Best Practice & Research Clinical Endocrinology & Metabolism RSS feed: Current Issue. Best Practice & Research Clinical Endocrinology & Metabolism is a topical serial publication integrating the results from the latest original research into practical, evidence-based review articles that seek to address the key clinical issues of diagnosis, treatment and patient management. Each issue follows a problem-orientated approach which focuses on the key questions to be addressed, clearly defining what is known and highlighting topics for future research. Management is described in practical terms so that it can be applied to the individual patient. The series is aimed at the physician either in practice or in training. In practical paperback format, each 200 page issue of Best Practice & Research Clinical Endocrinology & Metabolism provides a comprehensive review of clinical practice and thinking within one specific area of endocrinology and metabolism. Each issue, written by an international team of contributors and guest edited by a renowned expert, form part of a continuous update of current clinical practice. • Attractive format and two-colour text layout • Six issues published annually • Highlighting the latest 'best practice' and 'clinical evidence' • Topic-based, problem-orientated approach • Recommendations on diagnosis, treatment and patient management The objective of the series is to provide the physician with the most up-to-date source of information in the field. Click here to view a full table of contents on ScienceDirect. Topics covered in 2008: Volume 22 Issue 1 Fetal and Neonatal Endocrinology P. Mullis & W. Kiess Volume 22 Issue 2 Endocrinology and the Prostate F. Labrie Volume 22 Issue 3 The Small for Gestational Age Child L.B. Johnson & M.O. Savage Volume 22 Issue 4 Endocrine and Metabolic Determinants of Cancer Risk J.M.P. Holly Volume 22 Issue 5 Osteoporosis R. Rizzoli Volume 22 Issue 6 Thyroid Nodules and Cancer F. Pacini The Publisher Andrew Miller Publishing Editor Health Sciences, Elsevier Ltd The Boulevard, Langford Lane Kidlington Oxford, OX5 1GB UK Tel: +44 1865 843823 Fax: +44 1865 843997 Email: andrew.miller@elsevier.com http://www.bprcem.com/?rss=yesElsevier Inc.en © 2011 Elsevier Ltd. All rights reserved. Best Practice & Research Clinical Endocrinology & Metabolism1521-690X262April 2012 © 2011 Elsevier Ltd. All rights reserved. healthpermissions@elsevier.comhttp://www.bprcem.com/article/PIIS1521690X11001606/abstract?rss=yesPublic interest in genomics and personalized medicine is increasing. Clinicians need to be prepared to understand the difficulties, the limits and the ethical issues related to genetic testing for disease susceptibility and pharmacogenetics. This issue of Best Practice and Research Clinical Endocrinology and Metabolism is designed to provide a state of the art update on current understanding of the genetics of metabolism and diabetes. This should help clinicians and researchers to deliver to individuals the understandable information that is ethically acceptable and scientifically sound. Murielle Bochud reviewed the key elements required to understand statistical genetics and the various study designs in clinical and epidemiological research. A comprehensive clinical approach for genetic testing in patients with obesity has been prepared by Phan-Hug F., J.S. Beckmann and S. Jacquemont. Metabolic syndrome, obesity and diabetes share a common physiopathological state recognized as insulin resistance. A. Stears, S. O’Rahilly, R. Semple and D. Savage have nicely described the importance of recognizing and classifying extreme insulin resistance based on the molecular pathogenesis of the metabolic syndrome and related traits. The recent contributions of large scale genomewide association studies (GWAS) to identify several important determinants of glucose and lipid homeostasis have been reviewed by A. Barker and E. Young and co-authors, respectively. Quantitative measures of hyperglycaemia are directly associated to micro- and macrovascular complications of diabetes. It is therefore fascinating to unravel the genetic determinants of quantitative measures of glycaemia rather than simply the presence or the absence of diabetes. The identified variants associated with hyperglycemia, diabetes, abnormal insulin secretion or action, have been used to generate genetic risk scores to predict type 2 diabetes onset. The limits of these genetic scores have been extensively reviewed by J.L. Vassy and J.B. Meigs. These prediction scores are still unable to discriminate the development of diabetes in individuals with more accuracy than clinical scores. However, the potential use of these genetic scores requires a careful evaluation to identify new areas of research, in particular in anticipating much earlier the risk of developing a disease. So it remains to be clarified if genetic testing in young individuals can offer a better motivation to start a prevention program. If GWA studies identified several variants of yet unknown significance, the molecular dissection of MODYs genes played a critical role for understanding some aspects of the pathogenesis of diabetes and related traits. Martine Vaxillaire, Amélie Bonnefond and Philippe Froguel reviewed extensively the lessons of early-onset monogenic diabetes for genomic medicine. This may have profound clinical consequences. As an example, the discovery of mutations in the KATP channel responsible for neonatal diabetes allowed the treatment of these young patients with sulfonylurea drugs rather than insulin. Widely recognized scientists in their field have kindly agreed to provide a state of the art update in this important topic of genetics of metabolism