CerS6 gene methylation in peripheral blood is associated with asthma and the frequent exacerbator phenotype

doi:10.21203/rs.3.rs-5309554/v1

Background

Sphingolipids metabolism regulated by ceramide synthase (CerS) enzyme is closely related to asthma development, but the underlying biological mechanism remains unclear. Given the critical role of epigenetics in the pathogenesis of asthma, we explored the DNA methylation patterns of CerS1-6, the genes encoding the CerS enzyme, in asthma patients.

Methods

We enrolled 26 asthma patients and six healthy controls for this study. Peripheral blood samples were collected for the analysis of serum phospholipid profiles and DNA methylation assays. Linear regression models were employed to estimate DNA methylation dynamics of CerS1-6 genes between asthma patients and healthy controls, followed by bootstrap-based internal validation. Subgroup analyses were conducted for various asthma phenotypes. The correlation between the identified differentially methylated CpG sites and ceramide metabolites was further investigated.

Results

Among 127 CpG sites on CerS1-6, four sites (cg18956199, cg21465008, cg03236449, and cg15455300) on CerS6 gene were significantly differentially methylated between asthma patients and healthy controls. Specifically, cg15455300 exhibited significantly lower methylation levels in asthma patients and was significantly associated with frequent asthma exacerbations and poor asthma control. Internal validation indicated robust and significant differences at locus cg18956199. We further observed varying degrees of correlation between ceramide metabolites and the methylation levels of the four identified CpG sites. A differentially methylated region (chr2: 169311373–169312695) located on CerS6 was also identified.

Conclusion

Our study offered potential insights into asthma pathogenesis by revealing distinct DNA methylation patterns across CerS6 gene between asthma patients and healthy controls.

Asthma

Ceramide synthase 6

DNA methylation

Epigenetics

Asthma, as one of the prevalent respiratory diseases, significantly impacts the health of both children and adults worldwide, resulting in substantial disease burden and economic costs, leading to a profound decline in the quality of life. Characterized by multiple phenotypes and endotypes, asthma is a complex disease arising due to the combined influence of genetics and the environment¹. Epigenetics serves as a bridge in the interplay between genetics and the environment, enabling the modulation of gene expression without altering the gene sequence. Emerging evidence has revealed that epigenetics plays a regulatory role in the immune response and gene expression associated with asthma². However, the precise epigenetic mechanisms underlying the onset of asthma remain unclear.

Furthermore, asthma is a chronic respiratory condition intricately linked to airway inflammation. Ceramides are essential cell membrane lipids that simultaneously function as second messengers in cellular signaling pathways, exhibiting potent proinflammatory and proapoptotic properties. Existing studies suggest that ceramides play a crucial role in the pathogenesis of asthmatic responses^{3, 4}. Ceramide synthase, coded by CerS genes, is a pivotal enzyme in the de novo synthesis pathway of ceramides⁵. One possible mechanism influencing asthma onset is by affecting the expression of CerS genes. As the most dynamic and reversible epigenetic modification, DNA methylation, achieved by the addition of methyl groups to the cytosine rings of DNA molecules, modulates gene expression primarily by altering the methylation status of promoter regions and chromatin structure. Several epigenome-wide association studies (EWAS) have identified associations between asthma and DNA methylation at CpG sites located in genes that are either known or hypothesized to be involved in asthma^{6, 7}. Nevertheless, there is currently no research focusing on whether the pathogenesis of asthma is associated with DNA methylation of CerS genes.

Therefore, we investigated the dynamics of the DNA methylation of CpG sites mapped on six CerS genes (CerS1 to CerS6) between 26 asthma patients and six healthy controls, and internal validation based on bootstrap resampling was subsequently performed to ensure the robustness of the preliminary findings. We secondarily conducted stratified analyses within the asthma patients to explore whether differences in DNA methylation patterns exist among different subgroups of asthma patients. An additional exploration incorporated the downstream metabolites were also performed to investigate the correlation between the identified differential methylated CpG sites and the expression of Ceramide synthase.

