Response of plasma microRNAs to nusinersen treatment in patients with SMA.

peer reviewedOBJECTIVE: Spinal muscular atrophy (SMA) is a common genetic cause of infant mortality. Nusinersen treatment ameliorates the clinical outcome of SMA, however, some patients respond well, while others have limited response. We investigated microRNAs in blood samples from SMA patients and their response to nusinersen treatment evaluating the potential of circulating microRNAs as biomarkers for SMA. METHODS: In a discovery cohort study, microRNA next-generation sequencing was performed in blood samples from SMA patients (SMA type 2, n = 10; SMA type 3, n = 10) and controls (n = 7). The dysregulated microRNAs were further analysed in the therapeutic response cohort comprised of SMA type 1 patients (n = 22) who had received nusinersen treatment, at three time points along the treatment course (baseline, 2 and 6 months of treatment). The levels of the studied microRNAs were correlated to the SMA clinical outcome measures. RESULTS: In the discovery cohort, 69 microRNAs were dysregulated between SMA patients and controls. In the therapeutic response cohort, the baseline plasma levels of miR-107, miR-142-5p, miR-335-5p, miR-423-3p, miR-660-5p, miR-378a-3p and miR-23a-3p were associated with the 2 and 6 months response to nusinersen treatment. Furthermore, the levels of miR-107, miR-142-5p, miR-335-5p, miR-423-3p, miR-660-5p and miR-378-3p at 2 months of treatment were associated with the response after 6 months of nusinersen treatment. INTERPRETATION: Blood microRNAs could be used as biomarkers to indicate SMA patients' response to nusinersen and to monitor the efficacy of the therapeutic intervention. In addition, some of these microRNAs provide insight into processes involved in SMA that could be exploited as novel therapeutic targets

GGPS1-associated muscular dystrophy with and without hearing loss

Ultra-rare biallelic pathogenic variants in geranylgeranyl diphosphate synthase 1 (GGPS1) have recently been associated with muscular dystrophy/hearing loss/ovarian insufficiency syndrome. Here, we describe 11 affected individuals from four unpublished families with ultra-rare missense variants in GGPS1 and provide follow-up details from a previously reported family. Our cohort replicated most of the previously described clinical features of GGPS1 deficiency; however, hearing loss was present in only 46% of the individuals. This report consolidates the disease-causing role of biallelic variants in GGPS1 and demonstrates that hearing loss and ovarian insufficiency might be a variable feature of the GGPS1-associated muscular dystrophy

Recessive mutations in MSTO1 cause mitochondrial dynamics impairment, leading to myopathy and ataxia.

We report here the first families carrying recessive variants in the MSTO1 gene: compound heterozygous mutations were identified in two sisters and in an unrelated singleton case, who presented a multisystem complex phenotype mainly characterized by myopathy and cerebellar ataxia. Human MSTO1 is a poorly studied protein, suggested to have mitochondrial localization and to regulate morphology and distribution of mitochondria. As for other mutations affecting genes involved in mitochondrial dynamics, no biochemical defects typical of mitochondrial disorders were reported. Studies in patients' fibroblasts revealed that MSTO1 protein levels were strongly reduced, the mitochondrial network was fragmented, and the fusion events among mitochondria were decreased, confirming the deleterious effect of the identified variants and the role of MSTO1 in modulating mitochondrial dynamics. We also found that MSTO1 is mainly a cytosolic protein. These findings indicate recessive mutations in MSTO1 as a new cause for inherited neuromuscular disorders with multisystem features.Contract grant sponsors: EU NeurOmics (project N. 2012‐305121‐2); the European Community's Seventh Framework Programme (FP7/2007‐2013); Regione Emilia Romagna; the Telethon (grant GGP15041); the Pierfranco and Luisa Mariani Foundation; the MRC‐QQR (2015‐20120); the ERC advanced grant (FP7‐322424); the NRJ‐Institut de France grant; Telethon Network of Genetic Biobanks (grant GTB12001J); MRC Neuromuscular Centre (for the Biobank); Muscular Dystrophy UK; National Institute for Health Research Biomedical Research Centre at Great Ormond Street Hospital for Children NHS Foundation Trust and University College London

Association study in the 5q31-32 linkage region for schizophrenia using pooled DNA genotyping

<p>Abstract</p> <p>Background</p> <p>Several linkage studies suggest that chromosome 5q31-32 might contain risk loci for schizophrenia (SZ). We wanted to identify susceptibility genes for schizophrenia within this region.</p> <p>Methods</p> <p>We saturated the interval between markers D5S666 and D5S436 with 90 polymorphic microsatellite markers and genotyped two sets of DNA pools consisting of 300 SZ patients of Bulgarian origin and their 600 parents. Positive associations were followed-up with SNP genotyping.</p> <p>Results</p> <p>Nominally significant evidence for association (p < 0.05) was found for seven markers (D5S0023i, IL9, RH60252, 5Q3133_33, D5S2017, D5S1481, D5S0711i) which were then individually genotyped in the trios. The predicted associations were confirmed for two of the markers: D5S2017, localised in the <it>SPRY4-FGF1 </it>locus (p = 0.004) and IL9, localized within the IL9 gene (p = 0.014). Fine mapping was performed using single nucleotide polymorphisms (SNPs) around D5S2017 and IL9. In each region four SNPs were chosen and individually genotyped in our full sample of 615 SZ trios. Two SNPs showed significant evidence for association: rs7715300 (p = 0.001) and rs6897690 (p = 0.032). Rs7715300 is localised between the <it>TGFBI </it>and <it>SMAD5 </it>genes and rs6897690 is within the <it>SPRY4 </it>gene.</p> <p>Conclusion</p> <p>Our screening of 5q31-32 implicates three potential candidate genes for SZ: <it>SMAD5</it>, <it>TGFBI </it>and <it>SPRY4</it>.</p

