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Karine Clément

Bio: Karine Clément is an academic researcher from Pierre-and-Marie-Curie University. The author has contributed to research in topics: Adipose tissue & White adipose tissue. The author has an hindex of 73, co-authored 228 publications receiving 14710 citations. Previous affiliations of Karine Clément include Institute of Chartered Accountants of Nigeria & Paris Descartes University.


Papers
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Journal Article
01 Jan 2016-Gut
TL;DR: In this paper, the authors evaluated the association between faecal A. muciniphila abundance and microbial gene richness after calorie restriction (CR) in overweight and obese adults.
Abstract: Objective Individuals with obesity and type 2 diabetes differ from lean and healthy individuals in their abundance of certain gut microbial species and microbial gene richness. Abundance of Akkermansia muciniphila, a mucin-degrading bacterium, has been inversely associated with body fat mass and glucose intolerance in mice, but more evidence is needed in humans. The impact of diet and weight loss on this bacterial species is unknown. Our objective was to evaluate the association between faecal A. muciniphila abundance, faecal microbiome gene richness, diet, host characteristics, and their changes after calorie restriction (CR). Design The intervention consisted of a 6-week CR period followed by a 6-week weight stabilisation diet in overweight and obese adults (N=49, including 41 women). Faecal A. muciniphila abundance, faecal microbial gene richness, diet and bioclinical parameters were measured at baseline and after CR and weight stabilisation. Results At baseline A. muciniphila was inversely related to fasting glucose, waist-to-hip ratio and subcutaneous adipocyte diameter. Subjects with higher gene richness and A. muciniphila abundance exhibited the healthiest metabolic status, particularly in fasting plasma glucose, plasma triglycerides and body fat distribution. Individuals with higher baseline A. muciniphila displayed greater improvement in insulin sensitivity markers and other clinical parameters after CR. These participants also experienced a reduction in A. muciniphila abundance, but it remained significantly higher than in individuals with lower baseline abundance. A. muciniphila was associated with microbial species known to be related to health. Conclusions A. muciniphila is associated with a healthier metabolic status and better clinical outcomes after CR in overweight/obese adults. The interaction between gut microbiota ecology and A. muciniphila warrants further investigation. Trial registration number NCT01314690.

1,035 citations

Journal ArticleDOI
TL;DR: The results suggest that an at-risk haplotype of common variants located in the promoter and rare mutations in exon 3 contribute to the variation of the adipocyte-secreted adiponectin hormone level, and may be part of the genetic determinants for T2D in the French Caucasian population.
Abstract: Adiponectin (ACRP30), an adipocyte-secreted protein encoded by the APM1 gene, is known to modulate insulin sensitivity and glucose homeostasis, those effects protecting obese mice from diabetes. Plasma adiponectin levels correlate well with insulin sensitivity in humans, and are decreased in both type 2 diabetes (T2D) and obesity. We screened for single-nucleotide polymorphisms (SNPs) the APM1 gene coding and 5' sequences in 40 French Caucasians: 12 SNPs and 4 rare non-synonymous mutations of exon 3 were detected. The 10 most frequent SNPs were genotyped in 1373 T2D and obese French Caucasian subjects and in all subjects available from 148 T2D multiplex families. The screening for rare mutations of exon 3 was extended to 1246 T2D and obese French subjects and to the members of the 148 T2D multiplex families. A haplotype including SNPs -11391 and -11377, both located in the 5' sequences, was associated with adiponectin levels (P<0.0001) and with T2D (P=0.004). The presence of at least one non-synonymous mutation in exon 3 showed evidence of association with adiponectin levels (P=0.0009) and with T2D (P=0.005). We failed to detect an association with insulin resistance indexes. Although family-based association analysis with T2D did not reach significance, our results suggest that an at-risk haplotype of common variants located in the promoter and rare mutations in exon 3 contribute to the variation of the adipocyte-secreted adiponectin hormone level, and may be part of the genetic determinants for T2D in the French Caucasian population.

496 citations

Journal ArticleDOI
TL;DR: It is confirmed that TM6SF2 minor allele carriage is associated with NAFLD and is causally related to a previously reported chromosome 19 GWAS signal that was ascribed to the gene NCAN.
Abstract: Non-alcoholic fatty liver disease (NAFLD) is an increasingly common condition, strongly associated with the metabolic syndrome, that can lead to progressive hepatic fibrosis, cirrhosis and hepatic failure. Subtle inter-patient genetic variation and environmental factors combine to determine variation in disease progression. A common non-synonymous polymorphism in TM6SF2 (rs58542926 c.449 C>T, p.Glu167Lys) was recently associated with increased hepatic triglyceride content, but whether this variant promotes clinically relevant hepatic fibrosis is unknown. Here we confirm that TM6SF2 minor allele carriage is associated with NAFLD and is causally related to a previously reported chromosome 19 GWAS signal that was ascribed to the gene NCAN. Furthermore, using two histologically characterized cohorts encompassing steatosis, steatohepatitis, fibrosis and cirrhosis (combined n=1,074), we demonstrate a new association, independent of potential confounding factors (age, BMI, type 2 diabetes mellitus and PNPLA3 rs738409 genotype), with advanced hepatic fibrosis/cirrhosis. These findings establish new and important clinical relevance to TM6SF2 in NAFLD.

