149 research outputs found

    Urinary Metal Levels and Coronary Artery Calcification: Longitudinal Evidence in the Multi-Ethnic Study of Atherosclerosis (MESA)

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    Objective: Growing evidence indicates that exposure to metals are risk factors for cardiovascular disease (CVD). We hypothesized that higher urinary levels of metals with prior evidence of an association with CVD, including non-essential (cadmium , tungsten, and uranium) and essential (cobalt, copper, and zinc) metals are associated with baseline and rate of change of coronary artery calcium (CAC) progression, a subclinical marker of atherosclerotic CVD. Methods: We analyzed data from 6,418 participants in the Multi-Ethnic Study of Atherosclerosis (MESA) with spot urinary metal levels at baseline (2000-2002) and 1-4 repeated measures of spatially weighted coronary calcium score (SWCS) over a ten-year period. SWCS is a unitless measure of CAC highly correlated to the Agatston score but with numerical values assigned to individuals with Agatston score=0. We used linear mixed effect models to assess the association of baseline urinary metal levels with baseline SWCS, annual change in SWCS, and SWCS over ten years of follow-up. Urinary metals (adjusted to μg/g creatinine) and SWCS were log transformed. Models were progressively adjusted for baseline sociodemographic factors, estimated glomerular filtration rate, lifestyle factors, and clinical factors. Results: At baseline, the median and interquartile range (25th, 75th) of SWCS was 6.3 (0.7, 58.2). For urinary cadmium, the fully adjusted geometric mean ratio (GMR) (95%Cl) of SWCS comparing the highest to the lowest quartile was 1.51 (1.32, 1.74) at baseline and 1.75 (1.47, 2.07) at ten years of follow-up. For urinary tungsten, uranium, and cobalt the corresponding GMRs at ten years of follow-up were 1.45 (1.23, 1.71), 1.39 (1.17, 1.64), and 1.47 (1.25, 1.74), respectively. For copper and zinc, the association was attenuated with adjustment for clinical risk factors; GMRs at ten years of follow-up before and after adjustment for clinical risk factors were 1.55 (1.30, 1.84) and 1.33 (1.12, 1.58), respectively, for copper and 1.85 (1.56, 2.19) and 1.57 (1.33, 1.85) for zinc. Conclusion: Higher levels of cadmium, tungsten, uranium, cobalt, copper, and zinc, as measured in urine, were associated with subclinical CVD at baseline and at follow-up. These findings support the hypothesis that metals are pro-atherogenic factors.The Multi-Ethnic Study of Atherosclerosis (MESA) is supported 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 and N01-HC-95169 from the National Heart, Lung, and Blood Institute, and by grants UL1-TR-000040, UL1-TR-001079, and UL1-TR-001420 from the National Center for Advancing Translational Sciences (NCATS). This publication was developed under the Science to Achieve Results (STAR) research assistance agreements, No. RD831697 (MESA Air) and RD-83830001 (MESA Air Next Stage), awarded by the U.S Environmental Protection Agency (EPA). It has not been formally reviewed by the EPA. The views expressed in this document are solely those of the authors and the EPA does not endorse any products or commercial services mentioned in this publication. Dr. Maria Tellez-Plaza was supported by grants PI15/00071 and PI22/00029 from the Strategic Action for Health Research, Instituto de Salud Carlos III and the Spanish Ministry of Science and Innovation, and co-funded with European Funds for Regional Development (FEDER). The opinions and views expressed in this article are those of the authors and do not necessarily represent the official position of the Instituto de Salud Carlos III (Spain). Work in the authors? laboratories is also supported in part by NIH grants P42ES023716, P42ES010349, P42ES033719, P30ES009089, T32ES007322, R01ES029967, R01HL155576. The authors thank the other investigators, the staff, and the participants of the MESA study for their valuable contributions. A full list of participating MESA investigators and institutions can be found at http://www.mesa-nhlbi.org. This paper has been reviewed and approved by the MESA Publications and Presentations Committee.N

    Comparing different definitions of prediabetes with subsequent risk of diabetes: an individual participant data meta-analysis involving 76 513 individuals and 8208 cases of incident diabetes

