Two methods are currently available for left atrial (LA) strain measurement by speckle tracking echocardiography, with two different reference timings for starting the analysis: QRS (QRS-LASr) and P wave (P-LASr). The aim of MASCOT HIT study was to define which of the two was more reproducible, more feasible, and less time consuming. In 26 expert centers, LA strain was analyzed by two different echocardiographers (young vs senior) in a blinded fashion. The study population included: healthy subjects, patients with arterial hypertension or aortic stenosis (LA pressure overload, group 2) and patients with mitral regurgitation or heart failure (LA volume–pressure overload, group 3). Difference between the inter-correlation coefficient (ICC) by the two echocardiographers using the two techniques, feasibility and analysis time of both methods were analyzed. A total of 938 subjects were included: 309 controls, 333 patients in group 2, and 296 patients in group 3. The ICC was comparable between QRS-LASr (0.93) and P-LASr (0.90). The young echocardiographers calculated QRS-LASr in 90% of cases, the expert ones in 95%. The feasibility of P-LASr was 85% by young echocardiographers and 88% by senior ones. QRS-LASr young median time was 110 s (interquartile range, IR, 78-149) vs senior 110 s (IR 78-155); for P-LASr, 120 s (IR 80-165) and 120 s (IR 90-161), respectively. LA strain was feasible in the majority of patients with similar reproducibility for both methods. QRS complex guaranteed a slightly higher feasibility and a lower time wasting compared to the use of P wave as the reference.

We present here the results of the Analysis of HLA Population Data (AHPD) project of the 16th International HLA and Immunogenetics Workshop (16IHIW) held in Liverpool in May-June 2012. Thanks to the collaboration of 25 laboratories from 18 different countries, HLA genotypic data for 59 new population samples (either well-defined populations or donor registry samples) were gathered and 55 were analysed statistically following HLA-NET recommendations. The new data included, among others, large sets of well-defined populations from north-east Europe and West Asia, as well as many donor registry data from European countries. The Gene[rate] computer tools were combined to create a Gene[rate] computer pipeline to automatically (i) estimate allele frequencies by an expectation-maximization algorithm accommodating ambiguities, (ii) estimate heterozygosity, (iii) test for Hardy-Weinberg equilibrium (HWE), (iv) test for selective neutrality, (v) generate frequency graphs and summary statistics for each sample at each locus and (vi) plot multidimensional scaling (MDS) analyses comparing the new samples with previous IHIW data. Intrapopulation analyses show that HWE is rarely rejected, while neutrality tests often indicate a significant excess of heterozygotes compared with neutral expectations. The comparison of the 16IHIW AHPD data with data collected during previous workshops (12th-15th) shows that geography is an excellent predictor of HLA genetic differentiations for HLA-A, -B and -DRB1 loci but not for HLA-DQ, whose patterns are probably more influenced by natural selection. In Europe, HLA genetic variation clearly follows a north to south-east axis despite a low level of differentiation between European, North African and West Asian populations. Pacific populations are genetically close to Austronesian-speaking South-East Asian and Taiwanese populations, in agreement with current theories on the peopling of Oceania. Thanks to this project, HLA genetic variation is more clearly defined worldwide and better interpreted in relation to human peopling history and HLA molecular evolution.

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The major histocompatibility complex (MHC; 6p21.3) contains the most polymorphic genes, the most gene dense parts, and the highest diversity of functional gene clusters of the human genome. The clusters form haplotypes, which differ in linkage disequilibrium and show large variations in strength and extent between populations. Haplotype cis‐ and trans‐expression quantitative trait loci have increased the knowledge of regulatory interactions between multiple MHC genes. The detailed haplotype data offer a reference for future studies in immune‐mediated diseases and may unravel disease associations in conditions traditionally considered not to be immunologic. This article aims to describe the structural and functional variations of the MHC genes and haplotypes and their role on selected immune‐mediated diseases. In immune‐/inflammation‐mediated complex diseases, hundreds of common variants influence the development of the disease trait, but the individual variants have small effects on the disease phenotypes as seen in genome‐wide association studies. The genetic influence may still be significant on the cellular or molecular level. Nonetheless, the HLA alone is not sufficient as a susceptible genetic background to deduce the disease. For a comprehensive insight of the disease mechanisms, both immunological and genome assays methods are required.