Study design and participants

This cross-sectional study was conducted in the outpatient clinic of respiratory medicine at Peking University Third Hospital from October 2022 to December 2022. Patients met the diagnostic criteria for asthma, according to the 2022 Global Initiative for Asthma guideline. All asthma patients underwent standard pulmonary function tests and serum specific allergen detection. Subjects were excluded if they had acute exacerbation of asthma, bronchiectasis, pneumonia, chronic obstructive pulmonary disease, severe cardiovascular disease, acute or chronic respiratory failure, or malignant tumors. The original recruitment included 40 participants, comprising 34 asthma patients in the case group and six non-smoking normal individuals in the control group. Due to the potential impact of smoking on DNA methylation, seven asthma patients who were smokers were excluded. Additionally, one patient's DNA sample degraded, resulting in the inclusion of 26 asthma patients and six healthy individuals in the primary analysis. This single-center cross-sectional study was approved by the Research Ethics Committee of Peking University Third Hospital (No. 2022348). All procedures were in accordance with the Declaration of Helsinki. All participants were informed about the study protocols and signed informed written consent forms.

Health assessments

Demographic characteristics of all participants such as sex, age, body mass index (BMI), allergic status, age of onset of asthma and asthma exacerbation frequency in the past year were recorded. Additionally, an Asthma Control Test (ACT) score, a widely used questionnaire for assessing the degree of asthma control in patients, was calculated for each asthma patient⁸. Fasting (after at least 8 h) peripheral blood samples were collected from patients using EDTA-Na²⁺ tubes. The blood samples were left at room temperature for approximately 30 min until complete clotting, and then, the samples were centrifuged at 4°C at 2,500 × g for 15 min. The upper serum samples were extracted and then placed in frozen storage at − 80°C. The remaining whole blood cells were also frozen at -80℃.

Liquid chromatography–mass spectrometry

The serum metabolite components were analyzed via liquid chromatography–mass spectrometry (LC–MS) using a Waters ACQUITY UPLC system (Milford, MA) UPLC BEH C18 columns (1.7 µm, 100 mm × 2.1 mm id) were used at 25°C and flow rate 0.25 mL/min). as previously described⁹. Nineteen sphingolipids were analyzed including Cer (8 species), dhCer (1 species), and SM (10 species). Briefly, 100 µL of serum was mixed with 400 µL of 75% ice-cold methanol; 10 µL of lipidomic standard mixture mother liquor was added, and the mixture was ultrasonicated for 2 min. Following this, 1 mL of methyl tertiary butyl ether was added. The samples were vortexed for 1 h at room temperature before the addition of 250 µL H₂O. After stratification for 10 min, the samples were centrifuged at 12,000 ×g at 4°C for another 10 minutes to allow the fat-soluble substances to distribute into the upper layer. Then the upper layer was transferred to a new tube to be dried. After adding in 100% methanol, the sample was filtered into a vial. The lipidomic internal standard mixture comprised 20 mg/mL each of Cer (d18:1/17:0), sphingosine (So, d17:1), sphingomyelin (SM, d18:1/17:0), and sphingosine-1-phosphate (S1P, d17:1). Liquid A consisted of 60% acetonitrile(5 mmol/L ammonium acetate), while liquid B was isopropanol:acetonitrile(9:1). The B liquid gradient was set up sequentially over a 20-minute period as follows: starting at 15% for the first 3 minutes, then increasing to 99% from minute 3 to minute 15, maintaining at 99% for minutes 15 to 17, decreasing back to 15% from minute 17 to minute 19, and finally returning to 15% for the last minute. An AB Sciex 5500 QTRAP mass spectrometer with a Turbo Ion Spray electrospray ionization ion source was used in multiple reaction monitoring scan mode with the following ion-source parameters: CUR, 40 psi; GS1, 30 psi; GS2, 30 psi; IS, − 4500 V; CAD, MEDIUM; TEMP, 350°C.

