Whole genome sequencing of families diagnosed with cardiac channelopathies reveals structural variants missed by whole exome sequencing.

Cardiac channelopathies are a group of heritable disorders that affect the heart's electrical activity due to genetic variations present in genes coding for ion channels. With the advent of new sequencing technologies, molecular diagnosis of these disorders in patients has paved the way for early identification, therapeutic management and family screening. The objective of this retrospective study was to understand the efficacy of whole-genome sequencing in diagnosing patients with suspected cardiac channelopathies who were reported negative after whole exome sequencing and analysis. We employed a 3-tier analysis approach to identify nonsynonymous variations and loss-of-function variations missed by exome sequencing, and structural variations that are better resolved only by sequencing whole genomes. By performing whole genome sequencing and analyzing 25 exome-negative cardiac channelopathy patients, we identified 3 pathogenic variations. These include a heterozygous likely pathogenic nonsynonymous variation, CACNA1C:NM_000719:exon19:c.C2570G:p. P857R, which causes autosomal dominant long QT syndrome in the absence of Timothy syndrome, a heterozygous loss-of-function variation CASQ2:NM_001232.4:c.420+2T>C classified as pathogenic, and a 9.2 kb structural variation that spans exon 2 of the KCNQ1 gene, which is likely to cause Jervell-Lange-Nielssen syndrome. In addition, we also identified a loss-of-function variation and 16 structural variations of unknown significance (VUS). Further studies are required to elucidate the role of these identified VUS in gene regulation and decipher the underlying genetic and molecular mechanisms of these disorders. Our present study serves as a pilot for understanding the utility of WGS over clinical exomes in diagnosing cardiac channelopathy disorders.

Molecular basis of DEL phenotype in the Indian population: Insights from next-generation sequencing analysis of two cases.

The DEL phenotype represents an intriguing and challenging aspect of blood group serology. This condition is characterized by an extremely weak expression of the D antigen on red blood cells, to the extent that it often eludes detection through routine serological methods. Identifying the DEL phenotype necessitates more specialized techniques, such as adsorption and elution tests, to reveal the presence of the D antigen. This distinctive phenotype underscores the complexity and subtlety of blood group genetics and highlights the importance of using advanced methods to accurately classify individuals with this condition, as their ability to form anti-D antibodies can have clinical implications during transfusion and pregnancy scenarios. There is a paucity of data for the DEL phenotype in the Indian population, and the molecular basis has not been elucidated yet. Our investigation delves into the genetic underpinnings of two distinct DEL phenotype cases that pose challenges for resolution through conventional serological techniques. We employ next-generation amplicon sequencing to unravel the intricate genetic landscape underlying these cases. In the D-negative donor, the DEL phenotype was first identified serologically, which was subsequently confirmed by molecular analysis. In the second case, it was associated with an anti-D antibody in a D-positive patient. Initial data analysis unveiled a substantial reduction in coverage across the exonic segments of the RHD gene in both samples, suggesting the potential presence of RHD exon deletions. On both occasions, we identified a homozygous intronic RHD polymorphism that is well established to be linked to the RHD* 01EL.32/RHD*DEL32 variant.

WilsonGenAI a deep learning approach to classify pathogenic variants in Wilson Disease.

BACKGROUND: Advances in Next Generation Sequencing have made rapid variant discovery and detection widely accessible. To facilitate a better understanding of the nature of these variants, American College of Medical Genetics and Genomics and the Association of Molecular Pathologists (ACMG-AMP) have issued a set of guidelines for variant classification. However, given the vast number of variants associated with any disorder, it is impossible to manually apply these guidelines to all known variants. Machine learning methodologies offer a rapid way to classify large numbers of variants, as well as variants of uncertain significance as either pathogenic or benign. Here we classify ATP7B genetic variants by employing ML and AI algorithms trained on our well-annotated WilsonGen dataset. METHODS: We have trained and validated two algorithms: TabNet and XGBoost on a high-confidence dataset of manually annotated, ACMG & AMP classified variants of the ATP7B gene associated with Wilson's Disease. RESULTS: Using an independent validation dataset of ACMG & AMP classified variants, as well as a patient set of functionally validated variants, we showed how both algorithms perform and can be used to classify large numbers of variants in clinical as well as research settings. CONCLUSION: We have created a ready to deploy tool, that can classify variants linked with Wilson's disease as pathogenic or benign, which can be utilized by both clinicians and researchers to better understand the disease through the nature of genetic variants associated with it.

