CoNVaDING:Single Exon Variation Detection in Targeted NGS Data

We have developed a tool for detecting single exon copy number variations (CNVs) in targeted next-generation sequencing data: CoNVaDING (Copy Number Variation Detection In Next-generation sequencing Gene panels). CoNVaDING includes a stringent quality control metric, that excludes or flags low quality exons. Since this quality control shows exactly which exons can be reliably analysed and which exons are in need of an alternative analysis method, CoNVaDING is not only useful for CNV detection in a research setting, but also in clinical diagnostics. During the validation phase, CoNVaDING detected all known CNVs in high quality targets in 320 samples analysed, giving 100% sensitivity and 99.998% specificity for 308,574 exons. CoNVaDING outperforms existing tools by exhibiting a higher sensitivity and specificity and by precisely identifying low-quality samples and regions. This article is protected by copyright. All rights reserved.</p

Feasibility of Follow-Up Studies and Reclassification in Spinocerebellar Ataxia Gene Variants of Unknown Significance

Spinocerebellar ataxia (SCA) is a heterogeneous group of neurodegenerative disorders with autosomal dominant inheritance. Genetic testing for SCA leads to diagnosis, prognosis and risk assessment for patients and their family members. While advances in sequencing and computing technologies have provided researchers with a rapid expansion in the genetic test content that can be used to unravel the genetic causes that underlie diseases, the large number of variants with unknown significance (VUSes) detected represent challenges. To minimize the proportion of VUSes, follow-up studies are needed to aid in their reclassification as either (likely) pathogenic or (likely) benign variants. In this study, we addressed the challenge of prioritizing VUSes for follow-up using (a combination of) variant segregation studies, 3D protein modeling, in vitro splicing assays and functional assays. Of the 39 VUSes prioritized for further analysis, 13 were eligible for follow up. We were able to reclassify 4 of these VUSes to LP, increasing the molecular diagnostic yield by 1.1%. Reclassification of VUSes remains difficult due to limited possibilities for performing variant segregation studies in the classification process and the limited availability of routine functional tests

Diagnostic yield of targeted next generation sequencing in 2002 Dutch cardiomyopathy patients

BACKGROUND: Next-generation sequencing (NGS) is increasingly used for clinical evaluation of cardiomyopathy patients as it allows for simultaneous screening of multiple cardiomyopathy-associated genes. Adding copy number variant (CNV) analysis of NGS data is not routine yet and may contribute to the diagnostic yield. OBJECTIVES: Determine the diagnostic yield of our targeted NGS gene panel in routine clinical diagnostics of Dutch cardiomyopathy patients and explore the impact of exon CNVs on diagnostic yield. METHODS: Patients (N = 2002) referred for clinical genetic analysis underwent diagnostic testing of 55-61 genes associated with cardiomyopathies. Samples were analyzed and evaluated for single nucleotide variants (SNVs), indels and CNVs. CNVs identified in the NGS data and suspected of being pathogenic based on type, size and location were confirmed by additional molecular tests. RESULTS: A (likely) pathogenic (L)P variant was detected in 22.7% of patients, including 3 with CNVs and 25 where a variant was identified in a gene currently not associated with the patient's cardiomyopathy subtype. Only 15 out of 2002 patients (0.8%) were found to carry two (L)P variants. CONCLUSION: The yield of routine clinical diagnostics of cardiomyopathies was relatively low when compared to literature. This is likely due to the fact that our study reports the outcome of patients in daily routine diagnostics, therefore also including patients not fully fulfilling (subtype specific) cardiomyopathy criteria. This may also explain why (L)P variants were identified in genes not associated with the reported subtype. The added value of CNV analysis was shown to be limited but not negligible

Development, characterization, and in vivo validation of a humanized C6 monoclonal antibody that Inhibits the membrane attack complex

