NGS based studies on primary immunodeficiencies (PIDs) : causative gene identification, tool development and application

Primary immunodeficiency diseases (PIDs) are composed by a group of highly heterogeneous immune system diseases, of which approximately 350 forms of PID have been described so far. The causative gene of around 60% of patients with PIDs has yet unknown. In recent years, Next Generation Sequencing (NGS) has been increasingly adopted for gene identification and molecular diagnosis of rare diseases, including PIDs. An overview of the genetic makeup that underlies PID using NGS has been suggested as a promising approach to elucidate the etiology of PIDs, which could yield diagnostic and, possibly, provide new treatment advances for PID. To approach this goal, we performed either whole exome sequencing (WES, 454 samples) or targeted region sequencing (TRS, 217 samples) on 602 samples of 500 PID pedigrees. We have summarized the practical suggestions for the interpretation of NGS data and the techniques that can be used to search disease-causative PID genes in Paper I. This work aims to improve data annotation, interpretation, and application of NGS data in PIDs, which also facilitates a wide range of application of NGS data analysis in other Mendelian disorders. The genetic approach together with immunological investigations have identified potential pathogenic variants in 86 primary antibody deficiency (PAD) patients (68.2%), and a correct diagnosis can guide/change treatment plan in around half of the patients with PAD (Paper II). We identified potentially disease-causing variants (including variants classified as VUS (variants of unknown clinical significance)) in around 34% of genetically unidentified PID samples, which had been subjected to TRS using a panel of 219 common PID genes. Notably, the genetic diagnosis of a specific atypical ITK deficiency case adds to the growing amount of evidence supporting the importance of genetic investigations initiated at an early stage of the patient´s disease (Paper III). Altogether, around 60% of PID patients have a possible diagnosis via WES/TRS. Copy number variation defects were identified in 16 patients (4 genes were involved, LRBA, ATM, DOCK8 and PMS2). Beyond the identification of the monogenic causal gene based on pedigree analysis, mutation frequency analysis has been used to identify genes with rare functional variants in the higher proportion of patients in specific patient group compared to control samples, which have discovered several potential novel PID genes (TNFRSF18, PIK3CG, LILRB1, EPHB2, TXNIP, CD5 and NLRP5). Other possible models beyond the monogenic scenario were also explored, and 16 severe combined immunodeficiency (SCID) or common variable immunodeficiency (CVID) patients might be due to an accumulation of rare amino acid substitution variants in genes related to the same function or pathway (RAG1 & RAG2, RAG1 & ATM, C3 & ITGB2, PRKDC & ATM, C5 & NIPBL, LRBA & CR2, CR2 & NFKB1, UNC93B1 & NIPBL, PLCG2 & NOD2 and IGLL1 & ATM). These findings indicate that NGS, together with a large sample size, is powerful in decoding the genetic characteristics of PID and provide insight into molecular mechanisms that cause the disease. Existing variants impact prediction software/algorithms still have a challenge to evaluate the pathological consequences of the prioritized variants or genes. We thus developed a Random Forest-based discriminator, Variant Impact Predictor for PIDs (VIPPID), to refine the prediction algorithms, which utilized the features of pathogenic variants and benign mutations, integrated with other 24 predictive softwares currently used. Evaluation of VIPPID showed that it had superior performance (AUC=0.95) over existing tools, we also showed the gene-specific model outperformed the non-gene-specific model and provided a possibility to explore the underlying molecular mechanism based on our gene-specific model in Paper IV. Specific mutations of PID causative genes may exert different effects on TCR repertoire diversity and composition, which ultimately lead to heterogeneous phenotypes. DNA damage response/methylation is an essential process during antigen receptor recombination. To investigate the effect of mutations in DNA repair genes on adaptive immunity, 19 patients with DNA repair/methylation defects were selected and subdivided into several groups based on their causative genes, we then performed deep immune repertoire sequencing and comparison with 14 age-matched healthy controls. Patients with different molecular diagnosis exhibited distinct repertoire diversity, clonality and V-J pairing patterns. Aberrant complementarity-determining region 3 (CDR3) length distribution was observed both in unproductive and productive TCRs in all patients, suggesting that it predominantly arose before thymic selection. Shorter CDR3 lengths in AT patients resulted from a decreased number of insertions, led to an increase in the number of shared clonotypes, whereas patients with DNMT3B and ZBTB24 mutations presented longer CDR3 lengths and reduced specificity for pathogen-associated CDR3 sequences (Paper V). This study revealed the role of DNA repair/methylation machinery in patients with ATM, DNMT3B and ZBTB24 deficiency, and shed light on the mechanistic etiology of their T cell dysfunction

Calculating and comparing codon usage values in rare disease genes highlights codon clustering with disease-and tissue- specific hierarchy