477 citations

Journal ArticleDOI
TL;DR: This study provides the first evidence that the secretome from EAT promotes myocardial fibrosis through the secretion of adipo-fibrokines such as Activin A.
Abstract: Aims Recent studies have reported a relationship between the abundance of epicardial adipose tissue (EAT) and the risk of cardiovascular diseases including atrial fibrillation (AF). However, the underlying mechanisms are unknown. The aim of this study was to examine the effects of the secretome of human EAT on the histological properties of the myocardium. Methods and results Samples of EAT and subcutaneous adipose (SAT), obtained from 39 patients undergoing coronary bypass surgery, were analysed and tested in an organo-culture model of rat atria to evaluate the fibrotic properties of human fat depots. The EAT secretome induced global fibrosis (interstitial and peripheral) of rat atria in organo-culture conditions. Activin A was highly expressed in EAT compared with SAT and promoted atrial fibrosis, an effect blocked using neutralizing antibody. In addition, Activin A levels were enhanced in patients with low left-ventricular function. In sections of human atrial and ventricular myocardium, adipose and myocardial tissues were in close contact, together with fibrosis. Conclusion This study provides the first evidence that the secretome from EAT promotes myocardial fibrosis through the secretion of adipo-fibrokines such as Activin A.

414 citations

Journal ArticleDOI
01 Jun 2021-Gut
TL;DR: The key classes of microbiota-derived metabolites that are altered in metabolic diseases and their role in pathogenesis are defined to represent potential biomarkers for early diagnosis and prognosis as well as promising targets for the development of novel therapeutic tools for metabolic disorders.
Abstract: Metabolic disorders represent a growing worldwide health challenge due to their dramatically increasing prevalence. The gut microbiota is a crucial actor that can interact with the host by the production of a diverse reservoir of metabolites, from exogenous dietary substrates or endogenous host compounds. Metabolic disorders are associated with alterations in the composition and function of the gut microbiota. Specific classes of microbiota-derived metabolites, notably bile acids, short-chain fatty acids, branched-chain amino acids, trimethylamine N-oxide, tryptophan and indole derivatives, have been implicated in the pathogenesis of metabolic disorders. This review aims to define the key classes of microbiota-derived metabolites that are altered in metabolic diseases and their role in pathogenesis. They represent potential biomarkers for early diagnosis and prognosis as well as promising targets for the development of novel therapeutic tools for metabolic disorders.

354 citations


Cited by
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28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations

Journal ArticleDOI
TL;DR: A WHO Consultation has taken place in parallel with a report by an American Diabetes Association Expert Committee to re‐examine diagnostic criteria and classification of diabetes mellitus and is hoped that the new classification will allow better classification of individuals and lead to fewer therapeutic misjudgements.
Abstract: The classification of diabetes mellitus and the tests used for its diagnosis were brought into order by the National Diabetes Data Group of the USA and the second World Health Organization Expert Committee on Diabetes Mellitus in 1979 and 1980. Apart from minor modifications by WHO in 1985, little has been changed since that time. There is however considerable new knowledge regarding the aetiology of different forms of diabetes as well as more information on the predictive value of different blood glucose values for the complications of diabetes. A WHO Consultation has therefore taken place in parallel with a report by an American Diabetes Association Expert Committee to re-examine diagnostic criteria and classification. The present document includes the conclusions of the former and is intended for wide distribution and discussion before final proposals are submitted to WHO for approval. The main changes proposed are as follows. The diagnostic fasting plasma (blood) glucose value has been lowered to > or =7.0 mmol l(-1) (6.1 mmol l(-1)). Impaired Glucose Tolerance (IGT) is changed to allow for the new fasting level. A new category of Impaired Fasting Glycaemia (IFG) is proposed to encompass values which are above normal but below the diagnostic cut-off for diabetes (plasma > or =6.1 to or =5.6 to <6.1 mmol l(-1)). Gestational Diabetes Mellitus (GDM) now includes gestational impaired glucose tolerance as well as the previous GDM. The classification defines both process and stage of the disease. The processes include Type 1, autoimmune and non-autoimmune, with beta-cell destruction; Type 2 with varying degrees of insulin resistance and insulin hyposecretion; Gestational Diabetes Mellitus; and Other Types where the cause is known (e.g. MODY, endocrinopathies). It is anticipated that this group will expand as causes of Type 2 become known. Stages range from normoglycaemia to insulin required for survival. It is hoped that the new classification will allow better classification of individuals and lead to fewer therapeutic misjudgements.

15,167 citations

Journal ArticleDOI
TL;DR: It was deemed essential to develop an appropriate, uniform terminology and a functional, working classification of diabetes that reflects the current knowledge about the disease.
Abstract: the growth of knowledge regarding the etiology and pathogenesis of diabetes has led many individuals and groups in the diabetes community to express the need for a revision of the nomenclature, diagnostic criteria, and classification of diabetes. As a consequence, it was deemed essential to develop an appropriate, uniform terminology and a functional, working classification of diabetes that reflects the current knowledge about the disease. (1)

11,886 citations

Christopher M. Bishop1
01 Jan 2006
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

10,141 citations

01 Jan 2014
TL;DR: These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care.
Abstract: XI. STRATEGIES FOR IMPROVING DIABETES CARE D iabetes is a chronic illness that requires continuing medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires that many issues, beyond glycemic control, be addressed. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes. These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care. While individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. These standards are not intended to preclude more extensive evaluation and management of the patient by other specialists as needed. For more detailed information, refer to Bode (Ed.): Medical Management of Type 1 Diabetes (1), Burant (Ed): Medical Management of Type 2 Diabetes (2), and Klingensmith (Ed): Intensive Diabetes Management (3). The recommendations included are diagnostic and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A grading system (Table 1), developed by the American Diabetes Association (ADA) and modeled after existing methods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E.

9,618 citations