
==== Front
iScience
iScience
iScience
2589-0042
Elsevier

S2589-0042(24)01896-0
10.1016/j.isci.2024.110671
110671
Article
Blood cell traits and venous thromboembolism in East Asians: Observational and genetic evidence
Li Haobo 1210
Duo Mengjie 1210
Zhang Zhu zhuperfectlife@126.com
111∗
Weng Haoyi 3
Liu Dong 14
Zhang Yu 15
Xi Linfeng 15
Zou Bingzhang 12
Li Huiwen 16
Chen Gang 3
Zuo Xianbo 7
Ito Kaoru 8
Xie Wanmu 1
Yang Peiran 9
Wang Chen 1
Zhai Zhenguo zhaizhenguo2011@126.com
1∗∗
on behalf of the China pUlmonary Thromboembolism REgistry Study (CURES) Investigators

1 National Center for Respiratory Medicine, State Key Laboratory of Respiratory Health and Multimorbidity, National Clinical Research Center for Respiratory Diseases, Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
2 China-Japan Friendship Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
3 Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, China
4 Peking University China-Japan Friendship School of Clinical Medicine, Beijing, China
5 China-Japan Friendship Hospital, Capital Medical University, Beijing, China
6 Department of Pulmonary and Critical Care Medicine, Second Affiliated Hospital of Harbin Medical University, Harbin, China
7 Department of Dermatology, China-Japan Friendship Hospital, Department of Pharmacy, China-Japan Friendship Hospital, Beijing, China
8 Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
9 State Key Laboratory of Respiratory Health and Multimorbidity, Department of Physiology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, National Center for Respiratory Medicine, Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, National Clinical Research Center for Respiratory Diseases, Beijing, China
∗ Corresponding author zhuperfectlife@126.com
∗∗ Corresponding author zhaizhenguo2011@126.com
10 These authors contributed equally

11 Lead contact

06 8 2024
20 9 2024
06 8 2024
27 9 11067121 1 2024
11 6 2024
1 8 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Summary

Previous studies have indicated that various blood cell traits are associated with a higher risk of venous thromboembolism (VTE). However, the causal relationship remains uncertain. We collected data from the China pulmonary thromboembolism registry study and the China pulmonary health study, using propensity score matching and two-sample Mendelian randomization analyses with summary statistics from genome-wide association studies of blood cell traits and VTE in the East Asian population. Our findings revealed that platelet (PLT) count and hemoglobin (Hb) levels were significantly higher in VTE patients compared to the general population (p value <0.01). Genetically predicted Hb levels were positively associated with VTE, with an odds ratio (OR) of 2.38 (1.13–5.01), p value = 0.022. Similarly, genetically predicted PLT count was positively correlated with VTE, with an OR of 1.33 (1.02–1.74), p value = 0.038. These results suggest a causal relationship and potential targets for prevention.

Graphical abstract

Highlights

• MR analysis shows a positive causal link between PLT, Hb, and VTE in East Asians

• Clinicians can identify high-risk VTE individuals early by hematologic parameters

• Targeting specific blood cell traits in VTE could improve therapies and research

Clinical genetics; Cardiovascular medicine

Subject areas

Clinical genetics
Cardiovascular medicine
Published: August 6, 2024
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pmcIntroduction

Venous thromboembolism (VTE) is among the top five most common cardiovascular diseases with high morbidity and mortality rates in the world, afflicting nearly 10 million people worldwide each year, with an incidence of 1–2 per 1,000 in Europe and the United States, and 3.2–17.5 per 100,000 in East Asian.1,2,3 VTE can be categorized into two clinical manifestations, pulmonary thromboembolism (PTE) and deep vein thrombosis (DVT), based on the location of the clot embolism, and is affected by acquired clinical and genetic risk factors.

Blood cell traits are commonly measured in large-scale clinical studies and play essential roles in physiological processes such as immune response, oxygen transport, and hemostasis.4,5 In addition, quantitative blood cell traits, including red blood cell (RBC) count, white blood cell (WBC) count, and platelet (PLT) count, with strong heritability have been found in previous studies and used to explore the genetics of complex diseases through various genome-wide association studies (GWASs).6,7 Many observational studies have found that blood cells count parameters, such as elevated WBC and PLT counts and decreased hemoglobin (Hb) are associated with thrombosis, especially in cancer patients.8 However, it has also been found that high Hb is associated with elevated VTE risk.9 Conversely, DVT can also elicit an immune response to WBC infiltration of the thrombus.10 The unclear causal relationship between blood cell traits and VTE hampers their potential value in studying VTE pathogenesis, identifying at-risk populations, and developing new therapeutic strategies.

