Can Psoriasis Cause Low White Blood Cell Count – Introduction: Psoriasis is a chronic inflammatory skin disease. Several studies have shown that psoriasis is an immune-mediated disease in which multiple immune cells play a key role. However, the link between circulating immune cells and psoriasis remains elusive.
Methods: To investigate the role of circulating immune cells in psoriasis, 361,322 individuals from the United Kingdom Biobank (UKB) and 3,971 psoriasis patients from China were enrolled to investigate the association between white Blood cells and psoriasis through an observational study. Genome-wide association studies (GWAS) and Mendelian randomization (MR) were used to evaluate the causal relationship between circulating leukocytes and psoriasis.
Can Psoriasis Cause Low White Blood Cell Count
Results: The risk of psoriasis increases with high levels of monocytes, neutrophils and eosinophils (relative risks and 95% confidence intervals, respectively: 1.430 (1.291-1.584) for monocytes, 1.527 (1.379-1.6921, 1.379-1.6921) –1.551) for eosinophils). Upon further MR analysis, eosinophils showed a definite causal relationship with psoriasis (inverse variance weighted odds ratio: 1.386, 95% confidence intervals: 1.092-1.759) and a positive correlation with psoriasis area and severity index (PSI) = 6.6 × 10
Psoriasis: Manifestations, Management, And Mimics
). The roles of neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR) and lymphocyte-monocyte ratio (LMR) in psoriasis were also evaluated. More than 20,000 genetic variations associated with NLR, PLR and LMR were detected in a GWAS analysis using the UKB data. After adjustment for covariates in the observational study, NLR and PLR were found to be risk factors for psoriasis, while LMR was a protective factor. The MR results showed that there was no causal relationship between these three indicators and psoriasis; however, NLR, PLR, and LMR correlated with PASI score (NLR: rho = 0.244, P = 2.1 × 10
Discussion: Our findings revealed an important association between circulating leukocytes and psoriasis, which is instructive for the clinical practice of psoriasis treatment.
As a common chronic inflammatory skin disease, psoriasis affects more than 60 million adults and children, significantly impairs patients’ quality of life, and places a heavy burden on individuals and society (1); however, the pathogenesis of psoriasis has not yet been fully elucidated (2). Immune cells play a key role in the pathogenesis of psoriasis (1, 3, 4), and previous studies have indicated the importance of systemic immunity in psoriasis, such as excessive interleukin 17 (IL-17) and interleukin 36, in circulating immune cells (5 , 6). Meanwhile, patients with psoriasis have shown a unique profile of circulating leukocytes (7, 8), and increased numbers of neutrophils have been found in multiple studies (9, 10). However, more studies have focused on immunocytes from psoriasis skin lesions (11-13), and the role of circulating white blood cells in psoriasis remains unclear. Lymphocytes, especially T cells, are recognized as disease-causing cells in psoriasis (14); however, some studies have shown decreased circulating lymphocytes in patients with psoriasis (15). The relationship between psoriasis and other circulating cells, such as eosinophils and basophils, is rarely reported. Therefore, it is necessary to further investigate this association.
Although some studies have shown the important role of circulating immune cells in psoriasis, these results were based on observational studies that were limited by sample size and bias. More appropriate methods are needed to improve these studies. Mendelian randomization (MR) studies use instrumental variables related to exposure to assess possible causal relationships with outcomes. This method can reduce potential confounding bias (16, 17). Causal relationships between different phenotypes and diseases have been revealed using MR analysis (18, 19). Thus, it is feasible to use MR to investigate the causal relationship between circulating immune cells and psoriasis.
Psoriatic Disease Affects More Than Skin And Joints
To further understand the role of circulating immune cells in psoriasis, we investigated the association between the five major types of white blood cells and psoriasis using data from the United Kingdom Biobank (UKB) and the Chinese population and assessed a potential causal relationship between psoriasis and white blood cells. cells. We further investigated the roles of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) in psoriasis. Our results provide a comprehensive overview of the association between circulating white blood cells and psoriasis, suggesting that eosinophil Count is a potential factor associated with the incidence and severity of psoriasis.
