Startseite Rhesus factor is a stronger predictor for the risk of Sars-CoV-2 and mortality than ABO blood types
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Rhesus factor is a stronger predictor for the risk of Sars-CoV-2 and mortality than ABO blood types

  • Soner Yesilyurt ORCID logo EMAIL logo , Osman Erinc ORCID logo , Almila Senat ORCID logo , Cem Tugrul Gezmis ORCID logo und Mustafa Bahadir Can Balci ORCID logo
Veröffentlicht/Copyright: 12. September 2023
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Turkish Journal of Biochemistry
Aus der Zeitschrift Turkish Journal of Biochemistry Band 48 Heft 5

Abstract

Objectives

In this study, we aimed to evaluate the relationship between ABO blood groups and Rhesus factor (Rf) and severe acute respiratory syndrome coronavirus-2 (Sars-CoV-2), as well as the risk of infection susceptibility and death according to pre-existing comorbidities.

Methods

This retrospective study included patients medical record between March 2020 and March 2021. A total 470 patients were included in the study. The subjects were categorized according to diagnose of Sars-CoV-2. Also, we evaluated the subject according to severity of Sars-CoV-2 infection. The logistic and multivariate regression analysis were performed to predict possible effect of ABO and Rf types as well as comorbidities on indicators of Sars-CoV-2 severity including Intensive care unit (ICU) hospitalization, intubation, and mortality.

Results

The distribution of ABO blood type and Rf were not statistically different cases with and without Sars-CoV-2. Blood type B and A were the most groups in intubation and mortality among patients with Sars-CoV-2. However, ABO blood types had no significant effect on risk of Sars-CoV-2 and mortality while, Rf had a significantly effect on it. Additionally, Rf had a statistically significant effect on all severity indicators of Sars-CoV-2 but ABO had not.

Conclusions

While Rf was significantly associated with risk of Sars-CoV-2 and had a strong effect on ICU admission, intubation, and mortality, ABO groups were not associated with risk of disease. Intubation and mortality rates were higher in patients with blood group B (OR: 2.93 p:0.390 95 % CI [0.253–33.9], OR: 0.217 p:0.211 95 % CI [0.020–2.37]) and Rh factor + (OR: 1.63 p:0.027 95 % CI [0.046–0.828]).

Keywords: ABO blood type; mortality; rhesus factor; Sars-CoV-2

Introduction

Severe Acute Respiratory Syndrome Coronavirus-2 (Sars-CoV-2) or Coronavirus disease-2019 (COVID-19) was identified in Wuhan, China on December 31, 2019, and soon spread worldwide to become a global pandemic [1, 2]. According to World Health Organization (WHO), from the first day the pandemic was declared (March 11, 2020) to the end of February 2023, more than 750 million people have been affected [3]. The Sars-CoV-2 pandemic is not over yet and continue affecting people. Although a significant majority of the world’s population has now been vaccinated, the pandemic has so far caused numerous health issues and high rates of mortality. In Turkey, the first Sars-CoV-2 case was declared on March 11, 2020. Similar to other countries, Turkey has also suffered from serious health concerns and deaths due to the pandemic [4].

The blood types are determined depending on whether specific antigen on erythrocytes surface or not. This surface antigen has been suggested to play a role in the development of several diseases. In addition to this, blood groups are divided into two categories according to the presence or absence of the Rhesus (Rh) factor protein [5, 6]. ABO blood types have been investigated to illuminate possible mechanisms of susceptibility or protection for Sars-CoV-2 infection. One of the early studies about ABO and Sars-CoV-2 has suggested that blood type A was more susceptible to infection whereas blood type O was less associated with the risk of Sars-CoV-2. After this study, reports from Europe supported that blood type A was prone to severe symptoms of viral infection but, blood type O had a lower risk of Sars-CoV-2 [7, 8]. However, available data on the relationship between ABO groups and Sars-CoV-2 infection have so far been controversial [6, 9], [10], [11].

Within this scope, the purpose of the present study is to investigate the possible relationship between ABO blood types as well as Rh factor and Sars-CoV-2 infection by using patients’ medical data. A second aim of this study is to evaluate possible associations between Sars-CoV-2 and clinical outcomes, the severity of infection, and mortality.

Materials and methods

Study design

This retrospective study was conducted with the medical records of patients who were admitted to Taksim Training and Research Hospital (Istanbul, Turkey) between March 2020 and March 2021. A total of 470 patients with an age range of 18–99 were categorized into two main groups as patients who tested positive for Sars-CoV-2 and were hospitalized due to coronavirus infection (n=363) and patients who tested negative for Sars-CoV-2 and were hospitalized for other health issues (n=107) such as traffic accidents, bone fracture, anemia, and neurologic diseases. The CONSORT diagram was summarized patient selection in Figure 1. A priori power analysis was performed to determine the sample size for detecting a difference between the groups at an effect size of f=0.40 in laboratory measurements based on the statistical methods (α=0.05, power=0.80). The diagnosis of Sars-CoV-2 was confirmed by reverse transcription polymerase chain reaction (RT‐PCR) and computed tomography (CT). Patients whose negative test results were not also confirmed by their CT scans were excluded from the study.

Figure 1: CONSORT diagram of patients’ selection.
Figure 1:

CONSORT diagram of patients’ selection.

Clinical data including duration of hospital stay, intensive care unit (ICU) hospitalization, intubation, case fatality (CF) percentage, lung involvement, presence of comorbidities such as diabetes mellitus (DM), hypertension (HT), coroner artery disease (CAD), chronic obstructive pulmonary disease (COPD), cerebrovascular disease (CVD), and asthma were recorded and evaluated.