Protocol for next-generation sequencing of the LSD virus genome using an amplicon-based approach.

Lumpy skin disease (LSD) is a viral disease predominantly affecting cattle caused by a poxvirus belonging to the capripoxvirus genus. Here, we present a protocol for next-generation sequencing of the LSD virus genome using an amplicon-based approach. We describe steps for DNA extraction, viral DNA enrichment, amplicon pooling and purification, and library preparation and pooling. We then detail procedures for sequencing and computational analysis. This protocol can be adapted to any Illumina sequencing platform as an accelerated and scalable system. For complete details on the use and execution of this protocol, please refer to Bhatt et al.1,2.

Spectrum of rare and common mitochondrial DNA variations from 1029 whole genomes of self-declared healthy individuals from India.

Mitochondrial disorders are a class of heterogeneous disorders caused by genetic variations in the mitochondrial genome (mtDNA) as well as the nuclear genome. The spectrum of mtDNA variants remains unexplored in the Indian population. In the present study, we have cataloged 2689 high confidence single nucleotide variants, small insertions and deletions in mtDNA in 1029 healthy Indian individuals. We found a major proportion (76.5 %) of the variants being rare (AF<=0.005) in the studied population. Intriguingly, we found two 'confirmed' pathogenic variants (m.1555 A>G and m.14484 T>C) with a frequency of ∼1 in 250 individuals in our dataset. The high carrier frequency underscores the need for screening of the mtDNA pathogenic mutations in newborns in India. Interestingly, our analysis also revealed 202 variants in our dataset which have been 'reported' in disease cases as per the MITOMAP database. Additionally, we found the frequency of haplogroup M (52.2 %) to be the highest among all the 18 top-level haplogroups found in our dataset. In comparison to the global population datasets, 20 unique mtDNA variants are found in the Indian population. We hope the whole genome sequencing based compendium of mtDNA variants along with their allele frequencies and heteroplasmy levels in the Indian population will drive additional genome scale studies for mtDNA. Furthermore, the identification of clinically relevant variants in our dataset will aid in better clinical interpretation of the variants in mitochondrial disorders.

Whole genome sequencing followed by functional analysis of genomic deletion encompassing ERCC8 and NDUFAF2 genes in a non-consanguineous Indian family reveals dysfunctional mitochondrial bioenergetics leading to infant mortality.

Genomic investigations on an infant who presented with a putative mitochondrial disorder led to identification of compound heterozygous deletion with an overlapping region of ∼142 kb encompassing two nuclear encoded genes namely ERCC8 and NDUFAF2. Investigations on fetal-derived fibroblast culture demonstrated impaired bioenergetics and mitochondrial dysfunction, which explains the phenotype and observed infant mortality in the present study. The genetic findings from this study extended the utility of whole-genome sequencing as it led to development of a MLPA-based assay for carrier screening in the extended family and the prenatal testing aiding in the birth of two healthy children.

The genomic landscape of CYP2D6 variation in the Indian population.

Aim: The CYP2D6 gene is highly polymorphic, causing large interindividual variability in the metabolism of several clinically important drugs. Materials & methods: The authors investigated the diversity and distribution of CYP2D6 alleles in Indians using whole genome sequences (N = 1518). Functional consequences were assessed using pathogenicity scores and molecular dynamics simulations. Results: The analysis revealed population-specific CYP2D6 alleles (*86, *7, *111, *112, *113, *99) and remarkable differences in variant and phenotype frequencies with global populations. The authors observed that one in three Indians could benefit from a dose alteration for psychiatric drugs with accurate CYP2D6 phenotyping. Molecular dynamics simulations revealed large conformational fluctuations, confirming the predicted reduced function of *86 and *113 alleles. Conclusion: The findings emphasize the utility of comprehensive CYP2D6 profiling for aiding precision public health.

Forward genetic screen using a gene-breaking trap approach identifies a novel role of grin2bb-associated RNA transcript (grin2bbART) in zebrafish heart function.

