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Primary lipodystrophies represent a heterogeneous group of very rare diseases with a prevalence of less than 1 case for 100.000, inherited or acquired, caracterized by a loss of body fat either generalized or localized (lipoatrophy). In some forms, lipoatrophy is associated with a selective hypertrophy of other fat depots. Clinical signs of insulin resistance are often present: acanthosis nigricans, signs of hyperandrogenism. All lipodystrophies are associated with dysmetabolic alterations with insulin resistance, altered glucose tolerance or diabetes and hypertriglyceridemia leading to a risk of acute pancreatitis. Chronic complications are those resulting from diabetes involving the retina, kidney and nerves, cardiovascular complications and steatotic liver lesions that could result in cirrhosis. Genetic forms of generalized lipodystrophy (or Berardinelli-Seip syndrome) result, in most cases, from recessive mutations in one of two genes: either BSCL2 coding seipin or BSCL1 coding AGPAT2, an acyl-transferase involved in triglyceride synthesis. Acquired generalized lipodystrophy (Lawrence syndrome) is of unknown origin but is sometimes associated with signs of autoimmunity. Partial lipodystrophies can be familial with dominant transmission. Heterozygous mutations have been identified in the LMNA gene encoding nuclear lamin A/C belonging to the nuclear lamina, or in PPARG encoding the adipogenic transcription factor PPARgamma. Some less typical lipodystrophies, associated with signs of premature aging, have been linked to mutations in LMNA or in the ZMPSTE24 gene encoding the protease responsible for the maturation of prelamin A into lamin A. Acquired partial lipodystrophy (Barraquer-Simons syndrome) is characterized by cephalothoracic fat loss. Its aetiology is unknown but mutations in LMNB2, encoding the lamina protein lamin B2, could represent susceptibility factors. Highly active antiretroviral treatments for HIV infection are currently the most frequent cause of acquired secondary lipodystrophic syndromes. The genetic diagnosis is performed in specialized laboratories and, in the most severe forms, antenatal diagnosis could be proposed. Treatment of diabetes, dyslipidemia and complications involves the classical intervention strategies. Insulino-sensitizing drugs are useful. Therapeutic trials with recombinant human leptin in patients with very low leptin levels reported good results with respect to the metabolic and liver alterations. The prognosis is linked to the precocity and severity of the diabetic, cardiovascular and liver complications.
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PMID:[Primary lipodystrophies]. 1732 32

In 1988 the task of identifying Type 2 diabetes genes was described as a nightmare. For the next 17 years this proved to be largely correct. In the meantime the prevalence of Type 2 diabetes rose sharply due to non-genetic factors, compounding the problem of trying to find genes. Despite a huge amount of effort, progress was disappointing and only two genes, PPARG and KCNJ11, were confirmed beyond doubt as Type 2 diabetes risk factors in multiple studies. The reasons for this have been well documented and mainly consist of the use of inappropriate levels of statistical inference given the many hundreds of thousands of potential risk polymorphisms in the genome and their small effect sizes. The good news is that these problems are now surmountable and prospects for finding many more genes are bright. This year saw the identification of a third gene, TCF7L2, that has a greater impact on risk than the first two and provided important lessons for Type 2 diabetes genetic studies. The most important of these lessons was that previously unsuspected genes may be involved. In this review I discuss why this year is the start of a new era in our understanding of Type 2 diabetes genes and how this may lead to improved patient care.
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PMID:A new era in finding Type 2 diabetes genes-the unusual suspects. 1756 64

The contribution of genetic factors to the development of obesity has been widely recognized, but the identity of the genes involved has not yet been fully clarified. Variation in genes involved in adipocyte differentiation and energy metabolism is expected to have a role in the etiology of obesity. We assessed the potential association of a polymorphism in one candidate gene, peroxisome proliferator-activated receptor-gamma (PPARGgamma), involved in these pathways and obesity-related phenotypes in 335 Brazilians of European descent. All individuals included in the sample were adults. Pregnant women, as well as those individuals with secondary hyperlipidemia due to renal, liver or thyroid disease, and diabetes, were not invited to participate in the study; all other individuals were included. The gene variant PPARG Pro12Ala was studied by a PCR-based method and the association between this genetic polymorphism and obesity-related phenotypes was evaluated by analysis of covariance. Variant allele frequency was PPARG Ala12 = 0.09 which is in the same range as described for European and European-derived populations. No statistically significant differences were observed for mean total cholesterol, LDL cholesterol, HDL cholesterol, or triglyceride levels among PPARG genotypes in either gender. In the male sample, an association between the PPARG Pro12Ala variant and body mass index was detected, with male carriers of the Ala variant presenting a higher mean body mass index than wild-type homozygotes (28.3 vs 26.2 kg/m2, P = 0.037). No effect of this polymorphism was detected in women. This finding suggests that the PPARG gene has a gender-specific effect and contributes to the susceptibility to obesity in this population.
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PMID:Effects of a PPARG gene variant on obesity characteristics in Brazil. 1765 45

