Lung function impairment may increase secondary thrombocytopenia susceptibility: a Mendelian randomization

doi:10.21203/rs.3.rs-3147993/v1

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Lung function impairment may increase secondary thrombocytopenia susceptibility: a Mendelian randomization

https://doi.org/10.21203/rs.3.rs-3147993/v1

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Purpose

This study explored the relationship between lung function and secondary thrombocytopenia by analyzing Mendelian randomization (MR).

Methods

As instrumental genetic variables, appropriate single nucleotide polymorphisms (SNPs) were extracted from genome-wide association study (GWAS) data on lung function. We choose secondary thrombocytopenia as the outcome. Inverse variance weighting, weighted median methods, and MR- Egger's method were used to explore the association between lung function and the risk of secondary thrombocytopenia. The analysis results were shown as odds ratio (OR) and 95% confidence interval to evaluate the causal association between lung function parameters and secondary thrombocytopenia.

Results

The inverse variance weighted (IVW) analysis showed that forced expiratory volume in the first second (FEV1) significantly led to the occurrence of secondary thrombocytopenia [OR: 0.2126; 95% confidence interval (CI): 0.0508–0.8886, P = 0.0339], reduced peak expiratory flow (PEF) increased the occurrence of secondary thrombocytopenia [OR: 0.1018; 95% CI: 0.0143–0.7234, P = 0.0224]. The decline of FEV1 and PEF contributed to the risk of secondary thrombocytopenia. Furthermore, FVC (Forced Vital Capacity), FEV1/FVC, and lung volume were not associated with secondary thrombocytopenia.

Conclusion

FEV1 and PEF could be important precipitating factors of secondary thrombocytopenia, which provided new ideas for treating and preventing secondary thrombocytopenia.

secondary thrombocytopenia

lung function

mendelian randomization

platelet

Secondary thrombocytopenia is defined as thrombocytopenia with definite pathogenesis or occurring based on some primary diseases. Guidelines in some regional countries set the criteria for thrombocytopenia at < 150 × /L[1, 2], typically presenting as thrombocytopenia with or without bleeding, which can be preceded by a history of exposure to some causative factors[3]. Notably, the pathogenesis of this disease is influenced by several factors: drugs, infectious diseases, tumors, immune destruction, pregnancy, splenomegaly, and thrombosis[4–11]. An Italian epidemiological survey of primary and secondary thrombocytopenia mentioned that the incidence of thrombocytopenia was 14.8/100,000 per year, and the proportion of secondary thrombocytopenia was 31.5%[12].

The lung has been reported to be the primary site of platelet production, producing approximately 50% of the body's platelets[13]. Emerging evidence also indicates lung injury is an important factor that reduces platelet counts[14–21]. In recent years, many studies focused on the pathology of secondary thrombocytopenia. However, the studies based on observation would be susceptible to the risk of bias originating from statistics or the environment[22]. Other studies based on experiments would provide weak evidence due to the information mainly on clinical purposes[23]. Therefore, the relationship between lung function and secondary thrombocytopenia remains unclear and needs to be evaluated.

Mendelian randomization (MR) analysis, which introduces genetic variation as an instrumental variable, could be used as an assessment of the causal relationship between exposure and outcome[24]. The underlying principle refers to Mendel's second law of inheritance: alleles are assigned randomly and fixed at conception[25]. Like the traditional randomized controlled trial (RCT), affected subjects are randomly divided into treatment and control groups according to the MR rule[26]. Additionally, the random distribution of genetic variation can eliminate confounding factors and reverse causality, imitating the randomization process of a RCT and avoiding the interference of reverse causal associations, potential confounders, encountered in traditional RCTs[27]. Furthermore, two-sample MR analysis requires summary-level data from two independent genome-wide association studies (GWAS) to determine putative exposures and outcomes[28].

In this study, we searched for parameters and information regarding lung function and secondary thrombocytopenia from the ieu open gwas project website (https://gwas.mrcieu.ac.uk). Then, a two-sample MR study was used for the first time to explore the association between parameters (FEV1, PEF, FVC, FEV1/FVC, and lung volume) of lung function and secondary thrombocytopenia. Finally, sensitivity analysis was employed to assess the robustness of the statistically significant causal associations. Importantly, this study provides novel insights into preventing secondary thrombocytopenia.

