Karine Clément

Bio: Karine Clément is an academic researcher from University of Paris. The author has contributed to research in topics: Adipose tissue & Medicine. The author has an hindex of 78, co-authored 275 publications receiving 32185 citations. Previous affiliations of Karine Clément include French Institute of Health and Medical Research & Hotel Dieu Hospital.

Richness of human gut microbiome correlates with metabolic markers

Abstract: We are facing a global metabolic health crisis provoked by an obesity epidemic. Here we report the human gut microbial composition in a population sample of 123 non-obese and 169 obese Danish individuals. We find two groups of individuals that differ by the number of gut microbial genes and thus gut bacterial richness. They contain known and previously unknown bacterial species at different proportions; individuals with a low bacterial richness (23% of the population) are characterized by more marked overall adiposity, insulin resistance and dyslipidaemia and a more pronounced inflammatory phenotype when compared with high bacterial richness individuals. The obese individuals among the lower bacterial richness group also gain more weight over time. Only a few bacterial species are sufficient to distinguish between individuals with high and low bacterial richness, and even between lean and obese participants. Our classifications based on variation in the gut microbiome identify subsets of individuals in the general white adult population who may be at increased risk of progressing to adiposity-associated co-morbidities.

A mutation in the human leptin receptor gene causes obesity and pituitary dysfunction

Abstract: The adipocyte-specific hormone leptin, the product of the obese (ob) gene, regulates adipose-tissue mass through hypothalamic effects on satiety and energy expenditure Leptin acts through the leptin receptor, a single-transmembrane-domain receptor of the cytokine-receptor family In rodents, homozygous mutations in genes encoding leptin or the leptin receptor cause early-onset morbid obesity, hyperphagia and reduced energy expenditure These rodents also show hypercortisolaemia, alterations in glucose homeostasis, dyslipidaemia, and infertility due to hypogonadotropic hypogonadisms In humans, leptin deficiency due to a mutation in the leptin gene is associated with early-onset obesity Here we describe a homozygous mutation in the human leptin receptor gene that results in a truncated leptin receptor lacking both the transmembrane and the intracellular domains In addition to their early-onset morbid obesity, patients homozygous for this mutation have no pubertal development and their secretion of growth hormone and thyrotropin is reduced These results indicate that leptin is an important physiological regulator of several endocrine functions in humans

Dietary intervention impact on gut microbial gene richness

Abstract: Complex gene-environment interactions are considered important in the development of obesity. The composition of the gut microbiota can determine the efficacy of energy harvest from food and changes in dietary composition have been associated with changes in the composition of gut microbial populations. The capacity to explore microbiota composition was markedly improved by the development of metagenomic approaches, which have already allowed production of the first human gut microbial gene catalogue and stratifying individuals by their gut genomic profile into different enterotypes, but the analyses were carried out mainly in non-intervention settings. To investigate the temporal relationships between food intake, gut microbiota and metabolic and inflammatory phenotypes, we conducted diet-induced weight-loss and weight-stabilization interventions in a study sample of 38 obese and 11 overweight individuals. Here we report that individuals with reduced microbial gene richness (40%) present more pronounced dys-metabolism and low-grade inflammation, as observed concomitantly in the accompanying paper. Dietary intervention improves low gene richness and clinical phenotypes, but seems to be less efficient for inflammation variables in individuals with lower gene richness. Low gene richness may therefore have predictive potential for the efficacy of intervention.

Akkermansia muciniphila and improved metabolic health during a dietary intervention in obesity: relationship with gut microbiome richness and ecology

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

Leptin regulation of bone resorption by the sympathetic nervous system and CART

Abstract: Bone remodelling, the mechanism by which vertebrates regulate bone mass, comprises two phases, namely resorption by osteoclasts and formation by osteoblasts; osteoblasts are multifunctional cells also controlling osteoclast differentiation. Sympathetic signalling via beta2-adrenergic receptors (Adrb2) present on osteoblasts controls bone formation downstream of leptin. Here we show, by analysing Adrb2-deficient mice, that the sympathetic nervous system favours bone resorption by increasing expression in osteoblast progenitor cells of the osteoclast differentiation factor Rankl. This sympathetic function requires phosphorylation (by protein kinase A) of ATF4, a cell-specific CREB-related transcription factor essential for osteoblast differentiation and function. That bone resorption cannot increase in gonadectomized Adrb2-deficient mice highlights the biological importance of this regulation, but also contrasts sharply with the increase in bone resorption characterizing another hypogonadic mouse with low sympathetic tone, the ob/ob mouse. This discrepancy is explained, in part, by the fact that CART ('cocaine amphetamine regulated transcript'), a neuropeptide whose expression is controlled by leptin and nearly abolished in ob/ob mice, inhibits bone resorption by modulating Rankl expression. Our study establishes that leptin-regulated neural pathways control both aspects of bone remodelling, and demonstrates that integrity of sympathetic signalling is necessary for the increase in bone resorption caused by gonadal failure.

WGCNA: an R package for weighted correlation network analysis.

Abstract: Correlation networks are increasingly being used in bioinformatics applications For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets These methods have been successfully applied in various biological contexts, eg cancer, mouse genetics, yeast genetics, and analysis of brain imaging data While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software Along with the R package we also present R software tutorials While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings The WGCNA package provides R functions for weighted correlation network analysis, eg co-expression network analysis of gene expression data The R package along with its source code and additional material are freely available at http://wwwgeneticsuclaedu/labs/horvath/CoexpressionNetwork/Rpackages/WGCNA

Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists

Abstract: Functional analysis of large gene lists, derived in most cases from emerging high-throughput genomic, proteomic and bioinformatics scanning approaches, is still a challenging and daunting task. The gene-annotation enrichment analysis is a promising high-throughput strategy that increases the likelihood for investigators to identify biological processes most pertinent to their study. Approximately 68 bioinformatics enrichment tools that are currently available in the community are collected in this survey. Tools are uniquely categorized into three major classes, according to their underlying enrichment algorithms. The comprehensive collections, unique tool classifications and associated questions/issues will provide a more comprehensive and up-to-date view regarding the advantages, pitfalls and recent trends in a simpler tool-class level rather than by a tool-by-tool approach. Thus, the survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.

Report of the expert committee on the diagnosis and classification of diabetes mellitus

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)

Standards of Medical Care in Diabetes

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.

Central nervous system control of food intake

Abstract: New information regarding neuronal circuits that control food intake and their hormonal regulation has extended our understanding of energy homeostasis, the process whereby energy intake is matched to energy expenditure over time. The profound obesity that results in rodents (and in the rare human case as well) from mutation of key signalling molecules involved in this regulatory system highlights its importance to human health. Although each new signalling pathway discovered in the hypothalamus is a potential target for drug development in the treatment of obesity, the growing number of such signalling molecules indicates that food intake is controlled by a highly complex process. To better understand how energy homeostasis can be achieved, we describe a model that delineates the roles of individual hormonal and neuropeptide signalling pathways in the control of food intake and the means by which obesity can arise from inherited or acquired defects in their function.