A Mendelian randomization (MR) study of blood cells and VTE based on European population found that red cell distribution width (RDW), mean reticulocyte volume (MRV), mean corpuscular volume (MCV), and low monocyte count were associated with an increased risk of VTE.11 Given that the genetic structure and distribution of hematological traits vary by ethnicity and that non-European populations are severely under-represented in most genetic studies of blood cells,12,13 the results of this study may not be directly applicable to East Asian patients.

In this study, we aim to quantify the relationship between blood cell traits and VTE using a cohort study in East Asia. Additionally, we seek to unravel the causal contributions of blood cell traits to the risk of VTE in Asians through MR analysis. This research is essential for the early recognition and timely adjustment of clinical treatment strategies for VTE in East Asia.

Results

Blood cell traits of VTE patients and controls

This study included 6,306 VTE patients from CURES and 2,321 controls from China Pulmonary Health(Figure 1). After performing propensity score matching, 1,173 VTE patients were matched to 1,173 general controls. The distributions of propensity scores demonstrated successful matching between groups (Figure S1). The characteristics of both groups were well-balanced, as demonstrated in Table 1. Notably, the PLT count in the VTE patients remained substantially higher than those in the healthy controls (216.39 vs. 189.46 × 10−9/L, p value <0.001), the Hb and WBC levels in the VTE patient group were also higher (Hb: 130.11 vs. 128.48 g/L, p-value <0.01; WBC: 7.90 vs. 5.94 × 10−9/L, p value <0.001). In our cohort, there are no patients with DVT alone. We compared the blood cell traits of patients with PTE and DVT against those with PTE alone (Table S1). We conducted a subgroup analysis in the cohort and found that PLT, Hb, and WBC in the VTE group were higher than those in healthy people, both in males and females (Table S2).Figure 1 The study flowchart

Association and causal effect of blood cell traits and venous thromboembolism.

Table 1 Characteristics of participants in the cohort study after propensity score matching

	Propensity-score matched	
VTE	Healthy	p value	
No.	1173	1173		
Male (%)	651 (55.5)	684 (58.3)	0.182	
Age	61.53 ± 12.52	61.78 ± 11.41	0.608	
BMI (kg/m2)	24.12 ± 3.31	24.30 ± 2.98	0.168	
PLT (×10−9/L)	216.39 ± 75.29	189.46 ± 61.18	<0.001	
Hb (g/L)	130.11 ± 15.85	128.48 ± 13.20	0.007	
WBC (×10−9/L)	7.90 ± 3.28	5.94 ± 1.58	<0.001	
Abbreviations: BMI, body mass index; PLT, platelet; Hb, hemoglobin; WBC, white blood cell.

Instrumental variable selection

For the MR analysis, we included significant and independent SNPs, excluding those with an F-statistic less than 10. For BBJ, a total of 133 PLT-related SNPs, 41 Hb-related SNPs, and 73 WBC-related SNPs were selected for two-sample MR analysis. For KoGES, a total of 72 PLT-related SNPs, 35 Hb-related SNPs, and 26 WBC-related SNPs were selected for two-sample MR analysis. For TWB, a total of 130 PLT-related SNPs, 47 Hb-related SNPs, and 53 WBC-related SNPs were selected for two-sample MR analysis. All these SNPs are listed in Tables S3–S5.

Association of blood cell traits with risk of VTE

We found evidence for a potential causal effect of PLT on increased risk of VTE (OR = 1.33 [1.02–1.74], p value = 0.038). We also found that genetically assessed Hb (OR = 2.38 [1.13–5.01], p value = 0.022) showed a positive potential association with VTE risk. Other results from the weighted median, MR-Egger, simple mode, and weighted mode are listed in Figure 2. Associations between each instrumental variant for blood cell traits and the risks of VTE were presented in Figure 3. Leave-one-out analyses indicated that the results were stable and not driven by any single SNP (Figures S2–S4). The MR analysis conducted in the reverse direction did not provide any reliable evidence to suggest that VTE may be the cause of changed blood cell traits (Table S6).Figure 2 Forest plot of the observational and genetic associations between blood cell traits and the risk of VTE

Error bars represent 95% confidence intervals. All statistical tests were two-sided.