Study design

Two-sample MR with summary data from publicly available GWAS databases was used to investigate the relationship between lung function and secondary thrombocytopenia. Single nucleotide polymorphisms (SNPs) significantly associated with lung function were used as the instrumental variable. Secondary thrombocytopenia was selected as the outcome of the MR analysis. The appropriate instrumental variables for two-sample MR analysis should be consistent with the following three key hypotheses: (i) there was a significant association between instrumental variables and lung function; (ii) instrumental variables were not associated with all confounders of the lung function-secondary thrombocytopenia association; and (iii) the instrumental variables only influence the outcome through association with lung function[29]. All of the information is shown in Fig. 1.

Lung function and secondary thrombocytopenia data sources

Data on lung function and secondary thrombocytopenia were obtained from the ieu website (https://gwas.mrcieu.ac.uk). We used Forced Expiratory Volume in the first second (FEV1), Forced Vital Capacity (FVC), FEV1/FVC, Peak Expiratory Flow (PEF), and lung volume to represent lung function[30]. Data on FEV1, PEF, and FVC were all derived from the MRC-IEU database, including 421,986 European descent males and females, and the number of SNPs was 9,851,867. FEV1/FVC data was obtained from a GWAS study of Shrine N[31]. Additionally, data was collected from Europeans and contained 19,671,887,321 SNPs for 321,047 samples. Lung volume data was derived from a GWAS study by Liu Y, which included 32,860 males and females of European descent with 9,275,407 SNPs[32]. Furthermore, genetic data for secondary thrombocytopenia was obtained from a Finnish database with a SNP volume of 16,380,462. All of the data information is shown in Table 1.

Table 1

Information about the source of the original data extracted from GWAS summary statistics.
Trait	Sample size	Number of SNPs	populations	First author/database
FEV1	421,986	9,851,867	European	Ben Elsworth
FVC	421,986	9,851,867	European	Ben Elsworth
Fev1/Fvc	321,047	19,671,887	European	Shrine N
PEF	421,986	9,851,867	European	Ben Elsworth
Lung volume	32,860	9,275,407	European	Liu Y
secondary thrombocytopenia	429,209	16,380,462	European	FinnGen
FEV1, Forced Expiratory Volume in the first second; FVC, Forced Vital Capacity; PEF, Peak Expiratory Flow; SNPs, Single Nucleotide Polymorphisms.

Screening of instrumental variables

Association threshold and LD cutoff

SNPs pooled with significant association with lung function (P < 5.0 × 10^− 8) were selected, and the parameter r² threshold was set at 0.001 and kilobase pairs (kb) at 10,000 to exclude interference from linkage disequilibrium (LD).

Exclude SNP associated with confounds

To eliminate the effect of confounds on the estimate, SNPs associated with secondary thrombocytopenia need to be manually removed using PhenoScanner (http://www.phenoscanner.medschl.cam.ac.uk/). Potential confounds for secondary thrombocytopenia include alcohol abuse and nutritional deficiencies[33].

F-statistics

SNPs were searched by parameters closely related to the exposure to satisfy the criteria of the hypothesis of MR analysis. Thus, the F value was calculated according to

Harmonization

First, the information on secondary thrombocytopenia in the outcome was extracted from GWAS. Then, the SNPs, strongly correlated with lung function, were obtained from the outcome. Next, the datasets derived from exposure and outcome were merged, which contained the instrumental variables concerning both outcome and exposure. Finally, the final SNPs were obtained when the palindromic and incompatible SNPs were removed.

Steiger filtering on inference direction from exposure to outcome

To mitigate the potential impact of reverse association (that is, the lung function as the outcome and secondary thrombocytopenia as exposure), we used the Steiger filtering approach to identify the correct directions of inference (that is, the lung function as exposure; secondary thrombocytopenia as outcome). Additionally, the Steiger filtering directionality test was implemented by using the TwoSampleMR R package.

