgers University5, University of Colorado Denver6, Colorado Department of Public Health and Environment7, University of Wisconsin-Madison8, United States Department of Energy9, Johns Hopkins University10, University of Arkansas for Medical Sciences11, Washington University in St. Louis12, University of Minnesota13
TL;DR: This report provides updated ASD prevalence estimates for children aged 8 years during the 2014 surveillance year, on the basis of DSM-IV-TR criteria, and describes characteristics of the population of children with ASD.
Abstract: Problem/condition Autism spectrum disorder (ASD). Period covered 2014. Description of system The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance system that provides estimates of the prevalence of autism spectrum disorder (ASD) among children aged 8 years whose parents or guardians reside within 11 ADDM sites in the United States (Arizona, Arkansas, Colorado, Georgia, Maryland, Minnesota, Missouri, New Jersey, North Carolina, Tennessee, and Wisconsin). ADDM surveillance is conducted in two phases. The first phase involves review and abstraction of comprehensive evaluations that were completed by professional service providers in the community. Staff completing record review and abstraction receive extensive training and supervision and are evaluated according to strict reliability standards to certify effective initial training, identify ongoing training needs, and ensure adherence to the prescribed methodology. Record review and abstraction occurs in a variety of data sources ranging from general pediatric health clinics to specialized programs serving children with developmental disabilities. In addition, most of the ADDM sites also review records for children who have received special education services in public schools. In the second phase of the study, all abstracted information is reviewed systematically by experienced clinicians to determine ASD case status. A child is considered to meet the surveillance case definition for ASD if he or she displays behaviors, as described on one or more comprehensive evaluations completed by community-based professional providers, consistent with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) diagnostic criteria for autistic disorder; pervasive developmental disorder-not otherwise specified (PDD-NOS, including atypical autism); or Asperger disorder. This report provides updated ASD prevalence estimates for children aged 8 years during the 2014 surveillance year, on the basis of DSM-IV-TR criteria, and describes characteristics of the population of children with ASD. In 2013, the American Psychiatric Association published the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), which made considerable changes to ASD diagnostic criteria. The change in ASD diagnostic criteria might influence ADDM ASD prevalence estimates; therefore, most (85%) of the records used to determine prevalence estimates based on DSM-IV-TR criteria underwent additional review under a newly operationalized surveillance case definition for ASD consistent with the DSM-5 diagnostic criteria. Children meeting this new surveillance case definition could qualify on the basis of one or both of the following criteria, as documented in abstracted comprehensive evaluations: 1) behaviors consistent with the DSM-5 diagnostic features; and/or 2) an ASD diagnosis, whether based on DSM-IV-TR or DSM-5 diagnostic criteria. Stratified comparisons of the number of children meeting either of these two case definitions also are reported. Results For 2014, the overall prevalence of ASD among the 11 ADDM sites was 16.8 per 1,000 (one in 59) children aged 8 years. Overall ASD prevalence estimates varied among sites, from 13.1-29.3 per 1,000 children aged 8 years. ASD prevalence estimates also varied by sex and race/ethnicity. Males were four times more likely than females to be identified with ASD. Prevalence estimates were higher for non-Hispanic white (henceforth, white) children compared with non-Hispanic black (henceforth, black) children, and both groups were more likely to be identified with ASD compared with Hispanic children. Among the nine sites with sufficient data on intellectual ability, 31% of children with ASD were classified in the range of intellectual disability (intelligence quotient [IQ] 85). The distribution of intellectual ability varied by sex and race/ethnicity. Although mention of developmental concerns by age 36 months was documented for 85% of children with ASD, only 42% had a comprehensive evaluation on record by age 36 months. The median age of earliest known ASD diagnosis was 52 months and did not differ significantly by sex or race/ethnicity. For the targeted comparison of DSM-IV-TR and DSM-5 results, the number and characteristics of children meeting the newly operationalized DSM-5 case definition for ASD were similar to those meeting the DSM-IV-TR case definition, with DSM-IV-TR case counts exceeding DSM-5 counts by less than 5% and approximately 86% overlap between the two case definitions (kappa = 0.85). Interpretation Findings from the ADDM Network, on the basis of 2014 data reported from 11 sites, provide updated population-based estimates of the prevalence of ASD among children aged 8 years in multiple communities in the United States. The overall ASD prevalence estimate of 16.8 per 1,000 children aged 8 years in 2014 is higher than previously reported estimates from the ADDM Network. Because the ADDM sites do not provide a representative sample of the entire United States, the combined prevalence estimates presented in this report cannot be generalized to all children aged 8 years in the United States. Consistent with reports from previous ADDM surveillance years, findings from 2014 were marked by variation in ASD prevalence when stratified by geographic area, sex, and level of intellectual ability. Differences in prevalence estimates between black and white children have diminished in most sites, but remained notable for Hispanic children. For 2014, results from application of the DSM-IV-TR and DSM-5 case definitions were similar, overall and when stratified by sex, race/ethnicity, DSM-IV-TR diagnostic subtype, or level of intellectual ability. Public health action Beginning with surveillance year 2016, the DSM-5 case definition will serve as the basis for ADDM estimates of ASD prevalence in future surveillance reports. Although the DSM-IV-TR case definition will eventually be phased out, it will be applied in a limited geographic area to offer additional data for comparison. Future analyses will examine trends in the continued use of DSM-IV-TR diagnoses, such as autistic disorder, PDD-NOS, and Asperger disorder in health and education records, documentation of symptoms consistent with DSM-5 terminology, and how these trends might influence estimates of ASD prevalence over time. The latest findings from the ADDM Network provide evidence that the prevalence of ASD is higher than previously reported estimates and continues to vary among certain racial/ethnic groups and communities. With prevalence of ASD ranging from 13.1 to 29.3 per 1,000 children aged 8 years in different communities throughout the United States, the need for behavioral, educational, residential, and occupational services remains high, as does the need for increased research on both genetic and nongenetic risk factors for ASD.
