Genetic architecture of the APM1 gene and its influence on adiponectin plasma levels and parameters of the metabolic syndrome in 1,727 healthy Caucasians

Copyright: Copyright 2008 Elsevier B.V., All rights reserved.The associations of the adiponectin (APM1) gene with parameters of the metabolic syndrome are inconsistent. We performed a systematic investigation based on fine-mapped single nucleotide polymorphisms (SNPs) highlighting the genetic architecture and their role in modulating adiponectin plasma concentrations in a particularly healthy population of 1,727 Caucasians avoiding secondary effects from disease processes. Genotyping 53 SNPs (average spacing of 0.7 kb) in the APM1 gene region in 81 Caucasians revealed a two-block linkage disequilibrium (LD) structure and enabled comprehensive tag SNP selection. We found particularly strong associations with adiponectin concentrations for 11 of the 15 tag SNPs in the 1,727 subjects (five P values <0.0001). Haplotype analysis provided a thorough differentiation of adiponectin concentrations with 9 of 17 haplotypes showing significant associations (three P values <0.0001). No significant association was found for any SNP with the parameters of the metabolic syndrome. We observed a two-block LD structure of APM1 pointing toward at least two independent association signals, one including the promoter SNPs and a second spanning the relevant exons. Our data on a large number of healthy subjects suggest a clear modulation of adiponectin concentrations by variants of APM1, which are not merely a concomitant effect in the course of type 2 diabetes or coronary artery disease.publishersversionPeer reviewe

Mitochondrial DNA haplogroup T is associated with coronary artery disease and diabetic retinopathy: a case control study

<p>Abstract</p> <p>Background</p> <p>There is strong and consistent evidence that oxidative stress is crucially involved in the development of atherosclerotic vascular disease. Overproduction of reactive oxygen species (ROS) in mitochondria is an unifying mechanism that underlies micro- and macrovascular atherosclerotic disease. Given the central role of mitochondria in energy and ROS production, mitochondrial DNA (mtDNA) is an obvious candidate for genetic susceptibility studies on atherosclerotic processes. We therefore examined the association between mtDNA haplogroups and coronary artery disease (CAD) as well as diabetic retinopathy.</p> <p>Methods</p> <p>This study of Middle European Caucasians included patients with angiographically documented CAD (n = 487), subjects with type 2 diabetes mellitus with (n = 149) or without (n = 78) diabetic retinopathy and control subjects without clinical manifestations of atherosclerotic disease (n = 1527). MtDNA haplotyping was performed using multiplex PCR and subsequent multiplex primer extension analysis for determination of the major European haplogroups. Haplogroup frequencies of patients were compared to those of control subjects without clinical manifestations of atherosclerotic disease.</p> <p>Results</p> <p>Haplogroup T was significantly more prevalent among patients with CAD than among control subjects (14.8% vs 8.3%; p = 0.002). In patients with type 2 diabetes, the presence of diabetic retinopathy was also significantly associated with a higher prevalence of haplogroup T (12.1% vs 5.1%; p = 0.046).</p> <p>Conclusion</p> <p>Our data indicate that the mtDNA haplogroup T is associated with CAD and diabetic retinopathy in Middle European Caucasian populations.</p

Automatic identification of variables in epidemiological datasets using logic regression

textabstractBackground: For an individual participant data (IPD) meta-analysis, multiple datasets must be transformed in a consistent format, e.g. using uniform variable names. When large numbers of datasets have to be processed, this can be a time-consuming and error-prone task. Automated or semi-automated identification of variables can help to reduce the workload and improve the data quality. For semi-automation high sensitivity in the recognition of matching variables is particularly important, because it allows creating software which for a target variable presents a choice of source variables, from which a user can choose the matching one, with only low risk of having missed a correct source variable. Methods: For each variable in a set of target variables, a number of simple rules were manually created. With logic regression, an optimal Boolean combination of these rules was searched for every target variable, using a random subset of a large database of epidemiological and clinical cohort data (construction subset). In a second subset of this database (validation subset), this optimal combination rules were validated. Results: In the construction sample, 41 target variables were allocated on average with a positive predictive value (PPV) of 34%, and a negative predictive value (NPV) of 95%. In the validation sample, PPV was 33%, whereas NPV remained at 94%. In the construction sample, PPV was 50% or less in 63% of all variables, in the validation sample in 71% of all variables. Conclusions: We demonstrated that the application of logic regression in a complex data management task in large epidemiological IPD meta-analyses is feasible. However, the performance of the algorithm is poor, which may require backup strategies

