Clinical features of patients with homozygous complement C4A or C4B deficiency

Introduction Homozygous deficiencies of complement C4A or C4B are detected in 1-10% of populations. In genome-wide association studies C4 deficiencies are missed because the genetic variation of C4 is complex. There are no studies where the clinical presentation of these patients is analyzed. This study was aimed to characterize the clinical features of patients with homozygous C4A or C4B deficiency. Material and methods Thirty-two patients with no functional C4A, 87 patients with no C4B and 120 with normal amount of C4 genes were included. C4A and C4B numbers were assessed with genomic quantitative real-time PCR. Medical history was studied retrospectively from patients' files. Results Novel associations between homozygous C4A deficiency and lymphoma, coeliac disease and sarcoidosis were detected. These conditions were present in 12.5%, (4/32 in patients vs. 0.8%, 1/120, in controls, OR = 17.00, 95%Cl = 1.83-158.04, p = 0.007), 12.5% (4/32 in patients vs. 0%, 0/120 in controls, OR = 1.14, 95%Cl = 1.00-1.30, p = 0.002) and 12.5%, respectively (4/32 in patients vs. 2.5%, 3/120 in controls, OR = 5.571, 95%Cl = 1.79-2.32, p = 0.036). In addition, C4A and C4B deficiencies were both associated with adverse drug reactions leading to drug discontinuation (34.4%, 11/32 in C4A-deficient patients vs. 14.2%, 17/120 in controls, OR = 3.174, 95%Cl = 1.30-7.74, p = 0.009 and 28.7%, 25/87 in C4B-deficient patients, OR = 2.44, 95%Cl = 1.22-4.88, p = 0.010). Conclusion This reported cohort of homozygous deficiencies of C4A or C4B suggests that C4 deficiencies may have various unrecorded disease associations. C4 gene should be considered as a candidate gene in studying these selected disease associations.Peer reviewe

Translating land cover/land use classifications to habitat taxonomies for landscape monitoring: A Mediterranean assessment

Periodic monitoring of biodiversity changes at a landscape scale constitutes a key issue for conservation managers. Earth observation (EO) data offer a potential solution, through direct or indirect mapping of species or habitats. Most national and international programs rely on the use of land cover (LC) and/or land use (LU) classification systems. Yet, these are not as clearly relatable to biodiversity in comparison to habitat classifications, and provide less scope for monitoring. While a conversion from LC/LU classification to habitat classification can be of great utility, differences in definitions and criteria have so far limited the establishment of a unified approach for such translation between these two classification systems. Focusing on five Mediterranean NATURA 2000 sites, this paper considers the scope for three of the most commonly used global LC/LU taxonomies—CORINE Land Cover, the Food and Agricultural Organisation (FAO) land cover classification system (LCCS) and the International Geosphere-Biosphere Programme to be translated to habitat taxonomies. Through both quantitative and expert knowledge based qualitative analysis of selected taxonomies, FAO-LCCS turns out to be the best candidate to cope with the complexity of habitat description and provides a framework for EO and in situ data integration for habitat mapping, reducing uncertainties and class overlaps and bridging the gap between LC/LU and habitats domains for landscape monitoring—a major issue for conservation. This study also highlights the need to modify the FAO-LCCS hierarchical class description process to permit the addition of attributes based on class-specific expert knowledge to select multi-temporal (seasonal) EO data and improve classification. An application of LC/LU to habitat mapping is provided for a coastal Natura 2000 site with high classification accuracy as a result

Homology modelling and spectroscopy, a never-ending love story

Homology modelling is normally the technique of choice when experimental structure data are not available but three-dimensional coordinates are needed, for example, to aid with detailed interpretation of results of spectroscopic studies. Herein, the state of the art of homology modelling will be described in the light of a series of recent developments, and an overview will be given of the problems and opportunities encountered in this field. The major topic, the accuracy and precision of homology models, will be discussed extensively due to its influence on the reliability of conclusions drawn from the combination of homology models and spectroscopic data. Three real-world examples will illustrate how both homology modelling and spectroscopy can be beneficial for (bio)medical research

SAF-A Regulates Interphase Chromosome Structure through Oligomerization with Chromatin-Associated RNAs

Higher eukaryotic chromosomes are organized into topologically constrained functional domains; however, the molecular mechanisms required to sustain these complex interphase chromatin structures are unknown. A stable matrix underpinning nuclear organization was hypothesized, but the idea was abandoned as more dynamic models of chromatin behavior became prevalent. Here, we report that scaffold attachment factor A (SAF-A), originally identified as a structural nuclear protein, interacts with chromatin-associated RNAs (caRNAs) via its RGG domain to regulate human interphase chromatin structures in a transcription-dependent manner. Mechanistically, this is dependent on SAF-A’s AAA+ ATPase domain, which mediates cycles of protein oligomerization with caRNAs, in response to ATP binding and hydrolysis. SAF-A oligomerization decompacts large-scale chromatin structure while SAF-A loss or monomerization promotes aberrant chromosome folding and accumulation of genome damage. Our results show that SAF-A and caRNAs form a dynamic, transcriptionally responsive chromatin mesh that organizes large-scale chromosome structures and protects the genome from instability

Modulation of Genetic Associations with Serum Urate Levels by Body-Mass-Index in Humans

We tested for interactions between body mass index (BMI) and common genetic variants affecting serum urate levels, genome-wide, in up to 42569 participants. Both stratified genome-wide association (GWAS) analyses, in lean, overweight and obese individuals, and regression-type analyses in a non BMI-stratified overall sample were performed. The former did not uncover any novel locus with a major main effect, but supported modulation of effects for some known and potentially new urate loci. The latter highlighted a SNP at RBFOX3 reaching genome-wide significant level (effect size 0.014, 95% CI 0.008-0.02, P-inter= 2.6 x 10(-8)). Two top loci in interaction term analyses, RBFOX3 and ERO1LB-EDAR-ADD, also displayed suggestive differences in main effect size between the lean and obese strata. All top ranking loci for urate effect differences between BMI categories were novel and most had small magnitude but opposite direction effects between strata. They include the locus RBMS1-TANK (men, Pdifflean-overweight= 4.7 x 10(-8)), a region that has been associated with several obesity related traits, and TSPYL5 (men, Pdifflean-overweight= 9.1 x 10(-8)), regulating adipocytes-produced estradiol. The top-ranking known urate loci was ABCG2, the strongest known gout risk locus, with an effect halved in obese compared to lean men (Pdifflean-obese= 2 x 10(-4)). Finally, pathway analysis suggested a role for N-glycan biosynthesis as a prominent urate-associated pathway in the lean stratum. These results illustrate a potentially powerful way to monitor changes occurring in obesogenic environment.Peer reviewe