3,967 citations
University of Pennsylvania1, University of Texas Southwestern Medical Center2, University of Oslo3, Boston Children's Hospital4, University of Utah5, Université de Montréal6, Goethe University Frankfurt7, University of Minnesota8, Children's Mercy Hospital9, Emory University10, Ghent University11, Kyoto University12, Stanford University13, Duke University14, Oregon Health & Science University15, University of Michigan16, Medical University of Vienna17, University of Paris18, Royal Children's Hospital19, University of Milan20, University of Toronto21, Novartis22, University of Southern California23
TL;DR: In this global study of CAR T‐cell therapy, a single infusion of tisagenlecleucel provided durable remission with long‐term persistence in pediatric and young adult patients with relapsed or refractory B‐cell ALL, with transient high‐grade toxic effects.
Abstract: Background In a single-center phase 1–2a study, the anti-CD19 chimeric antigen receptor (CAR) T-cell therapy tisagenlecleucel produced high rates of complete remission and was associated with serious but mainly reversible toxic effects in children and young adults with relapsed or refractory B-cell acute lymphoblastic leukemia (ALL) Methods We conducted a phase 2, single-cohort, 25-center, global study of tisagenlecleucel in pediatric and young adult patients with CD19+ relapsed or refractory B-cell ALL The primary end point was the overall remission rate (the rate of complete remission or complete remission with incomplete hematologic recovery) within 3 months Results For this planned analysis, 75 patients received an infusion of tisagenlecleucel and could be evaluated for efficacy The overall remission rate within 3 months was 81%, with all patients who had a response to treatment found to be negative for minimal residual disease, as assessed by means of flow cytometry The rates of event-f
3,237 citations
TL;DR: This annotated reference sequence of wheat is a resource that can now drive disruptive innovation in wheat improvement, as this community resource establishes the foundation for accelerating wheat research and application through improved understanding of wheat biology and genomics-assisted breeding.
Abstract: An annotated reference sequence representing the hexaploid bread wheat genome in 21 pseudomolecules has been analyzed to identify the distribution and genomic context of coding and noncoding elements across the A, B, and D subgenomes. With an estimated coverage of 94% of the genome and containing 107,891 high-confidence gene models, this assembly enabled the discovery of tissue- and developmental stage-related coexpression networks by providing a transcriptome atlas representing major stages of wheat development. Dynamics of complex gene families involved in environmental adaptation and end-use quality were revealed at subgenome resolution and contextualized to known agronomic single-gene or quantitative trait loci. This community resource establishes the foundation for accelerating wheat research and application through improved understanding of wheat biology and genomics-assisted breeding.
2,118 citations
TL;DR: The state of the art in the area of Industry 4.0 as it relates to industries is surveyed, with a focus on China's Made-in-China 2025 and formal methods and systems methods crucial for realising Industry 5.0.
Abstract: Rapid advances in industrialisation and informatisation methods have spurred tremendous progress in developing the next generation of manufacturing technology. Today, we are on the cusp of the Fourth Industrial Revolution. In 2013, amongst one of 10 ‘Future Projects’ identified by the German government as part of its High-Tech Strategy 2020 Action Plan, the Industry 4.0 project is considered to be a major endeavour for Germany to establish itself as a leader of integrated industry. In 2014, China’s State Council unveiled their ten-year national plan, Made-in-China 2025, which was designed to transform China from the world’s workshop into a world manufacturing power. Made-in-China 2025 is an initiative to comprehensively upgrade China’s industry including the manufacturing sector. In Industry 4.0 and Made-in-China 2025, many applications require a combination of recently emerging new technologies, which is giving rise to the emergence of Industry 4.0. Such technologies originate from different disciplines ...
1,780 citations
University of Minnesota1, University of Colorado Boulder2, VU University Amsterdam3, Harvard University4, University of Southern California5, University of Queensland6, University of Tartu7, Erasmus University Rotterdam8, Hospital for Special Surgery9, Statens Serum Institut10, University of Copenhagen11, Broad Institute12, University of Essex13, University of Edinburgh14, University of Cambridge15, University Hospital of Lausanne16, Geisinger Health System17, Wenzhou Medical College18, Stanford University19, University of North Carolina at Chapel Hill20, University of Wisconsin-Madison21, Hofstra University22, The Feinstein Institute for Medical Research23, University of Dundee24, University of Toronto25, Princeton University26, National Bureau of Economic Research27, Queen's University28, New York University Shanghai29, Karolinska Institutet30, Uppsala University31, University of Lausanne32, New York University33, Stockholm School of Economics34
TL;DR: A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11–13% of the variance ineducational attainment and 7–10% ofthe variance in cognitive performance, which substantially increases the utility ofpolygenic scores as tools in research.
Abstract: Here we conducted a large-scale genetic association analysis of educational attainment in a sample of approximately 1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of around 0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11-13% of the variance in educational attainment and 7-10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research.
1,658 citations
TL;DR: This analysis expands upon previous analyses by working under the hypothesis that both bodies were neutron stars that are described by the same equation of state and have spins within the range observed in Galactic binary neutron stars.
