Molecular clues unveiling spinocerebellar ataxia type-12 pathogenesis.

Spinocerebellar Ataxia type-12 (SCA12) is a neurodegenerative disease caused by tandem CAG repeat expansion in the 5'-UTR/non-coding region of PPP2R2B. Molecular pathology of SCA12 has not been studied in the context of CAG repeats, and no appropriate models exist. We found in human SCA12-iPSC-derived neuronal lineage that expanded CAG in PPP2R2B transcript forms nuclear RNA foci and were found to sequester variety of proteins. Further, the ectopic expression of transcript containing varying length of CAG repeats exhibits non-canonical repeat-associated non-AUG (RAN) translation in multiple frames in HEK293T cells, which was further validated in patient-derived neural stem cells using specific antibodies. mRNA sequencing of the SCA12 and control neurons have shown a network of crucial transcription factors affecting neural fate, in addition to alteration of various signaling pathways involved in neurodevelopment. Altogether, this study identifies the molecular signatures of SCA12 disorder using patient-derived neuronal cell lines.

Investigation of RFC1 tandem nucleotide repeat locus in diverse neurodegenerative outcomes in an Indian cohort.

An intronic bi-allelic pentanucleotide repeat expansion mutation, (AAGGG)400-2000, at AAAAG repeat locus in RFC1 gene, is known as underlying genetic cause in cases with cerebellar ataxia, neuropathy, and vestibular areflexia syndrome (CANVAS) and late-onset sporadic ataxia. Biallelic positive cases carry a common recessive risk haplotype, "AAGA," spanning RFC1 gene. In this study, our aim is to find prevalence of bi-allelic (AAGGG)exp in Indian ataxia and other neurological disorders and investigate the complexity of RFC1 repeat locus and its potential association with neurodegenerative diseases in Indian population-based cohorts. We carried out repeat number and repeat type estimation using flanking PCR and repeat primed PCR (AAAAG/AAAGG/AAGGG) in four Indian disease cohorts and healthy controls. Haplotype assessment of suspected cases was done by genotyping and confirmed by Sanger sequencing. Blood samples and consent of all the cases and detailed clinical details of positive cases were collected in collaboration with A.I.I.M.S. Furthermore, comprehension of RFC1 repeat locus and risk haplotype analysis in Indian background was performed on the NGS data of Indian healthy controls by ExpansionHunter, ExpansionHunter Denovo, and PHASE analysis, respectively. Genetic screening of RFC1-TNR locus in 1998 uncharacterized cases (SCA12: 87; uncharacterized ataxia: 1818, CMT: 93) and 564 heterogenous controls showed that the frequency of subjects with bi-allelic (AAGGG)exp are 1.15%, < 0.05%, 2.15%, and 0% respectively. Two RFC1 positive sporadic late-onset ataxia cases, one bi-allelic (AAGGG)exp and another, (AAAGG)~700/(AAGGG)exp, had recessive risk haplotype and CANVAS symptoms. Long normal alleles, 15-27, are significantly rare in ataxia cohort. In IndiGen control population (IndiGen; N = 1029), long normal repeat range, 15-27, is significantly associated with A3G3 and some rare repeat motifs, AGAGG, AACGG, AAGAG, and AAGGC. Risk-associated "AAGA" haplotype of the original pathogenic expansion of A2G3 was found associated with the A3G3 representing alleles in background population. Apart from bi-allelic (AAGGG)exp, we report cases with a new pathogenic expansion of (AAAGG)exp/(AAGGG)exp in RFC1 and recessive risk haplotype. We found different repeat motifs at RFC1 TNR locus, like AAAAG, AAAGG, AAAGGG, AAAAGG, AAGAG, AACGG, AAGGC, AGAGG, and AAGGG, in Indian background population except ACAGG and (AAAGG)n/(AAGGG)n. Our findings will help in further understanding the role of long normal repeat size and different repeat motifs, specifically AAAGG, AAAGGG, and other rare repeat motifs, at the RFC1 locus.

Sequencing through hyperexpanded Friedreich's ataxia-GAA repeats by nanopore technology: implications in genotype-phenotype correlation.