Damage and disease of nerves activates the complement system. We demonstrated that activation of the terminal pathway of the complement system leads to the formation of the membrane attack complex (MAC) and delays regeneration in the peripheral nervous system. Animals deficient in the complement component C6 showed improved recovery after neuronal trauma. Thus, inhibitors of the MAC might be of therapeutic use in neurological disease. Here, we describe the development, structure, mode of action, and properties of a novel therapeutic monoclonal antibody, CP010, against C6 that prevents formation of the MAC in vivo. The monoclonal antibody is humanized and specific for C6 and binds to an epitope in the FIM1-2 domain of human and primate C6 with sub-nanomolar affinity. Using biophysical and structural studies, we show that the anti-C6 antibody prevents the interaction between C6 and C5/C5b by blocking the C6 FIM1-2:C5 C345c axis. Systemic administration of the anti-C6 mAb caused complete depletion of free C6 in circulation in transgenic rats expressing human C6 and thereby inhibited MAC formation. The antibody prevented disease in experimental autoimmune myasthenia gravis and ameliorated relapse in chronic relapsing experimental autoimmune encephalomyelitis in human C6 transgenic rats. CP010 is a promising complement C6 inhibitor that prevents MAC formation. Systemic administration of this C6 monoclonal antibody has therapeutic potential in the treatment of neuronal disease

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

Multidifferential study of identified charged hadron distributions in ZZ-tagged jets in proton-proton collisions at s=\sqrt{s}=13 TeV

Jet fragmentation functions are measured for the first time in proton-proton collisions for charged pions, kaons, and protons within jets recoiling against a $Z$ boson. The charged-hadron distributions are studied longitudinally and transversely to the jet direction for jets with transverse momentum 20 $< p_{\textrm{T}} < 100$ GeV and in the pseudorapidity range $2.5 < \eta < 4$. The data sample was collected with the LHCb experiment at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 1.64 fb$^{-1}$. Triple differential distributions as a function of the hadron longitudinal momentum fraction, hadron transverse momentum, and jet transverse momentum are also measured for the first time. This helps constrain transverse-momentum-dependent fragmentation functions. Differences in the shapes and magnitudes of the measured distributions for the different hadron species provide insights into the hadronization process for jets predominantly initiated by light quarks.Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-013.html (LHCb public pages

Study of the B−→Λc+Λˉc−K−B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-} decay

The decay $B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-}$ is studied in proton-proton collisions at a center-of-mass energy of $\sqrt{s}=13$ TeV using data corresponding to an integrated luminosity of 5 $\mathrm{fb}^{-1}$ collected by the LHCb experiment. In the $\Lambda_{c}^+ K^{-}$ system, the $\Xi_{c}(2930)^{0}$ state observed at the BaBar and Belle experiments is resolved into two narrower states, $\Xi_{c}(2923)^{0}$ and $\Xi_{c}(2939)^{0}$, whose masses and widths are measured to be $$m(\Xi_{c}(2923)^{0}) = 2924.5 \pm 0.4 \pm 1.1 \,\mathrm{MeV}, \\ m(\Xi_{c}(2939)^{0}) = 2938.5 \pm 0.9 \pm 2.3 \,\mathrm{MeV}, \\ \Gamma(\Xi_{c}(2923)^{0}) = \phantom{000}4.8 \pm 0.9 \pm 1.5 \,\mathrm{MeV},\\ \Gamma(\Xi_{c}(2939)^{0}) = \phantom{00}11.0 \pm 1.9 \pm 7.5 \,\mathrm{MeV},$$ where the first uncertainties are statistical and the second systematic. The results are consistent with a previous LHCb measurement using a prompt $\Lambda_{c}^{+} K^{-}$ sample. Evidence of a new $\Xi_{c}(2880)^{0}$ state is found with a local significance of $3.8\,\sigma$, whose mass and width are measured to be $2881.8 \pm 3.1 \pm 8.5\,\mathrm{MeV}$ and $12.4 \pm 5.3 \pm 5.8 \,\mathrm{MeV}$, respectively. In addition, evidence of a new decay mode $\Xi_{c}(2790)^{0} \to \Lambda_{c}^{+} K^{-}$ is found with a significance of $3.7\,\sigma$. The relative branching fraction of $B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-}$ with respect to the $B^{-} \to D^{+} D^{-} K^{-}$ decay is measured to be $2.36 \pm 0.11 \pm 0.22 \pm 0.25$, where the first uncertainty is statistical, the second systematic and the third originates from the branching fractions of charm hadron decays.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-028.html (LHCb public pages