Abstract: On 17 August 2017, the LIGO and Virgo observatories made the first direct detection of gravitational waves from the coalescence of a neutron star binary system. The detection of this gravitational-wave signal, GW170817, offers a novel opportunity to directly probe the properties of matter at the extreme conditions found in the interior of these stars. The initial, minimal-assumption analysis of the LIGO and Virgo data placed constraints on the tidal effects of the coalescing bodies, which were then translated to constraints on neutron star radii. Here, we expand upon previous analyses by working under the hypothesis that both bodies were neutron stars that are described by the same equation of state and have spins within the range observed in Galactic binary neutron stars. Our analysis employs two methods: the use of equation-of-state-insensitive relations between various macroscopic properties of the neutron stars and the use of an efficient parametrization of the defining function pðρÞ of the equation of state itself. From the LIGO and Virgo data alone and the first method, we measure the two neutron star radii as R1 ¼ 10.8 þ2.0 −1.7 km for the heavier star and R2 ¼ 10.7 þ2.1 −1.5 km for the lighter star at the 90% credible level. If we additionally require that the equation of state supports neutron stars with masses larger than 1.97 M⊙ as required from electromagnetic observations and employ the equation-of-state parametrization, we further constrain R1 ¼ 11.9 þ1.4 −1.4 km and R2 ¼ 11.9 þ1.4 −1.4 km at the 90% credible level. Finally, we obtain constraints on pðρÞ at supranuclear densities, with pressure at twice nuclear saturation density measured at 3.5 þ2.7 −1.7 × 1034 dyn cm−2 at the 90% level.
1,595 citations
University of Oxford1, University of Minnesota2, International Food Policy Research Institute3, Commonwealth Scientific and Industrial Research Organisation4, Potsdam Institute for Climate Impact Research5, Technical University of Madrid6, Wageningen University and Research Centre7, Chatham House8, Stockholm Resilience Centre9, Royal Swedish Academy of Sciences10, Bioversity International11, American University of Beirut12, Johns Hopkins University13, University of California, Santa Barbara14, Harvard University15
TL;DR: A global model finds that the environmental impacts of the food system could increase by 60–90% by 2050, and that dietary changes, improvements in technologies and management, and reductions in food loss and waste will all be needed to mitigate these impacts.
Abstract: The food system is a major driver of climate change, changes in land use, depletion of freshwater resources, and pollution of aquatic and terrestrial ecosystems through excessive nitrogen and phosphorus inputs. Here we show that between 2010 and 2050, as a result of expected changes in population and income levels, the environmental effects of the food system could increase by 50–90% in the absence of technological changes and dedicated mitigation measures, reaching levels that are beyond the planetary boundaries that define a safe operating space for humanity. We analyse several options for reducing the environmental effects of the food system, including dietary changes towards healthier, more plant-based diets, improvements in technologies and management, and reductions in food loss and waste. We find that no single measure is enough to keep these effects within all planetary boundaries simultaneously, and that a synergistic combination of measures will be needed to sufficiently mitigate the projected increase in environmental pressures.
1,521 citations
Health Canada1, United States Environmental Protection Agency2, Brigham Young University3, University of Texas at Austin4, University of British Columbia5, Health Effects Institute6, McGill University7, University of Minnesota8, Harvard University9, Utrecht University10, University of Washington11, Fudan University12, New York University13, University of California, Los Angeles14, University of Ottawa15, American Cancer Society16, University of California, Davis17, Cancer Prevention Institute of California18, University of New Brunswick19, Dalhousie University20, Carleton University21, Statistics Canada22, University of Toronto23, Chinese Center for Disease Control and Prevention24, St George's, University of London25, University of Hong Kong26, University of Ulm27, SERC Reliability Corporation28
TL;DR: PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.
Abstract: Exposure to ambient fine particulate matter (PM2.5) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that incorporate risk information from multiple PM2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM2.5-mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries-the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million [95% confidence interval (CI): 7.5-10.3] deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9-8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3-4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.
1,283 citations
TL;DR: In insights into the role of alcohol consumption in the genetic architecture of hypertension, a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions is conducted.
Abstract: Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.
1,218 citations
TL;DR: A tool is proposed to evaluate the methodological quality of case reports and case series based on the domains of selection, ascertainment, causality and reporting and signalling questions to aid evidence-based practitioners and systematic reviewers in their assessment.
Abstract: Case reports and case series are uncontrolled study designs known for increased risk of bias but have profoundly influenced the medical literature and continue to advance our knowledge. In this guide, we present a framework for appraisal, synthesis and application of evidence derived from case reports and case series. We propose a tool to evaluate the methodological quality of case reports and case series based on the domains of selection, ascertainment, causality and reporting and provide signalling questions to aid evidence-based practitioners and systematic reviewers in their assessment. We suggest using evidence derived from case reports and case series to inform decision-making when no other higher level of evidence is available.
University of Virginia1, Louisiana State University2, University of Minnesota3, Emory University4, University of Pennsylvania5, Fred Hutchinson Cancer Research Center6, Durham University7, University of Texas MD Anderson Cancer Center8, University of California, San Francisco9, American Cancer Society10
TL;DR: This guideline update used an existing systematic evidence review of the CRC screening literature and microsimulation modeling analyses, including a new evaluation of the age to begin screening by race and sex and additional modeling that incorporates changes in US CRC incidence.