DNA methylation assessment

Illumina Infinium HumanMethylation EPIC V1 BeadChip (Illumina, USA) was used to measure methylation level of CpG probes. To minimize potential batch effects, samples were randomized across chips and plates, and all samples were analyzed in one batch. The raw data, which stores the signal intensity for each probe, is exported directly from the Illumina iScan system as IDAT files and subsequently processed using the Bioconductor package "minfi" for quality control and normalization. Data quality control was performed by removing 1) CpG probes with a detection p value > 0.01 in at least one sample; 2) CpG probes on sex chromosomes; 3) SNP-associated CpG probes¹⁰. The remaining loci underwent preprocessing, including Illumina-type background correction, dye-bias adjustment, and NOOB normalization¹¹, to derive methylation status. The methylation statuses were quantitatively expressed as β values within the range of 0 (no methylation) to 1 (full methylation), which were calculated using the formula β = M / (M + U + e), where M represents the signal intensity of the methylated probe, U represents the signal intensity of the unmethylated probe, and e is a small constant. Since DNA was extracted from whole blood, leukocyte compositions were assessed for the purpose of adjusting for leukocyte subtypes, including CD8⁺T lymphocytes, CD4⁺T lymphocytes, natural killer cells, B cells, monocytes, and granulocytes, using a previously-established method for each blood sample¹². Finally, 127 CpG sites located on the CerS1-CerS6 genes annotated on the EPIC V1 chip were selected for further analysis.

Statistical analysis

For demographic information of the study participants, categorical variables were summarized using counts (percentages), while continuous variables were described using mean and standard deviation (SD). The differences between the case and control groups were assessed using independent samples t-test for continuous variables and chi-square test for categorical variables. The linear regression model was employed to examine the dynamics of DNA methylation between asthma patients and healthy controls. The binary variables representing the case and control groups were utilized as independent variables, while the methylation levels of each of the 127 CpG sites were treated as dependent variables. The model was adjusted for sex, age, BMI, and estimated leukocyte subtypes. CpG sites with p values < 0.05 were considered differentially methylated sites between asthma patients and healthy controls. A differential methylation region (DMR) analysis using the R package DMRcate was further conducted to identify regional methylation changes in the CerS1-6 genes between asthma patients and healthy controls. To ensure the robustness of the preliminary findings, internal validation based on bootstrap resampling (500 iterations) was subsequently conducted and interval distributions for regression coefficients of each CpG site were derived with the bootstrap percentile interval method¹³.

Moreover, subgroup analyses were conducted to explore whether differences in DNA methylation patterns exist among different subgroups of asthma patients, stratified by sex, age, BMI, allergic status, ACT scores, age of asthma onset, and episodes of acute exacerbations. Among these, asthma patients were classified as young (< 45 years old) and middle-aged/elderly (≥ 45 years old); overweight (BMI > 24) and non-overweight (BMI ≤ 24); and allergic asthma and non-allergic asthma based on allergic status. Asthma control was assessed using ACT scores, with patients scoring less than 15 classified as having poor asthma control, scores ranging from 16 to 10 as suboptimal, and scores between 20 and 25 as indicative of good control. Onset of asthma before the age of 18 was categorized as early-onset asthma, while onset at or after the age of 18 was considered late-onset. Additionally, classification was also performed based on the occurrence or absence of frequent asthma exacerbation, which is defined as two or more exacerbations in the past 12 months^{14, 15}.

To further understand the potential role of DNA methylation in regulating gene expression and metabolic processes, the identified differentially methylated CpG sites were tested for their correlation with ceramide metabolites. Concentrations of ceramide metabolites were logarithmically transformed with a base of 2, and Pearson correlation coefficients were calculated between these concentrations and the methylation levels of the identified differential CpG sites.

All analyses were conducted using R statistical software (R version 4.1.1; R Development Core Team). A two-sided < 0.05 p-value was considered statistically significant.

