April’s customer publications with clinical genomic insights across healthy aging genes in Super Seniors, chronic kidney disease, and breast cancer risk stratification.
Each month, we highlight new research from the scientific community that advances our understanding of complex genetic diseases and showcases the tools researchers rely on for precise variant interpretation. Our customer publications in April explored healthy aging genes in Super Seniors, chronic kidney disease, and breast cancer risk stratification.
Title: Genome-Wide Association Study and Pathway Analysis of Healthy Aging in Super Seniors
Background: Genome-wide association studies have identified some genetic loci linked to longevity and health span, but only a few, such as APOE and FOXO3, are consistently replicated across populations. This inconsistency likely reflects the significant role of environmental and lifestyle factors, as well as differences in how healthy aging is defined. While genetics do contribute to lifespan, they explain only about 15–40% of the variation in human longevity.
Objective: This article aims to better understand resilience to age-related diseases in Super Seniors, including cancer, cardiovascular disease, diabetes, pulmonary disease, and dementia. This exceptionally healthy group offers a valuable opportunity to identify genetic factors that may protect against disease and support healthy aging.
Subjects and Methods: Researchers collected and genotyped DNA samples from 1017 individuals (597 cases and 420 controls), applied extensive quality control, and focused on individuals of European ancestry, yielding millions of high-quality genetic variants for analysis. They then conducted targeted analyses of known longevity-related genes (like APOE and FOXO3) and a genome-wide association study (GWAS) to identify genetic factors linked to healthy aging, including potential sex-specific effects
Results: This study expanded earlier analyses of longevity-related genes in a larger sample, confirming that variants in APOE, particularly the ε4 type, are associated with lower odds of healthy aging, with stronger effects observed in females. Additional variants near APOE (in TOMM40 and APOC1) and in FOXO3 showed modest or sex-specific associations, further supporting their role in aging and disease resistance. Overall, the results reinforce APOE ε4 as a risk factor and suggest FOXO3 contributes to healthy aging, especially in women. A genome-wide analysis also indicated that healthy aging is likely influenced by many genetic variants with small effects, rather than a few major ones.
Conclusions: Healthy aging appears to have a polygenic basis, meaning it is influenced by many genetic variants with small effects acting through interconnected biological pathways. These pathways—such as those involved in immune function, metabolism, stress response, and cell survival—work together to support longevity and health. Further functional studies are needed to clarify these mechanisms and to help develop interventions that could promote healthy aging even in individuals without a strong genetic advantage.
How SVS was used: “A total of 1127 DNA samples (673 Super Seniors and 454 controls) were genotyped for 4,559,465 single nucleotide polymorphisms (SNPs) using a custom Infinium Omni5Exome-4 v1.3 Bead Chip (Illumina, San Diego, CA, USA) at the McGill University/Genome Quebec Innovation Centre. Quality control (QC) was conducted using Golden Helix and PLINK v1.9.0-b7.7 [16]. QC procedures included re-clustering, removal of duplicate and tri-allelic SNPs, strand error checks, and assessments of sex discrepancies (8 samples removed) and relatedness. Related individuals were identified using KING v2.2.8 [17] with a 3rd-degree relatedness threshold, yielding 39 related pairs. Of these, 24 pairs were replicated samples included for QC purposes and 15 represented biological relatedness of participants; in the latter case, the younger individual was removed (39 samples in total). Genetic principal component analysis (PCA) was used to filter to include only the largest ethnicity group, individuals of European ancestry (44 individuals removed). In the final step, individuals exhibiting excessive heterozygosity (± 3 SD) were removed (16 individuals removed). Afterward, 1020 unrelated individuals of European ancestry (599 Super Seniors and 421 controls) and 3,482,546 variants remained.”
Citation: Hoque, R., Leach, S. & Brooks-Wilson, A. Genome-wide association study and pathway analysis of healthy aging in Super Seniors. GeroScience (2026). https://doi.org/10.1007/s11357-026-02229-4
Title: A Whole-Exome Sequencing-Based Exploration of Chronic Kidney Disease of Unknown Etiology (CKDu) in an Endemic Population in Sri Lanka
Background: Chronic kidney disease (CKD) is a growing global health problem, driven largely by conditions like diabetes, hypertension, and aging, and influenced by both genetic and environmental factors. It disproportionately affects disadvantaged populations and can lead to major financial and health burdens, especially in advanced stages requiring dialysis or transplantation.