Laboratory data

The diagnosis of Sars-CoV-2 was confirmed by RT-PCR via the analysis of the viral genome at the Cemil Tascioglu City Hospital (Istanbul, Turkey), using nasopharyngeal swab samples. Alanine aminotransferase (ALT), glucose, creatinine, and C-reactive protein (CRP) was measured at the Roche cobas c501 clinical chemistry autoanalyzer (Roche Diagnostics, Mannheim, Germany). D-Dimer tests were analyzed using a Stago Compact Max3 analyzer with a commercial kit (Stago Diagnostics). The whole blood count analysis was conducted with a Mindray BC8000 autoanalyzer. Data concerning ABO and Rh factors of the patients were obtained from the database of the Taksim Training and Research Hospital.

Statistical analyses

All statistical analyses were conducted with SPSS software version 23.0 (Armonk, USA). The normality analysis of variables was performed with the Kolmogorov-Smirnov test. Normally distributed variables were presented as mean + standard deviation (SD), non-normally distributed variables as median (inter-quartile range), and categorical variables as percentages. The ANOVA test and independent samples t-test were used to compare normally distributed variables, whereas Kruskal–Wallis and Mann Whitney-U tests were performed for non-parametric variables. The Pearson Chi-square and the Fisher’s Exact tests were conducted for the analysis of categorical variables. Logistic regression was performed to predict the potential risk of susceptibility and mortality for ABO blood type and Rhesus factor, and multivariate linear regression analyses were used to predict the possible effect of demographic and clinical characteristics, such as comorbid diseases, on the severity indicators of Sars-CoV-2 infection, including ICU hospitalization, intubation, and case fatality. All comparisons were two-tailed and a p value of <0.05 was defined as showing statistical significance.

Results

The demographic and clinical characteristics of subjects with and without Sars-CoV-2 are summarized in Table 1. There were not any significant differences with respect to gender, the distribution of blood type, and rhesus factor (p>0.05). On the other hand, ICU hospitalization, the number of intubated patients, and case fatality (CF) were higher in the subjects with Sars-CoV-2 (p<0.0001 for all).

Table 1:

Demographic and clinical characteristics of all subjects with and without Sars-CoV-2.

Without Sars-CoV-2 n=107 With SARS-CoV-2 n=363 p-Value
Gender
 Female, % 47 (43.9) 210 (57.6) 0.588
 Male, % 59 (55.1) 153 (42.4)
Age, year 62.6 ± 18.9 56.6 ± 14.7 0.001
Blood type
 A, % 40 (37.4) 119 (32.8) 0.171
 B, % 16 (14.9) 50 (13.7)
 AB, % 14 (13.1) 30 (8.3)
 O, % 37 (34.6) 164 (45.2)
Rhesus factor
 Rh +, % 79 (73.8) 283 (78) 0.399
 Rh –, % 28 (26.2) 80 (22)
DM, % 11 (10.3) 63 (17.4) 0.075
HT, % 11 (10.3) 181 (49.8) <0.0001
CAD, % 3 (2.8) 68 (18.7) <0.0001
COPD, % 4 (3.74) 30 (8.26) 0.110
CVD, % 2 (1.87) 24 (6.61) 0.058
Asthma, % 0 (0.0) 48 (13.2) <0.0001
Lung involvement, % 0 (0.0) 314 (86.5) <0.0001
ALT, U/L 12.8 (9–21.4) 35 (20–58.7) <0.0001
Creatinine, mg/dL 0.86 (0.63–1.12) 0.75 (0.63–0.91) 0.014
eGFR, mL/min/1.73m2 83.1 ± 33.2 93.9 ± 24.7 <0.0001
CRP, mg/L 18.8 (3.1–75.9) 16.7 (6.80–60.1) 0.984
D-Dimer, µg/L, FEU 674 (419–1905) 760 (456–1,295) 0.934
Lymphocyte, 103/µL 1.51 (0.94–2.20) 1.52 (1.09–2.05) 0.817
Neutrophile, 103/µL 5.93 (4.55–9.63) 3.87 (2.91–5.46) <0.0001
Platelets, 103/µL 274 (180–331) 269 (207–354) 0.321
ESR, s 62 ± 45.2 63.5 ± 31.1 0.944
Duration of hospital stay, day 2 (1–4) 9 (6–13) <0.0001
ICU hospitalization, % 4 (3.73) 49 (13.4) <0.0001
Intubation, % 0 (0.0) 35 (9.64) <0.0001
CF, % 0 (0.0) 29 (7.98) <0.0001

  1. DM, diabetes mellitus; HT, Hypertension; CAD, coroner artery disease; COPD, chronic obstructive pulmonary disease; CVD, cerebrovascular disease; ALT, alanine transaminase; CRP, C-reactive protein; ESR, erythrocyte sedimentation rate; ICU, intensive care unit; CF, case fatality. Bold values indicate the statistically important ones (<0.05).

The comparison of demographic and clinical characteristics according to ABO blood type and rhesus factor in patients with Sars-CoV-2 are shown in Tables 2 and 3. There were no differences between age and gender in terms of the ABO and Rh groups. Additionally, the groups had no differences concerning the presence of DM, HT, CAD, CVD, and asthma (p>0.05). The number of intubated patients and CF were statistically different in groups in terms of ABO blood type (p=0.045 and p=0.021, respectively). Furthermore, there were significant statistical differences in ICU hospitalization, intubated patients, and CF in terms of the rhesus factor (p=0.032, p=0.014, and p=0.012; respectively).

Table 2:

Demographic and clinical characteristics of subjects with Sars-CoV-2 according to blood types.