Abstract: In the United States, colorectal cancer (CRC) is the fourth most common cancer diagnosed among adults and the second leading cause of death from cancer. For this guideline update, the American Cancer Society (ACS) used an existing systematic evidence review of the CRC screening literature and microsimulation modeling analyses, including a new evaluation of the age to begin screening by race and sex and additional modeling that incorporates changes in US CRC incidence. Screening with any one of multiple options is associated with a significant reduction in CRC incidence through the detection and removal of adenomatous polyps and other precancerous lesions and with a reduction in mortality through incidence reduction and early detection of CRC. Results from modeling analyses identified efficient and model-recommendable strategies that started screening at age 45 years. The ACS Guideline Development Group applied the Grades of Recommendations, Assessment, Development, and Evaluation (GRADE) criteria in developing and rating the recommendations. The ACS recommends that adults aged 45 years and older with an average risk of CRC undergo regular screening with either a high-sensitivity stool-based test or a structural (visual) examination, depending on patient preference and test availability. As a part of the screening process, all positive results on noncolonoscopy screening tests should be followed up with timely colonoscopy. The recommendation to begin screening at age 45 years is a qualified recommendation. The recommendation for regular screening in adults aged 50 years and older is a strong recommendation. The ACS recommends (qualified recommendations) that: 1) average-risk adults in good health with a life expectancy of more than 10 years continue CRC screening through the age of 75 years; 2) clinicians individualize CRC screening decisions for individuals aged 76 through 85 years based on patient preferences, life expectancy, health status, and prior screening history; and 3) clinicians discourage individuals older than 85 years from continuing CRC screening. The options for CRC screening are: fecal immunochemical test annually; high-sensitivity, guaiac-based fecal occult blood test annually; multitarget stool DNA test every 3 years; colonoscopy every 10 years; computed tomography colonography every 5 years; and flexible sigmoidoscopy every 5 years. CA Cancer J Clin 2018;68:250-281. © 2018 American Cancer Society.
University of Oxford1, University of Michigan2, Wellcome Trust Sanger Institute3, Amgen4, University of Cambridge5, University of Copenhagen6, University of Liverpool7, University of Freiburg8, Boston University9, University of Tartu10, Erasmus University Medical Center11, Leiden University Medical Center12, Pasteur Institute13, Icahn School of Medicine at Mount Sinai14, UCLA Medical Center15, Vanderbilt University Medical Center16, Wake Forest University17, National University of Singapore18, London North West Healthcare NHS Trust19, Imperial College London20, Charité21, Innsbruck Medical University22, Washington University in St. Louis23, Queen Mary University of London24, University of Southern Denmark25, National and Kapodistrian University of Athens26, Robertson Centre for Biostatistics27, University of Exeter28, Uppsala University29, University of Düsseldorf30, Steno Diabetes Center31, Aalborg University32, University of Eastern Finland33, Broad Institute34, Frederiksberg Hospital35, University of Bergen36, Lund University37, Technische Universität München38, University of North Carolina at Chapel Hill39, University of Edinburgh40, Ninewells Hospital41, University of Minnesota42, University of Glasgow43, Ludwig Maximilian University of Munich44, University of Iceland45, Aarhus University46, Science for Life Laboratory47, Stanford University48, University of Helsinki49, National Institutes of Health50, University of Dundee51, Harvard University52
TL;DR: Combining 32 genome-wide association studies with high-density imputation provides a comprehensive view of the genetic contribution to type 2 diabetes in individuals of European ancestry with respect to locus discovery, causal-variant resolution, and mechanistic insight.
Abstract: We expanded GWAS discovery for type 2 diabetes (T2D) by combining data from 898,130 European-descent individuals (9% cases), after imputation to high-density reference panels. With these data, we (i) extend the inventory of T2D-risk variants (243 loci, 135 newly implicated in T2D predisposition, comprising 403 distinct association signals); (ii) enrich discovery of lower-frequency risk alleles (80 index variants with minor allele frequency 2); (iii) substantially improve fine-mapping of causal variants (at 51 signals, one variant accounted for >80% posterior probability of association (PPA)); (iv) extend fine-mapping through integration of tissue-specific epigenomic information (islet regulatory annotations extend the number of variants with PPA >80% to 73); (v) highlight validated therapeutic targets (18 genes with associations attributable to coding variants); and (vi) demonstrate enhanced potential for clinical translation (genome-wide chip heritability explains 18% of T2D risk; individuals in the extremes of a T2D polygenic risk score differ more than ninefold in prevalence).
Yale University1, Cornell University2, Washington University in St. Louis3, University of Michigan4, University of Vermont5, University of Colorado Boulder6, Florida International University7, Virginia Commonwealth University8, University of Minnesota9, University of California, San Diego10, Harvard University11
TL;DR: An overview of the imaging procedures of the ABCD study is provided, the basis for their selection and preliminary quality assurance and results that provide evidence for the feasibility and age-appropriateness of procedures and generalizability of findings to the existent literature are provided.
University of British Columbia1, University of Toronto2, University of Michigan3, University of Minnesota4, McMaster University5, University of Western Ontario6, McGill University7, Dalhousie University8, University of Calgary9, Queen's University10, Kyushu University11, University of São Paulo12, Stanford University13, Case Western Reserve University14, University of Barcelona15, University of Sydney16, George Washington University17, Deakin University18
TL;DR: These 2018 CANMAT and ISBD Bipolar Treatment Guidelines represent the significant advances in the field since the last full edition was published in 2005, including updates to diagnosis and management as well as new research into pharmacological and psychological treatments.
