Analysis of Body Fluid Distribution, Phase Angle and Its Association With Maximal Oxygen Consumption in Facioscapulohumeral Dystrophy: An Observational Study

Background and Aims: Body composition parameters associated with aerobic fitness, mirrored by maximal oxygen consumption (VO(2)max), have recently gained interest as indicators of physical efficiency in facioscapulohumeral dystrophy (FSHD). Bioimpedance analysis (BIA) allows a noninvasive and repeatable estimate of body composition but is based on the use of predictive equations which, if used in cohorts with different characteristics from those for which the equation was originally formulated, could give biased results. Instead, the phase angle (PhA), a BIA raw bioelectrical parameter reflecting body fluids distribution, could provide reliable data for such analysis. Methods: 33 clinically and genetically characterized FSHD patients (mean age 35.7; 10 females) and 27 sex and age-matched healthy controls (HC) were included in the analysis. BIA was used to evaluate body fluids distribution (intracellular water [ICW], extracellular water [ECW], and total body water [TBW]), and PhA, while cardiopulmonary exercise test was used to estimate VO(2)max. Results: The groups were comparable for ECW and TBW. Instead, patients showed lower values of ICW (p = 0.020), ICW/ECW ratio (p < 0.001), and PhA (p < 0.001). Moreover, patients reported lower VO(2)max (p = 0.001 for absolute values; p = 0.002 for values expressed in relation to body weight) which, unlike HC, was not associated to PhA. Conclusion: Based on our results, PhA of FSHD patients is lower than HC. Since PhA mirrors the ICW/ECW ratio, the lower share of ICW seems to be the basis of such difference. Given the lack of association with VO(2)max, PhA cannot be considered a reliable indicator of aerobic fitness in FSHD

The Italian National Registry for FSHD: an enhanced data integration and an analytics framework towards Smart Health Care and Precision Medicine for a rare disease

Background: The Italian Clinical network for FSHD (ICNF) has established the Italian National Registry for FSHD (INRF), collecting data from patients affected by Facioscapulohumeral dystrophy (FSHD) and their relatives. The INRF has gathered data from molecular analysis, clinical evaluation, anamnestic information, and family history from more than 3500 participants. Methods: A data management framework, called Mediator Environment for Multiple Information Sources (MOMIS) FSHD Web Platform, has been developed to provide charts, maps and search tools customized for specific needs. Patients’ samples and their clinical information derives from the Italian Clinical network for FSHD (ICNF), a consortium consisting of fourteen neuromuscular clinics distributed across Italy. The tools used to collect, integrate, and visualize clinical, molecular and natural history information about patients affected by FSHD and their relatives are described. Results: The INRF collected the molecular data regarding FSHD diagnosis conducted on 7197 subjects and identified 3362 individuals carrying a D4Z4 Reduced Allele (DRA): 1634 were unrelated index cases. In 1032 cases the molecular testing has been extended to 3747 relatives, 1728 carrying a DRA. Since 2009 molecular analysis has been accompanied by clinical evaluation based standardized evaluation protocols. In the period 2009–2020, 3577 clinical forms have been collected, 2059 follow the Comprehensive Clinical Evaluation form (CCEF). The integration of standardized clinical information and molecular data has made possible to demonstrate the wide phenotypic variability of FSHD. The MOMIS (Mediator Environment for Multiple Information Sources) data integration framework allowed performing genotype–phenotype correlation studies, and generated information of medical importance either for clinical practice or genetic counseling. Conclusion: The platform implemented for the FSHD Registry data collection based on OpenClinica meets the requirement to integrate patient/disease information, as well as the need to adapt dynamically to security and privacy concerns. Our results indicate that the quality of data collection in a multi-integrated approach is fundamental for clinical and epidemiological research in a rare disease and may have great value in allowing us to redefine diagnostic criteria and disease markers for FSHD. By extending the use of the MOMIS data integration framework to other countries and the longitudinal systematic collection of standardized clinical data will facilitate the understanding of disease natural history and offer valuable inputs towards trial readiness. This approach is of high significance to FSHD medical community and also to rare disease research in general

Muscle Fiber Conduction Velocity Correlates With the Age at Onset in Mild FSHD Cases