LncRNA-based control affects cardiac pathophysiologies like myocardial infarction, coronary artery disease, hypertrophy, and myotonic muscular dystrophy. This study used a gene-break transposon (GBT) to screen zebrafish (Danio rerio) for insertional mutagenesis. We identified three insertional mutants where the GBT captured a cardiac gene. One of the adult viable GBT mutants had bradycardia (heart arrhythmia) and enlarged cardiac chambers or hypertrophy; we named it "bigheart." Bigheart mutant insertion maps to grin2bb or N-methyl D-aspartate receptor (NMDAR2B) gene intron 2 in reverse orientation. Rapid amplification of adjacent cDNA ends analysis suggested a new insertion site transcript in the intron 2 of grin2bb. Analysis of the RNA sequencing of wild-type zebrafish heart chambers revealed a possible new transcript at the insertion site. As this putative lncRNA transcript satisfies the canonical signatures, we called this transcript grin2bb associated RNA transcript (grin2bbART). Using in situ hybridization, we confirmed localized grin2bbART expression in the heart, central nervous system, and muscles in the developing embryos and wild-type adult zebrafish atrium and bulbus arteriosus. The bigheart mutant had reduced Grin2bbART expression. We showed that bigheart gene trap insertion excision reversed cardiac-specific arrhythmia and atrial hypertrophy and restored grin2bbART expression. Morpholino-mediated antisense downregulation of grin2bbART in wild-type zebrafish embryos mimicked bigheart mutants; this suggests grin2bbART is linked to bigheart. Cardiovascular tissues use Grin2bb as a calcium-permeable ion channel. Calcium imaging experiments performed on bigheart mutants indicated calcium mishandling in the heart. The bigheart cardiac transcriptome showed differential expression of calcium homeostasis, cardiac remodeling, and contraction genes. Western blot analysis highlighted Camk2d1 and Hdac1 overexpression. We propose that altered calcium activity due to disruption of grin2bbART, a putative lncRNA in bigheart, altered the Camk2d-Hdac pathway, causing heart arrhythmia and hypertrophy in zebrafish.

Landscape of pharmacogenetic variants associated with non-insulin antidiabetic drugs in the Indian population.

INTRODUCTION: Genetic variants contribute to differential responses to non-insulin antidiabetic drugs (NIADs), and consequently to variable plasma glucose control. Optimal control of plasma glucose is paramount to minimizing type 2 diabetes-related long-term complications. India's distinct genetic architecture and its exploding burden of type 2 diabetes warrants a population-specific survey of NIAD-associated pharmacogenetic (PGx) variants. The recent availability of large-scale whole genomes from the Indian population provides a unique opportunity to generate a population-specific map of NIAD-associated PGx variants. RESEARCH DESIGN AND METHODS: We mined 1029 Indian whole genomes for PGx variants, drug-drug interaction (DDI) and drug-drug-gene interactions (DDGI) associated with 44 NIADs. Population-wise allele frequencies were estimated and compared using Fisher's exact test. RESULTS: Overall, we found 76 known and 52 predicted deleterious common PGx variants associated with response to type 2 diabetes therapy among Indians. We report remarkable interethnic differences in the relative cumulative counts of decreased and increased response-associated alleles across NIAD classes. Indians and South Asians showed a significant excess of decreased metformin response-associated alleles compared with other global populations. Network analysis of shared PGx genes predicts high DDI risk during coadministration of NIADs with other metabolic disease drugs. We also predict an increased CYP2C19-mediated DDGI risk for CYP3A4/3A5-metabolized NIADs, saxagliptin, linagliptin and glyburide when coadministered with proton-pump inhibitors (PPIs). CONCLUSIONS: Indians and South Asians have a distinct PGx profile for antidiabetes drugs, marked by an excess of poor treatment response-associated alleles for various NIAD classes. This suggests the possibility of a population-specific reduced drug response in atleast some NIADs. In addition, our findings provide an actionable resource for accelerating future diabetes PGx studies in Indians and South Asians and reconsidering NIAD dosing guidelines to ensure maximum efficacy and safety in the population.

Decoding the genetic symphony: Profiling protein-coding and long noncoding RNA expression in T-acute lymphoblastic leukemia for clinical insights.

