A framework for the molecular identification of CHIP for clinical research

TL;DR

This study created a consistent framework to identify individuals with CHIP, a condition linked to aging-related diseases, using genetic data from 2,328 participants.

Contribution

The study introduces a systematic and resource-efficient framework for categorizing CHIP status in clinical research.

Findings

15% of participants were identified as CHIP positive with 400 CHIP-associated variants.

62% of participants were classified as CHIP negative with no somatic variation in target regions.

23% of participants had indeterminate CHIP status due to uninterpretable variants.

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.

This study developed a framework to support the identification of individuals with clonal hematopoiesis of indeterminate potential (CHIP), and those without, for recruitment into a clinical study. 2,328 individuals aged 64–74 were screened, and 15% were identified to have CHIP, 62% did not have CHIP, and 23% had indeterminate findings.

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