Data analysis

MR analysis was based on the "TwoSampleMR" package and the "MRPRESSO" package in R version 4.1.2. Three methods were used for MR analysis: inverse variance weighted analysis (IVW), MR egger, and weighted median. IVW was mainly used to evaluate the relationship between lung function and secondary thrombocytopenia. The IVW method focuses on the inverse of the variance of each instrumental variable as a weight to be calculated, and this process was performed to assess horizontal pleiotropy by ensuring that all instrumental variables were valid[35]. In contrast, the MR-egger regression method used the inverse of the variance of the outcome as the weight for the fit, adding an intercept term to the regression[36]. The weighted median method (WME), defined as the median of the weighted empirical density function of the ratio estimates, still provided consistent effect estimates when the proportion of invalid instrumental variables was as high as 50%, and the precision of the estimates varied widely between instrumental variables[37]. Notably, MR-egger and weighted median can complement the IVW approach. As the outcome was a binary variable, this study further converted the effect estimates into an odds ratio (OR) to more visually observe the relationship between lung function and secondary thrombocytopenia. P < 0.05 was statistically significant.

Sensitivity analysis

Sensitivity analysis is essential to further test the stability and reliability of the results[38]. Heterogeneity tests use Cochran’s Q test to determine the heterogeneity of SNPs and assess the possible bias in estimating causal effects due to measurement errors in SNPs caused by different analytical platforms, experimental conditions, analytical populations, etc[35]. Notably, the intercept obtained from the MR-Egger regression was an indicator for directional pleiotropy (p < 0.05 was considered as the presence of directional pleiotropy). The MRPRESSO method can also be used to assess horizontal pleiotropy and consists of three components: (1) The MR-PRESSO global test was used to detect the existence of horizontal pleiotropy. (2) The MR-PRESSO outlier test was used to remove abnormal SNPs (outliers) and estimate the corrected outcome (removing horizontal pleiotropy). (3) The MR-PRESSO distortion test was used to test for differences between pre- and post-correction results[39]. Furthermore, the "Leave-one-out" method eliminates each SNP in turn. Moreso, it uses the remaining SNPs as instrumental variables (IVs) in a two-sample MR analysis to determine how much a single SNP influences the causal association effect[24].

Selection of instrumental variables

The SNPs associated with the confounders were removed, and the F value for each SNP was > 10, indicating a small probability of weak instrument variable bias. Furthermore, we used the Steiger filtering to identify the correct direction of inference (Supplementary Tables 1–5). Details regarding SNPs related to lung function and secondary thrombocytopenia are listed in Supplementary Tables 6–10.

The effect of FEV1, PEF on secondary thrombocytopenia

IVW method results [OR: 0.2126; 95% confidence interval (CI): 0.0508–0.8886, P = 0.0339 < 0.05] suggested that genetic prediction of FEV1 was significantly associated with the risk of secondary thrombocytopenia, meaning that each standard deviation in the risk of FEV1 had a 21% higher risk of secondary thrombocytopenia (Fig. 2). Moreso, we found a remarkable association between PEF and the risk of secondary thrombocytopenia, with each standard deviation increase in PEF leading to a 10% reduction in the risk of secondary thrombocytopenia [OR: 0.1018; 95% CI: 0.0143–0.7234, P = 0.0224 < 0.05] (Fig. 2). The results of three Mendelian analyses are displayed in Table 2. Scatter plots showed the estimated exposure effect (FEV1, PEF) on the outcome (secondary thrombocytopenia). The scatter plots are shown in Supplementary Figures R1-2.

Table 2

Mendelian randomization estimates of FEV1, FVC, and FEV1/FVC.
Exposures	IVW			Weighed median		MR-Egger
Exposures	OR(95%CI)	P-value	Heterogeneity P-value	OR(95%CI)	P-value	OR(95%CI)	P-value	Heterogeneity P-value
FEV1	0.21(0.05,0.89)	0.03	0.96	0.34(0.04,2.80)	0.31	0.50(0.01,38.73)	0.75	0.96
FVC	0.33(0.09,1.18)	0.32	0.80	0.59(0.09,4.06)	0.59	0.11(0.00,3.80)	0.22	0.79
FEV1/FVC	0.81(0.36,1.80)	0.80	0.49	0.52(0.14,1.87)	0.31	0.61(0.10,3.73)	0.59	0.47
PEF	0.10(0.01,0.72)	0.02	0.59	0.29(0.02,4.90)	0.39	0.18(0.00,140.13)	0.61	0.56
Lung volume	0.67(0.05,9.43)	0.67	0.57	0.18(0.00,6.51)	0.35	3.841494e + 07(0.03,5.103736e + 16)	0.16	0.85
PEF, Lung volume on secondary thrombocytopenia. FEV1, Forced Expiratory Volume in the first second; FVC, Forced Vital Capacity; PEF, Peak Expiratory Flow; OR, Odds Ratio; CI, Confidence Interval; IVW, Inverse Variance Weighted.