T-acute lymphoblastic leukemia (T-ALL) is a heterogeneous malignancy characterized by the abnormal proliferation of immature T-cell precursors. Despite advances in immunophenotypic classification, understanding the molecular landscape and its impact on patient prognosis remains challenging. In this study, we conducted comprehensive RNA sequencing in a cohort of 35 patients with T-ALL to unravel the intricate transcriptomic profile. Subsequently, we validated the prognostic relevance of 23 targets, encompassing (i) protein-coding genes-BAALC, HHEX, MEF2C, FAT1, LYL1, LMO2, LYN, and TAL1; (ii) epigenetic modifiers-DOT1L, EP300, EML4, RAG1, EZH2, and KDM6A; and (iii) long noncoding RNAs (lncRNAs)-XIST, PCAT18, PCAT14, LINC00202, LINC00461, LINC00648, ST20, MEF2C-AS1, and MALAT1 in an independent cohort of 99 patients with T-ALL. Principal component analysis revealed distinct clusters aligning with immunophenotypic subtypes, providing insights into the molecular heterogeneity of T-ALL. The identified signature genes exhibited associations with clinicopathologic features. Survival analysis uncovered several independent predictors of patient outcomes. Higher expression of MEF2C, BAALC, HHEX, and LYL1 genes emerged as robust indicators of poor overall survival (OS), event-free survival (EFS), and relapse-free survival (RFS). Higher LMO2 expression was correlated with adverse EFS and RFS outcomes. Intriguingly, increased expression of lncRNA ST20 coupled with RAG1 demonstrated a favorable prognostic impact on OS, EFS, and RFS. Conclusively, several hitherto unreported associations of gene expression patterns with clinicopathologic features and prognosis were identified, which may help understand T-ALL's molecular pathogenesis and provide prognostic markers.

Understanding the variant landscape, and genetic epidemiology of Multiple Endocrine Neoplasia in India.

PURPOSE: Multiple Endocrine Neoplasia (MEN) is a group of familial cancer syndromes that encompasses several types of endocrine tumors differentiated by genetic mutations in RET, MEN1 and CDKN1B genes. Accurate diagnosis of MEN subtypes can thus be performed through genetic testing. However, MEN variants remain largely understudied in Indian populations. Additionally, few dedicated resources to understand these disorders currently exist. METHODS: Using the gold-standard ACMG/AMP guidelines, we systematically classified variants reported across the three genes in the IndiGen dataset, and established the genetic epidemiology of MEN in the Indian population. We further classified ClinVar and Mastermind variants and compiled all into a database. Finally, we designed a multiplex primer panel for rapid variant identification. RESULTS: We have established the genetic prevalence of MEN as the following: 1 in 1026 individuals is likely to be afflicted with MEN linked with pathogenic RET mutations. We have further created the MAPVar database containing 3280 ACMG-classified variants freely accessible at: https://clingen.igib.res.in/MAPVar/ . Finally, our NGS primer panel covers 33 exonic regions across two pools through 38 amplicons with a total amplified region of 65 kb. CONCLUSION: Our work establishes that MEN is a prevalent disorder in India. The rare nature of Indian variants underscores the need of genomic and functional studies to establish a more comprehensive variant landscape. Additionally, our panel offers a means of cost-effective genetic testing, and the MAPVar database a ready reference to aid in a better understanding of variant pathogenicity in clinical as well as research settings.

Development of pathophysiologically relevant models of sickle cell disease and ß-thalassemia for therapeutic studies.

Ex vivo cellular system that accurately replicates sickle cell disease and ß-thalassemia characteristics is a highly sought-after goal in the field of erythroid biology. In this study, we present the generation of erythroid progenitor lines with sickle cell disease and ß-thalassemia mutation using CRISPR/Cas9. The disease cellular models exhibit similar differentiation profiles, globin expression and proteome dynamics as patient-derived hematopoietic stem/progenitor cells. Additionally, these cellular models recapitulate pathological conditions associated with both the diseases. Hydroxyurea and pomalidomide treatment enhanced fetal hemoglobin levels. Notably, we introduce a therapeutic strategy for the above diseases by recapitulating the HPFH3 genotype, which reactivates fetal hemoglobin levels and rescues the disease phenotypes, thus making these lines a valuable platform for studying and developing new therapeutic strategies. Altogether, we demonstrate our disease cellular systems are physiologically relevant and could prove to be indispensable tools for disease modeling, drug screenings and cell and gene therapy-based applications.

A Rapid and Scalable Multiplex PCR-Based Next-Generation Amplicon Sequencing Method for Familial Hypercholesterolemia Genetic Screening.