Figure 3 Scatterplot of the relationship of the SNP effects on blood cell traits against the SNP effects on the risks of VTE

(A) Plot showing the effect sizes of the SNP effects on PLT (x axes) and the SNP effects on VTE (y axes) with 95% confidence intervals.

(B) Plot showing the effect sizes of the SNP effects on Hemoglobin (x axes) and the SNP effects on VTE (y axes) with 95% confidence intervals.

(C) Plot showing the effect sizes of the SNP effects on WBC (x axes) and the SNP effects on VTE (y axes) with 95% confidence intervals. Each dot represents an SNP used as an IV. The slope of each line corresponds to the estimated causal effect per method.

Pleiotropy

The results of MR-Egger suggested no potential horizontal pleiotropy (p value >0.05, Table 2). Moreover, the funnel plot exhibited a symmetric distribution of the point estimate of the causal association effect when using a single SNP as an instrument. This finding further indicated that the underlying bias was unlikely to influence the causal association.Table 2 Egger regression analyses for horizontal pleiotropy

Phenotype	Egger-intercept	Egger-SE	Egger p value	
PLT	−0.0059	0.0113	0.603	
Hb	−0.0311	0.0271	0.257	
WBC	0.0030	0.0177	0.866	
Abbreviations: PLT, platelet; Hb, hemoglobin; WBC, white blood cell.

Discussion

Identifying risk factors for VTE can provide important information on prevention strategies in East Asian populations. To our knowledge, this study is the first MR study to explore the relationship between blood cell traits and VTE in East Asian using cohort studies in China, Japan, and South Korea. We found that Hb and PLT were independent predictors of VTE in East Asian populations. Increased PLT and Hb levels significantly increase the risk of VTE incidence.

Our MR analysis findings underscore the positive causal relationship between PLT and Hb for the risk of VTE. This finding has also been corroborated in previous observational studies. For instance, a prospective cohort study from general population of Tromsø found that high Hb were risk factors for VTE.14 HCT was significantly associated with both total and unprovoked VTE risk, and the risk was higher in men than in women. Similarly, a prospective Atherosclerosis Risk in Communities study (ARIC) in the United States of America suggested that high Hb in samples from the general middle-aged population are associated with an increased long-term risk of VTE, especially provoked VTE.9 However, there are also studies that have presented opposing views. One randomized controlled trial (RCT) study found that, in acutely hospitalized patients, anemia was independently associated with an increased risk of symptomatic VTE. This finding led to the inclusion of anemia in the IMPROVE VTE risk score to enhance risk stratification, even with the provision of thromboprophylaxis.15 Likewise, Hb below 100 g/L was included in a predictive assessment model for chemotherapy-associated thrombosis in cancer patients.16 Many observational studies have found a significant association between anemia and VTE.17,18 Some blood diseases with symptoms of anemia, such as sickle cell disease, warm autoimmune hemolytic anemia, also have a significantly increased risk of VTE.19,20

Several factors may contribute to the differences observed. Firstly, population variances could be significant, which is also one of the implications of our study. For example, RDW, MRV, MCV, and monocyte counts were associated with an increased risk of VTE in European populations, but these results were not significant in East Asian populations (Figure S5). The genetic loci related to blood cells have diverged during the development and evolution of populations with different ancestries, driven by the critical role of blood cells in pathogen defense and inflammatory response.21,22,23 Secondly, current observational studies are limited in their ability to establish a causal relationship due to the persistent presence of residual confounders. To address this limitation, MR analysis was employed to investigate the potential causal links. The inverse variance weighted results suggested potential causal relationships between Hb, PLT, and VTE, respectively, whereas there was no significant evidence of causality between other blood cell traits and VTE. Importantly, repeated analyses with other MR analysis methods yielded consistent results. Subsequent sensitivity analyses also excluded horizontal pleiotropy and heterogeneity, further validating the reliability and robustness of the MR analysis results. MR-Egger analysis provides the possibility of horizontal pleiotropy. For Hb, the Egger intercept was −0.0311 with a p value of 0.257. Although this result was not statistically significant, the negative intercept suggests the possibility of horizontal pleiotropy and deserves further consideration. The lack of statistical significance (p > 0.05) suggests that we could not conclusively confirm the existence of horizontal pleiotropy in Hb. However, the observed intercept values imply the possibility of pleiotropic effects. Further studies are necessary to fully understand the nature and impact of this pleiotropy. It is crucial to underscore that the level of evidence provided by MR analysis ranks second only to RCTs. Thirdly, RBC may indirectly increase the risk of VTE through other pathways rather than through direct mechanisms. A retrospective cohort study in late pregnancy found that low Hb level was associated with decreased alkaline phosphatase (ALP) levels and significantly mediated the increased risk of ALP-related VTE.24 Another study also found that iron-deficiency anemia (IDA) during pregnancy was associated with an increased risk of postpartum VTE and suggested a possible association with IDA leading to reactive thrombocytosis.25