and diabetes. May I warmly thank all of them for having provided an extensive overview of the field which will be useful to all of us.PrefaceGérard Waeber10.1016/j.beem.2011.12.003Best Practice & Research Clinical Endocrinology & Metabolism 26, 2 (2012)2012-04-01Best Practice & Research Clinical Endocrinology & Metabolism2012-04-01262S1521-690X(12)X0004-6117118http://www.bprcem.com/article/PIIS1521690X11001217/abstract?rss=yesHuman genetics has progressed at an unprecedented pace during the past 10 years. DNA microarrays currently allow screening of the entire human genome with high level of coverage and we are now entering the era of high-throughput sequencing. These remarkable technical advances are influencing the way medical research is conducted and have boosted our understanding of the structure of the human genome as well as of disease biology. In this context, it is crucial for clinicians to understand the main concepts and limitations of modern genetics. This review will describe key concepts in genetics, including the different types of genetic markers in the human genome, review current methods to detect DNA variation, describe major online public databases in genetics, explain key concepts in statistical genetics and finally present commonly used study designs in clinical and epidemiological research. This review will therefore concentrate on human genetic variation analysis.Genetics for clinicians: From candidate genes to whole genome scans (technological advances)Murielle Bochud10.1016/j.beem.2011.09.001Best Practice & Research Clinical Endocrinology & Metabolism 26, 2 (2012)2012-04-01Best Practice & Research Clinical Endocrinology & Metabolism2012-04-01262S1521-690X(12)X0004-6119132http://www.bprcem.com/article/PIIS1521690X11001576/abstract?rss=yesThe obesity epidemic is associated with the recent availability of highly palatable and inexpensive caloric food as well as important changes in lifestyle. Genetic factors, however, play a key role in regulating energy balance and numerous twin studies have estimated the BMI heritability between 40 and 70%. While common variants, identified through genome-wide association studies (GWAS) point toward new pathways, their effect size are too low to be of any use in the clinic. This review therefore concentrates on genes and genomic regions associated with very high risks of human obesity. Although there are no consensus guidelines, we review how the knowledge on these “causal factors” can be translated into the clinic for diagnostic purposes. We propose genetic workups guided by clinical manifestations in patients with severe early-onset obesity. While etiological diagnoses are unequivocal in a minority of patients, new genomic tools such as Comparative Genomic Hybridization (CGH) array, have allowed the identification of novel “causal” loci and next-generation sequencing brings the promise of accelerated pace for discoveries relevant to clinical practice.Genetic testing in patients with obesityF. Phan-Hug, J.S. Beckmann, S. Jacquemont10.1016/j.beem.2011.11.010Best Practice & Research Clinical Endocrinology & Metabolism 26, 2 (2012)2012-04-01Best Practice & Research Clinical Endocrinology & Metabolism2012-04-01262S1521-690X(12)X0004-6133143http://www.bprcem.com/article/PIIS1521690X11001230/abstract?rss=yesAs well as improving diagnostic and clinical outcomes for affected patients, understanding the genetic basis of rare human metabolic disorders has resulted in several fundamental biological insights. In some cases understanding extreme phenotypes has also informed thinking about more prevalent metabolic diseases. Insulin resistance underpins the twin epidemics of obesity and type 2 diabetes as well as accounting for many of the metabolic problems encompassed by the term metabolic syndrome. This review provides a brief update on current understanding of human severe insulin resistance syndromes, before highlighting recent insights provided by studies in these rare syndromes into the molecular pathogenesis of elements of the metabolic syndrome.Metabolic insights from extreme human insulin resistance phenotypesAnna Stears, Stephen O’Rahilly, Robert K. Semple, David B. Savage10.1016/j.beem.2011.09.003Best Practice & Research Clinical Endocrinology & Metabolism 26, 2 (2012)2012-04-01Best Practice & Research Clinical Endocrinology & Metabolism2012-04-01262S1521-690X(12)X0004-6145157http://www.bprcem.com/article/PIIS1521690X1100159X/abstract?rss=yesType 2 diabetes is a complex metabolic disorder characterised by varying degrees of impairment in insulin secretion and resistance to the action of insulin. Considerable progress has been made recently in understanding the genetic determinants of diabetes. A logical next step is to describe how these variants relate to the underlying pathophysiological processes that lead to diabetes as this may provide insights into pathways to disease. These quantitative traits are, of course, of direct interest in themselves and a growing literature is now emerging on the genetic determinants of insulin secretion and insulin resistance. This review article focuses on describing the complex associations between type 2 diabetes risk variants and quantitative glycaemic traits and the relationship between variants initially discovered in association studies of these traits and risk of type 2 diabetes.Genetic determinants of glucose homeostasisAdam Barker, Claudia Langenberg, Nicholas J. Wareham10.1016/j.beem.2011.12.002Best Practice & Research Clinical Endocrinology & Metabolism 26, 2 (2012)2012-04-01Best Practice & Research Clinical Endocrinology & Metabolism2012-04-01262S1521-690X(12)X0004-6159170http://www.bprcem.com/article/PIIS1521690X11001588/abstract?rss=yesMonogenic