A well-worn medical aphorism states that "when you hear hoof beats, think of a horse and not a zebra." When applying this principle to the cardiometabolic syndrome (CMS), the horse would be represented by the prevalent CMS phenotype that affects approximately 30% of individuals in Westernized societies, while the zebra is represented by very rare conditions--such as lipodystrophy syndromes--that share some features with the more prevalent CMS. For instance, familial partial lipodystrophy types 2 and 3 result from heterozygous mutations in LMNA, encoding nuclear lamin A/C, and in PPARG, encoding peroxisome proliferator-activated receptor (PPAR)-gamma, respectively. Patients with either subtype of partial lipodystrophy exhibit an increased ratio of central to peripheral fat stores, dysglycemia, dyslipidemia, and hypertension, with predisposition for developing insulin-resistant diabetes and atherosclerosis end points. Sometimes, however, the zebra serves as a model that can help us understand the horse, so that the rare partial lipodystrophies might offer some insight into pathogenesis and treatment of the more prevalent CMS.
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PMID:Genetic forms of the cardiometabolic syndrome: what can they tell the clinician? 1768 46

Diabetes mellitus is one of the most common endocrine disorders. It affects almost 6% of the world's population, and its prevalence continues to increase. The causes of diabetes mellitus are multifactorial, and in the general population both genetic and environmental factors contribute evenly to its development. Several genes have been consistently associated with type 2 diabetes mellitus; however, it is not clear how many of those translate into increased cardiovascular disease risk. Recent evidence suggests that genetic variation at the CALPN10, FABP4, GK, GST, PPARA, and PPARG loci may confer higher cardiovascular disease risk in patients with type 2 diabetes mellitus. However, the evidence is scattered and inconclusive and its translation into practical clinical testing will require studies properly designed to examine not only simple genetic associations but also gene-gene and gene-environment interactions.
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PMID:Genetic links between diabetes mellitus and coronary atherosclerosis. 1824 14

The Pro12Ala polymorphism of peroxisome proliferator-activated receptor-gamma (PPARG; NCBI dbSNP rs1801282) has been associated with preservation of cognitive function, decreased risk of diabetes, and increased risk of obesity. We attempted to replicate these associations, testing cognitive function and lifetime cognitive change in 519 participants who took the same cognitive test at ages 11 and 79 years. Scores were also available for other cognitive tests at age 79 years, along with history of diabetes, current Body Mass Index (BMI), and other disease and demographic variables. Pro12Ala carrier status was not directly associated with diabetes history or BMI. In carriers who contracted diabetes despite carrying the protective allele, cognitive decline as measured by one test was significantly greater than in other groups. Only six individuals fell into this group; the other cognitive tests did not show this effect. This sample did not replicate the direct association of the PPARG Pro12Ala allele with diabetes status or preserved cognitive function. The data did suggest that risk of cognitive decline is greater when Pro12Ala carriers contract diabetes.
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PMID:PPARG Pro12Ala genotype and risk of cognitive decline in elders? Maybe with diabetes. 1828 41

Genome-wide association (GWA) studies identified novel gene variants that are associated with type 2 diabetes. However, results were not always consistent across different populations. Thus, the aims of this study were (i) to replicate findings from previous GWA studies in mainly Northern European populations using data from the German KORA 500 K diabetes project and (ii) to assess the impact of BMI on associations between single nucleotide polymorphisms (SNPs) and type 2 diabetes. The KORA 500 K diabetes project includes 433 cases with validated type 2 diabetes and 1 438 nondiabetic controls from two population-based KORA surveys. Genotyping was performed using the Affymetrix GeneChip Human Mapping 500 K Array Set. We investigated associations between SNPs and type 2 diabetes in 10 genes that have been reported to increase the risk of type 2 diabetes or were in complete or near-complete linkage disequilibrium with these variants. SNPs in the CDKAL1 gene showed the strongest association with type 2 diabetes [range of age and sex-adjusted odds ratios (OR): 1.30-1.39, p-values 0.0008-0.0004]. In addition, we found evidence for association of SNPs in the genes PPARG, IGF2BP2, HHEX, TCF7L2, and FTO with type 2 diabetes in the same directions as previously described (p<0.05), but not for WFS1, CDKN2A/B, KCNJ11, or EXT2. Adjustment for BMI slightly strengthened the link between CDKAL1 and type 2 diabetes, but had almost no impact on the other associations. We conclude that gene variants of CDKAL1, PPARG, IGF2BP2, HHEX, TCF7L2, and FTO predispose to type 2 diabetes in the German KORA 500 K study population. These associations appear to be independent of BMI.
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PMID:Variants of the PPARG, IGF2BP2, CDKAL1, HHEX, and TCF7L2 genes confer risk of type 2 diabetes independently of BMI in the German KORA studies. 1859 14

