From Blood Sample to Biological Age — Five Validated Steps
Our end-to-end pipeline is built on gold-standard molecular biology protocols and validated against independent cohorts totalling over 15,000 samples. Every step is CLIA-compliant and reproducible.
Peripheral blood samples are collected via standard venipuncture. Genomic DNA is extracted using validated protocols, quantified by fluorometry, and assessed for quality prior to bisulfite conversion.
DNA undergoes sodium bisulfite conversion, converting unmethylated cytosines to uracil while methylated cytosines remain unchanged. Converted DNA is hybridized to the Illumina Infinium EPIC v2.0 BeadChip, interrogating 935,000+ CpG sites.
Raw IDAT files are processed using the minfi and ChAMP R pipelines. Samples undergo stringent QC filtering: detection p-value < 0.01, bisulfite conversion efficiency > 95%, and minimum bead count thresholds.
Beta values at clock CpG sites are extracted and fed into validated epigenetic clock algorithms — Horvath (2013), Hannum (2013), PhenoAge (2018), and GrimAge (2019) — producing multi-clock biological age estimates with confidence intervals.
Biological age estimates are contextualized against population norms, stratified by sex and ancestry. The XELGEN clinical report delivers age acceleration metrics, organ-specific clock scores, and longitudinal tracking capabilities.
Four Validated Clocks. One Comprehensive Score.
XELGEN runs all four landmark epigenetic clocks in parallel, then computes an ensemble biological age score that is more robust than any single clock alone.
The original multi-tissue epigenetic clock. Trained on 8,000 samples across 51 tissue types. Measures intrinsic biological aging independent of lifestyle factors.
Blood-specific clock trained on 656 whole blood samples. Correlates strongly with chronological age and predicts age-related disease risk.
Phenotypic age clock trained to predict biological phenotypic age using clinical biomarkers. Strong predictor of mortality, morbidity, and healthspan.
The strongest mortality predictor among all epigenetic clocks. Trained on time-to-death outcomes. Predicts lifespan, healthspan, and disease onset.
47 Publications. 3 Nature-Family Journals.
Search and filter the full XELGEN publication database.
Led by World-Class Epigenetic Scientists
Our scientific team combines deep expertise in molecular biology, computational genomics, and clinical medicine — with a combined publication record of 88 peer-reviewed papers.
Dr. Chou is a world-leading researcher in epigenetic aging and regenerative medicine. His laboratory pioneered the application of genome-wide methylation analysis to stem cell potency assessment. He has published 47 peer-reviewed papers in journals including Nature Aging, Cell Stem Cell, and Genome Biology.
Dr. Chen leads XELGEN's computational pipeline development. She designed the multi-clock ensemble scoring algorithm and the ancestry-correction framework used in all XELGEN clinical reports. Previously a postdoctoral researcher at the Broad Institute.
Dr. Patel bridges XELGEN's laboratory science with clinical practice. He oversees the design of clinical integration protocols, physician training programs, and outcome monitoring frameworks for enrolled regenerative medicine clinics.
Validated. Reproducible. Peer-Endorsed.
"XELGEN's multi-clock ensemble approach represents a meaningful advance over single-clock biological age estimation. The ancestry correction methodology is particularly well-designed for diverse clinical populations."
"The clinical integration framework developed by the XELGEN team is the most rigorous I have seen applied to epigenetic testing in a regenerative medicine context. The QC standards are exemplary."