Participants’ characteristics

The clinical characteristics of the 26 asthma patients and 6 healthy controls were detailed in Table 1. The average age of asthma patients was 44.2 years old, and 84.6% of these patients were female. As for the control group, average age was 49.3 years old, and 50% were female. The average BMI levels for the case group and the control group were 23.2 ± 3.4 (mean ± SD) and 24.5 ± 4.5 kg/m², respectively. Additionally, among the 26 asthma patients, 11 patients had allergic rhinitis, and 3 patients had eczema, which are two common allergic conditions. There were no significant differences observed between the case group and the control group in the aforementioned clinical characteristics.

Table 1

Basic information of asthma patients and control group.
	Asthma(n = 26)	Control (n = 6)	p-value ^a
Age (years) [mean ± SD]	44.2 ± 15.4	49.3 ± 8.6	0.440
Sex [n (%)]			0.064
Male	4 (15.4%)	3 (50%)
Female	22 (84.6%)	3 (50%)
BMI (kg/m²) [mean ± SD]	23.2 ± 3.4	24.5 ± 4.5	0.419
Complications [n (%)]
allergic rhinitis	11(42.3%)	0 (0%)	0.151
eczema	3(11.5%)	0 (0%)	0.943

Abbreviations: BMI, body mass index; SD, standard deviation.

a: The p-values were calculated from two sample t-test.

Differential Methylation Analysis of CerS Genes in Asthma Patients and Controls

The Illumina Human Methylation EPIC BeadChip covers a total of 127 CpG sites across the CerS1 to CerS6 genes. We firstly examined DNA methylation differences at these loci between the asthma patients and healthy controls, incorporating sex, age, BMI, and leukocyte subtypes as covariates. As shown in Table 2, four CpG sites located within the CerS6 gene, including cg18956199, cg21465008, cg03236449 and cg15455300, exhibit significant differences between the two groups (p value < 0.05). Compared to healthy controls, asthma patients exhibited significantly higher methylation levels at three loci (cg18956199, cg21465008, and cg03236449), with estimated coefficients of 2.02%, 4.99%, and 2.52%, respectively (p value < 0.05). Conversely, methylation levels at the cg15455300 locus were lower (-2.14%, p value < 0.05) in asthma patients. The box plots illustrate that in asthma patients, the mean β-value for cg21465008 is higher than that in healthy controls, whereas cg18956199 is lower. The mean values for the other two loci are essentially similar (Fig. 1a). Notably, the DMR analysis further revealed a differentially methylated region (chr2: 169311373–169312695, FDR < 0.05) annotated on the CerS6 gene, consistent with the findings of the differential methylation position analyses (Table 3). Moreover, internal validation based on 500 iterations of bootstrap resampling indicated robust and significant differences at locus cg18956199 between asthma patients and healthy controls (Table 4). Nevertheless, all other sites located on the CerS1 to CerS5 genes did not demonstrate any significant differences.

Table 2

Characteristics of the differentially methylated CpG sites located on *CerS6* gene between asthma patients and healthy controls.
CpG	Gene	Asthma (n = 26)^b	Control (n = 6)^b	Estimate (SE, %)	p-value^a	CHR	Location	Relation to Island
cg18956199	CerS6	0.0285 ± 0.0070	0.0080 ± 0.0005	2.02 (0.55)	0.0015	2	TSS200	Island
cg21465008	CerS6	0.1363 ± 0.1045	0.1365 ± 0.0471	4.99 (1.91)	0.0160	2	TSS1500	N_Shore
cg15455300	CerS6	0.9188 ± 0.0181	0.9233 ± 0.0052	-2.14 (0.92)	0.0312	2	Body	OpenSea
cg03236449	CerS6	0.8408 ± 0.0239	0.8394 ± 0.0086	2.52 (1.20)	0.0473	2	Body	OpenSea

Abbreviations: SE, standard error. Estimate (SE, %) were percentage change in DNA methylation estimated by linear mixed effect models with adjustment for age, sex (categorical), body mass index (BMI), and cellular component. CHR, chromosome.

a: Estimates (SE, %) and p-values were calculated with the linear regression models with adjustment for age, sex, BMI, and cellular component. The estimate represents the percentage change in DNA methylation between asthma patients and healthy controls.

b: The mean ± standard deviation of DNA methylation levels (β value) of four identified CpG sites between asthma patients and healthy controls.