diabetes consists of different subtypes of single gene disorders comprising a large spectrum of phenotypes, namely neonatal diabetes mellitus or monogenic diabetes of infancy, dominantly inherited familial forms of early-onset diabetes (called Maturity-Onset Diabetes of the Young) and rarer diabetes-associated syndromic diseases. All these forms diagnosed at a very-young age are unrelated to auto-immunity. Their genetic dissection has revealed major genes in developmental and/or functional processes of the pancreatic β-cell physiology, and various molecular mechanisms underlying the primary pancreatic defects. Most of these discoveries have had remarkable consequences on the patients care and patient’s long-term condition with outstanding examples of successful genomic medicine, which are highlighted in this chapter. Increasing evidence also shows that frequent polymorphisms in or near monogenic diabetes genes may contribute to adult polygenic type 2 diabetes. In this regard, unelucidated forms of monogenic diabetes represent invaluable models for identifying new targets of β-cell dysfunction.The lessons of early-onset monogenic diabetes for the understanding of diabetes pathogenesisMartine Vaxillaire, Amélie Bonnefond, Philippe Froguel10.1016/j.beem.2011.12.001Best Practice & Research Clinical Endocrinology & Metabolism 26, 2 (2012)2012-04-01Best Practice & Research Clinical Endocrinology & Metabolism2012-04-01262S1521-690X(12)X0004-6171187http://www.bprcem.com/article/PIIS1521690X11001229/abstract?rss=yesThe early identification of individuals at risk for type 2 diabetes (T2D) enables prevention. Recent genome-wide association studies (GWAS) have added at least 40 genetic variants to the list of already well characterized T2D risk predictors, including family history, obesity, and elevated fasting plasma glucose levels. Although these variants can significantly predict T2D alone and as a part of genotype risk scores, they do not yet offer clinical discrimination beyond that achieved with common clinical measurements. Future progress on at least two research fronts may improve the predictive performance of genotype information. First, expanded GWAS efforts in non-European populations will allow targeted sequencing of risk loci and the identification of true causal variants. Second, studies with longer prediction time horizons may demonstrate that genotype information performs better than clinical risk predictors over a longer period of the life course. At present, however, genetic testing cannot be recommended for clinical T2D risk prediction in adults.Is Genetic testing useful to predict type 2 diabetes?Jason L. Vassy, James B. Meigs10.1016/j.beem.2011.09.002Best Practice & Research Clinical Endocrinology & Metabolism 26, 2 (2012)2012-04-01Best Practice & Research Clinical Endocrinology & Metabolism2012-04-01262S1521-690X(12)X0004-6189201http://www.bprcem.com/article/PIIS1521690X11001515/abstract?rss=yesCirculating levels of blood lipids are heritable risk factors for atherosclerosis and heart disease, and are the target of therapeutic intervention. Studies of monogenic disorders and – more recently – genome-wide association studies have identified several important genetic determinants of blood lipid levels. These have the potential to provide new drug targets to alter blood lipid levels and may improve prediction of cardiovascular disease. Better functional validation of lipid loci is required to clarify the biological role of proteins encoded by specific genomic regions and understand how they influence lipid metabolism and confer disease risk.Genetic determinants of lipid homeostasisElizabeth H. Young, Theodore Papamarkou, Nicholas W.J. Wainwright, Manjinder S. Sandhu10.1016/j.beem.2011.11.004Best Practice & Research Clinical Endocrinology & Metabolism 26, 2 (2012)2012-04-01Best Practice & Research Clinical Endocrinology & Metabolism2012-04-01262S1521-690X(12)X0004-6203209http://www.bprcem.com/article/PIIS1521690X11001503/abstract?rss=yesGenome-wide association studies (GWAS) have revolutionised the discovery of genes for common traits and diseases, including obesity-related traits. In less then four years time, 52 genetic loci were identified to be unequivocally associated with obesity-related traits. This vast success raised hope and expectations that genetic information would become soon an integral part of personalised medicine. However, these loci have only small effects on obesity-susceptibility and explain just a fraction of the total variance. As such, their accuracy to predict obesity is poor and not competitive with the predictive ability of traditional risk factors. Nevertheless, some of these loci are being used in commercially available personal genome tests to estimate individuals’ lifetime risk of obesity. While proponents believe that personal genome profiling could have beneficial effects on behaviour, early reports do not support this hypothesis. To conclude, the most valuable contribution of GWAS-identified loci lies in their contribution to elucidating new physiological pathways that underlie obesity-susceptibility.Genetic determinants of common obesity and their value in predictionRuth J.F. Loos10.1016/j.beem.2011.11.003Best Practice & Research Clinical Endocrinology & Metabolism 26, 2 (2012)2012-04-01Best Practice & Research Clinical Endocrinology & Metabolism2012-04-01262S1521-690X(12)X0004-6211226http://www.bprcem.com/article/PIIS1521690X12000395/abstract?rss=yesKeyword index10.1016/S1521-690X(12)00039-5Best Practice & Research Clinical Endocrinology & Metabolism 26, 2 (2012)2012-04-01Best Practice & Research Clinical Endocrinology & Metabolism2012-04-01262S1521-690X(12)X0004-6I1I1