A related condition, CKDu (chronic kidney disease of unknown cause), has emerged in agricultural communities in tropical regions, where environmental exposures such as heat stress, toxins, and agrochemicals are suspected contributors. However, patterns of familial clustering suggest that genetic susceptibility may also play a role, even though the exact causes remain unclear.
Objective: Whole-exome sequencing studies of CKDu are currently limited, highlighting the need for larger, more comprehensive genomic research that includes diverse populations and examines interactions between genetic and environmental factors. This study aims to address that gap by analyzing patients and control groups from both endemic and non-endemic regions in Sri Lanka to better understand the genetic basis of the disease.
Subjects and Methods: This study recruited CKDu patients from a high-risk region and compared them with healthy individuals from both endemic and non-endemic areas, ensuring that all participants were carefully screened to exclude known risk factors such as diabetes and hypertension. Blood samples were collected, DNA was extracted, and whole-exome sequencing was performed, followed by rigorous quality control and filtering to identify rare, potentially disease-related genetic variants.
The analysis focused on variants likely to impact gene function and linked them to kidney-related traits using established databases and computational tools, enabling comparisons between patients and controls to identify genetic factors associated with CKDu.
Results: Whole-exome sequencing of 86 participants identified over 4 million genetic variants, which were progressively filtered to focus on rare, high-confidence variants likely to affect protein function and be relevant to CKDu. This process narrowed the dataset to 173 potentially pathogenic variants across 121 genes مرتبط with kidney function and toxin handling.
Several genes, particularly LFNG, PNLDC1, and ATXN3, showed higher variant prevalence in CKDu patients, with LFNG demonstrating a statistically significant association. Overall, CKDu individuals were more likely to carry multiple co-occurring variants, supporting the idea that the disease may result from the combined effects of multiple genetic factors rather than a single cause.
Conclusions: This study shows that chronic kidney disease of unknown etiology (CKDu) in Sri Lanka likely arises from a complex mix of genetic and environmental factors. Although ATXN3 variants were common, they don’t appear to play a major direct role in causing the disease. In contrast, LFNG variants may contribute to CKDu by disrupting kidney repair mechanisms, possibly through altered Notch signaling. The mixed pattern of HLA-DRB1 variants further suggests that disease risk depends on interactions among genetic, environmental, and immune factors.
How VarSeq v2.6.2 was used: “Exome libraries were constructed using Illumina’s DNA prep with exome 2.5 enrichment, per the manufacturer’s instructions (Illumina Inc., San Diego, CA, USA, catalog #: 20077595). Libraries were sequenced on the Illumina NovaSeqX platform, 150 bp paired-end reads to an average read depth of 84,475,876 reads per sample. Raw reads underwent QC, mapping and variant calling using Sentieon’s DNAscope pipeline with the GRCh38 human reference genome build (Sentieon Inc., San Jose, CA, USA). Variant calls from DNAscope for each sample were used as the input for interpretation using Golden Helix’s VarSeq™ v2.6.2 (Golden Helix, Inc., Bozeman, MT, USA, www.goldenhelix.com) variant filtration and interpretation software. In total, 74 endemic samples and 12 non-endemic samples in the cohort were sequenced (n = 86). Variants were filtered first for quality and had to have an average read depth of 50, a genotype quality Q-score had to be ≥20, and the variant allele fraction had to be ≥0.1.”
Citation: Tom, W., Weerakoon, C., Fernando, N., Hasantha, I., Bandara, M., Krzyzanowski, G., Nanayakkara, S., Cosgrove, D., Nanayakkara, N., & Fernando, M. R. (2026). A Whole-Exome Sequencing-Based Exploration of Chronic Kidney Disease of Unknown Etiology (CKDu) in an Endemic Population in Sri Lanka. International Journal of Molecular Sciences, 27(8), 3369. https://doi.org/10.3390/ijms27083369
Title: Integrating Baseline ctDNA-Derived Tumor Metrics Enhances Risk Stratification in HR-Positive/HER2-Negative Advanced Breast Cancer: A Real-World Multicenter Cohort Study from Austria
Background: Advances in endocrine therapies have significantly improved outcomes for patients with HR-positive/HER2-negative advanced breast cancer. However, a major challenge remains in effectively using molecular and clinical risk factors to guide personalized treatment decisions.