A (n=119) B (n=50) AB (n=30) O (n=164) p-Value
Gender
 Female, % 47 (39.5) 20 (40) 14 (46.7) 72 (43.9) 0.826
 Male, % 72 (60.5) 30 (60) 16 (53.3) 91 (56.1)
Age, year 57.5 ± 14.9 56.4 ± 14.1 51.6 ± 13 57.1 ± 15 0.250
Rh +, % 109 (91.5) 45 (90) 30 (100) 99 (60.4) <0.001
Rh –, % 10 (8.5) 5 (10) 0 (0) 65 (39.6)
DM, % 21 (17.6) 9 (18) 6 (20) 26 (15.8) 0.938
HT, % 65 (54.6) 26 (52) 11(36.6) 79 (48.2) 0.328
CAD, % 27 (22.7) 7 (14) 2 (6.7) 32 (19.5) 0.180
COPD, % 11 (9.2) 3 (6) 1 (3.3) 15 (9.14) 0.655
CVD, % 6 (5.04) 5 (10) 0 (0) 13 (7.93) 0.263
Asthma, % 12 (10.08) 6 (12) 4 (13.3) 26 (15.6) 0.557
Lung involvement, % 99 (83.2) 45 (90) 25 (83.3) 143 (87.2) 0.613
ALT, U/L 35 (21–52) 32 (18.5–73) 43 (21.7–75) 34 (20–55) 0.566
Creatinine, mg/dL 0.72 (0.61–0.87) 0.77 (0.68–0.92) 0.75 (0.66–0.89) 0.76 (0.64–0.94) 0.214
eGFR, mL/min/1.73m2 96.2 ± 22.9 92 ± 27 95.7 ± 27.1 92.3 ± 25 0.539
CRP, mg/L 15 (7–70.6) 23.8 (6.72–62.4) 15.8 (7.6–34.1) 17 (6.5–51.5) 0.752
D-Dimer, µg/L, FEU 790 (488–1,480) 648 (362–1,137) 731 (410–1,225) 781 (466–1,250) 0.644
Lymphocyte, 103/µL 1.45 (1.02–1.96) 1.37 (1–1.91) 1.57 (1.13–2.30) 1.57 (1.14–2.11) 0.160
Neutrophile, 103/µL 3.96 (2.93–6) 3.15 (2.53–5.86) 3.40 (2.94–4.93) 3.94 (2.98–5.24) 0.189
Platelets, 103/µL 267 (198–364) 251 (210–315) 298 (246–368) 277 (205–361) 0.249
ESR, s 69.4 ± 33 55.5 ± 36 68.1 ± 25 61.2 ± 29.6 0.381
Duration of hospital stay, day 9 (6–14) 9(6–14) 8.5 (5.5–15) 9 (6.3–13) 0.983
ICU hospitalization, % 20 (16.8) 11 (22) 2 (6.6) 19 (11.6) 0.099
Intubation, % 15 (12.6) 8 (16) 1 (3.3) 11 (6.7) 0.045
CF, % 13 (10.9) 8 (16) 1 (3.3) 7 (4.26) 0.021

  1. DM, diabetes mellitus; HT, hypertension; CAD, coroner artery disease; COPD, chronic obstructive pulmonary disease; CVD, cerebrovascular disease; ALT, alanine transaminase; CRP, C-Reactive protein; ESR, Erythrocyte sedimentation rate; ICU, Intensive Care Unit; CF, Case Fatality; and WBC, White Blood Cell. Bold values indicate the statistically important ones (<0.05).

Table 3:

Demographic and clinical characteristics of subjects with Sars-CoV-2 according to Rhesus factor (Rh).

Rh + (n=283) Rh − (n=80) p-Value
Gender
 Female, % 120 (42.4) 33 (41.3) 0.854
 Male, % 163 (57.6) 47 (58.7)
Age, year 56.4 ± 14.9 57.8 ± 13.9 0.439
DM, % 47 (16.6) 15 (18.8) 0.653
HT, % 135 (47.7) 46 (57.5) 0.122
CAD, % 54 (19.08) 14 (17.5) 0.749
COPD, % 23 (8.12) 7 (8.75) 0.858
CVD, % 18 (6.36) 6 (7.5) 0.717
Asthma, % 36 (12.7) 12 (15) 0.595
Lung involvement, % 241 (85.2) 71 (88.8) 0.414
ALT, U/L 35 (20–61) 34.5 (20–51) 0.711
Creatinine, mg/dL 0.75 (0.63–0.91) 0.77 (0.64–0.92) 0.779
eGFR, mL/min/1.73m2 94.4 ± 24.9 92 ± 24.6 0.458
CRP, mg/L 16.5 (6.8–70) 17.6 (6.5–44.2) 0.571
D-Dimer, µg/L, FEU 773 (456–1,290) 714 (472–1,355) 0.944
Lymphocyte, 103/µL 1.51 (1.08–2.04) 1.56 (1.07–2.07) 0.453
Neutrophile, 103/µL 3.87 (2.92–5.45) 3.93 (2.91–5.92) 0.801
Platelets, 103/µL 262 (207–355) 277 (209–354) 0.389
ESR, s 63.9 ± 31.4 62 ± 31.3 0.768
Duration of hospital stay, day 9 (6–13) 10 (7–13) 0.514
ICU hospitalization, % 44 (15.5) 5 (6.25) 0.032
Intubation, % 33 (11.6) 2 (2.5) 0.014
CF, % 28 (9.89) 1 (1.25) 0.012

  1. DM, diabetes mellitus; HT, hypertension; CAD, coroner artery disease; COPD, chronic obstructive pulmonary disease; CVD, cerebrovascular disease; ALT, alanine transaminase; CRP, C-reactive protein; ESR, erythrocyte sedimentation rate; ICU, intensive care unit; CF, case fatality. Bold values indicate the statistically important ones (<0.05).

