26 research outputs found
New genetic loci link adipose and insulin biology to body fat distribution.
Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms
Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019
Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens
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Relation of Physical Fitness to Brain Aging and Cognition in Older Adults
Level of physical fitness may be an important factor influencing the effects of brain aging and age-related cognitive decline. Multiple measures of aerobic fitness were used in a cohort of healthy older adults 50-89 years of age to identify how individual differences in fitness relate to brain aging and age-associated cognitive decline. Healthy adults (n=123; 65 F and 58 M; mean ± sd age = 67.9 ± 10.0; Mini-Mental State Exam = 29.1 ± 1.2) were screened to exclude neurological, psychiatric, and medical illnesses that could affect cognitive function, including hypertension. The Scaled Subprofile Model (SSM) with voxel-based morphometry and Statistical Parametric Mapping version 8 (VBM; SPM8 Dartel) were performed on T1-weighted 3T volumetric magnetic resonance imaging (MRI) scans to identify a gray matter pattern associated with brain aging. Performance on aerobic fitness measures, assessed during a graded exercise treadmill test (GXT), was evaluated in relation to the age-associated MRI gray matter network pattern and indices of neuropsychological function. Multivariate SSM VBM network analysis identified a linear combination of patterns that predicted age (R² = 0.48, p = 8.71e-19). This combined pattern was characterized by reductions in bilateral lateral and medial frontal, parietal, lateral temporal, and cerebellar regions with relative preservations in thalamic, occipital, and medial temporal regions including the hippocampus. Higher expression of the age-related network pattern was associated with poorer performance on multiple fitness indices. The best combination of fitness measures in predicting brain aging included overall treadmill exercise time, ventilatory efficiency, and the difference between basal and maximal respiratory rate (p = 6.67e-7). A higher combined fitness index score related to brain aging was associated with better performance on measures of memory, executive function, and processing speed in this cohort (6.08e-9≤ p≤ 0.05). Those individuals with higher levels of aerobic fitness had lower expression of the gray matter brain aging pattern and better performance on measures of memory, executive function, and processing speed. Identifying those fitness indices that are the best predictors of brain aging and cognitive performance may aid efforts in developing and evaluating exercise based interventions for age-related cognitive decline
Integrin α4β1-Dependent Adhesion to ADAM 28 (MDC-L) Requires an Extended Surface of the Disintegrin Domain †
Prefrontal cortex volumes in adolescents with alcohol use disorders: Unique gender effects
Background: Adolescents with alcohol use disorders (AUD) have shown smaller prefrontal cortex (PFC) volumes compared with healthy controls; however, differences may have been due to comorbid disorders. This study examined PFC volumes in male and female adolescents with AUD who did not meet criteria for comorbid mood or attention disorders.Methods: Participants were adolescents aged 15 to 17 who met criteria for AUD (n = 14), and demographically similar healthy controls (n = 17). Exclusions included any history of a psychiatric or neurologic disorder other than AUD or conduct disorder. Magnetic resonance imaging scans occurred after at least 5 days of abstinence from alcohol or drugs. Overall PFC volumes and white matter PFC volumes were compared between groups.Results: After controlling for conduct disorder, gender, and intracranial volume, AUD teens demonstrated marginally smaller anterior ventral PFC volumes (p = 0.09) than controls, and significant interactions between group and gender were observed (p < 0.001 to p < 0.03). Compared with same-gender controls, females with AUD demonstrated smaller PFC volumes, while males with AUD had larger PFC volumes. The same pattern was observed for PFC white matter volumes.Conclusions: Consistent with adult literature, alcohol use during adolescence is associated with prefrontal volume abnormalities, including white matter differences. However, adolescents with AUD demonstrated gender-specific morphometric patterns. Thus, it is possible that gender may moderate the impact of adolescent alcohol use on prefrontal neurodevelopment, and the neurodevelopmental trajectories of heavy drinking boys and girls should be evaluated separately in longitudinal studies
