Metabolon Delivers Large-Scale Metabolomics Dataset to Genomics England's 100,000 Genomes Project to Advance Rare Disease Research

Dataset from more than 7,500 participants expands multiomic analysis in rare disease research by combining metabolomics with genomic and clinical data

MORRISVILLE, N.C., June 24, 2026 /PRNewswire/ -- Metabolon, Inc., the global leader in metabolomics solutions advancing life science research, diagnostics, therapeutics, and precision medicine, today announced the successful completion and delivery of comprehensive metabolomic data generated through its collaboration with Genomics England, first publicized in October 2023. The dataset includes metabolomic profiles from more than 7,500 participants from the 100,000 Genomes Project, advancing one of the world's most ambitious efforts to apply multiomic methodologies to rare disease research. Metabolon is the first company to generate and deliver a metabolomics dataset of this scale for integration with a large national genomic initiative.

Rare diseases affect an estimated 350 million people worldwide and remain among the most challenging conditions to diagnose and treat. More than 7,000 rare diseases have been identified, with over 250 new diseases described each year, yet only about 360 have approved therapies. The burden is especially severe for children: half of all patients are pediatric, and 30% do not survive past age five. Diagnosis is often prolonged and uncertain, averaging 7.6 years in the U.S. and 5.6 years in the UK, with 41% of patients misdiagnosed at least once [1]. Although genomics has advanced rare disease research, genetic variants alone do not always explain clinical presentation or provide practical treatment options.

The collaboration between Metabolon and Genomics England was designed to help address these challenges by generating large-scale metabolomic data to complement existing genomic and clinical information. Metabolon has completed data generation, enabling the future integration of metabolomics into Genomics England's Trusted Research Environment (TRE). The metabolomics data will be available to approved clinicians and researchers in due course, who will be able to securely explore biochemical profiles alongside genomic variation and patient phenotypes.

Targeted metabolomics is commonly used in rare disease diagnostic workflows, but this new dataset represents a significant expansion in scope and scale. By applying global metabolomics across thousands of deeply characterized patients, the collaboration aims to demonstrate how metabolomics can improve diagnostic yield, support disease monitoring, and generate new treatment opportunities. In prior clinical studies, metabolomic profiling has been shown to deliver a 6-fold increase in diagnostic yield compared with standard assays alone [2].

Dr. Ellen Thomas, Chief Medical Officer of Genomics England, said: "These data, alongside the growing genomic and health data within the National Genomic Research Library, will be a valuable resource to researchers in making life-changing discoveries and breakthroughs for patients."

"We know how important research is in reducing the diagnostic odyssey that many with rare conditions face, and the need to provide researchers with all the available tools to improve the lives of these patients and their families. We're pleased that we will be able to offer this metabolomic data in due course, which targets faster diagnoses and better biological understanding of rare conditions."

"Rare disease patients often endure a diagnostic odyssey that can last years, with many experiencing misdiagnoses along the way," said Dr. Karl Bradshaw, Chief Business Officer at Metabolon. "By delivering this dataset, we aim to show the power of metabolomics to provide functional insights that complement genomics data and help uncover disease mechanisms that may otherwise remain hidden."

To learn more about how Metabolon can power your multiomic studies, visit:
https://www.metabolon.com/multiomics

About Metabolomics
Metabolomics, the large-scale study of all small molecules in a biological system, is the only omics technology that provides a complete current-state functional readout of a biological system. Metabolomics helps researchers see beyond individual genetic variation, capturing the combined impact of genetic and external factors, such as drugs, diet, lifestyle, and the microbiome, on human health. By measuring thousands of discrete chemical signals that form biological pathways in the body, metabolomics can reveal important biomarkers, enabling a better understanding of a drug's mechanism of action, pharmacodynamics, and safety profile, as well as individual responses to therapy.

About Metabolon 
Metabolon, Inc. is the global leader in metabolomics, with a mission to deliver biochemical data and insights that expand and accelerate the impact of life sciences research and complement other 'omics' technologies. With more than 25 years, 15,000+ projects, 4,000+ publications, and ISO 9001:2015, CLIA, and CAP certifications, Metabolon has developed industry-leading scientific, technological, and bioinformatics techniques. Metabolon's Global Discovery Panel is powered by the world's largest proprietary metabolomics reference library. Metabolon's industry-leading data and translational science expertise help customers and partners address some of the most challenging and pressing questions in the life sciences, accelerating research and enhancing development success. The company offers scalable, customizable multiomics solutions, including metabolomics and lipidomics, that support customer needs from discovery through clinical trials and product life-cycle management. For more information, please visit www.metabolon.com and follow us on LinkedIn and X.

Note to Editors (References)

1. Vandeborne, L., et al., Information needs of physicians regarding the diagnosis of rare diseases: a questionnaire-based study in Belgium. Orphanet J Rare Dis, 2019. 14(1): p. 99.
2. Liu, N., et al., Comparison of Untargeted Metabolomic Profiling vs Traditional Metabolic Screening to Identify Inborn Errors of Metabolism. JAMA Netw Open, 2021. 4(7): p. e2114155.

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