December 2025 brings a diverse set of customer publications highlighting how advanced genomic analysis is being applied to real clinical and population-scale challenges, from infectious disease susceptibility to pharmacogenomics and rare kidney disorders. Together, these studies underscore the growing importance of integrated variant interpretation, scalable sequencing strategies, and rigorous clinical classification frameworks in translating genomic data into meaningful clinical insight.
Title: Deleterious variants in the autophagy-related gene RB1CC1/FIP200 impair immunity to SARS-CoV-2
Background: Severe COVID-19 shows striking variability in clinical outcomes, with a substantial subset of critical cases linked to defects in innate antiviral immunity rather than traditional risk factors. Recent evidence identifies rare deleterious variants in the autophagy-related gene RB1CC1/FIP200 as impairing a non-canonical, interferon-independent antiviral pathway that restricts SARS-CoV-2 replication in airway epithelial cells.
Objectives: To determine whether deleterious variants in RB1CC1/FIP200 compromise cell-autonomous antiviral defenses and thereby increase susceptibility to critical SARS-CoV-2 infection by disrupting non-canonical autophagy pathways.
Subjects and Methods: Whole-exome sequencing was performed on a cohort of patients with critical COVID-19 lacking known risk factors to identify rare, potentially deleterious variants in autophagy-related genes, with a focus on RB1CC1/FIP200. Functional consequences of identified variants were assessed using patient-derived immune cells and engineered airway epithelial cell models, combining SARS-CoV-2 infection assays with molecular, imaging, and ultrastructural analyses to measure viral replication and autophagy flux. Comparative experiments in gene knockout and knock-in cell lines were used to distinguish canonical autophagy, interferon signaling, and non-canonical FIP200-dependent antiviral mechanisms.
Results:
- Rare heterozygous missense variants in RB1CC1/FIP200 were identified in unrelated patients with critical COVID-19 and were enriched compared to the general population. These variants were predicted to be deleterious and affected conserved regions of the FIP200 protein. pasted
- Cells deficient in FIP200 or expressing patient variants showed significantly increased SARS-CoV-2 replication across multiple airway epithelial and primary cell models. Viral entry was unaffected, indicating a defect in post-entry restriction rather than initial infection. pasted
- Loss of FIP200 impaired autophagic flux during infection without disrupting type I interferon or inflammatory cytokine responses. Canonical autophagy was not required for viral restriction, as ATG5 deficiency did not increase viral replication. pasted
- FIP200 mediated degradation of SARS-CoV-2 RNA and virions within acidified LC3-positive single-membrane compartments through a non-canonical autophagy pathway involving the selective autophagy receptor NDP52. Disruption of this pathway led to accumulation of viral material and enhanced replication.
Conclusions: Deleterious variants in RB1CC1/FIP200 define a previously unrecognized inborn error of immunity that predisposes individuals to critical COVID-19 by impairing cell-autonomous antiviral control of SARS-CoV-2. FIP200 restricts viral replication through a non-canonical, interferon-independent pathway that targets viral RNA and virions for lysosomal degradation. These findings expand the landscape of human antiviral defense mechanisms beyond classical interferon signaling and highlight autophagy-related pathways as clinically relevant determinants of COVID-19 severity.
How VarSeq Was Used: “Genomic DNA was isolated from whole blood from each patient as previously described90,91. WES was performed employing the Kapa HTP Library preparation and the Nimblegen SeqCap EZ MedExome Plus kit (Roche, 07681364001) for P1 and TWIST comprehensive exome with custom spike-ins for P2. Samples were analyzed on Illumina NextSeq 550 system (P1) and NovaSeq 6000 (P2), SNP calling relative to hg19 with BWA, PCR, and optical duplicates were identified and marked. The alignment was recalibrated using the GATK package. Single-nucleotide polymorphisms were identified employing the HaplotypeCaller from the GATK package. Variant call files were analyzed and filtered using VarSeq 2.3.0 (Golden Helix) or Tibco Spotfire Analyst and filtered according to confidence (call quality at least 30.0, read depth at least 5.0, allele fraction at least 25.0). We then used different variant scoring systems, including combined annotation-dependent depletion (CADD), mutation significance cut-off (MSC), gene damage index (GDI), SIFT, and PolyPhen-2, to identify variants of interest. The exomes were analyzed for deleterious variants using a CADD score >20 and a frequency below 0.001 in the general population based on frequencies reported to the Genome Aggregation Database (gnomAD), ExAC, and NHLBI ESP. Finally, identified variants were manually checked by inspecting BAM files using IGV.”
