Genetic and Metabolic Determinants of Atrial Fibrillation in a General Population Sample: The CHRIS Study.

Atrial fibrillation (AF) is a supraventricular arrhythmia deriving from uncoordinated electrical activation with considerable associated morbidity and mortality. To expand the limited understanding of AF biological mechanisms, we performed two screenings, investigating the genetic and metabolic determinants of AF in the Cooperative Health Research in South Tyrol study. We found 110 AF cases out of 10,509 general population individuals. A genome-wide association scan (GWAS) identified two novel loci (p-value < 5 × 10-8) around SNPs rs745582874, next to gene PBX1, and rs768476991, within gene PCCA, with genotype calling confirmed by Sanger sequencing. Risk alleles at both SNPs were enriched in a family detected through familial aggregation analysis of the phenotype, and both rare alleles co-segregated with AF. The metabolic screening of 175 metabolites, in a subset of individuals, revealed a 41% lower concentration of lysophosphatidylcholine lysoPC a C20:3 in AF cases compared to controls (p-adj = 0.005). The genetic findings, combined with previous evidence, indicate that the two identified GWAS loci may be considered novel genetic rare determinants for AF. Considering additionally the association of lysoPC a C20:3 with AF by metabolic screening, our results demonstrate the valuable contribution of the combined genomic and metabolomic approach in studying AF in large-scale population studies.

HDAC Inhibition Improves the Sarcoendoplasmic Reticulum Ca2+-ATPase Activity in Cardiac Myocytes.

SERCA2a is the Ca2+ ATPase playing the major contribution in cardiomyocyte (CM) calcium removal. Its activity can be regulated by both modulatory proteins and several post-translational modifications. The aim of the present work was to investigate whether the function of SERCA2 can be modulated by treating CMs with the histone deacetylase (HDAC) inhibitor suberanilohydroxamic acid (SAHA). The incubation with SAHA (2.5 µM, 90 min) of CMs isolated from rat adult hearts resulted in an increase of SERCA2 acetylation level and improved ATPase activity. This was associated with a significant improvement of calcium transient recovery time and cell contractility. Previous reports have identified K464 as an acetylation site in human SERCA2. Mutants were generated where K464 was substituted with glutamine (Q) or arginine (R), mimicking constitutive acetylation or deacetylation, respectively. The K464Q mutation ameliorated ATPase activity and calcium transient recovery time, thus indicating that constitutive K464 acetylation has a positive impact on human SERCA2a (hSERCA2a) function. In conclusion, SAHA induced deacetylation inhibition had a positive impact on CM calcium handling, that, at least in part, was due to improved SERCA2 activity. This observation can provide the basis for the development of novel pharmacological approaches to ameliorate SERCA2 efficiency.

FamAgg: an R package to evaluate familial aggregation of traits in large pedigrees.

UNLABELLED: Familial aggregation analysis is the first fundamental step to perform when assessing the extent of genetic background of a disease. However, there is a lack of software to analyze the familial clustering of complex phenotypes in very large pedigrees. Such pedigrees can be utilized to calculate measures that express trait aggregation on both the family and individual level, providing valuable directions in choosing families for detailed follow-up studies. We developed FamAgg, an open source R package that contains both established and novel methods to investigate familial aggregation of traits in large pedigrees. We demonstrate its use and interpretation by analyzing a publicly available cancer dataset with more than 20 000 participants distributed across approximately 400 families. AVAILABILITY AND IMPLEMENTATION: The FamAgg package is freely available at the Bioconductor repository, http://www.bioconductor.org/packages/FamAgg CONTACT: Christian.Weichenberger@eurac.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Dintor: functional annotation of genomic and proteomic data.

BACKGROUND: During the last decade, a great number of extremely valuable large-scale genomics and proteomics datasets have become available to the research community. In addition, dropping costs for conducting high-throughput sequencing experiments and the option to outsource them considerably contribute to an increasing number of researchers becoming active in this field. Even though various computational approaches have been developed to analyze these data, it is still a laborious task involving prudent integration of many heterogeneous and frequently updated data sources, creating a barrier for interested scientists to accomplish their own analysis. RESULTS: We have implemented Dintor, a data integration framework that provides a set of over 30 tools to assist researchers in the exploration of genomics and proteomics datasets. Each of the tools solves a particular task and several tools can be combined into data processing pipelines. Dintor covers a wide range of frequently required functionalities, from gene identifier conversions and orthology mappings to functional annotation of proteins and genetic variants up to candidate gene prioritization and Gene Ontology-based gene set enrichment analysis. Since the tools operate on constantly changing datasets, we provide a mechanism to unambiguously link tools with different versions of archived datasets, which guarantees reproducible results for future tool invocations. We demonstrate a selection of Dintor's capabilities by analyzing datasets from four representative publications. The open source software can be downloaded and installed on a local Unix machine. For reasons of data privacy it can be configured to retrieve local data only. In addition, the Dintor tools are available on our public Galaxy web service at http://dintor.eurac.edu . CONCLUSIONS: Dintor is a computational annotation framework for the analysis of genomic and proteomic datasets, providing a rich set of tools that cover the most frequently encountered tasks. A major advantage is its capability to consistently handle multiple versions of tool-associated datasets, supporting the researcher in delivering reproducible results.