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    Objective: There are currently five widely used definition of prediabetes. We compared the ability of these to predict 5-year conversion to diabetes and investigated whether there were other cut-points identifying risk of progression to diabetes that may be more useful. Research design and methods: We conducted an individual participant meta-analysis using longitudinal data included in the Obesity, Diabetes and Cardiovascular Disease Collaboration. Cox regression models were used to obtain study-specific HRs for incident diabetes associated with each prediabetes definition. Harrell's C-statistics were used to estimate how well each prediabetes definition discriminated 5-year risk of diabetes. Spline and receiver operating characteristic curve (ROC) analyses were used to identify alternative cut-points. Results: Sixteen studies, with 76 513 participants and 8208 incident diabetes cases, were available. Compared with normoglycemia, current prediabetes definitions were associated with four to eight times higher diabetes risk (HRs (95% CIs): 3.78 (3.11 to 4.60) to 8.36 (4.88 to 14.33)) and all definitions discriminated 5-year diabetes risk with good accuracy (C-statistics 0.79-0.81). Cut-points identified through spline analysis were fasting plasma glucose (FPG) 5.1 mmol/L and glycated hemoglobin (HbA1c) 5.0% (31 mmol/mol) and cut-points identified through ROC analysis were FPG 5.6 mmol/L, 2-hour postload glucose 7.0 mmol/L and HbA1c 5.6% (38 mmol/mol). Conclusions: In terms of identifying individuals at greatest risk of developing diabetes within 5 years, using prediabetes definitions that have lower values produced non-significant gain. Therefore, deciding which definition to use will ultimately depend on the goal for identifying individuals at risk of diabetes.This work was supported by the National Health and Medical Research Council of Australia (grant number 1103242). 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, under contract nos. HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700005I, HHSN268201700004I. ES was supported by NIH/NIDDK grant K24DK106414. The Coronary Artery Risk Development in Young Adults Study (CARDIA) is supported by contracts HHSN2682018000031, HHSN2682018000041, HHSN2682018000051, HHSN2682018000061 and HHSN2682018000071 from the National Heart, Lung, and Blood Institute (NHLBI). The Jackson Heart Study (JHS) is supported and conducted in collaboration with Jackson State University (HHSN268201800013I), Tougaloo College (HHSN268201800014I), the Mississippi State Department of Health (HHSN268201800015I) and the University of Mississippi Medical Center (HHSN268201800010I, HHSN268201800011I and HHSN268201800012I) contracts from the National Heart, Lung, and Blood Institute (NHLBI) and the National Institute for Minority Health and Health Disparities (NIMHD). The Melbourne Collaborative Cohort Study (MCCS) recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further augmented by Australian National Health and Medical Research Council grants 209057, 396414 and 1074383 and by infrastructure provided by Cancer Council Victoria. Cases and their vital status were ascertained through the Victorian Cancer Registry and the Australian Institute of Health and Welfare, including the National Death Index and the Australian Cancer Database. The Multi-Ethnic Study of Atherosclerosis was supported by contracts HHSN268201500003I, N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168 and N01-HC-95169 from the National Heart, Lung, and Blood Institute and by grants UL1-TR-000040 and UL1-TR-001079 from NCRR. The Population Study of Women in Gothenburg (PSWG) was financed in part by grants from the Swedish state under the agreement between the Swedish government and the county councils, the ALF-agreement ALFGBG-720201. VIVA Study received grants 95/0029 and 06/90270 from the Instituto de Salud Carlos III, Spain.S

    Quantifying trends in disease impact to produce a consistent and reproducible definition of an emerging infectious disease.

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    The proper allocation of public health resources for research and control requires quantification of both a disease's current burden and the trend in its impact. Infectious diseases that have been labeled as "emerging infectious diseases" (EIDs) have received heightened scientific and public attention and resources. However, the label 'emerging' is rarely backed by quantitative analysis and is often used subjectively. This can lead to over-allocation of resources to diseases that are incorrectly labelled "emerging," and insufficient allocation of resources to diseases for which evidence of an increasing or high sustained impact is strong. We suggest a simple quantitative approach, segmented regression, to characterize the trends and emergence of diseases. Segmented regression identifies one or more trends in a time series and determines the most statistically parsimonious split(s) (or joinpoints) in the time series. These joinpoints in the time series indicate time points when a change in trend occurred and may identify periods in which drivers of disease impact change. We illustrate the method by analyzing temporal patterns in incidence data for twelve diseases. This approach provides a way to classify a disease as currently emerging, re-emerging, receding, or stable based on temporal trends, as well as to pinpoint the time when the change in these trends happened. We argue that quantitative approaches to defining emergence based on the trend in impact of a disease can, with appropriate context, be used to prioritize resources for research and control. Implementing this more rigorous definition of an EID will require buy-in and enforcement from scientists, policy makers, peer reviewers and journal editors, but has the potential to improve resource allocation for global health

    The global burden of falls: Global, regional and national estimates of morbidity and mortality from the Global Burden of Disease Study 2017