Abstract: The Canadian Network for Mood and Anxiety Treatments (CANMAT) previously published treatment guidelines for bipolar disorder in 2005, along with international commentaries and subsequent updates in 2007, 2009, and 2013. The last two updates were published in collaboration with the International Society for Bipolar Disorders (ISBD). These 2018 CANMAT and ISBD Bipolar Treatment Guidelines represent the significant advances in the field since the last full edition was published in 2005, including updates to diagnosis and management as well as new research into pharmacological and psychological treatments. These advances have been translated into clear and easy to use recommendations for first, second, and third- line treatments, with consideration given to levels of evidence for efficacy, clinical support based on experience, and consensus ratings of safety, tolerability, and treatment-emergent switch risk. New to these guidelines, hierarchical rankings were created for first and second- line treatments recommended for acute mania, acute depression, and maintenance treatment in bipolar I disorder. Created by considering the impact of each treatment across all phases of illness, this hierarchy will further assist clinicians in making evidence-based treatment decisions. Lithium, quetiapine, divalproex, asenapine, aripiprazole, paliperidone, risperidone, and cariprazine alone or in combination are recommended as first-line treatments for acute mania. First-line options for bipolar I depression include quetiapine, lurasidone plus lithium or divalproex, lithium, lamotrigine, lurasidone, or adjunctive lamotrigine. While medications that have been shown to be effective for the acute phase should generally be continued for the maintenance phase in bipolar I disorder, there are some exceptions (such as with antidepressants); and available data suggest that lithium, quetiapine, divalproex, lamotrigine, asenapine, and aripiprazole monotherapy or combination treatments should be considered first-line for those initiating or switching treatment during the maintenance phase. In addition to addressing issues in bipolar I disorder, these guidelines also provide an overview of, and recommendations for, clinical management of bipolar II disorder, as well as advice on specific populations, such as women at various stages of the reproductive cycle, children and adolescents, and older adults. There are also discussions on the impact of specific psychiatric and medical comorbidities such as substance use, anxiety, and metabolic disorders. Finally, an overview of issues related to safety and monitoring is provided. The CANMAT and ISBD groups hope that these guidelines become a valuable tool for practitioners across the globe.
Northern Arizona University1, University of Minnesota2, University of California, Davis3, Woods Hole Oceanographic Institution4, Massachusetts Institute of Technology5, University of Copenhagen6, University of Trento7, Chinese Academy of Sciences8, University of California, San Francisco9, Children's Hospital of Philadelphia10, Pacific Northwest National Laboratory11, North Carolina State University12, University of Montana13, Dalhousie University14, University of British Columbia15, Shedd Aquarium16, University of Colorado Denver17, University of California, San Diego18, Michigan State University19, Stanford University20, Harvard University21, Broad Institute22, Australian National University23, University of Düsseldorf24, Sookmyung Women's University25, San Diego State University26, Howard Hughes Medical Institute27, Cornell University28, Max Planck Society29, University of Washington30, Colorado State University31, Google32, Syracuse University33, Webster University34, United States Department of Agriculture35, University of Arkansas for Medical Sciences36, Colorado School of Mines37, University of Southern Mississippi38, Atlantic Oceanographic and Meteorological Laboratory39, University of California, Merced40, Wageningen University and Research Centre41, University of Arizona42, Environment Agency43, University of Florida44, Merck & Co.45
TL;DR: QIIME 2 provides new features that will drive the next generation of microbiome research, including interactive spatial and temporal analysis and visualization tools, support for metabolomics and shotgun metagenomics analysis, and automated data provenance tracking to ensure reproducible, transparent microbiome data science.
Abstract: We present QIIME 2, an open-source microbiome data science platform accessible to users spanning the microbiome research ecosystem, from scientists and engineers to clinicians and policy makers. QIIME 2 provides new features that will drive the next generation of microbiome research. These include interactive spatial and temporal analysis and visualization tools, support for metabolomics and shotgun metagenomics analysis, and automated data provenance tracking to ensure reproducible, transparent microbiome data science.
TL;DR: In this article, the authors present possible observing scenarios for the Advanced LIGO, Advanced Virgo and KAGRA gravitational-wave detectors over the next decade, with the intention of providing information to the astronomy community to facilitate planning for multi-messenger astronomy with gravitational waves.
Abstract: We present possible observing scenarios for the Advanced LIGO, Advanced Virgo and KAGRA gravitational-wave detectors over the next decade, with the intention of providing information to the astronomy community to facilitate planning for multi-messenger astronomy with gravitational waves. We estimate the sensitivity of the network to transient gravitational-wave signals, and study the capability of the network to determine the sky location of the source. We report our findings for gravitational-wave transients, with particular focus on gravitational-wave signals from the inspiral of binary neutron star systems, which are the most promising targets for multi-messenger astronomy. The ability to localize the sources of the detected signals depends on the geographical distribution of the detectors and their relative sensitivity, and 90% credible regions can be as large as thousands of square degrees when only two sensitive detectors are operational. Determining the sky position of a significant fraction of detected signals to areas of 5– 20 deg2 requires at least three detectors of sensitivity within a factor of ∼2 of each other and with a broad frequency bandwidth. When all detectors, including KAGRA and the third LIGO detector in India, reach design sensitivity, a significant fraction of gravitational-wave signals will be localized to a few square degrees by gravitational-wave observations alone.
VU University Amsterdam1, Erasmus University Rotterdam2, Karolinska Institutet3, Charité4, Virginia Commonwealth University5, South London and Maudsley NHS Foundation Trust6, QIMR Berghofer Medical Research Institute7, King's College London8, University of Southern Denmark9, University of California, Riverside10, University of Southern California11, University of Minnesota12, University of Queensland13, University College London14, Johns Hopkins University15, University of California, Los Angeles16, University of Crete17, Veterans Health Administration18, Icahn School of Medicine at Mount Sinai19, Harvard University20, Yale University21, Haukeland University Hospital22, Trinity College, Dublin23, University of Edinburgh24, Hofstra University25, North Shore-LIJ Health System26, National Institutes of Health27, Oslo University Hospital28, University of Bergen29, National University of Ireland, Galway30, University of Helsinki31, University of Oslo32, Martin Luther University of Halle-Wittenberg33, Duke University34, Mental Health Research Institute35, National and Kapodistrian University of Athens36, University of Colorado Boulder37, Imperial College London38, University of Manchester39, Wellcome Trust40, Manchester Academic Health Science Centre41, Stanford University42, University of Oregon43, University of Toronto44, University of Michigan45, Erasmus University Medical Center46, Broad Institute47, University of North Carolina at Chapel Hill48
TL;DR: A large-scale genetic association study of intelligence identifies 190 new loci and implicates 939 new genes related to neurogenesis, neuron differentiation and synaptic structure, a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.