Table 3

Characteristics of the differentially methylated region located on *CerS1-6* genes between asthma patients and healthy controls.
Sequence	Start	End	Number of CpGs	Mean difference	FDR	Gene
Chr2	169312560	169312695	3	-0.01	< 0.0001	CerS6

Note: Differentially methylated region was conducted using DMRcate package. The FDR was calculated by Benjamini and Hochberg method.

Table 4

The 95% confidence intervals of regression coefficients based on bootstrap method.
CpG	Original Estimate ^a	95% CI lower limit ^b	95% CI upper limit ^b
cg18956199	2.02 (0.55)	1.02	3.95
cg21465008	4.99 (1.91)	-1.22	11.8
cg15455300	-2.14 (0.92)	-5.79	1.77
cg03236449	2.52 (1.20)	-2.58	5.15

Abbreviations: CI, confidence interval.

a: The original estimates were calculated with the linear regression models with adjustment for age, sex, BMI, and cellular component.

b: The 95% confidence intervals were calculated using the bootstrap percentile method.

Subgroup Analysis of DNA Methylation Differences in Asthma Patients

We then conducted subgroup analyses to explore whether differences in DNA methylation patterns exist among different subgroups of asthma patients. Frequent acute exacerbation of asthma was defined s more than two exacerbations in the past 12 months. Among the 26 patients with asthma, 6 had frequent exacerbation and 20 had infrequent acute exacerbation. As shown in Fig. 1, Table 5 and Table S1, patients with frequent exacerbation displayed lower average methylation levels of cg15455300 (by − 1.40%, p value < 0.05). While the other three loci, cg18956199, cg21465008, and cg03236449, exhibited no significant differences in the methylation levels of four identified asthma-related CpG sites between the two groups. ACT score of 20–25 indicates “well controlled” asthma, 16–19 indicates “poorly controlled”, and < 15 indicates “badly controlled”. As asthma control declined, the mean methylation levels for cg15455300 decreased, with β values ± SD of 0.9210 ± 0.0148, 0.9138 ± 0.0142, and 0.9113 ± 0.0329, respectively. There was also an almost significant consistent trend observed in the differential methylation analysis. We also observed that in the asthma patients of this study, compared to late-onset asthma and non-allergic asthma, early-onset asthma and allergic asthma exhibited higher average methylation levels at cg18956199 and cg21465008, while lower levels were observed at the other two CpG sites, cg15455300 and cg03236449. However, the differential methylation analysis yielded nonsignificant or nearly significant results for these associations. Additionally, overweight individuals exhibited higher average methylation levels at cg21465008 compared to non-overweight individuals, with the differential methylation analysis nearing significance (p value = 0.0589). Male had higher average methylation levels than female at cg18956199 and cg21465008, and lower levels at the other two sites, although not statistically significant. We also compared differences between middle-aged/elderly individuals and younger individuals. Middle-aged and elderly individuals showed higher average methylation levels at cg18956199 and cg15455300, while the other two loci exhibited the opposite trend, although these differences were not significant in the differential methylation analysis.