Identifying the correlation between blood cell traits and VTE in East Asian populations holds paramount importance in clinical practice. Given the recognized variances in genetic architecture cross populations, cognitive biases regarding the role of blood cell traits in VTE disease may exacerbate prevailing healthcare disparities. Thus, risk factors derived from European populations may not be accurately extrapolated to East Asian populations. Notably, blood cell traits serve as routine parameters in medical assessments at various healthcare facilities, especially primary care institutions. Clinicians can significantly reduce VTE incidence by early risk evaluation using standard hematological traits, identifying high-risk individuals, and implementing tailored interventions. Furthermore, if the relationship between PLT, Hb, and VTE is experimentally validated, it can further guide therapeutic strategies for related diseases. Developing antithrombotic agents targeting RBCs may reduce VTE by preventing RBC aggregation and adhesion through blocking the interaction between RBCs and fibrin or endothelium.

Limitations of the study

There are also limitations to this study. Firstly, not all potential confounders associated with VTE were included in the study cohort, which may have influenced the results. Secondly, the mechanisms concerning the pathophysiology of the interaction between Hb and PLT with VTE are not fully understood, and further studies are still needed. Refining these discoveries to target specific blood cell traits in VTE for either therapeutic or prophylactic purposes, and thereby implementing more efficient antithrombotic strategies, represents a prospective avenue for future research.

STAR★Methods

Key resources table

REAGENT or RESOURCE	SOURCE	IDENTIFIER	
Deposited data	
	
BBJ summary statistics	Biobank Japan (BBJ)	http://jenger.riken.jp/en/	
KoGES summary statistics	Korean Genome and Epidemiology Study (KoGES)	https://koges.leelabsg.org	
TWB summary statistics	Taiwan Biobank (TWB)	https://www.ebi.ac.uk/gwas/publications/38116116	
VTE summary statistics	This study	https://ngdc.cncb.ac.cn/omix/release/OMIX001381	
	
Software and algorithms	
	
R (v 4.3.0)	-	https://www.r-project.org	
TwosampleMR (v 0.5.7)		https://www.mrbase.org	

Resource availability

Lead contact

Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Zhu Zhang (zhuperfectlife@126.com).

Materials availability

This study did not generate new unique reagents.

Data and code availability

• All data reported in this paper will be shared by the lead contact upon request.

• This paper does not report original code.

• Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

Experimental model and study participant details

We conducted a cohort study on Chinese individuals from two nationwide population-based cohorts to investigate the relationship between blood cell traits and VTE risk. VTE patient data were collected from the China pUlmonary thromboembolism REgistry Study (CURES), an ongoing multicenter registry of patients with PTE between 2009 and 2015.26 The diagnosis of PTE was confirmed by helical computed tomographic pulmonary angiography (CTPA), ventilation-perfusion lung scintigraphy (V/Q scan), or pulmonary angiography. DVT was diagnosed by compression ultrasonography (CUS) or computed tomographic venography. In contrast, healthy controls were obtained from the China Pulmonary Health (CPH) study.27 The patients included in CURES study were enrolled between 2009 and 2015, and the individuals from CPH were collected between June, 2012, and May, 2015. The measurement of various variables was obtained during this time period. The Blood cell traits were conducted upon admission and at the onset of acute VTE, prior to initiating anticoagulation therapy.