We also assessed the subjects diagnosed with Sars-CoV-2 in terms of severity of infection as shown in Table 4. Mean age, percentage of comorbidities such as DM, HT, CAD, COPD, and as expected CF rate were significantly higher in the severe Sars-CoV-2 group than the subjects with mild/moderate Sars-CoV-2 (p<0.0001, p=0.002, p=0.003, p=0.001, p<0.0001; respectively). However, the presence of asthma in the mild/moderate group was higher than the subjects with severe Sars-CoV-2 (p<0.0001).

Table 4:

The comparison of blood type and rhesus factor according to severity of Sars-CoV-2.

Mild cases n=314 Severe cases n=49 p-Value
Gender
 Female, % 135 (42.9) 18 (36.7) 0.409
 Male, % 179 (57.1) 31 (63.3)
Age, year 55.3 ± 14.6 65.2 ± 12.1 <0.0001
Blood type
 A, % 100 (31.8) 19 (38.8) 0.098
 B, % 39 (12.4) 11 (22.4)
 AB, % 28 (8.9) 2 (4.1)
 O, % 147 (46.9) 17 (34.7)
Rhesus factor
 Rh +, % 239 (76.1) 44 (89.8) 0.032
 Rh −, % 75 (23.9) 5 (10.2)
Duration of hospital stay, day 10 (7–13) 13 (4.5–22.5) 0.202
DM, % 47 (14.9) 15 (30.6) 0.007
HT, % 147 (46.8) 34 (69.4) 0.003
CAD, % 50 (15.9) 18 (36.7) 0.001
COPD, % 20 (6.36) 10 (20.4) 0.001
CVD, % 21 (6.69) 3 (6.12) 0.882
Asthma, % 46 (14.6) 2 (4.08) 0.042
Lung involvement, % 264 (84.1) 48 (97.9) 0.009
CF, % 1 (0.3) 28 (57.1) <0.0001

  1. DM, diabetes mellitus; HT, hypertension; CAD, coroner artery disease; COPD, chronic obstructive pulmonary disease; CVD, cerebrovascular disease; ICU, intensive care unit; CF, case fatality. Bold values indicate the statistically important ones (<0.05).

In addition, we performed logistic regression analysis to predict ABO blood types to susceptibility and mortality. The blood type of A (Odds ratio: 0.668 p:0.497 95 % CI [0.468–4.791], Odds ratio: 2.75 p:0.258 95 % CI [0.476–15.9]), B (Odds ratio: 2.93 p:0.390 95 % CI [0.253–33.9], Odds ratio: 0.217 p:0.211 95 % CI [0.020–2.37]), AB (Odds ratio: 4.15 p:0.529 95 % CI [0.05–347], Odds ratio: 0.533 p:0.780 95 % CI [0.006–44.7]), and O (Odds ratio: 1.13 p:0.886 95 % CI [0.212–6.02], Odds ratio: 2.74 p:0.218 95 % CI [0.551–13.7]) were not predictive for susceptibility of Sars-CoV-2 and mortality respectively. On the other hand, the Rh factor was significantly predictive for both susceptibility and mortality (Odds ratio: 1.63 p:0.027 95 % CI [0.046–0.828], Odds ratio: 2.16 p:0.035 95 % CI [0.015–0.861]) respectively.

Furthermore, we performed multivariate linear regression analysis to assess possible effects of age, gender, and likely comorbidities on ICU hospitalization, intubation, and CF as summarized in Table 5. Age, gender, and ABO blood type were not found to affect ICU hospitalization, intubation, and mortality in all cases. However, age had an effect on indicators of severity of infection in cases with Sars-CoV-2, while gender and ABO blood type were not observed to have an effect on indicators in the Sars-CoV-2 group. Rh factor was more predictive on ICU hospitalization, intubation, and CF in all cases and in cases with Sars-CoV-2.

Table 5:

Multivariate Linear Regression analysis to predict likely comorbidities and demographic characteristics on indicators of the severity of Sars-CoV-2.