Citation: Hu, L., van der Sluis, R.M., Castelino, K.B. et al. Deleterious variants in the autophagy-related gene RB1CC1/FIP200 impair immunity to SARS-CoV-2. Nat Commun 16, 10618 (2025). https://doi.org/10.1038/s41467-025-65308-8
Title: Thiopurine pharmacogenomic landscape in India: TPMT and NUDT15 allele frequencies
Background:Thiopurines such as azathioprine, mercaptopurine, and thioguanine are widely used in hematology but carry a significant risk of myelosuppression due to interindividual variability in drug metabolism. Variants in the thiopurine‐metabolizing genes TPMT and NUDT15 are established predictors of toxicity, yet their allele frequencies and clinical relevance in the Indian population remain poorly characterized.
Objectives: To characterize the frequency and distribution of clinically actionable TPMT and NUDT15 variants in an Indian population and assess their enrichment across hematology and non-hematology cohorts to inform genotype-guided thiopurine therapy.
Subjects and Methods: We analyzed anonymized whole-exome sequencing data from 1,742 individuals tested at a collaborative tertiary laboratory in India, including 609 patients evaluated for hematologic indications. TPMT and NUDT15 variants curated from CPIC were annotated and classified using VarSeq with population, transcript, and clinical databases, with exclusion of common, synonymous, or benign variants. Allele frequencies were compared between hematology and non-hematology cohorts and benchmarked against global reference populations using contingency testing.
Results:
- Across the full cohort, two clinically actionable TPMT no-function variants (c.719A>G and c.460G>A) were identified at frequencies consistent with South Asian reference populations. These variants were significantly depleted in the hematology sub-cohort compared to the non-hematology cohort.
- Broad TPMT interrogation identified over 1,100 rare variants, including several pathogenic or likely pathogenic changes that were absent or extremely rare in global reference databases. These findings suggest the presence of potentially population-specific risk alleles.
- The NUDT15 c.415C>T variant was common nationwide and observed at frequencies comparable to South Asian populations in global datasets. This variant was significantly enriched in the hematology cohort, including homozygous individuals at high risk for severe toxicity.
- Additional rare functional NUDT15 alleles were detected at low frequency, including both non-functional and reduced-function variants. Although uncommon, these alleles further contribute to thiopurine toxicity risk in the population.
Conclusions: Clinically actionable TPMT and NUDT15 variants are present in the Indian population, with allele frequencies largely consistent with South Asian reference datasets. While TPMT no-function alleles were markedly depleted in the hematology cohort, the NUDT15 c.415C>T risk allele was common and significantly enriched, including homozygous high-risk genotypes. These findings support routine pre-treatment NUDT15 genotyping, with TPMT testing where indicated, to guide dose adjustment and reduce thiopurine-related myelosuppression.
How VarSeq Was Used: “Identifying with this goal, we analyzed anonymized whole-exome sequencing data (GRCh38) processed with the Illumina DRAGEN pipeline from 1,742 individuals tested at a collaborative tertiary laboratory in India, including 609 hematology cases evaluated for both benign and malignant indications. TPMT and NUDT15 variants were curated from Clinical Pharmacogenetics Implementation Consortium (CPIC) and annotated in VarSeq ((Golden Helix, Inc.) using 1000 Genomes Project, IndiGen, gnomAD v4.1, RefSeq, and ClinVar; variants with high population frequency, synonymous/nonfunctional annotations, or benign ClinVar classifications were excluded and the remainder classified according to ACMG/AMP guidelines. Allele frequencies in the hematology cohort were compared to the broader pan-India non-hematology cohort and benchmarked across major ancestry groups, with enrichment assessed by contingency testing.”
Citation: Chepsy Philip, Rajdeep Raha, Bani Jolly, Minu Luckose, Aakash Chozakade, Bonnie George, Anupa Jacob, Magdelin Simon, Bobby George, Sudhir Venkatesh, Vinod Scaria, Thiopurine pharmacogenomic landscape in India: TPMT and NUDT15 allele frequencies, Blood, Volume 146, Supplement 1, 2025, Page 7999, ISSN 0006-4971, https://doi.org/10.1182/blood-2025-7999.