Objective: This article aimed to use circulating tumor DNA (ctDNA) to analyze the genomic and prognostic features of patients with HR-positive/HER2-negative advanced breast cancer in early treatment lines. By taking a tumor-agnostic approach, the researchers aimed to more meaningfully stratify patients using baseline ctDNA metrics.
Subjects and Methods: This prospective study enrolled patients with HR-positive/HER2-negative advanced breast cancer across three Austrian centers and collected blood samples at diagnosis or treatment progression. Researchers analyzed circulating tumor DNA (ctDNA) from plasma using next-generation sequencing to identify genetic alterations and estimate tumor burden through multiple complementary methods. They applied rigorous variant filtering and statistical analyses to assess genomic patterns and their association with patient outcomes. Overall, the study aimed to evaluate the prognostic value of ctDNA metrics and improve risk stratification in real-world clinical settings.
Results: The study found that most blood samples from patients with advanced breast cancer, analyzed, contained detectable genetic mutations. Mutations in genes such as PIK3CA, TP53, and ESR1 were most common, with mutation frequency and complexity increasing in later treatment lines—especially for ESR1, which was often newly acquired after first-line therapy.
Measures of circulating tumor DNA (ctDNA) showed higher tumor burden in later-line patients and were strongly associated with worse clinical outcomes. Importantly, combining multiple ctDNA metrics improved detection and risk stratification, with higher ctDNA levels consistently predicting shorter progression-free and overall survival.
Conclusions: The findings show that ctDNA-based metrics have strong prognostic value in HR-positive/HER2-negative advanced breast cancer. Combining multiple ctDNA measures improves risk stratification beyond traditional clinical factors, making it a useful tool for baseline assessment. Future studies incorporating both baseline and ongoing ctDNA monitoring may further enhance personalized, response-adapted treatment strategies.
How VarSeq v2.2.0 was used: “Variant calling was carried out using the AVENIO Oncology Analysis Software (version 2.1.0, Roche, Basel, Switzerland), with customized filtration settings: variants with a minor allele frequency ≥1% as defined by ExAC version 1.0 or 1000 Genomes version phase_3_v5b databases, or those listed as common single nucleotide polymorphisms (SNPs) in the dbSNP150 database, were excluded by the software. Putative germline variants (characterized by a VAF ∼50% but a low TFx context) were additionally removed. To enable a high confidence variant call set, variants that passed these filters but had <10 mutated reads or a VAF below the assay limit of detection (LOD), as well as recurrent low-level variants observed in multiple patients (suggesting a sequencing or assay artifact) were flagged and manually excluded. The remaining variants were annotated and classified according to their pathogenicity using Golden Helix VarSeq v2.2.0 (Golden Helix Inc., Bozeman, MT) and the OncoKB database.25 For the primary analyses, a VAF threshold of 0.5% was applied to prioritize specificity and analytical confidence over maximal sensitivity, given the risk of false-positive variant calls from the hematopoietic background. Additionally, a secondary analysis using a lower detection threshold (LOD = 0.1% VAF) was conducted to assess the impact of including low-VAF variants on overall genomic landscape patterns.”
Citation: N. Dobrić, S.O. Hasenleithner, C. Suppan, E.V. Klocker, D. Hlauschek, R. Graf, C. Beichler, C. Albertini, D. Egle, D. Liu, A.M. Starzer, R. Bartsch, T. Moser, G. Rinnerthaler, P.J. Jost, E. Heitzer, N. Dandachi, M. Balic, Integrating baseline ctDNA-derived tumor metrics enhances risk stratification in HR-positive/HER2-negative advanced breast cancer: a real-world multicenter cohort study from Austria, ESMO Open, https://doi.org/10.1016/j.esmoop.2026.106939