ICU hospitalization% Intubation% CF%
St B 95 %CI p-Value St B 95 %CI p-Value St B 95 %CI p-Value
All cases
Age, year 0.045 [−0.001–0.003] 0.597 0.068 [0.00–0.003] 0.169 0.085 [0.00–0.003] 0.086
Gender −0.044 [−0.07–0.024] 0.326 −0.006 [−0.04–0.04] 0.894 −0.015 [−0.046–0.032] 0.734
ABO blood type −0.029 [−0.02–0.014] 0.525 −0.064 [−0.031–0.005] 0.167 −0.07 [−0.029–0.004] 0.136
Rhesus factor 0.098 [0.006–0.136] 0.031 0.09 [0.006–0.119] 0.031 0.104 [0.007–0.112] 0.026
DM, % 0.110 [0.019–0.166] 0.014 0.118 [0.022–0.150] 0.009 0.090 [0.00–0.119] 0.048
HT, % 0.120 [0.011–0.138] 0.021 0.065 [−0.021–0.090] 0.219 0.073 [−0.015–0.087] 0.166
CAD, % 0.140 [0.034–0.205] 0.006 0.138 [0.027–0.176] 0.008 0.064 [−0.026–0.112] 0.223
COPD, % 0.173 [0.09–0.309] <0.0001 0.109 [0.019–0.201] 0.018 0.129 [0.035–0.204] 0.006
CVD, % −0.059 [−0.201–0.044] 0.206 −0.022 [−0.132–0.081] 0.644 0.013 [−0.085–0.112] 0.789
Asthma, % −0.097 [−0.188 to −0.008] 0.032 −0.085 [−0.152–0.005] 0.065 −0.073 [−0.131–0.014] 0.115
Cases with Sars-CoV-2
Age, year 0.140 [0.003–0.006] 0.023 0.166 [0.001–0.006] 0.008 0.186 [–0.038–0.0059] 0.135
Gender −0.043 [−0.90–0.04] 0.395 0.000 [−0.06–0.061] 0.994 −0.011 [−0.06–0.050] 0.830
ABO blood type −0.033 [−0.04–0.018] 0.533 −0.075 [−0.04–0.007] 0.165 −0.08 [−0.038–0.005] 0.135
Rhesus factor 0.108 [ 0.003–0.175] 0.042 0.166 [0.001–0.151] 0.047 0.112 [0.004–0.143] 0.039
DM, % 0.112 [0.02–0.201] 0.017 0.128 [0.021–0.179] 0.013 0.097 [−0.003–0.143] 0.061
HT, % 0.032 [−0.06–0.105] 0.609 −0.023 [−0.09–0.059] 0.710 −0.013 [−0.074–0.06] 0.837
CAD, % 0.124 [0.009–0.209] 0.034 0.119 [0.003–0.178] 0.043 0.041 [−0.053–0.109] 0.494
COPD, % 0.162 [0.074–0.329] 0.002 0.091 [−0.014–0.208] 0.087 0.110 [0.005–0.211] 0.040
CVD, % −0.075 [−0.247–0.042] 0.163 −0.035 −0.168–0.084 0.511 0.002 [−0.114–0.119] 0.970
Asthma, % −0.108 [−0.21–0.006] 0.038 −0.093 −0.171–0.008 0.075 −0.079 [−0.146–0.019] 0.132

  1. DM, diabetes mellitus; HT, hypertension; CAD, coroner artery disease; COPD, chronic obstructive pulmonary disease; CVD, cerebrovascular disease; ICU, intensive care unit; CF, case fatality. Adjusted R square for ICU hospitalization: 0.106 for intubation: 0.081, and for CFR: 0.065 in all cases. Adjusted R square for ICU hospitalization: 0.110, for Intubation: 0.091, and for CFR 0.078 in cases with Sars-CoV-2. Bold values indicate the statistically important ones (<0.05).

Discussion

The present study exhibited the association between patients with and without Sars-CoV-2 and ABO blood type as well as Rh factor from a single center medical record. There were not any differences in the distribution of ABO blood types among patients with and without Sars-CoV-2. Our results showed that intubation and CF were statistically different between ABO blood types. The number of patients with B blood type were the highest with respect to intubation, followed by A blood type as the second group, and lastly O blood type. Similarly, the CF was significantly different between ABO blood types. In addition, ICU hospitalization, intubation, and CF were significantly higher in patients with Rh+ than the patients with Rh−. According to multivariate and logistic regression analyses, ABO blood types did not have an effect on indicators of Sars-CoV-2 infection severity, but Rh factors had a significant effect on all severity indicators of infection in all cases and cases with Sars-CoV-2.

The association between blood types and bacterial or viral diseases has recently been in the scope of researchers, and the potential relationship between blood types and several diseases have been investigated. For instance, some studies have evaluated the possible relationship between blood types and severe acute respiratory syndrome (SARS) or influenza infection [12, 13]. After the Sars-CoV-2 pandemic, it has been suggested that ABO blood types are related to susceptibility, severity, and mortality of Sars-CoV-2 infections and that the possible relationship results from that anti-A and anti-B of ABO blood type could provide a protection from Coronavirus spike protein binding cell receptors. Because of this finding, non-O blood types were thought to increase the risk of infection severity [14].

There are controversial results in the literature with respect to blood type and Sars-CoV-2 infection. A nation-based study carried out in Sweden has shown that people with blood types A, AB, and B are at increased risk of Sars-CoV-2 infection [15]. Another study suggested that blood types B and AB were more predictive of infection risk, and blood type B was significantly associated with mortality. In the same report, a relationship between Rh and Sars-CoV-2 infection was not observed [16]. Koc et al. have reported that the rate of mechanical ventilation and hospitalization in ICU was higher in patients with A and AB blood groups than other blood types. On the other hand, it was shown that the blood group O was more related to the risk of infection and worse prognosis than other blood types. However, researchers did not find any relationship between mortality and blood type [17]. A meta-analysis consisting of 23 studies have concluded that majority of reports indicated the blood type A to be more susceptible for Sars-CoV-2 infection, but there were some reports showing that the B blood type was the most vulnerable for infection. Furthermore, A and AB blood types were more related to severity of Sars-CoV-2 and mortality whereas, the O blood type had some protective properties against worse outcomes of Sars-CoV-2 or mortality [18]. In parallel to some reports [19], our results revealed no statistically significant relationship between ABO groups and Sars-CoV-2 infection meanwhile, the most frequent blood types were B and A with respect to ICU hospitalization and CF in the present study. Moreover, none of the ABO blood types were associated with the mortality of Sars-CoV-2. Additionally, the ABO blood type had no effect on severity indicators of Sars-CoV-2 including ICU hospitalization, intubation, and mortality.