We designed a novel strategy to define codon usage bias (CUB) in 6 specific small cohorts of human genes. We calculated codon usage (CU) values in 29 non-disease-causing (NDC) and 31 disease-causing (DC) human genes which are highly expressed in 3 distinct tissues, kidney, muscle, and skin. We applied our strategy to the same selected genes annotated in 15 mammalian species. We obtained CUB hierarchical clusters for each gene cohort which showed tissue-specific and disease-specific CUB fingerprints. We showed that DC genes (especially those expressed in muscle) display a low CUB, well recognizable in codon hierarchical clustering. We defined the extremely biased codons as “zero codons” and found that their number is significantly higher in all DC genes, all tissues, and that this trend is conserved across mammals. Based on this calculation in different gene cohorts, we identified 5 codons which are more differentially used across genes and mammals, underlining that some genes have favorite synonymous codons in use. Since of the muscle genes clear clusters, and, among these, dystrophin gene surprisingly does not show any “zero codon” we adopted a novel approach to study CUB, we called “mapping-on-codons”. We positioned 2828 dystrophin missense and nonsense pathogenic variations on their respective codon, highlighting that its frequency and occurrence is not dependent on the CU values. We conclude our strategy consents to identify a hierarchical clustering of CU values in a gene cohort-specific fingerprints, with recognizable trend across mammals. In DC muscle genes also a disease-related fingerprint can be observed, allowing discrimination between DC and NDC genes. We propose that using our strategy which studies CU in specific gene cohorts, as rare disease genes, and tissue specific genes, may provide novel information about the CUB role in human and medical genetics, with implications on synonymous variations interpretation and codon optimization algorithms

Molecular genetic analysis using targeted NGS analysis of 677 individuals with retinal dystrophy

Abstract Inherited retinal diseases (IRDs) are a common cause of visual impairment. IRD covers a set of genetically highly heterogeneous disorders with more than 150 genes associated with one or more clinical forms of IRD. Molecular genetic diagnosis has become increasingly important especially due to expanding number of gene therapy strategies under development. Next generation sequencing (NGS) of gene panels has proven a valuable diagnostic tool in IRD. We present the molecular findings of 677 individuals, residing in Denmark, with IRD and report 806 variants of which 187 are novel. We found that deletions and duplications spanning one or more exons can explain 3% of the cases, and thus copy number variation (CNV) analysis is important in molecular genetic diagnostics of IRD. Seven percent of the individuals have variants classified as pathogenic or likely-pathogenic in more than one gene. Possible Danish founder variants in EYS and RP1 are reported. A significant number of variants were classified as variants with unknown significance; reporting of these will hopefully contribute to the elucidation of the actual clinical consequence making the classification less troublesome in the future. In conclusion, this study underlines the relevance of performing targeted sequencing of IRD including CNV analysis as well as the importance of interaction with clinical diagnoses

Incremental value of non-invasive myocardial work for the evaluation and prediction of coronary microvascular dysfunction in angina with no obstructive coronary artery disease

BackgroundEvidence suggests that patients suffering from angina with no obstructive coronary artery disease (ANOCA) experience coronary microvascular dysfunction (CMD). We aimed to understand the diagnosis value of noninvasive myocardial work indices (MWIs) with left ventricular pressure-strain loop (LV PSL) by echocardiography in ANOCA patients with CMD.Methods97 patients with ANOCA were recruited. All subjects underwent standard echocardiography with traditional ultrasound parameters, two-dimensional speckle-tracking echocardiography with global longitudinal strain (GLS), LV PSL with MWIs include global work index (GWI), global constructive work (GCW), global waste work (GWW) and global work efficiency (GWE). In addition, all enrolled cases underwent high-dose adenosine stress echocardiography (SE) with coronary flow velocity reserve (CFVR). CMD was defined as CFVR <2.0.ResultsOf the 97 patients with ANOCA, 52 were placed in the CMD group and 45 in the control group. GWI and GCW were decreased significantly in the CMD group compared with the control group (P < 0.001 for both). GWI and GCW were moderately correlated with CFVR (r = 0.430, P < 0.001 and r = 0.538, P < 0.001, respectively). In the multiple logistic regression analyses, GCW was identified as the only independent echocardiography parameter associated with CMD after adjusting for age and baseline APV [OR (95%CI) 1.009 (1.005–1.013); P < 0.001]. Moreover, the best predictor of CMD in patients with ANOCA using receiver operating characteristic (ROC) curve was GWI and GCW, with an area under the curve (AUC) of 0.800 and 0.832, sensitivity of 67.3% and 78.8%, specificity of 80.0% and 75.6%, respectively.ConclusionMWIs with LV PSL is a new method to detect LV systolic function noninvasively in ANOCA patients with CMD

Myopia disease mouse models: a missense point mutation (S673G) and a protein-truncating mutation of the Zfp644 mimic human disease phenotype.

