DNA-binding by Haemophilus influenzae and Escherichia coli YbaB, members of a widely-distributed bacterial protein family

BACKGROUND: Genes orthologous to the ybaB loci of Escherichia coli and Haemophilus influenzae are widely distributed among eubacteria. Several years ago, the three-dimensional structures of the YbaB orthologs of both E. coli and H. influenzae were determined, revealing a novel tweezer -like structure. However, a function for YbaB had remained elusive, with an early study of the H. influenzae ortholog failing to detect DNA-binding activity. Our group recently determined that the Borrelia burgdorferi YbaB ortholog, EbfC, is a DNA-binding protein. To reconcile those results, we assessed the abilities of both the H. influenzae and E. coli YbaB proteins to bind DNA to which B. burgdorferi EbfC can bind. RESULTS: Both the H. influenzae and the E. coli YbaB proteins bound to tested DNAs. DNA-binding was not well competed with poly-dI-dC, indicating some sequence preferences for those two proteins. Analyses of binding characteristics determined that both YbaB orthologs bind as homodimers. Different DNA sequence preferences were observed between H. influenzae YbaB, E. coli YbaB and B. burgdorferi EbfC, consistent with amino acid differences in the putative DNA-binding domains of these proteins. CONCLUSION: Three distinct members of the YbaB/EbfC bacterial protein family have now been demonstrated to bind DNA. Members of this protein family are encoded by a broad range of bacteria, including many pathogenic species, and results of our studies suggest that all such proteins have DNA-binding activities. The functions of YbaB/EbfC family members in each bacterial species are as-yet unknown, but given the ubiquity of these DNA-binding proteins among Eubacteria, further investigations are warranted

High Prevalence of Cardiometabolic Risk Factors in Women Considered Low Risk by Traditional Risk Assessment

Background: Cardiovascular disease (CVD) is the leading cause of death in women in the United States. The purpose of this study was to characterize the prevalence and awareness of traditional CVD risk factors, obesity, and coronary heart disease (CHD) risk classification using the Framingham Risk Score (FRS) among women attending the 2006 Sister to Sister National Woman’s Heart Day event. Results: A total of 8936 participants (mean age 49 ± 14 years) were evaluated. There was a modest prevalence of traditional risk factors on screening, including non-high-density lipoprotein-cholesterol (HDL-C) \u3e 160 mg/dL (27%), HDL-C \u3c40 mg/dL (16%), random glucose level \u3e140 mg/dL (6%), uncontrolled blood pressure ≥140/90 mm Hg (12%), current smoking (6%), and a positive family history of CHD (21%). There was a high prevalence of overweight (39%) or obese individuals (35%) (body mass index [BMI] 25–30 and ≥ 30 kg/m2, respectively), as well as those with high waist circumference (≥35 inches) (55%). Women were classified by FRS as low (85%), intermediate (6%), and high risk (9%). When cardiometabolic risk analyses included waist circumference in addition to the FRS, 59% of low-risk and 50% of intermediate-risk women had 1 or 2 risk factors, and 19% and 41% had ≥ 3 risk factors, respectively. Women were often unaware of risk factors on screening; among women without a previous diagnosis of dyslipidemia or hypertension, 48% and 7%, respectively, were given new diagnoses. Conclusions: Women participating in the 2006 Sister to Sister National Woman’s Heart Day event have a high prevalence of cardiometabolic risk factors, especially dyslipidemia, obesity, and high central adiposity, that place them at higher risk for the development of CVD and other comorbidities. The newly identified multiple risk factors in this population support the value of community health screening in women

Estimating past hepatitis C infection risk from reported risk factor histories: implications for imputing age of infection and modeling fibrosis progression

BackgroundChronic hepatitis C virus infection is prevalent and often causes hepatic fibrosis, which can progress to cirrhosis and cause liver cancer or liver failure. Study of fibrosis progression often relies on imputing the time of infection, often as the reported age of first injection drug use. We sought to examine the accuracy of such imputation and implications for modeling factors that influence progression rates.MethodsWe analyzed cross-sectional data on hepatitis C antibody status and reported risk factor histories from two large studies, the Women’s Interagency HIV Study and the Urban Health Study, using modern survival analysis methods for current status data to model past infection risk year by year. We compared fitted distributions of past infection risk to reported age of first injection drug use.ResultsAlthough injection drug use appeared to be a very strong risk factor, models for both studies showed that many subjects had considerable probability of having been infected substantially before or after their reported age of first injection drug use. Persons reporting younger age of first injection drug use were more likely to have been infected after, and persons reporting older age of first injection drug use were more likely to have been infected before.ConclusionsIn studies of fibrosis progression, modern methods such as multiple imputation should be used to account for the substantial uncertainty about when infection occurred. The models presented here can provide the inputs needed by such methods. Using reported age of first injection drug use as the time of infection in studies of fibrosis progression is likely to produce a spuriously strong association of younger age of infection with slower rate of progression