BACKGROUND: Familial hypercholesterolemia (FH) is a frequently underdiagnosed genetic disorder characterized by elevated low-density lipoprotein (LDL) levels. Genetic testing of LDLR, APOB, and PCSK9 genes can identify variants in up to 80% of clinically diagnosed patients. However, limitations in time, scalability, and cost have hindered effective next-generation sequencing of these genes. Additionally, pharmacogenomic variants are associated with statin-induced adverse effects in FH patients. To address these challenges, we developed a multiplex primer-based amplicon sequencing approach for FH genetic testing. METHODS: Multiplex primers were designed for the exons of the LDLR, APOB, and PCSK9 genes, as well as for pharmacogenomic variants rs4149056 (SLCO1B1:c.521T > A), rs2306283 (SLCO1B1:c.388A > G), and rs2231142 (ABCG2:c.421C > A). Analytical validation using samples with known pathogenic variants and clinical validation with 12 FH-suspected probands were conducted. Library preparation was based on a bead-based tagmentation method, and sequencing was conducted on the NovaSeq 6000 platform. RESULTS: Our approach ensured no amplicon dropouts, with over 100× coverage on each amplicon. Known variants in 2 samples were successfully detected. Further, we identified one heterozygous LDLR (p.Glu228Ter) variant and 2 homozygous cases of LDLR (p.Lys294Ter) and LDLR (p.Ser177Leu) variants in patients. Pharmacogenomic analysis revealed that overall 3 patients may require reduced statin doses. Our approach offered reduced library preparation time (approximately 3 h), greater scalability, and lower costs (under $50) for FH genetic testing. CONCLUSIONS: Our method effectively sequences LDLR, APOB, and PCSK9 genes including pharmacogenomic variants that will guide appropriate screening and statin dosing, thus increasing both efficiency and affordability.

Impact of COVID-19 outbreak on healthcare workers in a Tertiary Healthcare Center in India: a cross sectional study.

Numerous speculations have continually emerged, trying to explore the association between COVID-19 infection and a varied range of demographic and clinical factors. Frontline healthcare workers have been the primary group exposed to this infection, and there have been limited global research that examine this cohort. However, while there are a few large studies conducted on Indian healthcare professionals to investigate their potential risk and predisposing factors to COVID-19 infection, to our knowledge there are no studies evaluating the development of long COVID in this population. This cross-sectional study systematically utilized the demographic and clinical data of 3329 healthcare workers (HCW) from a tertiary hospital in India to gain significant insights into the associations between disease prevalence, severity of SARS-Cov-2 infection and long COVID. Most of the study population was found to be vaccinated (2,615, 78.5%), while 654 (19.65%) HCWs were found to be SARS-CoV-2 positive at least once. Of the infected HCWs, 75.1% (491) did not require hospitalization, whereas the rest were hospitalized for an average duration of 9 days. A total of 206 (6.19%) individuals were found to be suffering from long COVID. Persistent weakness/tiredness was the most experienced long-COVID symptom, while females (1.79, 1.25-2.57), individuals who consumed alcohol (1.85, 1.3-2.64) or had blood group B (1.9, 1.33-2.7) were at a significantly higher risk for developing long COVID.

Scalable noninvasive amplicon-based precision sequencing (SNAPseq) for genetic diagnosis and screening of ß-thalassemia and sickle cell disease using a next-generation sequencing platform.

ß-hemoglobinopathies such as ß-thalassemia (BT) and Sickle cell disease (SCD) are inherited monogenic blood disorders with significant global burden. Hence, early and affordable diagnosis can alleviate morbidity and reduce mortality given the lack of effective cure. Currently, Sanger sequencing is considered to be the gold standard genetic test for BT and SCD, but it has a very low throughput requiring multiple amplicons and more sequencing reactions to cover the entire HBB gene. To address this, we have demonstrated an extraction-free single amplicon-based approach for screening the entire ß-globin gene with clinical samples using Scalable noninvasive amplicon-based precision sequencing (SNAPseq) assay catalyzing with next-generation sequencing (NGS). We optimized the assay using noninvasive buccal swab samples and simple finger prick blood for direct amplification with crude lysates. SNAPseq demonstrates high sensitivity and specificity, having a 100% agreement with Sanger sequencing. Furthermore, to facilitate seamless reporting, we have created a much simpler automated pipeline with comprehensive resources for pathogenic mutations in BT and SCD through data integration after systematic classification of variants according to ACMG and AMP guidelines. To the best of our knowledge, this is the first report of the NGS-based high throughput SNAPseq approach for the detection of both BT and SCD in a single assay with high sensitivity in an automated pipeline.