Effects of FVC, FEV1/FVC, Lung volume on secondary thrombocytopenia

Based on IVW, MR egger, and weighted median methods, there was no evidence supporting a causal association of FVC, FEV1/FVC, or lung volume with secondary thrombocytopenia (Fig. 2). Additionally, scatter plots showed the estimated effect of exposure (FVC, FEV1/FVC, lung volume) on the outcome (secondary thrombocytopenia). Specific results of scatter plots are shown in Supplementary Figures R3-5.

Sensitivity analysis

The Cochran’s Q test showed no heterogeneity between FEV1 and secondary thrombocytopenia, Similarly for PEF and secondary thrombocytopenia, we found no significant heterogeneity. Cochran’s Q test for each phenotype is also shown in Table 2. Next, MRPRESSO was used to test the presence of horizontal pleiotropy and outlier SNPs. MR-PRESSO analysis demonstrated that no abnormal SNPs were found in the instrumental variables for the specific associations of lung function on secondary thrombocytopenia (Supplementary Table 11). P-values for the MR-PRESSO global test for FEV1 and PEF were greater than 0.05, suggesting no horizontal pleiotropy (Supplementary Table 11). However, the P-values for the MR-PRESSO outlier test were less than 0.05. Still, the p-value of the MR-Egger intercept indicated no horizontal pleiotropy, and the leave-one-out sensitivity analysis did not suggest that there was a SNP that had a large effect on the results. Thus, the P-values for the MR-PRESSO outlier didn’t affect the choice of SNPs. MR-Egger’s intercept results (P = 0.37 > 0.05 and P = 0.87 > 0.05) were statistically insignificant compared to 0, suggesting no horizontal pleiotropy. "Leave-one-out" sensitivity analysis also showed that after excluding each SNP in turn, the IVW analysis for the remaining SNPs was similar to the analysis including all SNPs. (Supplementary Figures H1-2). The forest plot also demonstrated the causal effect of each SNP on the risk of secondary thrombocytopenia (Supplementary Figures T1-2). Furthermore, the funnel plot results showed that the scatter of causal association effects was symmetrically distributed when using SNPs individually as instrumental variables, and the results were not potentially biased (Supplementary Figures S1-2).

For FVC, FEV1/FVC, and lung volume on secondary thrombocytopenia, their funnel plots are shown in Supplementary Figures S3-5. Likewise, the forest plots are shown in Supplementary Figures T3-5. "Leave-one-out" plots were presented in Supplementary Figures H3-5. Notably, we found no significant heterogeneity (P > 0.05). The MR-Egger intercept also showed no substantial evidence of horizontal pleiotropy (intercept P > 0.05).

This is the first study of Mendelian randomization to explore the association between lung function and secondary thrombocytopenia. The Mendelian randomization results suggest that the decline of FEV1 and PEF significantly increases the risk of secondary thrombocytopenia. Multiple sensitivity analyses also confirmed the causal relationship between lung function and secondary thrombocytopenia. Several factors may explain its mechanism: firstly, the lung has been reported to be the site of platelet generation and a reservoir of hematopoietic progenitor cells, and the lung can release platelets by capturing megakaryocytes[40]. Thus, lung function decline due to lung injury may lead to abnormalities in pulmonary hematopoietic function[41]. Secondly, diseases that lead to poor lung function, such as COVID-19 and chronic obstructive pulmonary disease, induce activation of the RAS system, abnormalities in endothelial cells and coagulation, platelet adhesion, and aggregation, which depletes platelet amount. Thirdly, ACE2, CD13, and CD66a have been reported to be receptors present in human bone marrow CD34 + cells, monocytes, and platelets[42]. Pulmonary impairment can invade hematopoietic stem/progenitor cells, lymphocytes, and macrophages via ACE2, CD13, or CD66a receptors, leading to apoptosis, inhibition of cell proliferation, and thrombocytopenia[43].