Title: Whole genome sequencing identifies monogenic disease in 56.1% of families with early-onset steroid-resistant nephrotic syndrome
Background: Steroid-resistant nephrotic syndrome (SRNS) is a severe kidney disorder characterized by poor response to standard glucocorticoid therapy and a high risk of progression to chronic kidney disease. Increasing evidence shows that a substantial proportion of SRNS cases are driven by monogenic variants affecting podocyte structure and function, yet many patients remain undiagnosed using conventional genetic testing approaches.
Objectives: To evaluate the genetic basis of steroid-resistant nephrotic syndrome by applying genome sequencing as a first-tier diagnostic approach in affected patients.
Subjects and Methods: We enrolled children and young adults diagnosed with steroid-resistant nephrotic syndrome from unrelated families and collected detailed clinical, histopathologic, and family history data. Genomic DNA was extracted from peripheral blood and analyzed using whole genome sequencing with standardized bioinformatics pipelines for alignment, variant calling, annotation, and prioritization. Candidate variants were classified using established clinical guidelines and confirmed by segregation analysis when applicable.
Results:
- Whole genome sequencing identified disease-causing or likely disease-causing variants in over half of the affected families, substantially exceeding the diagnostic yield typically reported for targeted panels or exome sequencing. The highest detection rates were observed in patients with earlier disease onset and familial clustering.
- Pathogenic variants were detected across a diverse set of genes involved in podocyte structure and glomerular filtration, including several novel variants not previously associated with SRNS. NPHS2 was the most frequently implicated gene in the cohort.
- A range of variant types was identified, including missense, truncating, and splice-site variants, with most predicted to have deleterious effects on protein function. Structural modeling supported the pathogenic impact of missense variants.
- Genetic diagnoses provided clinically actionable information relevant to treatment selection, transplant planning, and family counseling. No deep intronic or regulatory variants were detected in unresolved cases.
Conclusions: Genome sequencing as a first-tier test achieved a high diagnostic yield in patients with steroid-resistant nephrotic syndrome, demonstrating its value over conventional genetic approaches. Identifying a monogenic cause has important implications for clinical management, including avoiding ineffective immunosuppression and informing transplant and family counseling decisions. These findings support the routine integration of genome sequencing into the diagnostic evaluation of SRNS.
How VarSeq Was Used: “VCF files were processed, and variants were prioritized using BaseSpace Variant Interpreter® (Illumina, San Diego, CA, USA), VarSeq® (Golden Helix, Inc., Bozeman, MT, USA), Congenica (Congenica LTD, Cambridgeshire, United Kingdom) and VarSome® (Lausanne, Switzerland). All genes previously reported as causative of SRNS (Supplementary Table 1) including both exonic and intronic regions were evaluated as a first step; however, the whole genome was examined when no conclusive pathogenic/likely pathogenic variants were detected in the target genes. In the second step, we evaluated all pathogenic and likely pathogenic variants detected by the above mentioned software programs across the whole genome and not previously related to SRNS. These variants were evaluated separately in the context of patients’clinical features and through reverse phenotyping if needed and only those overlapping significantly with their corresponding patients’phenotypes were reported. Copy number variants (CNVs) and structural variants (SVs) were assessed using BAM files uploaded to VarSeq® software. The pathogenicity of suspected variants was classified according to the American College of Medical Genetics and Genomics (ACMG) (Richards et al. 2015; Tavtigian et al. 2020) and the Association for Clinical Genomic Science (ACGS) (UK 2023) guidelines. Sanger sequencing was used to confirm the variants revealed by next-generation sequencing and to confirm that novel pathogenic variants properly segregated in parents and available family members according to the reported mode of inheritance for each affected gene.”
Citation: Ramadan, Eman, “Whole genome sequencing identifies monogenic disease in 56.1% of families with early-onset steroid-resistant nephrotic syndrome” (2025). Pharmacy. 896. https://buescholar.bue.edu.eg/pharmacy/896
These customer publications reflect a shared commitment to clinical rigor, diagnostic yield, and actionable interpretation across diverse disease areas and populations. Together, the studies featured in December 2025 demonstrate how scalable, integrated genomic analysis supports confident decision-making and continues to advance the practice of clinical genomics.