Table 5

Characteristics of four identified differentially methylated CpG sites among different subgroups of asthmatic patients.
	Number	cg18956199		cg21465008			cg15455300			cg03236449
	Number	Estimate (SE, %)	p-value^a	Estimate (SE, %)		p-value^a	Estimate (SE, %)		p-value^a	Estimate (SE, %)	p-value^a
Frequent acute exacerbation
No	20	Reference	-	Reference	-		Reference	-		Reference		-
Yes	6	0.02 (0.50)	0.9630	0.56 (1.34)	0.6848		-1.40 (0.64)	0.0463		0. 61 (1.05)		0.5706
Asthma control groups
Well-controlled	13	Reference	-	Reference	-		Reference	-		Reference		-
Poorly-controlled	7	-0.14 (0.45)	0.7580	-0.95 (1.16)	0.4276		-0.98 (0.64)	0.1481		-1.27 (0. 97)		0.2177
Badly-controlled	6	0.68 (0.36)	0.1066	1.89 (1.02)	0.0843		-1.19 (0.56)	0.0520		-1.26 (0. 86)		0.1638
Asthma onset
Early-onset	4	Reference	-	Reference	-		Reference	-		Reference		-
Late-onset	22	-0.18 (0.49)	0.7153	-1.65(1.25)	0.2068		1.17 (0.65)	0.0936		-0.66 (1.03)		0.5271
Allergic state
Non-allergic asthma	4	Reference	-	Reference	-		Reference	-		Reference		-
Allergic asthma	22	-0.89 (0.54)	0.1220	-1.29 (1.68)	0.4557		0.77 (0.87)	0.3907		0. 38 (1.20)		0.7575
Body mass index
Non-overweight	18	Reference	-	Reference	-		Reference	-		Reference		-
Overweight	8	-0.57 (0.36)	0.1381	2.19 (1.07)	0.0589		-0.97 (0.59)	0.1171		1.26 (0. 80)		0.1331
Sex
female	22	Reference	-	Reference	-		Reference	-		Reference		-
male	4	0.53 (0.45)	0.2476	-0.61 (1.21)	0.6216		0.56 (0.66)	0.4068		1.61 (0. 95)		0.1104
Age
young	15	Reference	-	Reference	-		Reference	-		Reference		-
Middle-aged/eldly	11	0.78 (1.58)	0.6269	1.21 (1.06)	0.2731		0.69 (0.73)	0.3586		-1.26 (2.00)		0.5391

Abbreviations: SE, standard error.

a: Estimates (SE, %) and p-values were calculated with the linear regression models with adjustment for age, sex, BMI, and cellular component. The estimate represents the percentage change in DNA methylation between different asthma phenotypes.

Correlation Analysis between ceramide metabolites and identified CpG sites

Correlations between ceramide metabolites levels and methylation levels at the four selected sites were examined. We observed varying degrees of correlation between ceramide metabolites and the methylation levels of the four identified CpG sites. Specifically, cg15455300 and cg03236449 exhibited negative correlations with almost all metabolites, whereas cg21465008 showed the opposite pattern, being positively correlated with nearly all metabolites. Among them, cg03236449 exhibited a significant negative correlation with Cer24.0 concentration (p value < 0.05), whereas cg18956199 showed a significant positive correlation with Cer16.1 (Table S2 and Fig. 2).

Accumulating evidence indicates that sphingolipids play a pivotal role in airway inflammation and the pathogenesis of asthma^{16, 17}. Sphingolipids demonstrate significant structural and functional diversity. Ceramides serve as the precursors for various sphingolipids. Through the action of ceramide synthases (CerS), fatty acyl-CoAs are added to the sphingosine backbone, resulting in the generation of ceramides¹⁸. Ceramide synthase (CerS) catalyzes the attachment of various acyl side chains to sphingosine groups, resulting in the synthesis of diverse ceramide species ¹⁹. Six different ceramide synthetases, abbreviated as CerS1-6, have been identified in mammals ¹⁸. To date, limited research has explored the role of ceramide synthetases (CerS) in asthma, despite their pivotal position in the metabolic pathways of sphingolipids and ceramides. However, a study from South Korea suggested that elevated expression of CerS6 played a significant role in the pathogenesis of obese asthma²⁰.

