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Record W2915866752 · doi:10.1182/blood-2018-99-116128

RNA-Seq Analysis of Clonal Hematopoiesis (CHIP) Blood Leukocytes Shows Dysregulation of Neutrophil / Innate Immunity-Related Genes

2018· article· en· W2915866752 on OpenAlexaffabout
Elina K. Cook, Richard N. Armstrong, Eshita Sharma, Brooke Snetsinger, Jacqueline Boultwood, Rena Buckstein, Andrea Pellagatti, Michael J. Rauh

Bibliographic record

VenueBlood · 2018
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsSunnybrook Health Science CentreHealth Sciences CentreQueen's University
Fundersnot available
KeywordsBiologyMyeloidHaematopoiesisTranscriptomeGeneImmunologyInnate immune systemGene expressionCancer researchGeneticsStem cellImmune system

Abstract

fetched live from OpenAlex

Abstract BACKGROUND: Clonal hematopoiesis of indeterminate potential (CHIP) involves the peripheral blood (PB) expansion of progeny of a hematopoietic stem or progenitor cell that is somatically mutated in a hematological cancer-associated gene (most often TET2 or DNMT3A). CHIP associates with comorbid diseases of aging such as cardiovascular disease. Murine knockout (Tet2 or Dnmt3a) and engraftment models of CHIP develop exacerbated cardiovascular disease and their mutated myeloid cells are more reactive to inflammatory stimuli. However, whether blood leukocytes in human CHIP are hyper-inflammatory remains speculative. We recently found people with CHIP have higher serum levels of certain pro-inflammatory cytokines and chemokines than controls (Cook et al, ASH 2017). Thus, we hypothesized that PB effector cells in people with CHIP will be enriched for pro-inflammatory gene expression and pathways. METHODS: The presence of CHIP (variant allele frequency, VAF>0.02) was determined in the whole PB of 30 hematologically healthy adults >65 years old at Baycrest and Sunnybrook Health Sciences Centers (Toronto, Canada) using Ion Proton DNA sequencing targeting 48 commonly mutated genes in myeloid neoplasms. RNA-Seq (HISeq 4000, Illumina, 75bp paired-end sequencing reads with a depth of >50 million/sample) was performed on corresponding ribo-depleted whole PB samples (PAXgene), reads were aligned with HISAT2, gene counts quantified with featureCount, and analyzed with DESeq2. FDR<0.1 was used as a cutoff for differential gene expression analyses. Correlations with clinical and comorbidity data were tested with logistic regressions. RESULTS: People with CHIP ("CHIP+", n: males=8, females=13; TET2=12, DNMT3A=8, SF3B1=1; VAF range=0.03-0.40) compared to those without CHIP ("CHIP-", n: males=3, females=6) had six significantly downregulated genes (e.g. GZMM) and 10 upregulated genes (e.g. DEFA4, LTF, MPO, see Figure 1A). Hierarchical clustering of these top genes yielded two groups, one consisting of most of the CHIP- cases (8/9 cases, in a cluster of 11, see Figure 1A). The three CHIP+ cases that clustered with CHIP- had VAFs lower than 0.15. Of the 16 differentially regulated genes between CHIP+ and CHIP-, nine were recognized by reactome, and most overlapped (≥6 genes) with pathways involving neutrophil degranulation and innate immunity (Figure 1B). DEFA4, LTF, CRISP3, BPI and MPO specifically encode components of neutrophil granules, with various anti-microbial and homeostatic functions. However, mean neutrophil counts (4.6±1.6 vs. 4.4±1.6 10^9/L for CHIP+ vs. CHIP-) and neutrophil to lymphocyte ratios (3.2±1.4 vs. 2.8±2.1 in CHIP+ vs. CHIP-) did not significantly differ between the groups. This suggests that mutations of CHIP may affect neutrophil/immune-related function or phenotype, potentially contributing to comorbid disease. For example, greater expression of alpha-defensins (i.e. DEFA4) in CHIP may involve dysregulated granulocyte maturation and inflammatory function as seen in myelodysplasia (Droin et al, 2010 Blood), suggesting a potential dysregulation of inflammation and immunity. Higher VAFs (>0.15) associated with higher ECOG scores (poorer overall daily functioning: odds ratio=44, 95% CI=4-500, p=0.002), suggesting that larger proportions of mutated cells may have greater effects on gene expression profiles. Accordingly, there were linear correlations between the VAFs of the mutated cell populations and the levels of differentially expressed genes (Figure 1C). CONCLUSIONS: The connection between mutant clones of CHIP and disease remains poorly elucidated. For the first time, to our knowledge, we studied gene expression in CHIP leukocytes. We report that the most prominent gene expression differences between people with CHIP and those without CHIP involve neutrophil degranulation and the innate immune system. Additionally, higher VAFs may have a greater influence on gene expression levels and health than lower VAFs. We plan to validate these candidate genes in a larger cohort. These novel data warrant further investigation of the cellular pathways perturbed by somatic mutations of CHIP. Disclosures Buckstein: Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.279
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2018
Admission routes2
Has abstractyes

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