Abstract: Intelligence is highly heritable1 and a major determinant of human health and well-being2. Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence3-7, but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.
TL;DR: This review describes recent progress in deciphering the mechanisms controlling ion homeostasis, cell activity responses, and epigenetic regulation in plants under salt stress and highlights research areas that require further research to reveal new determinants of salt tolerance in plants.
Abstract: Contents Summary 523 I. Introduction 523 II. Sensing salt stress 524 III. Ion homeostasis regulation 524 IV. Metabolite and cell activity responses to salt stress 527 V. Conclusions and perspectives 532 Acknowledgements 533 References 533 SUMMARY: Excess soluble salts in soil (saline soils) are harmful to most plants. Salt imposes osmotic, ionic, and secondary stresses on plants. Over the past two decades, many determinants of salt tolerance and their regulatory mechanisms have been identified and characterized using molecular genetics and genomics approaches. This review describes recent progress in deciphering the mechanisms controlling ion homeostasis, cell activity responses, and epigenetic regulation in plants under salt stress. Finally, we highlight research areas that require further research to reveal new determinants of salt tolerance in plants.
TL;DR: Treatment with opioids was not superior to treatment with nonopioid medications for improving pain-related function over 12 months and results do not support initiation of opioid therapy for moderate to severe chronic back pain or hip or knee osteoarthritis pain.
Abstract: Importance Limited evidence is available regarding long-term outcomes of opioids compared with nonopioid medications for chronic pain. Objective To compare opioid vs nonopioid medications over 12 months on pain-related function, pain intensity, and adverse effects. Design, Setting, and Participants Pragmatic, 12-month, randomized trial with masked outcome assessment. Patients were recruited from Veterans Affairs primary care clinics from June 2013 through December 2015; follow-up was completed December 2016. Eligible patients had moderate to severe chronic back pain or hip or knee osteoarthritis pain despite analgesic use. Of 265 patients enrolled, 25 withdrew prior to randomization and 240 were randomized. Interventions Both interventions (opioid and nonopioid medication therapy) followed a treat-to-target strategy aiming for improved pain and function. Each intervention had its own prescribing strategy that included multiple medication options in 3 steps. In the opioid group, the first step was immediate-release morphine, oxycodone, or hydrocodone/acetaminophen. For the nonopioid group, the first step was acetaminophen (paracetamol) or a nonsteroidal anti-inflammatory drug. Medications were changed, added, or adjusted within the assigned treatment group according to individual patient response. Main Outcomes and Measures The primary outcome was pain-related function (Brief Pain Inventory [BPI] interference scale) over 12 months and the main secondary outcome was pain intensity (BPI severity scale). For both BPI scales (range, 0-10; higher scores = worse function or pain intensity), a 1-point improvement was clinically important. The primary adverse outcome was medication-related symptoms (patient-reported checklist; range, 0-19). Results Among 240 randomized patients (mean age, 58.3 years; women, 32 [13.0%]), 234 (97.5%) completed the trial. Groups did not significantly differ on pain-related function over 12 months (overallP = .58); mean 12-month BPI interference was 3.4 for the opioid group and 3.3 for the nonopioid group (difference, 0.1 [95% CI, −0.5 to 0.7]). Pain intensity was significantly better in the nonopioid group over 12 months (overallP = .03); mean 12-month BPI severity was 4.0 for the opioid group and 3.5 for the nonopioid group (difference, 0.5 [95% CI, 0.0 to 1.0]). Adverse medication-related symptoms were significantly more common in the opioid group over 12 months (overallP = .03); mean medication-related symptoms at 12 months were 1.8 in the opioid group and 0.9 in the nonopioid group (difference, 0.9 [95% CI, 0.3 to 1.5]). Conclusions and Relevance Treatment with opioids was not superior to treatment with nonopioid medications for improving pain-related function over 12 months. Results do not support initiation of opioid therapy for moderate to severe chronic back pain or hip or knee osteoarthritis pain. Trial Registration clinicaltrials.gov Identifier:NCT01583985
TL;DR: There was an increase in the total number both of surgical and endoluminal bariatric/metabolic procedures performed worldwide in 2016 and the surgical trends from 2008 to 2016.
Abstract: Background and aim The International Federation for the Surgery of Obesity and Metabolic Disorders (IFSO), being a Federation of 62 national societies, is the ideal network to monitor the number and type of procedures at a global level. The IFSO survey, enriched with a special section on revisional procedures, aims to report the number and types of bariatric procedures performed worldwide in 2016 and analyzes the surgical trends from 2008 to 2016. Methods The 2016 IFSO Survey form was emailed to all IFSO societies. Each Society was requested to indicate the number and type of bariatric procedures performed in the country. Trend analyses from 2008 to 2016 were also performed. Results The total number of bariatric/metabolic procedures performed in 2016 was 685,874; 634,897 (92.6%) of which were primary and 50,977 were revisional (7.4%). Among the primary interventions, 609,897 (96%) were surgical and 25,359 (4%) were endoluminal. The most performed primary surgical bariatric/metabolic procedure was sleeve gastrectomy (SG) (N = 340,550; 53.6%), followed by Roux-en-Y gastric bypass (N = 191,326; 30.1%), and one-anastomosis gastric bypass (N = 30,563; 4.8%). Conclusions In 2016, there was an increase in the total number both of surgical and endoluminal bariatric/metabolic procedures. Revisional procedures represent about 7% of the total bariatric interventions. SG remains the most performed surgical procedure in the world.