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    Background: Falls can lead to severe health loss including death. Past research has shown that falls are an important cause of death and disability worldwide. The Global Burden of Disease Study 2017 (GBD 2017) provides a comprehensive assessment of morbidity and mortality from falls. Methods: Estimates for mortality, years of life lost (YLLs), incidence, prevalence, years lived with disability (YLDs) and disability-adjusted life years (DALYs) were produced for 195 countries and territories from 1990 to 2017 for all ages using the GBD 2017 framework. Distributions of the bodily injury (eg, hip fracture) were estimated using hospital records. Results: Globally, the age-standardised incidence of falls was 2238 (1990-2532) per 100 000 in 2017, representing a decline of 3.7% (7.4 to 0.3) from 1990 to 2017. Age-standardised prevalence w

    Hearing loss and cognition: A protocol for ensuring speech understanding before neurocognitive assessment

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    INTRODUCTION: Many neurocognitive evaluations involve auditory stimuli, yet there are no standard testing guidelines for individuals with hearing loss. The ensuring speech understanding (ESU) test was developed to confirm speech understanding and determine whether hearing accommodations are necessary for neurocognitive testing. METHODS: Hearing was assessed using audiometry. The probability of ESU test failure by hearing status was estimated in 2679 participants (mean age: 81.4 ± 4.6 years) using multivariate logistic regression. RESULTS: Only 2.2% (N = 58) of participants failed the ESU test. The probability of failure increased with hearing loss severity; similar results were observed for those with and without mild cognitive impairment or dementia. DISCUSSION: The ESU test is appropriate for individuals who have variable degrees of hearing loss and cognitive function. This test can be used prior to neurocognitive testing to help reduce the risk of hearing loss and compromised auditory access to speech stimuli causing poorer performance on neurocognitive evaluation

    Nested inversion polymorphisms predispose chromosome 22q11.2 to meiotic rearrangements [RETRACTED]

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    Inversion polymorphisms between low-copy repeats (LCRs) might predispose chromosomes to meiotic non-allelic homologous recombination (NAHR) events and thus lead to genomic disorders. However, for the 22q11.2 deletion syndrome (22q11.2DS), the most common genomic disorder, no such inversions have been uncovered as of yet. Using fiber-FISH, we demonstrate that parents transmitting the de novo 3 Mb LCR22A–D 22q11.2 deletion, the reciprocal duplication, and the smaller 1.5 Mb LCR22A–B 22q11.2 deletion carry inversions of LCR22B–D or LCR22C–D. Hence, the inversions predispose chromosome 22q11.2 to meiotic rearrangements and increase the individual risk for transmitting rearrangements. Interestingly, the inversions are nested or flanking rather than coinciding with the deletion or duplication sizes. This finding raises the possibility that inversions are a prerequisite not only for 22q11.2 rearrangements but also for all NAHR-mediated genomic disorders

    Relative Burden of Large CNVs on a Range of Neurodevelopmental Phenotypes

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    While numerous studies have implicated copy number variants (CNVs) in a range of neurological phenotypes, the impact relative to disease severity has been difficult to ascertain due to small sample sizes, lack of phenotypic details, and heterogeneity in platforms used for discovery. Using a customized microarray enriched for genomic hotspots, we assayed for large CNVs among 1,227 individuals with various neurological deficits including dyslexia (376), sporadic autism (350), and intellectual disability (ID) (501), as well as 337 controls. We show that the frequency of large CNVs (>1 Mbp) is significantly greater for ID–associated phenotypes compared to autism (p = 9.58×10−11, odds ratio = 4.59), dyslexia (p = 3.81×10−18, odds ratio = 14.45), or controls (p = 2.75×10−17, odds ratio = 13.71). There is a striking difference in the frequency of rare CNVs (>50 kbp) in autism (10%, p = 2.4×10−6, odds ratio = 6) or ID (16%, p = 3.55×10−12, odds ratio = 10) compared to dyslexia (2%) with essentially no difference in large CNV burden among dyslexia patients compared to controls. Rare CNVs were more likely to arise de novo (64%) in ID when compared to autism (40%) or dyslexia (0%). We observed a significantly increased large CNV burden in individuals with ID and multiple congenital anomalies (MCA) compared to ID alone (p = 0.001, odds ratio = 2.54). Our data suggest that large CNV burden positively correlates with the severity of childhood disability: ID with MCA being most severely affected and dyslexics being indistinguishable from controls. When autism without ID was considered separately, the increase in CNV burden was modest compared to controls (p = 0.07, odds ratio = 2.33)

    Bioinorganic Chemistry of Alzheimer’s Disease

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