Another interesting relationship with susceptibility of Sars-CoV-2 is Rh factor. The blood type is determined as positive or negative based on presence of Rh factor protein. Like ABO blood types, even though a significant number of studies have investigated the Rh factors in Sars-CoV-2, the results are controversial. We showed that the Rh factor was significantly predictive of susceptibility to Sars-CoV-2 and mortality. In addition, multivariate regression analysis revealed that the Rh factor had a significant effect on indicators of Sars-CoV-2 severity including ICU hospitalization, intubated patients, and CF in both all cases and cases with Sars-CoV-2. Furthermore, there was a statistically significant difference between mild and severe cases, the number of Rh+ patients being higher in severe cases than mild cases. Recently, it was reported that patients with blood types B and AB as well as Rh+ were more likely to test positive for Sars-CoV-2 [11]. Another study from India also supported these findings, indicating that Rh+ individuals were more susceptible to Sars-CoV-2 infection [20], whereas being Rh- was associated with a lower risk of infection in another reports [21]. However, in a study conducted in Turkey, the Rh factor was shown to be related to hospitalization in ICU while it was not statistically associated with mortality [22]. On the contrary, some studies suggested that the prevalence of Sars-CoV-2, rate of intubation, and mortality were significantly higher in Rh- patients [23]. There are some reports that suggest no relationship between the Rh factor and Sars-CoV-2 [24].

We assessed the effect of comorbidities on ICU hospitalization, intubation, and CF in the present study. In our study, Although, HT was the most frequently observed comorbidity in cases with Sars-CoV-2, it did not have any significant effects on severity indicators of Sars-CoV-2. DM and CAD had statistically similar effects on ICU hospitalization and intubation. On the other hand, COPD was the most important comorbidity on all severity indicators in cases with non-Sars-CoV-2 while it was the only comorbidity that had a statistically significant effect on mortality in patients with Sars-CoV-2. The clinical outcome of Sars-CoV-2 could be worse with presence of comorbid diseases. It has been reported that presence of one or more comorbidities in people diagnosed with Sars-CoV-2 was about 79 % [25]. Consistent with our results, Gamboa-Aguilar et al. reported that the rate of mortality in Sars-CoV-2 infection increased with presence of comorbidities, and DM, HT, and history of smoking were significantly related to increased risk of Sars-CoV-2 mortality [26]. In parallel with our results, the COPD had a higher prevalence in patients with severe symptoms and worse outcome of infection [27]. It was reported that the patients with COPD had a four folds higher risk for severe clinical manifestations of Sars-CoV-2 compared to patients without COPD [28]. Additionally, the mortality rate in subjects with Sars-CoV-2 was higher than in cases with non-Sars-CoV-2 [29, 30].

The present study had some restrictions. Firstly, we had a relatively small sample size. A larger population data could be more useful to understand the possible association between blood types and Rh factor and Sars-CoV-2. Secondly, the data on vaccination and detailed demographic characteristics of subject could be another limited part of our study.

Conclusions

We evaluated the relationship between ABO blood types, Rh factors and Sars-CoV-2. The distribution of ABO groups and Rh factors were similar between the patients with and without Sars-CoV-2. Meanwhile, intubation and mortality rates were higher in patients with B blood type with Rh+. The most of patients with Rh– were blood type O with a lower rate of ICP hospitalization, intubation, and CFR. However, logistic regression analysis indicated that Rh factor was more predictive risk of infection and death but ABO blood types were not. Additionally, multivariate linear regression analysis proved that ABO blood types did not have an effect on ICU hospitalization, intubation, and mortality whereas, Rh factors had significantly higher predictive power on severity indicators in both all cases and cases with Sars-CoV-2.

Corresponding author: Dr. Soner Yesilyurt, Department of Internal Medicine, Taksim Training and Research Hospital, Siraselviler st. No:48 34433 Beyoglu, Istanbul, Türkiye, E-mail:

  1. Research ethics: All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Ethical approval of the present study was received from The Clinical Research Ethics Committee of Gaziosmanpasa Training and Research Hospital [Approval No: 2021/261].

  2. Informed consent: Not applicable.

  3. Author contribution: Conceptualization: Soner Yesilyurt, Cem Tugrul Gezmis, Mustafa Bahadir Can Balci. Data curation: Soner Yesilyurt, Osman Erinc, Almila Senat, Cem Tugrul Gezmis, Mustafa Bahadir Can Balci. Formal analysis: Almila Senat. Funding acquisition: Soner Yesilyurt, Osman Erinc, Cem Tugrul Gezmis, Mustafa Bahadir Can Balci. Investigation: Soner Yesilyurt, Osman Erinc, Almila Senat, Cem Tugrul Gezmis, Mustafa Bahadir Can Balci. Methodology: Soner Yesilyurt, Osman Erinc, Almila Senat. Supervision: Soner Yesilyurt, Mustafa Bahadir Can Balci. Writing original draft: Soner Yesilyurt. Writing review & editing: Soner Yesilyurt, Osman Erinc, Almila Senat, Cem Tugrul Gezmis, Mustafa Bahadir Can Balci.

  4. Competing interest: The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

  5. Research funding: None declared.

  6. Data availability: This study does not have any data set to share. All records used in the present study were obtained from the Taksim Training and Research Hospital database.