The Cooperative Health Research in South Tyrol (CHRIS) study: rationale, objectives, and preliminary results.

The Cooperative Health Research In South Tyrol (CHRIS) study is a population-based study with a longitudinal lookout to investigate the genetic and molecular basis of age-related common chronic conditions and their interaction with life style and environment in the general population. All adults of the middle and upper Vinschgau/Val Venosta are invited, while 10,000 participants are anticipated by mid-2017. Family participation is encouraged for complete pedigree reconstruction and disease inheritance mapping. After a pilot study on the compliance with a paperless assessment mode, computer-assisted interviews have been implemented to screen for conditions of the cardiovascular, endocrine, metabolic, genitourinary, nervous, behavioral, and cognitive system. Fat intake, cardiac health, and tremor are assessed instrumentally. Nutrient intake, physical activity, and life-course smoking are measured semi-quantitatively. Participants are phenotyped for 73 blood and urine parameters and 60 aliquots per participant are biobanked (cryo-preserved urine, DNA, and whole and fractionated blood). Through liquid-chromatography mass-spectrometry analysis, metabolite profiling of the mitochondrial function is assessed. Samples are genotyped on 1 million variants with the Illumina HumanOmniExpressExome array and the first data release including 4570 fully phenotyped and genotyped samples is now available for analysis. Participants' follow-up is foreseen 6 years after the first visit. The target population is characterized by long-term social stability and homogeneous environment which should both favor the identification of enriched genetic variants. The CHRIS cohort is a valuable resource to assess the contribution of genomics, metabolomics, and environmental factors to human health and disease. It is awaited that this will result in the identification of novel molecular targets for disease prevention and treatment.

Haplotype analysis of the 4p16.3 region in Portuguese families with Huntington's disease.

Huntington's disease (HD) is a neurodegenerative disorder characterized by involuntary choreic movements, cognitive impairment, and behavioral changes, caused by the expansion of an unstable CAG repeat in HTT. We characterized the genetic diversity of the HD mutation by performing an extensive haplotype analysis of ∼1Mb region flanking HTT in over 300 HD families of Portuguese origin. We observed that haplotype A, marked by HTT delta2642, was enriched in HD chromosomes and carried the two largest expansions reported in the Portuguese population. However, the most frequent HD haplotype B carried one of the largest (+12 CAGs) expansions, which resulted in an allele class change to full penetrance. Despite having a normal CAG distribution skewed to the higher end of the range, these two core haplotypes had similar expanded CAG repeat sizes compared to the other major core haplotypes (C and D) and there was no statistical difference in transmitted repeat instability across haplotypes. We observed a diversity of HTT region haplotypes in both normal and expanded chromosomes, representative of more than one ancestral chromosome underlying HD in Portugal, where multiple independent events on distinct chromosome 4 haplotypes have given rise to expansion into the pathogenic range.

SNP-based linkage analysis in extended pedigrees: comparison between two alternative approaches.

BACKGROUND: Linkage analysis on extended pedigrees is often challenged by the high computational demand of exact identity-by-descent (IBD) matrix reconstruction. When such an analysis becomes not feasible, two alternative solutions are contrasted: a full pedigree analysis based on approximate IBD estimation versus a pedigree splitting followed by exact IBD estimation. A multiple splitting (MS) approach, which combines linkage results across different splitting configurations, has been proposed to increase the power of single-split solutions. METHODS: To assess whether MS can achieve a comparable power to a full pedigree analysis, we compared the power of linkage on a very large pedigree in both simulated and real-case scenarios, using variance components linkage analysis of a dense SNP array. RESULTS: Our results confirm that the power to detect linkage is affected by the pedigree size. The MS approach showed higher power than the single-split analysis, but it was substantially less powerful than the full pedigree approach in both scenarios, at any level of significance and variance explained by a quantitative trait locus. CONCLUSION: The MS approach should always be preferred to analyses based on a single split but, when adequate computational resources are available, a full pedigree analysis is better than the MS analysis. Rather than focusing on how to best split a pedigree, it might be more valuable to identify computational solutions that can make the IBD estimation of dense-marker maps practically feasible, thus allowing a full pedigree analysis.