Method details

Propensity score matching

To create a control group and minimize the effects of potential confounding factors, we employed a propensity score-matching strategy.28 Specifically, we compared the characteristics of the CURES participants to those of a subset of respondents from the CPH study who were similar to the CURES participants in all relevant background characteristics except for the presence of VTE. We estimated individual propensity scores by using a logistic regression model that incorporated four potential confounding factors as covariates, including demographic characteristics (sex, age, BMI, and cigarsomke). To compare blood cell traits between VTE patients and the general population, we performed propensity score matching (PSM) at the ratio of 1:1 to balance the effects of potential confounding factors. All P-values were two-tailed, and the significance level was set at P-value < 0.05. All statistical analyses were performed using R software (version 4.2.2).

GWAS summary statistics for blood cell traits and VTE

We performed MR analysis to detect the cause relationship between blood cell traits and VTE. Summary statistics for blood cell traits were obtained from Biobank Japan Project (BBJ),29 Korean Genome and Epidemiology Study (KoGES)30 and Taiwan Biobank (TWB).31 VTE summary statistics was obtained from a GWAS study of Chinese population.32

Instrumental variables selection

Genetic variants are used as instrumental variables (IVs) in MR analysis, which are required to be strongly related to the exposure but unrelated to confounders. Therefore, firstly, we selected SNPs strongly associated with the exposure at the level of genome-wide significance (P-value < 5×10-8). Secondly, we performed the clumping process (R2 < 0.001, window size = 10000 kb) with 1000 genomes of East Asian sample data as ref.33 Third, genetic variants with ambiguous strand were discarded in harmonizing process to ensure that the effect of an SNP on exposure and outcome corresponds to the same allele. Fourthly, SNPs were excluded which were not present in outcome summary statistics. Eventually, independent significant SNPs were identified to be IVs, which were used in subsequent two-sample MR analyses.

Mendelian randomization estimates

We estimate the causal effect of exposure on outcome using two-sample MR method which uses summary statistics from two GWAS studies to make cause inference. The inverse variance weighted (IVW)34 method was used for the main MR analyses, and the MR Egger35 and Weighted median36 approaches as complementary analyses were used to examine the robustness of the results.

We conducted bi-directional MR analysis to detect reverse causal effect occurs when the outcome has an effect on the exposure in addition to the exposure affecting the outcome. We also conducted leave-one-out analyses to evaluate the potential impact of excluding any IVs on the MR estimates.

Sensitivity analysis

When applying MR, we assume that the genetic variant should only be related to the outcome of interest through the exposure, which is commonly referred to as the “no pleiotropy” assumption. It ensures that the causal pathway from the genetic variant to the outcome is only via the exposure. The result can be biased if IVs suffer from horizontal pleiotropic effect. MR-Egger method37 was used to detect pleiotropy according to the intercept of weighted linear regression of the SNP-outcome coefficients on SNP-exposure coefficients. The intercept differs from zero as a measure of the average horizontal pleiotropic effect across IVs. The MR analysis was performed using the TwoSampleMR package,38 and all analyses were performed in R software. Results were considered statistically significant at p-value < 0.05.

Quantification and statistical analysis

Propensity score matching

We compared characteristics of CURES participants to those of a matched subset from the CPH study, using logistic regression to estimate individual propensity scores based on sex, age, BMI, and smoking status. Blood cell traits were compared between VTE patients and the general population using 1:1 PSM. Statistical significance was set at P-value < 0.05. All analyses were performed using R software (version 4.2.2).

GWAS summary statistics and instrumental variables selection

We selected SNPs associated with the exposure at genome-wide significance (P-value < 5×10-8) and performed clumping (R2 < 0.001, window size = 10000 kb) using 1000 genomes East Asian data. SNPs with ambiguous strands or absent in outcome summary statistics were excluded, yielding independent significant SNPs as instrumental variables (IVs).

Mendelian randomization estimates

We used two-sample MR to estimate causal effects, employing the IVW method for main analyses and MR Egger and Weighted median methods for robustness checks. Bi-directional MR and leave-one-out analyses were conducted to assess reverse causality and the impact of individual IVs, respectively. Analyses were performed using the TwoSampleMR package in R software (version 4.2.2), with statistical significance set at P-value < 0.05.

Sensitivity analysis

To test for pleiotropy, we applied the MR-Egger method, examining the intercept of weighted linear regression of SNP-outcome coefficients on SNP-exposure coefficients. An intercept differing from zero indicated horizontal pleiotropic effects. Results were considered significant at P-value < 0.05.