References

1. Usluoglu, F, Togay, A, Atici, M, Sahin Yoluk, İ. The effects of COVID-19 pandemic on adults living in Turkey and ways of coping. Soc Work Publ Health 2013;38:193–208. https://doi.org/10.1080/19371918.2022.2117754.Suche in Google Scholar PubMed

2. Beatty, K, Kavanagh, PM. A retrospective cohort study of outcomes in hospitalised COVID-19 patients during the first pandemic wave in Ireland. Ir J Med Sci 2021;191:1973–83. https://doi.org/10.1007/s11845-021-02753-6.Suche in Google Scholar PubMed PubMed Central

3. Miyashita, K, Hozumi, H, Furuhashi, K, Nakatani, E, Inoue, Y, Yasui, H, et al.. Changes in the characteristics and outcomes of COVID-19 patients from the early pandemic to the delta variant epidemic: a nationwide population-based study. Emerg Microb Infect 2023;12:2155250. https://doi.org/10.1080/22221751.2022.2155250.Suche in Google Scholar PubMed PubMed Central

4. Gun, MA, Hanci, O. The effect of social movements on COVID-19 case increases and death in Turkey. Clin Epidemiol Glob Health 2023;20:101260. https://doi.org/10.1016/j.cegh.2023.101260.Suche in Google Scholar PubMed PubMed Central

5. Lasić, L, Lojo-Kadrić, N, Silajdžić, E, Pojskić, L, Hadžiselimović, R, Pojskić, N. Molecular–genetic variance of RH blood group system within human population of Bosnia and Herzegovina. Bosn J Basic Med Sci 2023;13:10–3. https://doi.org/10.17305/bjbms.2013.2403.Suche in Google Scholar PubMed PubMed Central

6. Ozkarafakili, MA, Gareayaghi, N, Kara, ZMY. Relationship between ABO blood types and coronavirus disease 2019 severity. Sisli Etfal Hastan Tip Bul 2022;56:41–8. https://doi.org/10.14744/SEMB.2021.15045.Suche in Google Scholar PubMed PubMed Central

7. Li, J, Wang, X, Chen, J, Cai, Y, Deng, A, Yang, M. Association between ABO blood groups and risk of SARS‐CoV‐2 pneumonia. Br J Haematol 2020;190:24–7. https://doi.org/10.1111/bjh.16797.Suche in Google Scholar PubMed PubMed Central

8. Ellinghaus, D, Degenhardt, F, Bujanda, L, Buti, M, Albillos, A, Invernizzi, P, et al.. Severe Covid-19 GWAS Group. Genomewide association study of severe Covid-19 with respiratory failure. N Engl J Med 2020;383:1522–34. https://doi.org/10.1056/nejmoa2020283.Suche in Google Scholar

9. Önder, T, Hasbal, NB, Kahramanca, S, Anuk, T. Kronik Gastritli Hastalarda Helicobacter pylori Infeksiyonu ile Cinsiyet, ABO Kan Grupları ve Rhesus Faktör Arası İlişki. IKSST Derg 2016;8:93–6.Suche in Google Scholar

10. Barnkob, MB, Pottegård, A, Støvring, H, Haunstrup, TM, Homburg, K, Larsen, R, et al.. Reduced prevalence of SARS-CoV-2 infection in ABO blood group O. Blood Adv 2020;4:4990–3. https://doi.org/10.1182/bloodadvances.2020002657.Suche in Google Scholar PubMed PubMed Central

11. Latz, CA, DeCarlo, C, Boitano, L, Png, CYM, Patell, R, Conrad, MF, et al.. Blood type and outcomes in patients with COVID-19. Ann Hematol 2020;99:2113–18. https://doi.org/10.1007/s00277-020-04169-1.Suche in Google Scholar PubMed PubMed Central

12. Cheng, Y, Cheng, G, Chui, C, Lau, FY, Chan, PKS, Ng, MH. ABO blood group and susceptibility to severe acute respiratory syndrome. JAMA 2005;293:1447–51. https://doi.org/10.1001/jama.293.12.1450-c.Suche in Google Scholar PubMed

13. Lebiush, M, Rannon, L, Kark, J. The relationship between epidemic influenza A (H1N1) and ABO blood groups. J Hyg 1981;87:139–46. https://doi.org/10.1017/s002217240006931x.Suche in Google Scholar PubMed PubMed Central

14. Cetin, M, Cetin, S, Ulgen, A, Li, W. Blood-Type-A is a COVID-19 infection and hospitalization risk in a Turkish cohort. Transfus Clin Biol 2023;30:116–22. https://doi.org/10.1016/j.tracli.2022.10.003.Suche in Google Scholar PubMed PubMed Central

15. Dahlén, T, Li, H, Nyberg, F, Edgren, G. A population‐based, retrospective cohort study of the association between ABO blood group and risk of COVID‐19. J Intern Med 2023;293:398–402. https://doi.org/10.1111/joim.13588.Suche in Google Scholar PubMed PubMed Central

16. Hindawi, S, Daghistani, S, Elgemmezi, T, Radhwi, O, Badawi, M, Al‐Tayeb, W, et al.. Association of blood group with COVID‐19 disease susceptibility and severity in Saudi Arabia. Transfusion 2023;63:S3–9. https://doi.org/10.1111/trf.17202.Suche in Google Scholar PubMed

17. Koç, S, Batur, LK. Association between ABO blood types and the prognosis and mortality rates in patients with severe COVID-19 admitted in the intensive care unit of a tertiary-level hospital in Turkey. Curr Med Res Opin 2022;38:1515–20. https://doi.org/10.1080/03007995.2022.2101806.Suche in Google Scholar PubMed

18. Zhang, Y, Garner, R, Salehi, S, La Rocca, M, Duncan, D. Association between ABO blood types and coronavirus disease 2019 (COVID-19), genetic associations, and underlying molecular mechanisms: a literature review of 23 studies. Ann Hematol 2021;100:1123–32. https://doi.org/10.1007/s00277-021-04489-w.Suche in Google Scholar PubMed PubMed Central

19. Anderson, JL, May, HT, Knight, S, Bair, TL, Muhlestein, JB, Knowlton, KU, et al.. Association of sociodemographic factors and blood group type with risk of COVID-19 in a US population. JAMA Netw Open. 2021;1;4:e217429. https://doi.org/10.1001/jamanetworkopen.2021.7429.Suche in Google Scholar PubMed PubMed Central