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Prefrontal cortex volumes in adolescents with alcohol use disorders: Unique gender effects
Background: Adolescents with alcohol use disorders (AUD) have shown smaller prefrontal cortex (PFC) volumes compared with healthy controls; however, differences may have been due to comorbid disorders. This study examined PFC volumes in male and female adolescents with AUD who did not meet criteria for comorbid mood or attention disorders.Methods: Participants were adolescents aged 15 to 17 who met criteria for AUD (n = 14), and demographically similar healthy controls (n = 17). Exclusions included any history of a psychiatric or neurologic disorder other than AUD or conduct disorder. Magnetic resonance imaging scans occurred after at least 5 days of abstinence from alcohol or drugs. Overall PFC volumes and white matter PFC volumes were compared between groups.Results: After controlling for conduct disorder, gender, and intracranial volume, AUD teens demonstrated marginally smaller anterior ventral PFC volumes (p = 0.09) than controls, and significant interactions between group and gender were observed (p < 0.001 to p < 0.03). Compared with same-gender controls, females with AUD demonstrated smaller PFC volumes, while males with AUD had larger PFC volumes. The same pattern was observed for PFC white matter volumes.Conclusions: Consistent with adult literature, alcohol use during adolescence is associated with prefrontal volume abnormalities, including white matter differences. However, adolescents with AUD demonstrated gender-specific morphometric patterns. Thus, it is possible that gender may moderate the impact of adolescent alcohol use on prefrontal neurodevelopment, and the neurodevelopmental trajectories of heavy drinking boys and girls should be evaluated separately in longitudinal studies
Neuropsychological functioning in adolescent marijuana users: Subtle deficits detectable after a month of abstinence
In adults. Studies examining the long-lasting cognitive effects of marijuana use demonstrate subtle deficits in attention. executive function. and memory. Because neuromaturation continues through adolescence, these results cannot necessarily generalize to adolescent marijuana users. The goal of this Study was to examine neuropsychological functioning in abstinent marijuana using and demographically similar control adolescents. Data were collected from 65 adolescent marijuana users (n = 31, 26% females) and controls (n 34, 26% females) 16-18 years of age. Extensive exclusionary criteria included independent psychiatric, medical, and neurologic disorders. Neuropsychological assessments were conducted after > 23 days of monitored abstinence. After controlling for lifetime alcohol use and depressive symptoms, adolescent marijuana users demonstrated slower psychomotor speed (p < .05), and poorer complex attention (p < .04), story memory (p < .04), and planning and sequencing ability (p < .001) compared with controls. Post hoc analysis revealed that the number of lifetime marijuana use episodes was associated with poorer cognitive function, even after controlling for lifetime alcohol use. The general pattern of results suggested that, even after a month of monitored abstinence, adolescent marijuana users demonstrate subtle neuropsychological deficits compared with nonusers. It is possible that frequent marijuana use during adolescence may negatively influence neuromaturation and cognitive development
Age-related networks of regional covariance in MRI gray matter: reproducible multivariate patterns in healthy aging
Healthy aging is associated with brain volume reductions that involve the frontal cortex, but also affect other brain regions. We sought to identify an age-related network pattern of MRI gray matter using a multivariate statistical model of regional covariance, the Scaled Subprofile Model (SSM) with voxel based morphometry (VBM) in 29 healthy adults, 23-84 years of age (Group 1). In addition, we evaluated the reproducibility of the age-related gray matter pattern derived from a prior SSM VBM study of 26 healthy adults, 22-77 years of age (Group 2; Alexander et al., 2006) in relation to the current sample and tested the ability of the network analysis to extract an age-related pattern from both cohorts combined. The SSM VBM analysis of Group 1 identified a regional pattern of gray matter atrophy associated with healthy aging (R(2)=0.64, p\u3c0.000001) that included extensive reductions in bilateral dorsolateral and medial