Our study revealed that in peripheral blood methylation measurements of asthma patients and healthy controls, only the methylation sites on the CerS6 gene exhibited significant differences between the two groups. In contrast, the methylation levels of dozens of CpG sites on the CerS1-5 genes did not differ between the two groups. The associations between DNA methylation and asthma risk were reported in several studies previously. Studies in human cohorts demonstrated an association of DNA methylation with asthma in different tissues like peripheral whole blood²¹, peripheral blood monocytes²² and nasal cells²³. The Methylation level of specific genes associated with asthma were involved in various mechanisms such as inflammation and immunity, cell adhesion, extracellular matrix and autophagy²⁴. However, research on the relationship between methylation of sphingomyelin metabolic enzyme genes and asthma cannot be retrieved. Only one study mentioned that methylation of CpG sites on chromosome 17q21 was related to the expression of ORMDL3 gene⁷. The protein encoded by the ORMDL3 gene can inhibit the activity of serine palmitoyl transfer (SPT), which is the rate-limiting enzyme in the de novo synthesis of sphingolipids²⁵, and the genetic variants of ORMDL3 contribute to the risk of childhood asthma²⁶.

This is the first study examining the role of CerS6 gene’s methylation in patients with asthma. We found that four CpG sites of the CerS6 gene had significantly different methylation levels, especially cg15455300 had significantly lower methylation levels in asthma patients compared to controls. These sites are located on the chromosome at the positions of TSS200, TSS1500, and the gene body, which play crucial roles in gene expression regulation and transcriptional control. Some research results have shown that CerS6 played a proinflammatory and proapoptotic role. High CerS6 expression in ovarian cancer tissues was closely related to poor prognosis, through the AKT/mTOR/4EBP1 signaling pathway²⁷. CerS6 as an upstream regulator of calpain activity increased mitochondrial Ca²⁺ loading capacity and promoted apoptosis²⁸. Raichur.et al. found that CerS6 expression promoted the development of obesity and type 2 diabetes²⁹. Specific inhibition of CerS6 significantly ameliorated acute graft-vs-host-disease³⁰, indicated CerS6 inhibition as a novel therapeutic approach. However, there was little research on the role of CerS6 gene in asthma. Bootstrap-based internal validation and DMR analysis further elucidated the robustness and reliability of our findings, indicating the potential role of the CerS6 gene in the pathogenesis of asthma. However, due to the relatively modest effect sizes observed in our results, further validation in larger cohorts is warranted.

To further investigate the role of CerS6 in asthma inflammation, we screened four CpG sites and applied them to the comparison of various asthma phenotypes. Among the four sites, the estimate value of cg15455300 was negative which meant the degree of methylation at this site was low in asthma patients with frequent acute exacerbations compared to those with non-frequent exacerbations, consistent with trends in asthma and normal controls. Frequent exacerbators with severe asthma had a higher body mass index and poorer asthma control³¹, were more common in females than in males³², tended to manifest as elevated blood eosinophils and type 2 inflammation³³.Therefore, we compared the methylation levels of the CerS6 gene among obese, allergic, and different sex asthma patients, but unfortunately, there were no statistical differences, which may be related to our small sample size. Recent literature reported CerS6 expression and C16 ceramide levels are increased in the hypothalamus of obese mice³⁴. Individual sphingolipid species concentrations significantly differ between sexes, especially CerS6 status exhibit sex-dependent effects on hepatic sphingolipids metabolism³⁵. These studies suggested that the expression of CerS6 is related to obesity and sex, and both obesity and sex are associated with the occurrence of asthma^{36, 37}. Therefore, we speculate that obesity and sex may affect the DNAmethylation dynamics of CerS6 gene. Regrettably, our current results cannot confirm this conclusion. In the future, larger sample sizes of asthma patients can be included for grouping comparison to verify this hypothesis.

Moreover, in the comparison of asthma control levels, the methylation level of badly controlled asthma patients did indeed decrease, consistent with the findings in frequent acute exacerbation phenotypes. Among asthma patients with good compliance and self-management abilities, there was still a high proportion of asthma patients who are prone to acute attacks³¹. It was important to reveal the physiological mechanisms of asthma patients with frequent acute exacerbation phenotype and discover biomarkers³⁸. Here, reduced methylation of CerS6 cg15455300 in peripheral blood was associated with asthma and the frequent exacerbator phenotype. The other phenotypes were not identified as independent risk factors for CerS6 methylation.