20. Suman, S. Susceptibility of blood group ABO and Rh for COVID-19. Int J Res Med Sci 2020;8:4405. https://doi.org/10.18203/2320-6012.ijrms20205314.Suche in Google Scholar

21. Zietz, M, Zucker, J, Tatonetti, NP. Associations between blood type and COVID-19 infection, intubation, and death. Nat Commun. 2020;13;11:5761. https://doi.org/10.1038/s41467-020-19623-x.Suche in Google Scholar PubMed PubMed Central

22. Yaylacı, S, Dheir, H, İşsever, K, Genc, AB, Şenocak, D, Kocayigit, H, et al.. The effect of abo and rh blood group antigens on admission to intensive care unit and mortality in patients with COVID-19 infection. Rev Assoc Med Bras 2020;21:86–90. https://doi.org/10.1590/1806-9282.66.s2.86.Suche in Google Scholar

23. Zietz, M, Zucker, J, Tatonetti, N. Testing the association between blood type and COVID-19 infection, intubation, and death. Nat Commun. 2020;13;11:5761. https://doi.org/10.1038/s41467-020-19623-x.Suche in Google Scholar PubMed PubMed Central

24. Dal, MS, Ata, N, Altuntaş, F, Başcı, S, Yiğenoğlu, TN, Korkmaz, S, et al.. COVID-19 clinical course and blood groups: turkish population-based study. Turk J Med Sci. 2021;30;51:1659–64. https://doi.org/10.3906/sag-2101-321.Suche in Google Scholar PubMed

25. Öncü, MR, Aktaş, R, Gizli, G, Bilvanisi, S, Yıldız, H, Baran, AI. Use of ABO blood groups and co-morbidities as predictors of mortality in COVID-19 patients. Eur Rev Med Pharmacol Sci 2022;26:4449–55. https://doi.org/10.26355/eurrev_202206_29084.Suche in Google Scholar PubMed

26. Gamboa-Aguilar, J, Zamorano-Montaño, ÁC, Enriquez-Osorio, A, Torres-Cubillas, W, López-Arroyo, JL, Chapol, JAM, et al.. Abo blood group, atherothrombotic comorbidities, and COVID-19: a case-control study of their association in the Mexican population. Arch Med Res 2022;53:100–8. https://doi.org/10.1016/j.arcmed.2021.09.005.Suche in Google Scholar PubMed PubMed Central

27. Guan, W, Ni, Z, Hu, Y, Liang, W, Ou, C, He, J, et al.. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. 2020;30;382:1708–20. https://doi.org/10.1056/nejmoa2002032.Suche in Google Scholar PubMed PubMed Central

28. Zhao, Q, Meng, M, Kumar, R, Wu, Y, Huang, J, Lian, N, et al.. The impact of COPD and smoking history on the severity of COVID‐19: a systemic review and meta‐analysis. J Med Virol 2020;92:1915–21. https://doi.org/10.1002/jmv.25889.Suche in Google Scholar PubMed PubMed Central

29. Yang, X, Yu, Y, Xu, J, Shu, H, Xia, J, Liu, H, et al.. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med 2020;8:475–81. https://doi.org/10.1016/s2213-2600(20)30079-5.Suche in Google Scholar

30. Zhou, F, Yu, T, Du, R, Fan, G, Liu, Y, Liu, Z, et al.. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020;28;395:1054–62. https://doi.org/10.1016/s0140-6736(20)30566-3.Suche in Google Scholar PubMed PubMed Central

Received: 2023-03-26
Accepted: 2023-07-10
Published Online: 2023-09-12

© 2023 the author(s), published by De Gruyter, Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.

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https://doi.org/10.1515/tjb-2023-0063
Schlagwörter für diesen Artikel
ABO blood type; mortality; rhesus factor; Sars-CoV-2
Creative Commons
BY 4.0

Artikel in diesem Heft

  1. Frontmatter
  2. Review
  3. Exploring nanotechnology-based approaches using miRNAs to treat neurodegenerative disorders
  4. Research Articles
  5. Rhesus factor is a stronger predictor for the risk of Sars-CoV-2 and mortality than ABO blood types
  6. Clinical laboratory testing in the emergency department: a six-year analysis
  7. New data for endemic Phlomis brevibracteata Turrill from North Cyprus: biological activities and chemical composition
  8. Inhibitory effect of organic acids on human neutrophil myeloperoxidase’s peroxidation, chlorination, and nitration activities
  9. Prevalence and association of sIgA in saliva and Pseudomonas aeruginosa infection in TB patients: a cross-sectional study
  10. Within- and between-subject biological variation of hemostasis parameters in a study of 26 healthy individuals
  11. Nasal fluid sample as a reliable matrix for determination of cytokine levels in childhood asthma
  12. Evaluation of the monocyte-to-lymphocyte ratio (MLR) and C-reactive protein (CRP) as diagnostic biomarkers in different lung diseases, especially for SCLC
  13. The association between plasma concentration of pigment epithelium-derived factor and diabetic retinopathy
  14. Can preoperative neopterin levels predict acute kidney injury in patients undergoing on-pump cardiac surgery?
  15. Exosomal prognostic biomarkers predict metastatic progression and survival in breast cancer patients
  16. miR-145-5p suppresses cell proliferation by targeting IGF1R and NRAS genes in multiple myeloma cells
  17. miR-564 and miR-718 expressions are downregulated in colorectal cancer tissues
  18. Ischemic cerebrovascular disease caused by genetic mutation and patent foramen ovale
  19. Comprehensive geriatric assessment and drug burden in elderly chronic kidney disease patients
  20. Exploring the enzyme inhibitory properties of Antarctic algal extracts
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