Zinc finger 644 (Zfp644 in mouse, ZNF644 in human) gene is a transcription factor whose mutation S672G is considered a potential genetic factor of inherited high myopia. ZNF644 interacts with G9a/GLP complex, which functions as a H3K9 methyltransferase to silence transcription. In this study, we generated mouse models to unravel the mechanisms leading to symptoms associated with high myopia. Employing TALEN technology, two mice mutants were generated, either with the disease-carrying mutation (Zfp644 S673G ) or with a truncated form of Zfp644 (Zfp644 Δ8 ). Eye morphology and visual functions were analysed in both mutants, revealing a significant difference in a vitreous chamber depth and lens diameter, however the physiological function of retina was preserved as found under the high-myopia conditions. Our findings prove that ZNF644/Zfp644 is involved in the development of high-myopia, indicating that mutations such as, Zfp644 S673G and Zfp644 Δ8 are causative for changes connected with the disease. The developed models represent a valuable tool to investigate the molecular basis of myopia pathogenesis and its potential treatment

CancerUniT: Towards a Single Unified Model for Effective Detection, Segmentation, and Diagnosis of Eight Major Cancers Using a Large Collection of CT Scans

Human readers or radiologists routinely perform full-body multi-organ multi-disease detection and diagnosis in clinical practice, while most medical AI systems are built to focus on single organs with a narrow list of a few diseases. This might severely limit AI's clinical adoption. A certain number of AI models need to be assembled non-trivially to match the diagnostic process of a human reading a CT scan. In this paper, we construct a Unified Tumor Transformer (CancerUniT) model to jointly detect tumor existence & location and diagnose tumor characteristics for eight major cancers in CT scans. CancerUniT is a query-based Mask Transformer model with the output of multi-tumor prediction. We decouple the object queries into organ queries, tumor detection queries and tumor diagnosis queries, and further establish hierarchical relationships among the three groups. This clinically-inspired architecture effectively assists inter- and intra-organ representation learning of tumors and facilitates the resolution of these complex, anatomically related multi-organ cancer image reading tasks. CancerUniT is trained end-to-end using a curated large-scale CT images of 10,042 patients including eight major types of cancers and occurring non-cancer tumors (all are pathology-confirmed with 3D tumor masks annotated by radiologists). On the test set of 631 patients, CancerUniT has demonstrated strong performance under a set of clinically relevant evaluation metrics, substantially outperforming both multi-disease methods and an assembly of eight single-organ expert models in tumor detection, segmentation, and diagnosis. This moves one step closer towards a universal high performance cancer screening tool.Comment: ICCV 2023 Camera Ready Versio

Targeting the tubulin C-terminal tail by charged small molecules

10 p.-6 fig.The disordered tubulin C-terminal tail (CTT), which possesses a higher degree of heterogeneity, is the target for the interaction of many proteins and cellular components. Compared to the seven well-described binding sites of microtubule-targeting agents (MTAs) that localize on the globular tubulin core, tubulin CTT is far less explored. Therefore, tubulin CTT can be regarded as a novel site for the development of MTAs with distinct biochemical and cell biological properties. Here, we designed and synthesized linear and cyclic peptides containing multiple arginines (RRR), which are complementary to multiple acidic residues in tubulin CTT. Some of them showed moderate induction and promotion of tubulin polymerization. The most potent macrocyclic compound 1f was found to bind to tubulin CTT and thus exert its bioactivity. Such RRR containing compounds represent a starting point for the discovery of tubulin CTT-targeting agents with therapeutic potential.This research was funded by the CAMS Innovation Fund for Medical Sciences (Grant No. 2016-I2M-1-010), State Key Lab Grant type C (Grant No. GTZC201709) (W.-S. F.), Ministerio de Ciencia e Innovación (Grant No. PID2021-123399OB-I00 /AEI/10.13039/501100011033) (M. Á. O.), Ministerio de Ciencia e Innovacion (Grant No. PID2019-104545RB-I00 /AEI/10.13039/501100011033), European Commission-NextGenerationsEU (Regulation EU 2020/2094, through CSIC's Global Health Platform (PTI Salud Global)), Proyecto de Investigación en Neurociencia Fundacion Tatiana Pérez de Guzmán el Bueno 2020 (J. F. D.), the Voelcker Fund (A. R.), the Natural Science Foundation of Guangdong Province of China (Grant No. 2022A1515011419), and the Key Project in Higher Education of Guangdong, China (Grant No. 2022ZDZX2029) (Z. Y.).Peer reviewe