Evidence map›Paper›PMID 41566785›Full record

ArticleHGG advances2026

A framework for the molecular identification of CHIP for clinical research.

Philip Harraka, Robert L O'Reilly, Jared Burke, Paul Yeh, Kerryn Howlett, Kiarash Behrouzfar, Daniele Belluoccio, Amanda Rewse, Brigid M Lynch, Kristen J Bubb and 3 more

Abstract read
In one paragraph

Article in HGG advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Philip HarrakaPrecision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia.
Robert L O'ReillyPrecision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia.
Jared BurkePrecision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia.
Paul YehMonash Haematology, Monash Health, Clayton, VIC 3168, Australia; Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia.
Kerryn HowlettPrecision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia; Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia.
Kiarash BehrouzfarDepartment of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia.
Daniele BelluoccioDiagnostics and Genomics Group, Agilent Technologies Australia Pty Ltd., Mulgrave, VIC 3170, Australia; Clinical Genomics, School of Translational Medicine, Monash University, Melbourne, VIC 3004, Australia.
Amanda RewsePrecision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia.
Brigid M LynchCancer Epidemiology Division, Cancer Council Victoria, East Melbourne, VIC 3002, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3010, Australia.
Kristen J BubbBiomedicine Discovery Institute, Monash University, Clayton, VIC 3168, Australia; Victorian Heart Institute, Monash University, Clayton, VIC 3168, Australia.
Stephen J NichollsVictorian Heart Institute, Monash University, Clayton, VIC 3168, Australia; Victorian Heart Hospital, Clayton, VIC 3168, Australia.
Roger L MilnePrecision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia; Cancer Epidemiology Division, Cancer Council Victoria, East Melbourne, VIC 3002, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3010, Australia.
Melissa C SoutheyPrecision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia; Cancer Epidemiology Division, Cancer Council Victoria, East Melbourne, VIC 3002, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3010, Australia. Electronic address: melissa.southey@monash.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Biomedical ResearchClonal HematopoiesisAgedAgingAustraliaFemaleHumansMaleMiddle AgedCHIPclonal hematopoiesisclonal hematopoiesis of indeterminate potentialframeworkgenetics

Identifiers

PMID41566785
PMCPMC12925157

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.