Methylation of cg15455300 was negatively correlated with ceramide metabolite levels. Hence, we speculated that reduced methylation of CerS6 led to upregulation of CerS6 expression and of its downstream metabolite Cer16:0, which is more important in the pathogenesis of asthma than metabolites with other carbon-chain lengths. Each CerS has a preference for acyl side chains of different carbon-chain lengths. CerS1–5 mainly utilize the C20–C26 acyl CoA species to produce very-long-chain ceramides, whereas CerS6 mainly synthesizes ceramides (in this case, long-chain ceramides) using the shorter carbon-chain C16 as the substrate. Ceramides with different carbon chain lengths have different roles in inflammation³⁹. C16 ceramides typically have pro-apoptotic effects, while C24 ceramides promote cell survival^40–42. The mechanism by which CerS6 promotes airway inflammation and increases the probability of asthma may be related to the pro-inflammatory effect of the long-chain ceramides synthesized by CerS6. No prior studies have examined the association between C16 ceramides and asthma. Here, based on the significant differential methylation observed, we propose CerS6 and its downstream product C16 as pro-inflammatory factors involved in the inflammatory response of asthma.

This study had some limitations. First, the sample size in our study was relatively small, and being a cross-sectional study, we cannot establish causal relationships between CerS gene DNA methylation dynamics and asthma. Additionally, downstream Pearson correlation analyses require further animal or cellular experiments to complement and elucidate the relationship between ceramide metabolites and the methylation patterns of the four identified CpG sites. The methylation sites identified in this study should be further validated in other larger and independent asthma cohorts. Second, the menstrual cycle or pregnancy status of women affects the levels of sex hormones, which may be related to the metabolism of CerS. However, our research data regrettably lack relevant information. Third, methylation was analyzed using whole blood cells; although we corrected for cell composition, methylation measurements should be performed for other sample types, such as peripheral blood mononuclear cells or bronchial mucosal tissues. Additionally, although we collected most of the potential covariates that may be associated with asthma in this study, other risk factors, such as depression that could be affected by air pollution and genetics⁴³, were not assessed in our study. Finally, we did not consider other potential confounding factors, such as the type of therapy administered, medication usage, and environmental factors, which may lead to uncertainty in our results.

In conclusion, our study elucidated the DNA methylation dynamics of the CerS6 gene in asthma patients, suggesting its potential biological role in the pathophysiological mechanisms of asthma. These findings provide valuable insights and a foundation for future research.

Acknowledgements: Not applicable

Authors’ contributions

Zhu Song, Tingting Hu participated in the patient collection and determination of clinical samples, Yuting Wang，Heqing Huang participated in the analysis of the data, Zhu Song, Yuting Wang, Xu Gao，Chun Chang wrote the manuscript. All authors contributed to this article and reviewed and approved the final version.

Funding

This study was supported by grants from the National Natural Science Foundation of China (grant numbers 82200032, 82170028, 82304098, and 82370032). The funding bodies had no role in the design of the study; the collection, analysis, or interpretation of the data; or in writing the manuscript.

Availability of data and materials

The datasets generated and/or analyzed during the current study are available from the corresponding author (Chun Chang) upon reasonable request.

Ethics approval and consent to participate

We complied with all relevant ethical regulations for work with human participants. Informed consent was obtained. This study was approved by the Research Ethics Committee of Peking University Third Hospital (No. 2022348).

Consent for publication: All authors give consent for the publication of the manuscript.

Competing interests: The authors declare no competing financial interests.

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No competing interests reported.

SupplementTables.docx

CerS6 gene methylation in peripheral blood is associated with asthma and the frequent exacerbator phenotype

Status:

Version 1

Abstract

Background

Methods

Results

Conclusion

Figures

Introduction

Methods

Study design and participants

Health assessments

Liquid chromatography–mass spectrometry

DNA methylation assessment

Statistical analysis

Results

Participants’ characteristics

Differential Methylation Analysis of CerS Genes in Asthma Patients and Controls

Subgroup Analysis of DNA Methylation Differences in Asthma Patients

Correlation Analysis between ceramide metabolites and identified CpG sites

Discussions

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1