Intercomparison of Small Unmanned Aircraft System (sUAS) Measurements for Atmospheric Science During the LAPSE-RATE Campaign

Small unmanned aircraft systems (sUAS) are rapidly transforming atmospheric research. With the advancement of the development and application of these systems, improving knowledge of best practices for accurate measurement is critical for achieving scientific goals. We present results from an intercomparison of atmospheric measurement data from the Lower Atmospheric Process Studies at Elevation—a Remotely piloted Aircraft Team Experiment (LAPSE-RATE) field campaign. We evaluate a total of 38 individual sUAS with 23 unique sensor and platform configurations using a meteorological tower for reference measurements. We assess precision, bias, and time response of sUAS measurements of temperature, humidity, pressure, wind speed, and wind direction. Most sUAS measurements show broad agreement with the reference, particularly temperature and wind speed, with mean value differences of 1.6 ± 2.6 °C and 0.22 ± 0.59 m/s for all sUAS, respectively. sUAS platform and sensor configurations were found to contribute significantly to measurement accuracy. Sensor configurations, which included proper aspiration and radiation shielding of sensors, were found to provide the most accurate thermodynamic measurements (temperature and relative humidity), whereas sonic anemometers on multirotor platforms provided the most accurate wind measurements (horizontal speed and direction). We contribute both a characterization and assessment of sUAS for measuring atmospheric parameters, and identify important challenges and opportunities for improving scientific measurements with sUAS

Temporal changes in HCV genotype distribution in three different high risk populations in San Francisco, California

Abstract Background Hepatitis C virus (HCV) genotype (GT) has become an important measure in the diagnosis and monitoring of HCV infection treatment. In the United States (U.S.) HCV GT 1 is reported as the most common infecting GT among chronically infected patients. In Europe, however, recent studies have suggested that the epidemiology of HCV GTs is changing. Methods We assessed HCV GT distribution in 460 patients from three HCV-infected high risk populations in San Francisco, and examined patterns by birth cohort to assess temporal trends. Multiple logistic regression was used to assess factors independently associated with GT 1 infection compared to other GTs (2, 3, and 4). Results Overall, GT 1 was predominant (72.4%), however younger injection drug users (IDU) had a lower proportion of GT 1 infections (54.7%) compared to older IDU and HIV-infected patients (80.5% and 76.6%, respectively). Analysis by birth cohort showed increasing proportions of non-GT 1 infections associated with year of birth: birth before 1970 was independently associated with higher adjusted odds of GT 1: AOR 2.03 (95% CI: 1.23, 3.34). African-Americans as compared to whites also had higher adjusted odds of GT 1 infection (AOR: 3.37; 95% CI: 1.89, 5.99). Conclusions Although, HCV GT 1 remains the most prevalent GT, especially among older groups, changes in GT distribution could have significant implications for how HCV might be controlled on a population level and treated on an individual level

A Framework For Detecting Noncoding Rare-Variant associations of Large-Scale Whole-Genome Sequencing Studies

Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate multiple functional annotations. In non-gene-centric analysis, STAARpipeline uses SCANG-STAAR to incorporate dynamic window sizes and multiple functional annotations. We apply STAARpipeline to identify noncoding RV sets associated with four lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several of them in an additional 9,123 toPMed samples. We also analyze five non-lipid toPMed traits

Type 2 Diabetes Modifies the association of Cad Genomic Risk Variants With Subclinical atherosclerosis

BACKGROUND: Individuals with type 2 diabetes (T2D) have an increased risk of coronary artery disease (CAD), but questions remain about the underlying pathology. Identifying which CAD loci are modified by T2D in the development of subclinical atherosclerosis (coronary artery calcification [CAC], carotid intima-media thickness, or carotid plaque) may improve our understanding of the mechanisms leading to the increased CAD in T2D. METHODS: We compared the common and rare variant associations of known CAD loci from the literature on CAC, carotid intima-media thickness, and carotid plaque in up to 29 670 participants, including up to 24 157 normoglycemic controls and 5513 T2D cases leveraging whole-genome sequencing data from the Trans-Omics for Precision Medicine program. We included first-order T2D interaction terms in each model to determine whether CAD loci were modified by T2D. The genetic main and interaction effects were assessed using a joint test to determine whether a CAD variant, or gene-based rare variant set, was associated with the respective subclinical atherosclerosis measures and then further determined whether these loci had a significant interaction test. RESULTS: Using a Bonferroni-corrected significance threshold of CONCLUSIONS: These results highlight T2D as an important modifier of rare variant associations in CAD loci with CAC