The potential of sentinel-1 data to supplement high resolution earth observation data for monitoring green areas in cities

Green areas play an important role within urban agglomerations due to their impact on local climate and their recreation function. For detailed monitoring, frameworks like the flora fauna habitat (FFH) classification scheme of the European Union's Habitat Directive are broadly used. By date, FFH classifications are mostly expert-based. Within this study, a data-driven approach for FFH classification is tested. For two test areas in the municipality of Vienna, ALS point cloud data are used to derive predictor variables like terrain features, vegetation structure and potential insulation as well as reflection properties from full waveform analysis on a 1m grid. In addition, Sentinel-1 C-Band time series data are used to increase the temporal resolution of the predicting features and to add phenological characteristics. For two 1.3×1.3km test tiles, random forest classifiers are trained using different combinations (ALS, SAR, ALS+SAR) of input features. For all model test runs, the combination of ALS and SAR input features lead to best prediction accuracies when applied on test data.ISSN:1682-1750ISSN:2194-9034ISSN:1682-177

Pompe disease in Austria: clinical, genetic and epidemiological aspects

In this study, we performed a survey of infantile and late-onset Pompe disease (IOPD and LOPD) in Austria. Paediatric and neuromuscular centres were contacted to provide a set of anonymized clinical and genetic data of patients with IOPD and LOPD. The number of patients receiving enzyme replacement therapy (ERT) was obtained from the pharmaceutical company providing alglucosidase alfa. We found 25 patients in 24 families, 4 IOPD and 21 LOPD with a resulting prevalence of 1:350,914. The most frequent clinical manifestation in LOPD was a lower limb-girdle phenotype combined with axial weakness. Three patients were clinically pauci- or asymptomatic and were diagnosed because of persistent hyperCKemia. Diagnostic delay in LOPD was 7.4 ± 9.7 years. The most common mutation was c.-32-13T > G. All IOPD and 17 symptomatic LOPD patients are receiving ERT. Standardized follow-up was only available in six LOPD patients for the 6-min walk test (6minWT) and in ten for the forced vital capacity (FVC). Mean FVC did not decline (before ERT; 63.6 ± 39.7%; last evaluation during ERT: 61.9 ± 26.9%; P = 0.5) while there was a trend to decline in the mean distance covered by the 6minWT (before ERT: 373.5 ± 117.9 m; last evaluation during ERT: 308.5 ± 120.8 m; P = 0.077). The study shows a lower prevalence of Pompe disease in Austria than in other European countries and corroborates a limb-girdle phenotype with axial weakness as the most common clinical presentation, although asymptomatic hyperCKemia may be the first indication of LOPD

The clinical and molecular landscape of congenital myasthenic syndromes in Austria: a nationwide study.

BACKGROUND: Congenital myasthenic syndromes (CMS) are a heterogeneous group of disorders caused by genetic defects resulting in impaired neuromuscular transmission. Although effective treatments are available, CMS is probably underdiagnosed, and systematic clinico-genetic investigations are warranted. METHODS: We used a nationwide approach to collect Austrian patients with genetically confirmed CMS. We provide a clinical and molecular characterization of this cohort and aimed to ascertain the current frequency of CMS in Austria. RESULTS: Twenty-eight cases with genetically confirmed CMS were identified, corresponding to an overall prevalence of 3.1 per million (95% CI 2.0-4.3) in Austria. The most frequent genetic etiology was CHRNE (n = 13), accounting for 46.4% of the cohort. Within this subgroup, the variant c.1327del, p.(Glu443Lysfs*64) was detected in nine individuals. Moreover, causative variants were found in DOK7 (n = 4), RAPSN (n = 3), COLQ (n = 2), GMPPB (n = 2), CHAT (n = 1), COL13A1 (n = 1), MUSK (n = 1) and AGRN (n = 1). Clinical onset within the first year of life was reported in one half of the patients. Across all subtypes, the most common symptoms were ptosis (85.7%), lower limb (67.9%), upper limb (60.7%) and facial weakness (60.7%). The majority of patients (96.4%) received specific treatment, including acetylcholinesterase inhibitors in 20, adrenergic agonists in 11 and 3,4-diaminopyridine in nine patients. CONCLUSIONS: Our study presents the first systematic characterization of individuals with CMS in Austria, providing prevalence estimates and genotype-phenotype correlations that may help to improve the diagnostic approach and patient management