Friedreich's ataxia, an autosomal recessive disorder, is caused by tandem GAA nucleotide repeat expansions in intron 1 of the frataxin gene. The GAA repeats over 66 in number are considered as pathogenic, and commonly occurring pathogenic repeats are within a range of 600-1200. Clinically, the spectrum of features is confined mainly to neurological tissues; however, cardiomyopathy and diabetes mellitus have been reported in 60 and 30% of the subjects, respectively. The accurate detection of GAA repeat count is of utmost importance for clinical genetic correlation, and no study so far has attempted an approach that is of high-throughput nature and defines the exact sequence of GAA repeats. Largely, the method for detection of GAA repeats so far is either through the conventional polymerase chain reaction-based screening or Southern blot, which remains the gold standard method. We utilized an approach of long-range targeted amplification of FXN-GAA repeats using Oxford Nanopore Technologies MinION platform for accurate estimation of repeat length. We were able to achieve successful amplification of GAA repeats ranging from ∼120 to 1100 at ∼2600× mean coverage. The total throughput achievable through our protocol can allow for screening of up to 96 samples per flow cell in less than 24 h. The proposed method is clinically scalable and deployable for day-to-day diagnostics. In this paper, we demonstrate to resolve the genotype-phenotype correlation of Friedreich's ataxia patients with better accuracy.

Single-cell multiomics revealed the dynamics of antigen presentation, immune response and T cell activation in the COVID-19 positive and recovered individuals.

Introduction: Despite numerous efforts to describe COVID-19's immunological landscape, there is still a gap in our understanding of the virus's infections after-effects, especially in the recovered patients. This would be important to understand as we now have huge number of global populations infected by the SARS-CoV-2 as well as variables inclusive of VOCs, reinfections, and vaccination breakthroughs. Furthermore, single-cell transcriptome alone is often insufficient to understand the complex human host immune landscape underlying differential disease severity and clinical outcome. Methods: By combining single-cell multi-omics (Whole Transcriptome Analysis plus Antibody-seq) and machine learning-based analysis, we aim to better understand the functional aspects of cellular and immunological heterogeneity in the COVID-19 positive, recovered and the healthy individuals. Results: Based on single-cell transcriptome and surface marker study of 163,197 cells (124,726 cells after data QC) from the 33 individuals (healthy=4, COVID-19 positive=16, and COVID-19 recovered=13), we observed a reduced MHC Class-I-mediated antigen presentation and dysregulated MHC Class-II-mediated antigen presentation in the COVID-19 patients, with restoration of the process in the recovered individuals. B-cell maturation process was also impaired in the positive and the recovered individuals. Importantly, we discovered that a subset of the naive T-cells from the healthy individuals were absent from the recovered individuals, suggesting a post-infection inflammatory stage. Both COVID-19 positive patients and the recovered individuals exhibited a CD40-CD40LG-mediated inflammatory response in the monocytes and T-cell subsets. T-cells, NK-cells, and monocyte-mediated elevation of immunological, stress and antiviral responses were also seen in the COVID-19 positive and the recovered individuals, along with an abnormal T-cell activation, inflammatory response, and faster cellular transition of T cell subtypes in the COVID-19 patients. Importantly, above immune findings were used for a Bayesian network model, which significantly revealed FOS, CXCL8, IL1ß, CST3, PSAP, CD45 and CD74 as COVID-19 severity predictors. Discussion: In conclusion, COVID-19 recovered individuals exhibited a hyper-activated inflammatory response with the loss of B cell maturation, suggesting an impeded post-infection stage, necessitating further research to delineate the dynamic immune response associated with the COVID-19. To our knowledge this is first multi-omic study trying to understand the differential and dynamic immune response underlying the sample subtypes.

Increased Abundance of Achromobacter xylosoxidans and Bacillus cereus in Upper Airway Transcriptionally Active Microbiome of COVID-19 Mortality Patients Indicates Role of Co-Infections in Disease Severity and Outcome.