frontal, anterior cingulate, insula/perisylvian, precuneus, parietotemporal, and caudate regions with areas of relative preservation in bilateral cerebellum, thalamus, putamen, mid cingulate, and temporal pole regions. The age-related SSM VBM gray matter pattern, previously reported for Group 2, was highly expressed in Group 1 (R(2)=0.52, p\u3c0.00002). SSM analysis of the combined cohorts extracted a common age-related pattern of gray matter showing reductions involving bilateral medial frontal, insula/perisylvian, anterior cingulate and, to a lesser extent, bilateral dorsolateral prefrontal, lateral temporal, parietal, and caudate brain regions with relative preservation in bilateral cerebellum, temporal pole, and right thalamic regions. The results suggest that healthy aging is associated with a regionally distributed pattern of gray matter atrophy that has reproducible regional features. Whereas the network patterns of atrophy included parietal, temporal, and subcortical regions, involvement of the frontal brain regions showed the most consistently extensive and reliable reductions across samples. Network analysis with SSM VBM can help detect reproducible age-related MRI patterns, assisting efforts in the study of healthy and pathological aging
Gray matter network associated with risk for Alzheimer\u27s disease in young to middle-aged adults
The apolipoprotein E (APOE) ε4 allele increases the risk for late-onset Alzheimer\u27s disease (AD) and age-related cognitive decline. We investigated whether ε4 carriers show reductions in gray matter volume compared with ε4 non-carriers decades before the potential onset of AD dementia or healthy cognitive aging. Fourteen cognitively normal ε4 carriers, aged 26 to 45 years, were compared with 10 age-matched, ε4 non-carriers using T1-weighted volumetric magnetic resonance imaging (MRI) scans. All had reported first- or second-degree family histories of dementia. Group differences in gray matter were tested using voxel-based morphometry (VBM) and a multivariate model of regional covariance, the Scaled Subprofile Model (SSM). A combination of the first two SSM MRI gray matter patterns distinguished the APOE ε4 carriers from non-carriers. This combined pattern showed gray matter reductions in bilateral dorsolateral and medial frontal, anterior cingulate, parietal, and lateral temporal cortices with covarying relative increases in cerebellum, occipital, fusiform, and hippocampal regions. With these gray matter differences occurring decades before the potential onset of dementia or cognitive aging, the results suggest longstanding, gene-associated differences in brain morphology that may lead to preferential vulnerability for the later effects of late-onset AD or healthy brain aging
Practical Application Guide for the Discovery of Novel PFAS in Environmental Samples Using High Resolution Mass Spectrometry
Background
The intersection of the topics of high-resolution mass spectrometry (HRMS) and per- and polyfluoroalkyl substances (PFAS) bring together two disparate and complex subjects. Recently non-targeted analysis (NTA) for the discovery of novel PFAS in environmental and biological media has been shown to be valuable in multiple applications. Classical targeted analysis for PFAS using LC-MS/MS, though growing in compound coverage, is still unable to inform a holistic understanding of the PFAS burden in most samples. NTA fills at least a portion of this data gap.
Objectives
Entrance into the study of novel PFAS discovery requires identification techniques such as HRMS (e.g., QTOF and Orbitrap) instrumentation. This requires practical knowledge of best approaches depending on the purpose of the analyses. The utility of HRMS applications for PFAS discovery is unquestioned and will likely play a significant role in many future environmental and human exposure studies.
Methods/Results
PFAS have some characteristics that make them standout from most other chemicals present in samples. Through a series of tell-tale PFAS characteristics (e.g., characteristic mass defect range, homologous series and characteristic fragmentation patterns), and case studies different approaches and remaining challenges are demonstrated. Impact statement: The identification of novel PFAS via non-targeted analysis using high resolution mass spectrometry is an important and difficult endeavor. This synopsis document will hopefully make current and future efforts on this topic easier to perform for novice and experienced alike. The typical time devoted to NTA PFAS investigations (weeks to months or more) may benefit from these practical steps employed