Heterozygous frameshift variants in HNRNPA2B1 cause early-onset oculopharyngeal muscular dystrophy

Missense variants in RNA-binding proteins (RBPs) underlie a spectrum of disease phenotypes, including amyotrophic lateral sclerosis, frontotemporal dementia, and inclusion body myopathy. Here, we present ten independent families with a severe, progressive muscular dystrophy, reminiscent of oculopharyngeal muscular dystrophy (OPMD) but of much earlier onset, caused by heterozygous frameshift variants in the RBP hnRNPA2/B1. All disease-causing frameshift mutations abolish the native stop codon and extend the reading frame, creating novel transcripts that escape nonsense-mediated decay and are translated to produce hnRNPA2/B1 protein with the same neomorphic C-terminal sequence. In contrast to previously reported disease-causing missense variants in HNRNPA2B1, these frameshift variants do not increase the propensity of hnRNPA2 protein to fibrillize. Rather, the frameshift variants have reduced affinity for the nuclear import receptor karyopherin β2, resulting in cytoplasmic accumulation of hnRNPA2 protein in cells and in animal models that recapitulate the human pathology. Thus, we expand the phenotypes associated with HNRNPA2B1 to include an early-onset form of OPMD caused by frameshift variants that alter its nucleocytoplasmic transport dynamics

A review of career devoted to biophotonics-in memoriam to Ekaterina Borisova (1978-2021)

Regretfully, because of her sudden demise, Assoc. Prof. Ekaterina Borisova is no longer amongst us. COVID-19 pulled away a brilliant scientist during the peak of her scientific career (see Fig. 1). All authors would like to express deepest condolences and sincere support to her family, friends, relatives and colleagues! We, therefore, rightfully commemorate her dedicated and devoted contribution to biophotonics, her readiness to always support, help, motivate and inspire all her colleagues and collaborators

Solve-RD: systematic pan-European data sharing and collaborative analysis to solve rare diseases.

For the first time in Europe hundreds of rare disease (RD) experts team up to actively share and jointly analyse existing patient's data. Solve-RD is a Horizon 2020-supported EU flagship project bringing together >300 clinicians, scientists, and patient representatives of 51 sites from 15 countries. Solve-RD is built upon a core group of four European Reference Networks (ERNs; ERN-ITHACA, ERN-RND, ERN-Euro NMD, ERN-GENTURIS) which annually see more than 270,000 RD patients with respective pathologies. The main ambition is to solve unsolved rare diseases for which a molecular cause is not yet known. This is achieved through an innovative clinical research environment that introduces novel ways to organise expertise and data. Two major approaches are being pursued (i) massive data re-analysis of >19,000 unsolved rare disease patients and (ii) novel combined -omics approaches. The minimum requirement to be eligible for the analysis activities is an inconclusive exome that can be shared with controlled access. The first preliminary data re-analysis has already diagnosed 255 cases form 8393 exomes/genome datasets. This unprecedented degree of collaboration focused on sharing of data and expertise shall identify many new disease genes and enable diagnosis of many so far undiagnosed patients from all over Europe

Twist exome capture allows for lower average sequence coverage in clinical exome sequencing

Background Exome and genome sequencing are the predominant techniques in the diagnosis and research of genetic disorders. Sufficient, uniform and reproducible/consistent sequence coverage is a main determinant for the sensitivity to detect single-nucleotide (SNVs) and copy number variants (CNVs). Here we compared the ability to obtain comprehensive exome coverage for recent exome capture kits and genome sequencing techniques. Results We compared three different widely used enrichment kits (Agilent SureSelect Human All Exon V5, Agilent SureSelect Human All Exon V7 and Twist Bioscience) as well as short-read and long-read WGS. We show that the Twist exome capture significantly improves complete coverage and coverage uniformity across coding regions compared to other exome capture kits. Twist performance is comparable to that of both short- and long-read whole genome sequencing. Additionally, we show that even at a reduced average coverage of 70× there is only minimal loss in sensitivity for SNV and CNV detection. Conclusion We conclude that exome sequencing with Twist represents a significant improvement and could be performed at lower sequence coverage compared to other exome capture techniques

Solving patients with rare diseases through programmatic reanalysis of genome-phenome data.

Funder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health); doi: https://doi.org/10.13039/100011272; Grant(s): 305444, 305444Funder: Ministerio de Economía y Competitividad (Ministry of Economy and Competitiveness); doi: https://doi.org/10.13039/501100003329Funder: Generalitat de Catalunya (Government of Catalonia); doi: https://doi.org/10.13039/501100002809Funder: EC | European Regional Development Fund (Europski Fond za Regionalni Razvoj); doi: https://doi.org/10.13039/501100008530Funder: Instituto Nacional de Bioinformática ELIXIR Implementation Studies Centro de Excelencia Severo OchoaFunder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health)Reanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield of patients with rare diseases. However, the cost and efforts required for reanalysis prevent its routine implementation in research and clinical environments. The Solve-RD project aims to reveal the molecular causes underlying undiagnosed rare diseases. One of the goals is to implement innovative approaches to reanalyse the exomes and genomes from thousands of well-studied undiagnosed cases. The raw genomic data is submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP) together with standardised phenotypic and pedigree data. We have developed a programmatic workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP's Application Programming Interface (API) and relies on the big-data technologies upon which the system is built. We have applied the workflow to prioritise rare known pathogenic variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants per case, which first were evaluated in bulk by a panel of disease experts and afterwards specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised cases, 2.7% of all exome/genome-negative samples) have already been solved, with others being under investigation. The implementation of solutions as the one described here provide the technical framework to enable periodic case-level data re-evaluation in clinical settings, as recommended by the American College of Medical Genetics