Harvard University1, Broad Institute2, VU University Amsterdam3, University of Minnesota4, Hospital for Special Surgery5, University of Southern California6, University of Colorado Boulder7, Karolinska Institutet8, Uppsala University9, Stockholm School of Economics10, University of Queensland11, National Bureau of Economic Research12, New York University13, Research Institute of Industrial Economics14
TL;DR: Applying MTAG to summary statistics for depressive symptoms, neuroticism and subjective well-being increased discovery of associated loci as compared to single-trait analyses, yielding more informative bioinformatics analyses and increasing the variance explained by polygenic scores by approximately 25%, matching theoretical expectations.
Abstract: We introduce multi-trait analysis of GWAS (MTAG), a method for joint analysis of summary statistics from genome-wide association studies (GWAS) of different traits, possibly from overlapping samples. We apply MTAG to summary statistics for depressive symptoms (N eff = 354,862), neuroticism (N = 168,105), and subjective well-being (N = 388,538). As compared to the 32, 9, and 13 genome-wide significant loci identified in the single-trait GWAS (most of which are themselves novel), MTAG increases the number of associated loci to 64, 37, and 49, respectively. Moreover, association statistics from MTAG yield more informative bioinformatics analyses and increase the variance explained by polygenic scores by approximately 25%, matching theoretical expectations.
Vrije Universiteit Brussel1, University of Copenhagen2, University of Gothenburg3, New York University4, University of Pennsylvania5, University of Helsinki6, Wageningen University and Research Centre7, Institut national de la recherche agronomique8, King's College London9, University of Maryland, Baltimore10, Waseda University11, Harvard University12, University College Cork13, University of Minnesota14, University of Texas at Austin15, University of Warwick16, Veterans Health Administration17, Stanford University18, ETH Zurich19, Shanghai Jiao Tong University20, Katholieke Universiteit Leuven21, Molecular Medicine Partnership Unit22, Max Delbrück Center for Molecular Medicine23
TL;DR: The concept of enterotypes and their use to characterize the gut microbiome are debated, a classifier and standardized methodology is provided to aid cross-study comparisons, and a balanced application of the concept is encouraged.
Abstract: Population stratification is a useful approach for a better understanding of complex biological problems in human health and wellbeing. The proposal that such stratification applies to the human gut microbiome, in the form of distinct community composition types termed enterotypes, has been met with both excitement and controversy. In view of accumulated data and re-analyses since the original work, we revisit the concept of enterotypes, discuss different methods of dividing up the landscape of possible microbiome configurations, and put these concepts into functional, ecological and medical contexts. As enterotypes are of use in describing the gut microbial community landscape and may become relevant in clinical practice, we aim to reconcile differing views and encourage a balanced application of the concept.
TL;DR: This work first characterize a class of ‘learnable algorithms’ and then design DNNs to approximate some algorithms of interest in wireless communications, demonstrating the superior ability ofDNNs for approximating two considerably complex algorithms that are designed for power allocation in wireless transmit signal design, while giving orders of magnitude speedup in computational time.
Abstract: Numerical optimization has played a central role in addressing key signal processing (SP) problems Highly effective methods have been developed for a large variety of SP applications such as communications, radar, filter design, and speech and image analytics, just to name a few However, optimization algorithms often entail considerable complexity, which creates a serious gap between theoretical design/analysis and real-time processing In this paper, we aim at providing a new learning-based perspective to address this challenging issue The key idea is to treat the input and output of an SP algorithm as an unknown nonlinear mapping and use a deep neural network (DNN) to approximate it If the nonlinear mapping can be learned accurately by a DNN of moderate size, then SP tasks can be performed effectively—since passing the input through a DNN only requires a small number of simple operations In our paper, we first identify a class of optimization algorithms that can be accurately approximated by a fully connected DNN Second, to demonstrate the effectiveness of the proposed approach, we apply it to approximate a popular interference management algorithm, namely, the WMMSE algorithm Extensive experiments using both synthetically generated wireless channel data and real DSL channel data have been conducted It is shown that, in practice, only a small network is sufficient to obtain high approximation accuracy, and DNNs can achieve orders of magnitude speedup in computational time compared to the state-of-the-art interference management algorithm
TL;DR: Based on consumer guidelines, the results indicate the average person ingests over 5,800 particles of synthetic debris from these three sources annually, with the largest contribution coming from tap water (88%).
Abstract: Plastic pollution has been well documented in natural environments, including the open waters and sediments within lakes and rivers, the open ocean and even the air, but less attention has been paid to synthetic polymers in human consumables. Since multiple toxicity studies indicate risks to human health when plastic particles are ingested, more needs to be known about the presence and abundance of anthropogenic particles in human foods and beverages. This study investigates the presence of anthropogenic particles in 159 samples of globally sourced tap water, 12 brands of Laurentian Great Lakes beer, and 12 brands of commercial sea salt. Of the tap water samples analyzed, 81% were found to contain anthropogenic particles. The majority of these particles were fibers (98.3%) between 0.1-5 mm in length. The range was 0 to 61 particles/L, with an overall mean of 5.45 particles/L. Anthropogenic debris was found in each brand of beer and salt. Of the extracted particles, over 99% were fibers. After adjusting for particles found in lab blanks for both salt and beer, the average number of particles found in beer was 4.05 particles/L with a range of 0 to 14.3 particles/L and the average number of particles found in each brand of salt was 212 particles/kg with a range of 46.7 to 806 particles/kg. Based on consumer guidelines, our results indicate the average person ingests over 5,800 particles of synthetic debris from these three sources annually, with the largest contribution coming from tap water (88%).