Genetic loci associated with prevalent and incident myocardial infarction and coronary heart disease in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium

No funding sources had a role in the design of the study or the analysis or interpretation of the data. Infrastructure for the CHARGE Consortium is supported in part by the National Heart, Lung and Blood Institute (NHLBI) grant R01HL105756. JH, ACM and PSdeV were supported by NIH NHLBI R01HL141291. PSdV was additionally supported by American Heart Association grant number 18CDA34110116. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the NHLBI; the National Institutes of Health; or the U.S. Department of Health and Human Services. The Age, Gene, Environment, Susceptibility Study (AGES) study has been funded by NIH contracts N01-AG-1-2100 and HHSN271201200022C, the NIA Intramural Research Program, Hjartavernd (the Icelandic Heart Association), and the Althingi (the Icelandic Parliament). The Atherosclerosis Risk in Communities study has been funded in whole or in part with Federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services (contract numbers HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700004I and HHSN268201700005I). Funding support for “Building on GWAS for NHLBI-diseases: the U.S. CHARGE consortium” was provided by the NIH through the American Recovery and Reinvestment Act of 2009 (ARRA) (5RC2HL102419). Cardiovascular Health Study (CHS) research was supported by NHLBI contracts HHSN268201200036C, HHSN268200800007C, HHSN268201800001C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086; and NHLBI grants U01HL080295, R01HL087652, R01HL105756, R01HL103612, R01HL120393, and U01HL130114 with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided through R01AG023629 from the National Institute on Aging (NIA). A full list of principal CHS investigators and institutions can be found at https://chsnhlbi.org/. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR001881, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (DRC) grant DK063491 to the Southern California Diabetes Endocrinology Research Center. The Family Heart Study (FamHS) was supported by the grant R01-HL-117078 from the National Heart, Lung, and Blood Institute, and grant R01-DK-089256 from the National Institute of Diabetes and Digestive and Kidney Diseases. The Framingham Heart Study (FHS) The National Heart, Lung and Blood Institute’s Framingham Heart Study is supported by contract N01-HC-25195. GeneSTAR was supported by grants from the National Institutes of Health/National Heart, Lung and Blood Institute (HL49762, HL59684, HL071025, HL58625, U01 HL72518, HL089474, HL092165, HL099747, K23HL105897, K23HL094747, HL11006, and HL112064), National Institute of Nursing Research (NR0224103, NR008153), National Institute of Neurological Disorders and Stroke (NS062059), and by a grant from the National Center for Research Resources (M01-RR000052) to the Johns Hopkins General Clinical Research Center. Genotyping services were provided through the RS&G Service by the Northwest Genomics Center at the University of Washington, Department of Genome Sciences, under U.S. Federal Government contract number HHSN268201100037C from the National Heart, Lung, and Blood Institute. MESA and the MESA SHARe projects are conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support for MESA is provided by contracts 75N92020D00001, HHSN268201500003I, N01-HC-95159, 75N92020D00005, N01-HC-95160, 75N92020D00002, N01-HC-95161, 75N92020D00003, N01-HC-95162, 75N92020D00006, N01-HC-95163, 75N92020D00004, N01-HC-95164, 75N92020D00007, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-000040, UL1-TR-001079, UL1-TR-001420. Also supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR001881, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (DRC) grant DK063491 to the Southern California Diabetes Endocrinology Research Center. For the Rotterdam Study, the work was supported by the Erasmus Medical Center and Erasmus University, Rotterdam; The Netherlands Organisation for the Health Research and Development (ZonMw); the Research Institute for Diseases in the Elderly (014-93-015, RIDE2); the Ministry of Education, Culture and Science; the Ministry for Health, Welfare and Sports; the European Commission (DG XII); the Municipality of Rotterdam; The Netherlands Organisation of Scientific Research (NWO) (175.010.2005.011, 911-03-012); the Netherlands Genomics Initiative (NGI) (NWO 050-060-810), the Netherlands Organisation for Scientific Research (NWO) (veni 916.12.154). SHIP is supported by the German Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung (BMBF); grants 01ZZ9603, 01ZZ0103, and 01ZZ0403) and the German Research Foundation (Deutsche Forschungsgemeinschaft (DFG); grant GR 1912/5-1). The Study of Health in Pomerania (SHIP) and SHIP-TREND are part of the Community Medicine Research net (CMR) of the Ernst-Moritz-Arndt University Greifswald (EMAU) which is funded by the BMBF as well as the Ministry for Education, Science and Culture and the Ministry of Labor, Equal Opportunities, and Social Affairs of the Federal State of Mecklenburg-West Pomerania. The CMR encompasses several research projects that share data from SHIP. The EMAU is a member of the Center of Knowledge Interchange (CKI) program of the Siemens AG. SNP typing of SHIP and SHIP-TREND using the Illumina Infinium HumanExome BeadChip (version v1.0) was supported by the BMBF (grant 03Z1CN22). The Women’s Genome Health Study (WGHS) is supported by the National Heart, Lung, and Blood Institute (HL043851, HL080467, HL099355) and the National Cancer Institute (CA047988 and UM1CA182913), with collaborative scientific support and funding for genotyping provided by Amgen. There was no additional external funding received for this study. Publisher Copyright: Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.Background Genome-wide association studies have identified multiple genomic loci associated with coronary artery disease, but most are common variants in non-coding regions that provide limited information on causal genes and etiology of the disease. To overcome the limited scope that common variants provide, we focused our investigation on low-frequency and rare sequence variations primarily residing in coding regions of the genome. Methods and results Using samples of individuals of European ancestry from ten cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, both cross-sectional and prospective analyses were conducted to examine associations between genetic variants and myocardial infarction (MI), coronary heart disease (CHD), and all-cause mortality following these events. For prevalent events, a total of 27,349 participants of European ancestry, including 1831 prevalent MI cases and 2518 prevalent CHD cases were used. For incident cases, a total of 55,736 participants of European ancestry were included (3,031 incident MI cases and 5,425 incident CHD cases). There were 1,860 all-cause deaths among the 3,751 MI and CHD cases from six cohorts that contributed to the analysis of all-cause mortality. Single variant and gene-based analyses were performed separately in each cohort and then meta-analyzed for each outcome. A low-frequency intronic variant (rs988583) in PLCL1 was significantly associated with prevalent MI (OR = 1.80, 95% confidence interval: 1.43, 2.27; P = 7.12 × 10−7). We conducted gene-based burden tests for genes with a cumulative minor allele count (cMAC) > 5 and variants with minor allele frequency (MAF) < 5%. TMPRSS5 and LDLRAD1 were significantly associated with prevalent MI and CHD, respectively, and RC3H2 and ANGPTL4 were significantly associated with incident MI and CHD, respectively. No loci were significantly associated with all-cause mortality following a MI or CHD event. Conclusion This study identified one known locus (ANGPTL4) and four new loci (PLCL1, RC3H2, TMPRSS5, and LDLRAD1) associated with cardiovascular disease risk that warrant further investigation.Peer reviewe

