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1.
Cell Host Microbe ; 26(2): 252-264.e10, 2019 08 14.
Artigo em Inglês | MEDLINE | ID: mdl-31399369

RESUMO

Obesity and type 2 diabetes (T2D) are metabolic disorders that are linked to microbiome alterations. However, their co-occurrence poses challenges in disentangling microbial features unique to each condition. We analyzed gut microbiomes of lean non-diabetic (n = 633), obese non-diabetic (n = 494), and obese individuals with T2D (n = 153) from German population and metabolic disease cohorts. Microbial taxonomic and functional profiles were analyzed along with medical histories, serum metabolomics, biometrics, and dietary data. Obesity was associated with alterations in microbiome composition, individual taxa, and functions with notable changes in Akkermansia, Faecalibacterium, Oscillibacter, and Alistipes, as well as in serum metabolites that correlated with gut microbial patterns. However, microbiome associations were modest for T2D, with nominal increases in Escherichia/Shigella. Medications, including antihypertensives and antidiabetics, along with dietary supplements including iron, were significantly associated with microbiome variation. These results differentiate microbial components of these interrelated metabolic diseases and identify dietary and medication exposures to consider in future studies.


Assuntos
Diabetes Mellitus Tipo 2/complicações , Microbioma Gastrointestinal/fisiologia , Obesidade/complicações , Obesidade/microbiologia , Animais , Bactérias/classificação , Bactérias/genética , Bactérias/isolamento & purificação , Biodiversidade , Dieta , Suplementos Nutricionais , Fezes/microbiologia , Feminino , Alemanha , Humanos , Ferro/metabolismo , Magnésio/metabolismo , Masculino , Doenças Metabólicas/complicações , Metagenômica , Camundongos , Camundongos Endogâmicos C57BL , Análise Multivariada , Avaliação Nutricional , Soro/metabolismo
2.
Radiology ; 284(3): 706-716, 2017 09.
Artigo em Inglês | MEDLINE | ID: mdl-28481195

RESUMO

Purpose To quantify liver fat and liver iron content by measurement of confounder-corrected proton density fat fraction (PDFF) and R2* and to identify clinical associations for fatty liver disease and liver iron overload and their prevalence in a large-scale population-based study. Materials and Methods From 2008 to 2013, 2561 white participants (1336 women; median age, 52 years; 25th and 75th quartiles, 42 and 62 years) were prospectively recruited to the Study of Health in Pomerania (SHIP). Complex chemical shift-encoded magnetic resonance (MR) examination of the liver was performed, from which PDFF and R2* were assessed. On the basis of previous histopathologic calibration, participants were stratified according to their liver fat and iron content as follows: none (PDFF, ≤5.1%; R2*, ≤41.0 sec-1), mild (PDFF, >5.1%; R2*, >41 sec-1), moderate (PDFF, >14.1%; R2*, >62.5 sec-1), high (PDFF: >28.0%; R2*: >70.1 sec-1). Prevalence of fatty liver diseases and iron overload was calculated (weighted by probability of participation). Clinical associations were identified by using boosting for generalized linear models. Results Median PDFF was 3.9% (range, 0.6%-41.5%). Prevalence of fatty liver diseases was 42.2% (1082 of 2561 participants); mild, 28.5% (730 participants); moderate, 12.0% (307 participants); high content, 1.8% (45 participants). Median R2* was 34.4 sec-1 (range, 14.0-311.8 sec-1). Iron overload was observed in 17.4% (447 of 2561 participants; mild, 14.7% [376 participants]; moderate, 0.8% [20 participants]; high content, 2.0% [50 participants]). Liver fat content correlated with waist-to-height ratio, alanine transaminase, uric acid, serum triglycerides, and blood pressure. Liver iron content correlated with mean serum corpuscular hemoglobin, male sex, and age. Conclusion In a white German population, the prevalence of fatty liver diseases and liver iron overload is 42.2% (1082 of 2561) and 17.4% (447 of 2561). Whereas liver fat is associated with predictors related to the metabolic syndrome, liver iron content is mainly associated with mean serum corpuscular hemoglobin. © RSNA, 2017 Online supplemental material is available for this article.


Assuntos
Interpretação de Imagem Assistida por Computador/métodos , Sobrecarga de Ferro/epidemiologia , Imageamento por Ressonância Magnética/métodos , Hepatopatia Gordurosa não Alcoólica/epidemiologia , Adulto , Estudos Transversais , Feminino , Alemanha/epidemiologia , Humanos , Sobrecarga de Ferro/diagnóstico por imagem , Fígado/diagnóstico por imagem , Masculino , Pessoa de Meia-Idade , Hepatopatia Gordurosa não Alcoólica/diagnóstico por imagem , Estudos Prospectivos
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