TL;DR: This research presents a novel probabilistic approach to estimating the response of the immune system to laser-spot assisted, 3D image analysis of central nervous system injury.
Abstract: Powdery mildew is a widespread plant disease caused by obligate biotrophic fungal pathogens involving species-specific interactions between host and parasite. To gain genomic insights into the underlying obligate biotrophic mechanisms, we analyzed 15 microbial genomes covering powdery and downy mildews and rust. We observed a genome-wide, massive contraction of multiple gene families in powdery mildews, such as enzymes in the carbohydrate metabolism pathway, when compared with ascomycete phytopathogens, while the fatty acid metabolism pathway maintained its integrity. We also observed significant differences in Candidate Secreted Effector Protein (CSEP) families between monocot-parasitic and dicot-parasitic powdery mildews, perhaps due to different selection forces. While CSEPs in monocot mildews are likely subject to positive selection causing rapid expansion, CSEP families in dicot mildews are shrinking under strong purifying selection. Our results not only illustrate obligate biotrophic mechanisms of powdery mildews driven by gene family evolution in nutrient metabolism, but also demonstrate how the divergence of CSEPs between monocot and dicot lineages might contribute to species-specific adaption.
TL;DR: This work has identified a CAR containing the transmembrane domain of NKG2D, the 2B4 co-stimulatory domain, and the CD3ζ signaling domain to mediate strong antigen-specific NK cell signaling that provides standardized, targeted "off-the-shelf" lymphocytes for anti-cancer immunotherapy.
TL;DR: For the first time, specific loci that distinguish between BD and SCZ are discovered and polygenic components underlying multiple symptom dimensions are identified that point to the utility of genetics to inform symptomology and potential treatment.
TL;DR: In this paper, the authors train deep convolutional neural networks to identify, count, and describe the behaviors of 48 species in the 3.2 million-image Snapshot Serengeti dataset.
Abstract: Having accurate, detailed, and up-to-date information about the location and behavior of animals in the wild would improve our ability to study and conserve ecosystems. We investigate the ability to automatically, accurately, and inexpensively collect such data, which could help catalyze the transformation of many fields of ecology, wildlife biology, zoology, conservation biology, and animal behavior into “big data” sciences. Motion-sensor “camera traps” enable collecting wildlife pictures inexpensively, unobtrusively, and frequently. However, extracting information from these pictures remains an expensive, time-consuming, manual task. We demonstrate that such information can be automatically extracted by deep learning, a cutting-edge type of artificial intelligence. We train deep convolutional neural networks to identify, count, and describe the behaviors of 48 species in the 3.2 million-image Snapshot Serengeti dataset. Our deep neural networks automatically identify animals with >93.8% accuracy, and we expect that number to improve rapidly in years to come. More importantly, if our system classifies only images it is confident about, our system can automate animal identification for 99.3% of the data while still performing at the same 96.6% accuracy as that of crowdsourced teams of human volunteers, saving >8.4 y (i.e., >17,000 h at 40 h/wk) of human labeling effort on this 3.2 million-image dataset. Those efficiency gains highlight the importance of using deep neural networks to automate data extraction from camera-trap images, reducing a roadblock for this widely used technology. Our results suggest that deep learning could enable the inexpensive, unobtrusive, high-volume, and even real-time collection of a wealth of information about vast numbers of animals in the wild.
University of California, San Diego1, University of Montana2, San Diego State University3, North Carolina State University4, University of Oregon5, University of Queensland6, Harvard University7, Broad Institute8, King's College London9, University of Minnesota10, University of California, San Francisco11, Saint Petersburg State University12, Colorado State University13, Carnegie Mellon University14, University of Nantes15, University of Pittsburgh16, University of Colorado Boulder17, Argonne National Laboratory18, University of Southern Mississippi19, Atlantic Oceanographic and Meteorological Laboratory20, Duke University21
TL;DR: The utility of the living data resource and cross-cohort comparison is demonstrated to confirm existing associations between the microbiome and psychiatric illness and to reveal the extent of microbiome change within one individual during surgery, providing a paradigm for open microbiome research and education.
Abstract: Although much work has linked the human microbiome to specific phenotypes and lifestyle variables, data from different projects have been challenging to integrate and the extent of microbial and molecular diversity in human stool remains unknown. Using standardized protocols from the Earth Microbiome Project and sample contributions from over 10,000 citizen-scientists, together with an open research network, we compare human microbiome specimens primarily from the United States, United Kingdom, and Australia to one another and to environmental samples. Our results show an unexpected range of beta-diversity in human stool microbiomes compared to environmental samples; demonstrate the utility of procedures for removing the effects of overgrowth during room-temperature shipping for revealing phenotype correlations; uncover new molecules and kinds of molecular communities in the human stool metabolome; and examine emergent associations among the microbiome, metabolome, and the diversity of plants that are consumed (rather than relying on reductive categorical variables such as veganism, which have little or no explanatory power). We also demonstrate the utility of the living data resource and cross-cohort comparison to confirm existing associations between the microbiome and psychiatric illness and to reveal the extent of microbiome change within one individual during surgery, providing a paradigm for open microbiome research and education. IMPORTANCE We show that a citizen science, self-selected cohort shipping samples through the mail at room temperature recaptures many known microbiome results from clinically collected cohorts and reveals new ones. Of particular interest is integrating n = 1 study data with the population data, showing that the extent of microbiome change after events such as surgery can exceed differences between distinct environmental biomes, and the effect of diverse plants in the diet, which we confirm with untargeted metabolomics on hundreds of samples.