A majority of patients with facioscapulohumeral muscular dystrophy (FSHD) report severe fatigue. The aim of this study was to explore whether fatigability during a performance task is related to the main clinical features of the disease in mildly affected patients. A total of 19 individuals with a molecular genetic-based diagnosis of FSHD (median D4Z4 deletion length of 27 kb) performed two isometric flexions of the dominant biceps brachii at 20% of their maximal voluntary contraction (MVC) for 2 min, and then at 60% MVC until exhaustion. Fatigability indices (average rectified value, mean frequency, conduction velocity, and fractal dimension) were extracted from the surface electromyogram (sEMG) signal, and their correlations with age, age at onset, disease duration, D4Z4 contraction length, perceived fatigability, and clinical disability score were analyzed. The conduction velocity during the low level contraction showed a significant negative correlation with the age at onset (p < 0.05). This finding suggest the assessment of conduction velocity at low isometric contraction intensities, as a potential useful tool to highlight differences in muscle involvement in FSHD patients

Comparison of quantitative muscle ultrasound and whole-body muscle MRI in facioscapulohumeral muscular dystrophy type 1 patients

Introduction: Muscle ultrasound is a fast, non-invasive and cost-effective examination that can identify structural muscular changes by assessing muscle thickness and echointensity (EI) with a quantitative analysis (QMUS). To assess applicability and repeatability of QMUS, we evaluated patients with genetically confirmed facioscapulohumeral muscular dystrophy type 1 (FSHD1), comparing their muscle ultrasound characteristics with healthy controls and with those detected by MRI. We also evaluated relationships between QMUS and demographic and clinical characteristics. Materials and methods: Thirteen patients were included in the study. Clinical assessment included MRC sum score, FSHD score and The Comprehensive Clinical Evaluation Form (CCEF). QMUS was performed with a linear transducer scanning bilaterally pectoralis major, deltoid, rectus femoris, tibialis anterior and semimembranosus muscles in patients and healthy subjects. For each muscle, we acquired three images, which were analysed calculating muscle EI by computer-assisted grey-scale analysis. QMUS analysis was compared with semiquantitative 1.5 T muscle MRI scale. Results: All muscles in FSHD patients showed a significant increased echogenicity compared to the homologous muscles in healthy subjects. Older subjects and patients with higher FSHD score presented increased muscle EI. Tibialis anterior MRC showed a significant inverse correlation with EI. Higher median EI was found in muscles with more severe MRI fat replacement. Conclusions: QMUS allows quantitative evaluation of muscle echogenicity, displaying a tight correlation with muscular alterations, clinical and MRI data. Although a confirmation on larger sample is needed, our research suggests a possible future application of QMUS in diagnosis and management of muscular disorders

Large genotype–phenotype study in carriers of D4Z4 borderline alleles provides guidance for facioscapulohumeral muscular dystrophy diagnosis

Facioscapulohumeral muscular dystrophy (FSHD) is a myopathy with prevalence of 1 in 20,000. Almost all patients affected by FSHD carry deletions of an integral number of tandem 3.3 kilobase repeats, termed D4Z4, located on chromosome 4q35. Assessment of size of D4Z4 alleles is commonly used for FSHD diagnosis. However, the extended molecular testing has expanded the spectrum of clinical phenotypes. In particular, D4Z4 alleles with 9–10 repeat have been found in healthy individuals, in subjects with FSHD or affected by other myopathies. These findings weakened the strict relationship between observed phenotypes and their underlying genotypes, complicating the interpretation of molecular findings for diagnosis and genetic counseling. In light of the wide clinical variability detected in carriers of D4Z4 alleles with 9–10 repeats, we applied a standardized methodology, the Comprehensive Clinical Evaluation Form (CCEF), to describe and characterize the phenotype of 244 individuals carrying D4Z4 alleles with 9–10 repeats (134 index cases and 110 relatives). The study shows that 54.5% of index cases display a classical FSHD phenotype with typical facial and scapular muscle weakness, whereas 20.1% present incomplete phenotype with facial weakness or scapular girdle weakness, 6.7% display minor signs such as winged scapula or hyperCKemia, without functional motor impairment, and 18.7% of index cases show more complex phenotypes with atypical clinical features. Family studies revealed that 70.9% of relatives carrying 9–10 D4Z4 reduced alleles has no motor impairment, whereas a few relatives (10.0%) display a classical FSHD phenotype. Importantly all relatives of index cases with no FSHD phenotype were healthy carriers. These data establish the low penetrance of D4Z4 alleles with 9–10 repeats. We recommend the use of CCEF for the standardized clinical assessment integrated by family studies and further molecular investigation for appropriate diagnosis and genetic counseling. Especially in presence of atypical phenotypes and/or sporadic cases with all healthy relatives is not possible to perform conclusive diagnosis of FSHD, but all these cases need further studies for a proper diagnosis, to search novel causative genetic defects or investigate environmental factors or co-morbidities that may trigger the pathogenic process. These evidences are also fundamental for the stratification of patients eligible for clinical trials. Our work reinforces the value of large genotype–phenotype studies to define criteria for clinical practice and genetic counseling in rare diseases

