Quantitative Trait of Neutrophil Count Is Influenced By Variants in the Region of Gsdma and PSMD3-CSF3, aging, Cardiometabolic Comorbidities but Not By Chip
Authors: Gagnon Marie-France , Provost Sylvie , Ayachi Sami , Buscarlet Manuel , Mollica Luigina , Dubé Marie-Pierre , Busque Lambert 
Published: November 2021

Abstract
Introduction
Hematopoiesis ensures lifelong oxygenation, immune and hemostatic functions through the production of billions of blood cells on a daily basis. However, little is known about the factors regulating and influencing this highly coordinated process and the resulting peripheral blood cell quantitative traits during the aging process. In this study, we investigated germline and acquired factors associated with blood cell counts in a cohort of normal aging individuals.
Methods
Determinants underlying blood cell trait variability were assessed in a cohort of 2996 related and unrelated women of French-Canadian ancestry aged 55 to 101 years. All participants answered a medical questionnaire and provided a blood sample for complete blood count with differential (GenS, Beckman Coulter) and DNA analysis. Potential hereditary variants of significance were assessed using a genome-wide association study (GWAS). Genotyping was performed according to the manufacturer's specifications on the Illumina Infinium Global Array v3-MD (Illumina, San Diego, CA). Variants with a completion rate of ≥98%, minor allele frequency &gt;1% and imputation probability of ≥0.80 were retained. Genome-wide association testing was conducted with SAIGE_0.43.3 to account for the family-based design of our study. Genome-wide significance threshold was at 5x10 -8. Potential acquired factors of importance such as chronic comorbidities and clonal hematopoiesis of indeterminate potential (CHIP) were also sought. CHIP status was assessed with targeted next-generation sequencing of polymorphonuclear cells using the Ampliseq AML panel. Germline and acquired factors were then integrated in generalized linear mixed models to identify factors associated with blood cell indices in multivariate analysis and to characterize their relative contribution. Statistical analyses were conducted with R.
Results
Mean age of study participants was 69.2 years (standard deviation 9.1 years). Mean values (and standard deviation) of blood cell indices were as follows: total white blood count (WBC) 6.43x10 9/L (1.63), absolute lymphocyte count 1.86x10 9/L (0.57), absolute monocyte count 0.46x10 9/L (0.16), absolute neutrophil count 3.93x10 9/L (1.29), hemoglobin 131.2 g/L (9.67), platelet count 249.2x10 9/L (57.6). Neutrophil and monocyte counts increased with age (b1 coefficient 0.02 (p-value 6.06E-08) and 0.004 (p-value 2.2E-16) respectively), while lymphocyte and platelet counts decreased with advancing age (b1 coefficient -0.01 (p-value 3.65E-07) and -0.29 (p-value 0.023) respectively). GWAS identified 13 variants in the region of GSDMA and PSMD3-CSF3 (chromosome 17) that met genome-wide requirements for WBC and neutrophil counts. Platelet count was significantly associated with a variant intronic to ARHGEF3 (chromosome 3). Among acquired factors, smoking was positively associated with neutrophil, monocyte, lymphocyte counts and hemoglobin levels. Distinctly, we document that cardiometabolic comorbidities (diabetes, coronary heart disease, hypertension and dyslipidemia) are associated with a statistically higher count of myeloid-derived cells (neutrophil count 4.1 vs 3.83 (95%CI 0.28-0.37, p-value &lt;0.001), monocyte count 0.50 vs 0.45 (95%CI 0.02-0.05, p-value &lt;0.001), and platelet count 259 vs 243 (95%CI 10-20, p-value &lt;0.001). These results remained significant in multivariate analysis. In accordance with previous reports, CHIP, which was documented in 14% of the cohort, had no influence on blood counts.
Conclusion
We document that individual variation in blood counts in individuals is influenced by several factors: (i) germline variants related to GSDMA and PSMD3-CSF3 contribute to white blood cell and neutrophil counts and a variant intronic to ARHGEF3 is influential in determining platelet counts; (ii) aging is associated with increasing levels of neutrophils and monocytes, and reduced lymphocyte and platelet counts, indicating a shift towards myelopoiesis; (iii) this myeloid-biased skewing is further increased among individuals with cardiometabolic comorbidities; (iv) CHIP does not contribute to the age-associated myeloid shift. These findings support that chronic age-related diseases may promote myelopoiesis and contribute to population variability in peripheral blood traits, possibly through a state of low-grade inflammation.
Figure 1 Figure 1.

Disclosures
Busque: Novartis: Consultancy.