Supplemental information

Document S1. Figures S1–S5 and Tables S1–S6

Acknowledgments

We are grateful to the China Pulmonary Thromboembolism Registry Study (CURES), China Pulmonary Health (CPH), Biobank Japan Project (BBJ), Korean Genome and Epidemiology Study (KoGES), and Taiwan Biobank (TWB), which provided the data in this research.

The results were presented in abstract form at the 12th Congress of the Asian-Pacific Society on Thrombosis and Hemostasis (APSTH) 2023, Kuching, Malaysia, 18 October 2023 to 21 October 2023 and have been selected as one of the Young Investigator Awards.

Funding: this research was funded by Elite Medical Professionals project of China-Japan Friendship Hospital (no. ZRJY2021-QM12 ), 10.13039/501100012166 National Key Research and Development Program of China (no. 2024YFE0101900 ), 10.13039/501100005090 Beijing Nova Program (no. Z211100002121057 ), CAMS Innovation Fund for Medical Sciences (2021-I2M-1-061 , 2021-I2M-1-049 ).

Author contributions

Z. Zhang. and Z. Zhai. have full access to all the data in the study and takes responsibility for the content of the manuscript. Haobo Li. and M.D. conceived, designed the study and wrote the manuscript. Haobo Li., B.Z., H.W., and G.C. contributed to the MR analysis. Haobo Li., Y.Z., L.X., and D.L. contributed to the cohort study. Huiwen Li., Z. Zhang., and P.Y. participated in editing of the manuscript. X. Z. and K.I. provided methodological support. C.W., W.X., and Z. Zhai. contributed to the interpretation of the data and clinical inputs. All authors were involved in the revision of the manuscript for important intellectual content and approved the final version.

Declaration of interests

The authors have no conflicts of interest to declare.

Supplemental information can be found online at https://doi.org/10.1016/j.isci.2024.110671.
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References