In total, 361,322 individuals from UKB and 3,971 individuals from the Chinese population were included in our study (Figure 1). The UKB is a prospective cohort study with a large amount of genetic and phenotypic data collected from approximately 500,000 individuals across the United Kingdom from 2006 to 2010 (20–22). Psoriasis patients were included from primary care, hospital admissions, self-reports, and other sources at the ICU (Table S1). Participants were excluded from the UKB database based on the following criteria: failed genotypic data quality control (missing information for individual data > 0.02, gender mismatch and deviation of more than ± 3 standard deviations (SD) from heterozygosity rate mean of samples); consanguinity >relationship of the first degree; genetic ethnicity showed non-Caucasian (defined by data field: 22,006 from UKB based on principal component analysis of genotypes) (23); suffering from diseases of the blood and hematopoietic system, including leukemia, lymphoma, multiple myeloma, aplastic anemia, and agranulocytosis, among others (Table S1); and white blood cell count >200 × 10
Cells/L (24). The Chinese population included psoriasis patients admitted to Xiangya Hospital, Central South University between 2019 and 2020. Patients with diseases of the blood and hematopoietic system and abnormal white blood cell count (>200 × 10
Cells/L) were excluded. The diagnosis of psoriasis in the Chinese population was confirmed by two or more dermatologists. UKB received ethical approval from the North West Multi-centre Research Ethics Committee (11/NW/03820). All procedures involving study participants in the Chinese population were approved by the Xiangya Hospital Institutional Research Ethics Board (2018121106). Written informed consent was obtained from all participants prior to the investigation.
Low White Blood Cell Count: Causes And What It Means
We selected white blood cells, lymphocytes, monocytes, neutrophils, eosinophils, and basophil counts as indicators of circulating leukocytes (19). All measured white blood cell data were obtained from baseline at UKB. To obtain white blood cell counts, Beckman Coulter LH750 instruments were used to analyze blood samples collected in EDTA (ethylenediamine tetraacetic acid) vacutainers from UKB participants and the Chinese population. Regarding data distribution, eosinophils and basophils showed a skewed distribution in UKB (Figure S1). Moreover, the five main types of white blood cells correlated with each other (Fig. S2, all P
). We simultaneously calculated NLR, PLR and LMR by neutrophil count, lymphocyte count, monocyte count and platelet count excluding individuals whose denominator was zero.
Psoriasis phenotype was identified using International Classification of Diseases (ICD-9 and ICD-10) codes for UKB participants and the Chinese population. We assessed psoriasis severity using three indices: Psoriasis Area Score and Severity Index (PASI), Dermatology Life Quality Index (DLQI), and Body Surface Area (BSA) (25-27). The PASI score was calculated based on the intensity of three clinical signs (redness, thickness and peeling) in four parts of the body (head, arms, trunk and legs) (more details are available at https://dermnetnz.org/topics/pasi -score). BSA was calculated based on the percentage of skin affected by psoriasis, expressed as a percentage of total body surface area. DLQI was determined via questionnaires to assess the extent to which the skin problem affected patients’ lives during the past week (questionnaires available at https://www.nhsfife.org/media/32589/dermatology-life-quality- index-length.pdf). Dermatologists graded the PASI and BSA score according to the area and severity of the lesions, and the DLQI was obtained from a questionnaire.
Psoriasis patients were initially excluded from the UCD, and 353,418 participants were included in the cohort study. The mean follow-up time was 12.88 years. Z-score standardization was adopted to process the data to eliminate confounding of different dimensions among white blood cell types. The white blood cell count and the number of the five major types of white blood cells were divided into four categories in the UCD based on quartiles. Relative risks (RRs) and 95% confidence intervals (95% CIs) were calculated for each category, using the first category as reference. We also analyzed the relationship between different types of white blood cells and psoriasis in the continuously defined white blood cell count using Cox regression models with age as time scale and logistic regression models. Sex, age, smoking status (never, former, and current), alcohol drinking status (never, former, and current), and body mass index (BMI) were adjusted as covariates ( 28 ). To confirm the findings, a sensitivity analysis was performed excluding individuals with a reported incidence of psoriasis in the first two years after baseline. Because of the correlations among the major WBC types (fig. S2), a lasso regression model including five WBC types and covariates was used to select important variables and avoid potential multicollinearity (29). For NLR, PLR, and LMR, z-score standardization was used to remove the influence of dimension, and association with psoriasis was assessed using a Cox regression model. In the Chinese population, Spearman’s correlation was used to determine the correlation between indices associated with white
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