Multiethnic Exome-Wide Association Study of Subclinical AtherosclerosisCLINICAL PERSPECTIVE

The burden of subclinical atherosclerosis in asymptomatic individuals is heritable and associated with elevated risk of developing clinical coronary heart disease (CHD). We sought to identify genetic variants in protein-coding regions associated with subclinical atherosclerosis and the risk of subsequent CHD

DNA-binding by <it>Haemophilus influenzae </it>and <it>Escherichia coli </it>YbaB, members of a widely-distributed bacterial protein family

Abstract Background Genes orthologous to the ybaB loci of Escherichia coli and Haemophilus influenzae are widely distributed among eubacteria. Several years ago, the three-dimensional structures of the YbaB orthologs of both E. coli and H. influenzae were determined, revealing a novel "tweezer"-like structure. However, a function for YbaB had remained elusive, with an early study of the H. influenzae ortholog failing to detect DNA-binding activity. Our group recently determined that the Borrelia burgdorferi YbaB ortholog, EbfC, is a DNA-binding protein. To reconcile those results, we assessed the abilities of both the H. influenzae and E. coli YbaB proteins to bind DNA to which B. burgdorferi EbfC can bind. Results Both the H. influenzae and the E. coli YbaB proteins bound to tested DNAs. DNA-binding was not well competed with poly-dI-dC, indicating some sequence preferences for those two proteins. Analyses of binding characteristics determined that both YbaB orthologs bind as homodimers. Different DNA sequence preferences were observed between H. influenzae YbaB, E. coli YbaB and B. burgdorferi EbfC, consistent with amino acid differences in the putative DNA-binding domains of these proteins. Conclusion Three distinct members of the YbaB/EbfC bacterial protein family have now been demonstrated to bind DNA. Members of this protein family are encoded by a broad range of bacteria, including many pathogenic species, and results of our studies suggest that all such proteins have DNA-binding activities. The functions of YbaB/EbfC family members in each bacterial species are as-yet unknown, but given the ubiquity of these DNA-binding proteins among Eubacteria, further investigations are warranted.</p