The modulators of severe COVID-19 have emerged as the most intriguing features of SARS-CoV-2 pathogenesis. This is especially true as we are encountering variants of concern (VOC) with increased transmissibility and vaccination breakthroughs. Microbial co-infections are being investigated as one of the crucial factors for exacerbation of disease severity and complications of COVID-19. A key question remains whether early transcriptionally active microbial signature/s in COVID-19 patients can provide a window for future disease severity susceptibility and outcome? Using complementary metagenomics sequencing approaches, respiratory virus oligo panel (RVOP) and Holo-seq, our study highlights the possible functional role of nasopharyngeal early resident transcriptionally active microbes in modulating disease severity, within recovered patients with sub-phenotypes (mild, moderate, severe) and mortality. The integrative analysis combines patients' clinical parameters, SARS-CoV-2 phylogenetic analysis, microbial differential composition, and their functional role. The clinical sub-phenotypes analysis led to the identification of transcriptionally active bacterial species associated with disease severity. We found significant transcript abundance of Achromobacter xylosoxidans and Bacillus cereus in the mortality, Leptotrichia buccalis in the severe, Veillonella parvula in the moderate, and Actinomyces meyeri and Halomonas sp. in the mild COVID-19 patients. Additionally, the metabolic pathways, distinguishing the microbial functional signatures between the clinical sub-phenotypes, were also identified. We report a plausible mechanism wherein the increased transcriptionally active bacterial isolates might contribute to enhanced inflammatory response and co-infections that could modulate the disease severity in these groups. Current study provides an opportunity for potentially using these bacterial species for screening and identifying COVID-19 patient sub-groups with severe disease outcome and priority medical care. IMPORTANCE COVID-19 is invariably a disease of diverse clinical manifestation, with multiple facets involved in modulating the progression and outcome. In this regard, we investigated the role of transcriptionally active microbial co-infections as possible modulators of disease pathology in hospital admitted SARS-CoV-2 infected patients. Specifically, can there be early nasopharyngeal microbial signatures indicative of prospective disease severity? Based on disease severity symptoms, the patients were segregated into clinical sub-phenotypes: mild, moderate, severe (recovered), and mortality. We identified significant presence of transcriptionally active isolates, Achromobacter xylosoxidans and Bacillus cereus in the mortality patients. Importantly, the bacterial species might contribute toward enhancing the inflammatory responses as well as reported to be resistant to common antibiotic therapy, which together hold potential to alter the disease severity and outcome.

Extension in the approaches to treat cancer through siRNA system: a beacon of hope in cancer therapy.

Along with the evolutionary breakthrough of RNA interference and the applicability for gene knockdown, a subsequent development in siRNA-based therapeutics has been attained. The gene therapy based on RNAi is in transition progress from the research aspects to clinical base. Being a potent tool, siRNA is used as therapeutic against several disorders. Cancer which is one of the deadliest diseases is now treated with an advanced mechanism of siRNA delivery inside the genome, leading to gene silencing; thereby, blocking translation of gene to form protein. siRNA tool delivers remedial effects with the advantages of safe delivery and efficiency. Despite its merits, barriers including instability at physiological conditions, lack of ability to cross biological membranes, off-targets, and safety are also associated with siRNA delivery system. The gene silencing efficiency values both in vitro and in vivo reported in the past years have been reviewed by material type (lipid, polymer, silica, porous silicon, and metal). This review presents a deep insight in the development of targeted delivery of siRNA. Since several clinical trials have also been performed regarding the siRNA delivery against cancer, it can also be stated that the delivery system should be good enough to achieve effective siRNA drug development.

Genetics of Ataxias in Indian Population: A Collative Insight from a Common Genetic Screening Tool.

Cerebellar ataxias (CAs) represent a group of autosomal dominant and recessive neurodegenerative disorders affecting cerebellum with or without spinal cord. Overall, CAs have preponderance for tandem nucleotide repeat expansions as an etiological factor (10 TREs explain nearly 30-40% of ataxia cohort globally). The experience of 10 years of common genetic ataxia subtypes for ≈5600 patients' referrals (Pan-India) received at a single center is shared herein. Frequencies (in %, n) of SCA types and FRDA in the sample cohort are observed as follows: SCA12 (8.6%, 490); SCA2 (8.5%, 482); SCA1 (4.8%, 272); SCA3 (2%, 113); SCA7 (0.5%, 28); SCA6 (0.1%, 05); SCA17 (0.1%, 05), and FRDA (2.2%, 127). A significant amount of variability in TRE lengths at each locus is observed, we noted presence of biallelic expansion, co-occurrence of SCA-subtypes, and the presence of premutable normal alleles. The frequency of mutated GAA-FRDA allele in healthy controls is 1/158 (0.63%), thus an expected FRDA prevalence of 1:100 000 persons. The data of this study are relevant not only for clinical decision making but also for guidance in direction of genetic investigations, transancestral comparison of genotypes, and lastly provide insight for policy decision for the consideration of SCAs under rare disease category.

Single-Cell Genomics: Enabling the Functional Elucidation of Infectious Diseases in Multi-Cell Genomes.