Type 2 diabetes is one of the fastest growing public health problems worldwide. Both environmental (e.g. physical activity, obesity, and diet) and genetic factors are involved in the development of type 2 diabetes. The associations between physical activity and diabetes risk have been assessed by a number of prospective studies and clinical trials. The results from these studies consistently indicate that the regular physical activity during occupation, commuting, leisure time or daily life reduces the risk of type 2 diabetes by 15-60%; and lifestyle intervention, including counselling for physical activity, nutrition, and body weight, can reduce the risk of type 2 diabetes by 40-60% among adults with impaired glucose tolerance and by about 20% among general individuals. In the past decade, studies using traditional linkage analysis and candidate-gene association approach have found dozens of genes harboring common variants that were related to the common-form type 2 diabetes. However, most reported associations are lack of reproducibility, except TCF7L2, PPARG, CAPN10, and KCNJ11. Since 2007, seven genome-wide association (GWA) studies emerged to generate a list of new diabetes genes. The genetic effects are largely of moderate size. These findings provide novel insight into the diabetes etiology and pave new avenue for predicting the disease risk using genetic information. In addition, data especially those from intervention trials display preliminary but promising evidence that the genetic variants might interact with physical activity in predisposing to type 2 diabetes. The gene-environment interactions merit extensive exploration in large, prospective studies.
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PMID:Genes, environment, and interactions in prevention of type 2 diabetes: a focus on physical activity and lifestyle changes. 1878 59

Prediction of the disease status is one of the most important objectives of genetic studies. To select the genes with strong evidence of the association with type 2 diabetes mellitus, we validated the associations of the seven candidate loci extracted in our earlier study by genotyping the samples in two independent sample panels. However, except for KCNQ1, the association of none of the remaining seven loci was replicated. We then selected 11 genes, KCNQ1, TCF7L2, CDKAL1, CDKN2A/B, IGF2BP2, SLC30A8, HHEX, GCKR, HNF1B, KCNJ11 and PPARG, whose associations with diabetes have already been reported and replicated either in the literature or in this study in the Japanese population. As no evidence of the gene-gene interaction for any pair of the 11 loci was shown, we constructed a prediction model for the disease using the logistic regression analysis by incorporating the number of the risk alleles for the 11 genes, as well as age, sex and body mass index as independent variables. Cumulative risk assessment showed that the addition of one risk allele resulted in an average increase in the odds for the disease of 1.29 (95% CI=1.25-1.33, P=5.4 x 10(-53)). The area under the receiver operating characteristic curve, an estimate of the power of the prediction model, was 0.72, thereby indicating that our prediction model for type 2 diabetes may not be so useful but has some value. Incorporation of data from additional risk loci is most likely to increase the predictive power.
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PMID:Construction of a prediction model for type 2 diabetes mellitus in the Japanese population based on 11 genes with strong evidence of the association. 1924 72

Genetic variation can impact on efficacy and risk of adverse events to commonly used oral agents in -diabetes. Metformin is not metabolized and its mechanism of action remains debated; however, several cation transporters have been identified. Variation in these pharmacokinetic genes might influence metformin response. Conversely, although the cytochrome P450 system has been implicated in sulfonylurea response in some small studies, to date variants affecting pharmacodynamics, including those in ABCC8 (SUR1) and TCF7L2, are the most promising. For thiazolidinedione response, variants in PPARG or ADIPOQ (adiponectin) have been variably associated with response. With increasing well-phenotyped cohorts and new methods, including genome-wide association studies, the next few years offer great hope to use pharmacogenetics to unravel drug and disease mechanisms, as well as the possibility to individualize therapy by genotype.
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PMID:Pharmacogenetics in diabetes. 1932 63


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