In this study, there are some noted shortcomings. Firstly, the results of other MR analyses, such as those of the MR egger and weighted median methods, are inconsistent with the results of the IVW method in the MR analysis of FEV1, PEF, and secondary thrombocytopenia. However, based on the principle of method selection and the absence of any heterogeneity or pleiotropy, the OR values of the IVW, MR egger, and weighted median methods are in the same direction, and the results of the IVW method can be used in preference. Secondly, the MR study demonstrated secondary thrombocytopenia was correlated with FEV1 and PEF, not lung volume, FVC, or FEV1/FVC. Third, this study only covered European populations, which may limit the application of the findings to other ethnic populations. Fourthly, the participants involved in the two-sample MR analysis of exposure and outcome studies should not be overlapped. Although the extent of overlap in this study was inevitable, the F-statistical tool was used to calculate an F-value for each SNP, minimizing the bias of sample overlap[44]. Finally, the causal relationship between FEV1 and PEF and the risk of developing secondary thrombocytopenia can only be confirmed by bioinformatic analysis, and the underlying biological mechanisms of that should be investigated in further research.

Secondary thrombocytopenia is a very common disease in clinical practice[45], and platelet transfusion is the mainstay of treatment for severe thrombocytopenia, with splenectomy, steroid, and immunoglobulin infusions for other causes[46, 47]. However, these treatments have been reported to be less effective[48]. Our MR study clarified that FEV1 significantly led to secondary thrombocytopenia, and PEF significantly affected the occurrence of secondary thrombocytopenia. Thus, this study provides new ideas for treating secondary thrombocytopenia by testing lung function. Furthermore, the improvement of lung function may prevent the development of secondary thrombocytopenia.

In conclusion, pulmonary function indicators FEV and PEF are risk factors for secondary thrombocytopenia. This MR study on pulmonary function and secondary thrombocytopenia plays an important role in clinical and public health implications, given the high prevalence of secondary thrombocytopenia in clinical practice.

Data Availability

The original contribution presented in the study is included in the article/supplementary. Summary statistics for the GWASs concerning the exposures and outcome are available from the IEU GWAS database (https://gwas.mrcieu.ac.uk/). Further inquiries can be directed to the corresponding author.

Acknowledgments

We thank all investigators for sharing summary-level data on GWAS for lung function and secondary thrombocytopenia. The authors thank AiMi Academic Services (www.aimieditor.com) for English language editing and review services.

Authors' Contribution

Yuxin Liu designed the study. Yuxin Liu and Jieying Zhang performed data analysis and drafted the manuscript. Qiang Ran and Yuan Liu revised the manuscript. Chenglin Bin collected the data. Yan-Kun Liu leads the study and revised the manuscript. All authors contributed to the article and approved the submitted version.

Funding

This work was supported by the Natural Science Foundation of Hebei Province [no: H 2021105019] and the Key Laboratory of Precision Medical Testing in Tangshan [no:2021TS009b].

Declarations of Competing Interest

The authors have no conflicts of interest to disclose.

Ethics Approval and Consent to Participate

Our analysis used either published studies or publicly available GWAS summary data. Raw data were not collected for the analysis; therefore, ethics committee approval was not required. Each study was approved by its institutional ethics review board, and all participants provided written informed consent.

Consent for publication

Not applicable.

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No competing interests reported.

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Lung function impairment may increase secondary thrombocytopenia susceptibility: a Mendelian randomization

Status:

Version 1

Abstract

Purpose

Methods

Results

Conclusion

Figures

Introduction

Methods

Study design

Lung function and secondary thrombocytopenia data sources

Screening of instrumental variables

Association threshold and LD cutoff

Exclude SNP associated with confounds

F-statistics

Harmonization

Steiger filtering on inference direction from exposure to outcome

Data analysis

Sensitivity analysis

Results

Selection of instrumental variables

The effect of FEV1, PEF on secondary thrombocytopenia

Effects of FVC, FEV1/FVC, Lung volume on secondary thrombocytopenia

Sensitivity analysis

Discussion

Conclusion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1