1 Lutsey P.L. Zakai N.A. Epidemiology and prevention of venous thromboembolism Nat. Rev. Cardiol. 20 2023 248 262 10.1038/s41569-022-00787-6 36258120
2 Khan F. Tritschler T. Kahn S.R. Rodger M.A. Venous thromboembolism Lancet 398 2021 64 77 10.1016/s0140-6736(20)32658-1 33984268
3 Zhang Z. Lei J. Shao X. Dong F. Wang J. Wang D. Wu S. Xie W. Wan J. Chen H. Trends in Hospitalization and In-Hospital Mortality From VTE, 2007 to 2016, in China Chest 155 2019 342 353 10.1016/j.chest.2018.10.040 30419233
4 Koupenova M. Clancy L. Corkrey H.A. Freedman J.E. Circulating Platelets as Mediators of Immunity, Inflammation, and Thrombosis Circ. Res. 122 2018 337 351 10.1161/circresaha.117.310795 29348254
5 Pretini V. Koenen M.H. Kaestner L. Fens M.H.A.M. Schiffelers R.M. Bartels M. Van Wijk R. Red Blood Cells: Chasing Interactions Front. Physiol. 10 2019 945 10.3389/fphys.2019.00945 31417415
6 Hinckley J.D. Abbott D. Burns T.L. Heiman M. Shapiro A.D. Wang K. Di Paola J. Quantitative trait locus linkage analysis in a large Amish pedigree identifies novel candidate loci for erythrocyte traits Mol. Genet. Genomic Med. 1 2013 131 141 10.1002/mgg3.16 24058921
7 Astle W.J. Elding H. Jiang T. Allen D. Ruklisa D. Mann A.L. Mead D. Bouman H. Riveros-Mckay F. Kostadima M.A. The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease Cell 167 2016 1415 1429.e19 10.1016/j.cell.2016.10.042 27863252
8 Pabinger I. Thaler J. Ay C. Biomarkers for prediction of venous thromboembolism in cancer Blood 122 2013 2011 2018 10.1182/blood-2013-04-460147 23908470
9 Folsom A.R. Wang W. Parikh R. Lutsey P.L. Beckman J.D. Cushman M. Atherosclerosis Risk in Communities ARIC Study Investigators Hematocrit and incidence of venous thromboembolism Res. Pract. Thromb. Haemost. 4 2020 422 428 10.1002/rth2.12325 32211576
10 Nicklas J.M. Gordon A.E. Henke P.K. Resolution of Deep Venous Thrombosis: Proposed Immune Paradigms Int. J. Mol. Sci. 21 2020 2080 10.3390/ijms21062080
11 He J. Jiang Q. Yao Y. Shen Y. Li J. Yang J. Ma R. Zhang N. Liu C. Blood Cells and Venous Thromboembolism Risk: A Two-Sample Mendelian Randomization Study Front. Cardiovasc. Med. 9 2022 919640 10.3389/fcvm.2022.919640
12 Wojcik G.L. Graff M. Nishimura K.K. Tao R. Haessler J. Gignoux C.R. Highland H.M. Patel Y.M. Sorokin E.P. Avery C.L. Genetic analyses of diverse populations improves discovery for complex traits Nature 570 2019 514 518 10.1038/s41586-019-1310-4 31217584
13 Popejoy A.B. Ritter D.I. Crooks K. Currey E. Fullerton S.M. Hindorff L.A. Koenig B. Ramos E.M. Sorokin E.P. Wand H. The clinical imperative for inclusivity: Race, ethnicity, and ancestry (REA) in genomics Hum. Mutat. 39 2018 1713 1720 10.1002/humu.23644 30311373
14 Braekkan S.K. Mathiesen E.B. Njølstad I. Wilsgaard T. Hansen J.B. Hematocrit and risk of venous thromboembolism in a general population. The Tromso study Haematologica 95 2010 270 275 10.3324/haematol.2009.008417 19833630
15 Chi G. Gibson C.M. Hernandez A.F. Hull R.D. Kazmi S.H.A. Younes A. Walia S.S. Pitliya A. Singh A. Kahe F. Association of Anemia with Venous Thromboembolism in Acutely Ill Hospitalized Patients: An APEX Trial Substudy Am. J. Med. 131 2018 972.e1 972.e7 10.1016/j.amjmed.2018.03.031
16 Khorana A.A. Kuderer N.M. Culakova E. Lyman G.H. Francis C.W. Development and validation of a predictive model for chemotherapy-associated thrombosis Blood 111 2008 4902 4907 10.1182/blood-2007-10-116327 18216292
17 Achebe I. Mbachi C. Palacios P. Wang Y. Asotibe J. Ofori-Kuragu A. Gandhi S. Predictors of venous thromboembolism in hospitalized patients with inflammatory bowel disease and colon cancer: A retrospective cohort study Thromb. Res. 199 2021 14 18 10.1016/j.thromres.2020.12.017 33385795
18 Goto S. Turpie A.G.G. Farjat A.E. Weitz J.I. Haas S. Ageno W. Goldhaber S.Z. Angchaisuksiri P. Kayani G. MacCallum P. The influence of anemia on clinical outcomes in venous thromboembolism: Results from GARFIELD-VTE Thromb. Res. 203 2021 155 162 10.1016/j.thromres.2021.05.007 34023735
19 Lecouffe-Desprets M. Néel A. Graveleau J. Leux C. Perrin F. Visomblain B. Artifoni M. Masseau A. Connault J. Pottier P. Venous thromboembolism related to warm autoimmune hemolytic anemia: a case-control study Autoimmun. Rev. 14 2015 1023 1028 10.1016/j.autrev.2015.07.001 26162301
20 Davila J. Stanek J. O'Brien S.H. Venous thromboembolism prophylaxis in sickle cell disease: a multicenter cohort study of adolescent inpatients Blood Adv. 7 2023 1762 1768 10.1182/bloodadvances.2022007802 37103974
