A framework for the molecular identification of CHIP for clinical research

Clonal hematopoiesis of indeterminate potential (CHIP) is associated with many diseases of aging. Large research initiatives are needed to develop clinical guidelines for the management of individuals with CHIP and their risk of disease. However, little guidance is available for the classification of variants as CHIP associated or how to identify individuals consistently and systematically as having CHIP. This study aimed to develop and execute a resource-mindful framework for identifying individuals with CHIP, and those without, for downstream clinical studies. This framework was used to categorize CHIP in a cross-section of 2,328 participants from the Australian Breakthrough Cancer Study. DNA extracted from saliva samples was sequenced for a panel of ten gene regions that frequently carry variants that are associated with CHIP. Variants in these regions were curated for CHIP according to field-specific criteria. Individuals were categorized as either CHIP positive, CHIP negative, or CHIP indeterminate based on their variant findings. Sequencing was successfully performed on 2,328 individuals. The mean age (± standard deviation) was 68 ± 3 years, and 48% were men. 347 participants (15%) were identified as CHIP positive with a total of 400 CHIP-associated variants. 1,442 participants (62%) were considered CHIP negative based on finding no somatic variation within the target regions. The remaining 539 (23%) were considered CHIP indeterminate because they had at least one variant that could not be interpreted. This framework provides a consistent approach to the categorization of individuals as CHIP positive or CHIP negative for clinical research and provides an opportunity for improved harmonization in the curation of CHIP.

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Publication Details

Journal
Human Genetics and Genomics Advances
Published
2026-01-21
DOI
https://doi.org/10.1016/j.xhgg.2026.100575
Primary Topic
Genomics and Rare Diseases
Type
article
Field-Weighted Citation Impact
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article

A framework for the molecular identification of CHIP for clinical research

Philip Harraka, Kristen J. Bubb, Kiarash Behrouzfar, Daniele Belluoccio et al.
Human Genetics and Genomics Advances
Genomics and Rare Diseases
article

A framework for the molecular identification of CHIP for clinical research

Philip Harraka, Kristen J. Bubb, Kiarash Behrouzfar, Daniele Belluoccio, Kerryn Howlett, Brigid Mary Lynch, Amanda Rewse, Robert L O'Reilly, Melissa C. Southey, Paul Yeh, Stephen J. Nicholls, Jared Burke, Roger L. Milne
article en

Abstract

Clonal hematopoiesis of indeterminate potential (CHIP) is associated with many diseases of aging. Large research initiatives are needed to develop clinical guidelines for the management of individuals with CHIP and their risk of disease. However, little guidance is available for the classification of variants as CHIP associated or how to identify individuals consistently and systematically as having CHIP. This study aimed to develop and execute a resource-mindful framework for identifying individuals with CHIP, and those without, for downstream clinical studies. This framework was used to categorize CHIP in a cross-section of 2,328 participants from the Australian Breakthrough Cancer Study. DNA extracted from saliva samples was sequenced for a panel of ten gene regions that frequently carry variants that are associated with CHIP. Variants in these regions were curated for CHIP according to field-specific criteria. Individuals were categorized as either CHIP positive, CHIP negative, or CHIP indeterminate based on their variant findings. Sequencing was successfully performed on 2,328 individuals. The mean age (± standard deviation) was 68 ± 3 years, and 48% were men. 347 participants (15%) were identified as CHIP positive with a total of 400 CHIP-associated variants. 1,442 participants (62%) were considered CHIP negative based on finding no somatic variation within the target regions. The remaining 539 (23%) were considered CHIP indeterminate because they had at least one variant that could not be interpreted. This framework provides a consistent approach to the categorization of individuals as CHIP positive or CHIP negative for clinical research and provides an opportunity for improved harmonization in the curation of CHIP.

Human Genetics and Genomics AdvancesVol. 7(2)
Cancer Council Victoria (AU), Discovery Institute (US), Australian Regenerative Medicine Institute (AU), Monash Health (AU), Agilent Technologies (Australia) (AU), Monash University (AU)
Openalex Percentile: Top 78%
Genomics and Rare Diseases
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