| 3. |
- Jespersen, Naja Z., et al.
(författare)
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Heterogeneity in the perirenal region of humans suggests presence of dormant brown adipose tissue that contains brown fat precursor cells
- 2019
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Ingår i: Molecular Metabolism. - : Elsevier BV. - 2212-8778. ; 24, s. 30-43
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Tidskriftsartikel (refereegranskat)abstract
- Objective:Increasing the amounts of functionally competent brown adipose tissue (BAT) in adult humans has the potential to restore dysfunctional metabolism and counteract obesity. In this study, we aimed to characterize the human perirenal fat depot, and we hypothesized that there would be regional, within-depot differences in the adipose signature depending on local sympathetic activity.Methods:We characterized fat specimens from four different perirenal regions of adult kidney donors, through a combination of qPCR mapping, immunohistochemical staining, RNA-sequencing, and pre-adipocyte isolation. Candidate gene signatures, separated by adipocyte morphology, were recapitulated in a murine model of unilocular brown fat induced by thermoneutrality and high fat diet.Results:We identified widespread amounts of dormant brown adipose tissue throughout the perirenal depot, which was contrasted by multilocular BAT, primarily found near the adrenal gland. Dormant BAT was characterized by a unilocular morphology and a distinct gene expression profile, which partly overlapped with that of subcutaneous white adipose tissue (WAT). Brown fat precursor cells, which differentiated into functional brown adipocytes were present in the entire perirenal fat depot, regardless of state. We identified SPARC as a candidate adipokine contributing to a dormant BAT state, and CLSTN3 as a novel marker for multilocular BAT.Conclusions:We propose that perirenal adipose tissue in adult humans consists mainly of dormant BAT and provide a data set for future research on factors which can reactivate dormant BAT into active BAT, a potential strategy for combatting obesity and metabolic disease.
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| 6. |
- Wang, Haidong, et al.
(författare)
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Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015 : a systematic analysis for the Global Burden of Disease Study 2015
- 2016
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Ingår i: The Lancet. - 0140-6736 .- 1474-547X. ; 388:10053, s. 1459-1544
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures.METHODS: We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography-year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER).FINDINGS: Globally, life expectancy from birth increased from 61·7 years (95% uncertainty interval 61·4-61·9) in 1980 to 71·8 years (71·5-72·2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11·3 years (3·7-17·4), to 62·6 years (56·5-70·2). Total deaths increased by 4·1% (2·6-5·6) from 2005 to 2015, rising to 55·8 million (54·9 million to 56·6 million) in 2015, but age-standardised death rates fell by 17·0% (15·8-18·1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14·1% (12·6-16·0) to 39·8 million (39·2 million to 40·5 million) in 2015, whereas age-standardised rates decreased by 13·1% (11·9-14·3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42·1%, 39·1-44·6), malaria (43·1%, 34·7-51·8), neonatal preterm birth complications (29·8%, 24·8-34·9), and maternal disorders (29·1%, 19·3-37·1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000-183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000-532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death.INTERPRETATION: At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems.
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| 7. |
- Wingard, Louise, et al.
(författare)
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Initiation and long-term use of benzodiazepines and Z-drugs in bipolar disorder
- 2018
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Ingår i: Bipolar Disorders. - : Wiley. - 1398-5647 .- 1399-5618. ; 20:7, s. 634-646
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Tidskriftsartikel (refereegranskat)abstract
- ObjectivesIncreasing evidence points to the harmful effects of long‐term benzodiazepine treatment. Our objective was to study the incidence of, and predictors for, long‐term use of benzodiazepines and Z‐drugs in bipolar disorder.MethodsWe conducted a population‐based cohort study, using data from Swedish national registers. Swedish residents aged 18‐75 years with a recorded diagnosis of bipolar disorder or mania between July 2006 and December 2012, and no history of benzodiazepine/Z‐drug use in the past year, were included. Patients were followed for 1 year with regard to prescription fills of benzodiazepines/Z‐drugs. Initiators were followed for another year during which continuous use for >6 months was defined as “long‐term”. Patient and prescription characteristics were investigated as potential predictors for long‐term use in multivariate logistic regression models.ResultsOut of the 21 883 patients included, 29% started benzodiazepine/Z‐drug treatment, of whom one in five became long‐term users. Patients who were prescribed clonazepam or alprazolam had high odds for subsequent long‐term use (adjusted odds ratios [aORs] 3.78 [95% confidence interval (CI) 2.24‐6.38] and 2.03 [95% CI 1.30‐3.18], respectively), compared to those prescribed diazepam. Polytherapy with benzodiazepines/Z‐drugs also predicted long‐term use (aOR 2.46, 95% CI 1.79‐3.38), as did age ≥60 years (aOR 1.93, 95% CI 1.46‐2.53, compared to age <30 years), and concomitant treatment with psychostimulants (aOR 1.78, 95% CI 1.33‐2.39).ConclusionsThe incidence of subsequent long‐term use among bipolar benzodiazepine initiators is high. Patients on clonazepam, alprazolam or benzodiazepine/Z‐drug polytherapy have the highest risk of becoming long‐term users, suggesting that these treatments should be used restrictively.
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