21 Raj T. Kuchroo M. Replogle J.M. Raychaudhuri S. Stranger B.E. De Jager P.L. Common risk alleles for inflammatory diseases are targets of recent positive selection Am. J. Hum. Genet. 92 2013 517 529 10.1016/j.ajhg.2013.03.001 23522783
22 Lo K.S. Wilson J.G. Lange L.A. Folsom A.R. Galarneau G. Ganesh S.K. Grant S.F.A. Keating B.J. McCarroll S.A. Mohler E.R. 3rd Genetic association analysis highlights new loci that modulate hematological trait variation in Caucasians and African Americans Hum. Genet. 129 2011 307 317 10.1007/s00439-010-0925-1 21153663
23 Ding K. de Andrade M. Manolio T.A. Crawford D.C. Rasmussen-Torvik L.J. Ritchie M.D. Denny J.C. Masys D.R. Jouni H. Pachecho J.A. Genetic variants that confer resistance to malaria are associated with red blood cell traits in African-Americans: an electronic medical record-based genome-wide association study G3 (Bethesda) 3 2013 1061 1068 10.1534/g3.113.006452 23696099
24 Li Q. Wang H. Wang H. Deng J. Cheng Z. Lin W. Zhu R. Chen S. Guo J. Tang L.V. Hu Y. Association between serum alkaline phosphatase levels in late pregnancy and the incidence of venous thromboembolism postpartum: a retrospective cohort study EClinicalMedicine 62 2023 102088 10.1016/j.eclinm.2023.102088
25 Liu X. Liu Y. Qu C. Mol B. Li W. Ying H. The association of iron-deficiency anemia, thrombocytosis at delivery and postpartum venous thromboembolism Am. J. Hematol. 97 2022 10.1002/ajh.26657 E356-e358
26 Zhai Z. Wang D. Lei J. Yang Y. Xu X. Ji Y. Yi Q. Chen H. Hu X. Liu Z. Trends in risk stratification, in-hospital management and mortality of patients with acute pulmonary embolism: an analysis from the China pUlmonary thromboembolism REgistry Study (CURES) Eur. Respir. J. 58 2021 2002963 10.1183/13993003.02963-2020
27 Wang C. Xu J. Yang L. Xu Y. Zhang X. Bai C. Kang J. Ran P. Shen H. Wen F. Prevalence and risk factors of chronic obstructive pulmonary disease in China (the China Pulmonary Health [CPH] study): a national cross-sectional study Lancet 391 2018 1706 1717 10.1016/s0140-6736(18)30841-9 29650248
28 Weng H. Li H. Zhang Z. Zhang Y. Xi L. Zhang D. Deng C. Wang D. Chen R. Chen G. Association between uric acid and risk of venous thromboembolism in East Asian populations: a cohort and Mendelian randomization study Lancet Reg. Health West. Pac. 39 2023 100848 10.1016/j.lanwpc.2023.100848
29 Sakaue S. Kanai M. Tanigawa Y. Karjalainen J. Kurki M. Koshiba S. Narita A. Konuma T. Yamamoto K. Akiyama M. A cross-population atlas of genetic associations for 220 human phenotypes Nat. Genet. 53 2021 1415 1424 10.1038/s41588-021-00931-x 34594039
30 Nam K. Kim J. Lee S. Genome-wide study on 72,298 individuals in Korean biobank data for 76 traits Cell Genom. 2 2022 100189 10.1016/j.xgen.2022.100189
31 Chen C.Y. Chen T.T. Feng Y.C.A. Yu M. Lin S.C. Longchamps R.J. Wang S.H. Hsu Y.H. Yang H.I. Kuo P.H. Analysis across Taiwan Biobank, Biobank Japan, and UK Biobank identifies hundreds of novel loci for 36 quantitative traits Cell Genom. 3 2023 100436 10.1016/j.xgen.2023.100436
32 Zhang Z. Li H. Weng H. Zhou G. Chen H. Yang G. Zhang P. Zhang X. Ji Y. Ying K. Genome-wide association analyses identified novel susceptibility loci for pulmonary embolism among Han Chinese population BMC Med. 21 2023 153 10.1186/s12916-023-02844-4 37076872
33 1000 Genomes Project ConsortiumAuton A. Brooks L.D. Durbin R.M. Garrison E.P. Kang H.M. Korbel J.O. Marchini J.L. McCarthy S. McVean G.A. Abecasis G.R. A global reference for human genetic variation Nature 526 2015 68 74 10.1038/nature15393 26432245
34 Burgess S. Butterworth A. Thompson S.G. Mendelian randomization analysis with multiple genetic variants using summarized data Genet. Epidemiol. 37 2013 658 665 10.1002/gepi.21758 24114802
35 Burgess S. Thompson S.G. Interpreting findings from Mendelian randomization using the MR-Egger method Eur. J. Epidemiol. 32 2017 377 389 10.1007/s10654-017-0255-x 28527048
36 Bowden J. Davey Smith G. Haycock P.C. Burgess S. Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator Genet. Epidemiol. 40 2016 304 314 10.1002/gepi.21965 27061298
37 Bowden J. Davey Smith G. Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression Int. J. Epidemiol. 44 2015 512 525 10.1093/ije/dyv080 26050253
38 Verbanck M. Chen C.Y. Neale B. Do R. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases Nat. Genet. 50 2018 693 698 10.1038/s41588-018-0099-7 29686387