Since the time when detection of gene expression in single cells by microarrays to the Next Generation Sequencing (NGS) enabled Single Cell Genomics (SCG), it has played a pivotal role to understand and elucidate the functional role of cellular heterogeneity. Along this journey to becoming a key player in the capture of the individuality of cells, SCG overcame many milestones, including scale, speed, sensitivity and sample costs (4S). There have been many important experimental and computational innovations in the efficient analysis and interpretation of SCG data. The increasing role of AI in SCG data analysis has further enhanced its applicability in building models for clinical intervention. Furthermore, SCG has been instrumental in the delineation of the role of cellular heterogeneity in specific diseases, including cancer and infectious diseases. The understanding of the role of differential immune responses in driving coronavirus disease-2019 (COVID-19) disease severity and clinical outcomes has been greatly aided by SCG. With many variants of concern (VOC) in sight, it would be of great importance to further understand the immune response specificity vis-a-vis the immune cell repertoire, the identification of novel cell types, and antibody response. Given the potential of SCG to play an integral part in the multi-omics approach to the study of the host-pathogen interaction and its outcomes, our review attempts to highlight its strengths, its implications for infectious disease biology, and its current limitations. We conclude that the application of SCG would be a critical step towards future pandemic preparedness.

Plasma Gradient of Soluble Urokinase-Type Plasminogen Activator Receptor Is Linked to Pathogenic Plasma Proteome and Immune Transcriptome and Stratifies Outcomes in Severe COVID-19.

Disease caused by SARS-CoV-2 coronavirus (COVID-19) led to significant morbidity and mortality worldwide. A systemic hyper-inflammation characterizes severe COVID-19 disease, often associated with acute respiratory distress syndrome (ARDS). Blood biomarkers capable of risk stratification are of great importance in effective triage and critical care of severe COVID-19 patients. Flow cytometry and next-generation sequencing were done on peripheral blood cells and urokinase-type plasminogen activator receptor (suPAR), and cytokines were measured from and mass spectrometry-based proteomics was done on plasma samples from an Indian cohort of COVID-19 patients. Publicly available single-cell RNA sequencing data were analyzed for validation of primary data. Statistical analyses were performed to validate risk stratification. We report here higher plasma abundance of suPAR, expressed by an abnormally expanded myeloid cell population, in severe COVID-19 patients with ARDS. The plasma suPAR level was found to be linked to a characteristic plasma proteome, associated with coagulation disorders and complement activation. Receiver operator characteristic curve analysis to predict mortality identified a cutoff value of suPAR at 1,996.809 pg/ml (odds ratio: 2.9286, 95% confidence interval 1.0427-8.2257). Lower-than-cutoff suPAR levels were associated with a differential expression of the immune transcriptome as well as favorable clinical outcomes, in terms of both survival benefit (hazard ratio: 0.3615, 95% confidence interval 0.1433-0.912) and faster disease remission in our patient cohort. Thus, we identified suPAR as a key pathogenic circulating molecule linking systemic hyperinflammation to the hypercoagulable state and stratifying clinical outcomes in severe COVID-19 patients with ARDS.

Co-infections as Modulators of Disease Outcome: Minor Players or Major Players?

Human host and pathogen interaction is dynamic in nature and often modulated by co-pathogens with a functional role in delineating the physiological outcome of infection. Co-infection may present either as a pre-existing pathogen which is accentuated by the introduction of a new pathogen or may appear in the form of new infection acquired secondarily due to a compromised immune system. Using diverse examples of co-infecting pathogens such as Human Immunodeficiency Virus, Mycobacterium tuberculosis and Hepatitis C Virus, we have highlighted the role of co-infections in modulating disease severity and clinical outcome. This interaction happens at multiple hierarchies, which are inclusive of stress and immunological responses and together modulate the disease severity. Already published literature provides much evidence in favor of the occurrence of co-infections during SARS-CoV-2 infection, which eventually impacts the Coronavirus disease-19 outcome. The availability of biological models like 3D organoids, mice, cell lines and mathematical models provide us with an opportunity to understand the role and mechanism of specific co-infections. Exploration of multi-omics-based interactions across co-infecting pathogens may provide deeper insights into their role in disease modulation.

Respiratory Co-Infections: Modulators of SARS-CoV-2 Patients' Clinical Sub-Phenotype.