Recognition models to predict DNA-binding specificities of homeodomain proteins

Motivation: Recognition models for protein-DNA interactions, which allow the prediction of specificity for a DNA-binding domain based only on its sequence or the alteration of specificity through rational design, have long been a goal of computational biology. There has been some progress in constructing useful models, especially for C2H2 zinc finger proteins, but it remains a challenging problem with ample room for improvement. For most families of transcription factors the best available methods utilize k-nearest neighbor (KNN) algorithms to make specificity predictions based on the average of the specificities of the k most similar proteins with defined specificities. Homeodomain (HD) proteins are the second most abundant family of transcription factors, after zinc fingers, in most metazoan genomes, and as a consequence an effective recognition model for this family would facilitate predictive models of many transcriptional regulatory networks within these genomes

Predicting zinc binding at the proteome level

BACKGROUND: Metalloproteins are proteins capable of binding one or more metal ions, which may be required for their biological function, for regulation of their activities or for structural purposes. Metal-binding properties remain difficult to predict as well as to investigate experimentally at the whole-proteome level. Consequently, the current knowledge about metalloproteins is only partial. RESULTS: The present work reports on the development of a machine learning method for the prediction of the zinc-binding state of pairs of nearby amino-acids, using predictors based on support vector machines. The predictor was trained using chains containing zinc-binding sites and non-metalloproteins in order to provide positive and negative examples. Results based on strong non-redundancy tests prove that (1) zinc-binding residues can be predicted and (2) modelling the correlation between the binding state of nearby residues significantly improves performance. The trained predictor was then applied to the human proteome. The present results were in good agreement with the outcomes of previous, highly manually curated, efforts for the identification of human zinc-binding proteins. Some unprecedented zinc-binding sites could be identified, and were further validated through structural modelling. The software implementing the predictor is freely available at: CONCLUSION: The proposed approach constitutes a highly automated tool for the identification of metalloproteins, which provides results of comparable quality with respect to highly manually refined predictions. The ability to model correlations between pairwise residues allows it to obtain a significant improvement over standard 1D based approaches. In addition, the method permits the identification of unprecedented metal sites, providing important hints for the work of experimentalists

The Facioscapulohumeral muscular dystrophy region on 4qter and the homologous locus on 10qter evolved independently under different evolutionary pressure

BACKGROUND: The homologous 4q and 10q subtelomeric regions include two distinctive polymorphic arrays of 3.3 kb repeats, named D4Z4. An additional BlnI restriction site on the 10q-type sequence allows to distinguish the chromosomal origin of the repeats. Reduction in the number of D4Z4 repeats below a threshold of 10 at the 4q locus is tightly linked to Facioscapulohumeral Muscular Dystrophy (FSHD), while similar contractions at 10q locus, are not pathogenic. Sequence variations due to the presence of BlnI-sensitive repeats (10q-type) on chromosome 4 or viceversa of BlnI-resistant repeats (4q-type) on chromosome 10 are observed in both alleles. RESULTS: We analysed DNA samples from 116 healthy subiects and 114 FSHD patients and determined the size distributions of polymorphic 4q and 10q alleles, the frequency and the D4Z4 repeat assortment of variant alleles, and finally the telomeric sequences both in standard and variant alleles. We observed the same frequency and types of variant alleles in FSHD patients and controls, but we found marked differences between the repeat arrays of the 4q and 10q chromosomes. In particular we detected 10q alleles completely replaced by the 4q subtelomeric region, consisting in the whole set of 4q-type repeats and the distal telomeric markers. However the reciprocal event, 10q-type subtelomeric region on chromosome 4, was never observed. At 4q locus we always identified hybrid alleles containing a mixture of 4q and 10q-type repeats. CONCLUSION: The different size distribution and different structure of 10q variant alleles as compared with 4q suggests that these loci evolved in a different manner, since the 4q locus is linked to FSHD, while no inheritable disease is associated with mutations in 10qter genomic region. Hybrid alleles on chromosome 4 always retain a minimum number of 4q type repeats, as they are probably essential for maintaining the structural and functional properties of this subtelomeric region. In addition we found: i) several instances of variant alleles that could be misinterpreted and interfere with a correct diagnosis of FSHD; ii) the presence of borderline alleles in the range of 30–40 kb that carried a qA type telomere and were not associated with the disease