Co-infection with ancillary pathogens is a significant modulator of morbidity and mortality in infectious diseases. There have been limited reports of co-infections accompanying SARS-CoV-2 infections, albeit lacking India specific study. The present study has made an effort toward elucidating the prevalence, diversity and characterization of co-infecting respiratory pathogens in the nasopharyngeal tract of SARS-CoV-2 positive patients. Two complementary metagenomics based sequencing approaches, Respiratory Virus Oligo Panel (RVOP) and Holo-seq, were utilized for unbiased detection of co-infecting viruses and bacteria. The limited SARS-CoV-2 clade diversity along with differential clinical phenotype seems to be partially explained by the observed spectrum of co-infections. We found a total of 43 bacteria and 29 viruses amongst the patients, with 18 viruses commonly captured by both the approaches. In addition to SARS-CoV-2, Human Mastadenovirus, known to cause respiratory distress, was present in a majority of the samples. We also found significant differences of bacterial reads based on clinical phenotype. Of all the bacterial species identified, ∼60% have been known to be involved in respiratory distress. Among the co-pathogens present in our sample cohort, anaerobic bacteria accounted for a preponderance of bacterial diversity with possible role in respiratory distress. Clostridium botulinum, Bacillus cereus and Halomonas sp. are anaerobes found abundantly across the samples. Our findings highlight the significance of metagenomics based diagnosis and detection of SARS-CoV-2 and other respiratory co-infections in the current pandemic to enable efficient treatment administration and better clinical management. To our knowledge this is the first study from India with a focus on the role of co-infections in SARS-CoV-2 clinical sub-phenotype.

Threading the Pieces Together: Integrative Perspective on SARS-CoV-2.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has challenged the research community globally to innovate, interact, and integrate findings across hierarchies. Research on SARS-CoV-2 has produced an abundance of data spanning multiple parallels, including clinical data, SARS-CoV-2 genome architecture, host response captured through transcriptome and genetic variants, microbial co-infections (metagenome), and comorbidities. Disease phenotypes in the case of COVID-19 present an intriguing complexity that includes a broad range of symptomatic to asymptomatic individuals, further compounded by a vast heterogeneity within the spectrum of clinical symptoms displayed by the symptomatic individuals. The clinical outcome is further modulated by the presence of comorbid conditions at the point of infection. The COVID-19 pandemic has produced an expansive wealth of literature touching many aspects of SARS-CoV-2 ranging from causal to outcome, predisposition to protective (possible), co-infection to comorbidity, and differential mortality globally. As challenges provide opportunities, the current pandemic's challenge has underscored the need and opportunity to work for an integrative approach that may be able to thread together the multiple variables. Through this review, we have made an effort towards bringing together information spanning across different domains to facilitate researchers globally in pursuit of their response to SARS-CoV-2.

Association of serotonin and GABA pathway gene polymorphisms with alcohol dependence: A preliminary study.

BACKGROUND: Alcohol dependence (AD), characterized by profound disruptions in specific circuits of the brain is influenced by both environmental, which play a significant role in developing addiction and genetic factors, which make some individuals more susceptible to disruptions. Various polymorphisms in the neurotransmitter genes are reported to increase the risk of developing dependence. The present study aimed to identify association of serotonin and GABA polymorphisms with AD in Indian subjects. METHOD: The study group comprised of 141 AD cases recruited as per DSM IV TR criteria from the outpatient Department of Psychiatry and 110 volunteers from the general population. Clinical and family history was noted and 5 ml blood drawn for genetic studies. Polymorphisms 5-HTTLPR and STin2 of serotonin and rs2279020 and rs3219151 of the GABA pathway were analyzed and results correlated with age at first use quantity consumed, duration of use, dependence and age at onset of dependence. RESULTS: The marker frequencies were similar between cases and controls except for rs3219151. 5-HTTLPR was significantly associated with high AUDIT scores and alcohol intake (p < 0.0001), GABAA rs2279020 and rs3219151 with age at first use (p < 0.0001); rs2279020 with higher AUDIT score (p = 0.002) and rs3219151 with quantity (p = 0.0001). High frequency of GABRA6 rs3219151 TT genotype in AD and its association with lower age at first use, higher intake/day, and higher duration of dependence appears to confer risk. CONCLUSIONS: This preliminary study, though on a smaller sample size, suggests an association of 5-HTTLPR and GABAA receptor polymorphisms with AD in our population.