The relationship between ABO blood group and cardiovascular disease: results from the Cardiorisk program

BLOOD GROUP IS A LONG-TERM CARDIOVASCULAR RISK FACTOR AFTER CAROTID ENDARTERECTOMY

BACKGROUND

ABO blood group system has been clinically related to an increased incidence of cardiovascular diseases. Preliminary data relating Rhesus (Rh) factor and these outcomes also have been published. Our aim was to analyse the impact of blood group on the short and long-term outcomes after carotid endarterectomy (CEA).

MATERIALS AND METHODS

From 2012 to 2019, patients from a referral centre who underwent CEA for atherosclerotic carotid stenosis were prospectively followed. Our primary outcomes were long-term major adverse cardiovascular events (MACE) and all-cause mortality. Secondary outcomes were perioperative complications and myocardial injury after non-cardiac-surgery (MINS). Median follow-up was 50 months (interquartile range 21-69). Time-to-event analysis was used to determine the effect of ABO and Rh groups in long-term outcomes.

RESULTS

184 patients were included, with a mean age of 70.1 ± 9.1 years. Eighteen (25.7%) patients with O type and 48 (42.1%) patients with non-O type presented coronary artery disease (odds ratio [OR]: 2.313 5-95% Confidence Interval [CI] 1.245-4.297, P = 0.008). Patients Rh+ presented significantly more congestive heart failure, 23 (14,7%), P= 0.03. The incidence of MACE in the long-term was higher in non-O patients (adjusted Hazard Ratio: 2.034; CI: 1.032-4.010, P= 0.040). Rh- patients, presented a higher incidence of perioperative MINS. However, there was no statistically significant association with long-term risk of MACE.

CONCLUSION

The incidence of MACE in long-term analysis was higher in non-O blood type and 30-day MINS was significantly more common amongst Rh- patients. The benefit from a more complete preoperative cardiac study in these patients should be performed.

Genetic prediction of 33 blood group phenotypes using an existing genotype dataset

BACKGROUND

Accurate blood type data are essential for blood bank management, but due to costs, few of 43 blood group systems are routinely determined in Danish blood banks. However, a more comprehensive dataset of blood types is useful in scenarios such as rare blood type allocation. We aimed to investigate the viability and accuracy of predicting blood types by leveraging an existing dataset of imputed genotypes for two cohorts of approximately 90,000 each (Danish Blood Donor Study and Copenhagen Biobank) and present a more comprehensive overview of blood types for our Danish donor cohort.

STUDY DESIGN AND METHODS

Blood types were predicted from genome array data using known variant determinants. Prediction accuracy was confirmed by comparing with preexisting serological blood types. The Vel blood group was used to test the viability of using genetic prediction to narrow down the list of candidate donors with rare blood types.

RESULTS

Predicted phenotypes showed a high balanced accuracy >99.5% in most cases: A, B, C/c, Coa /Cob , Doa /Dob , E/e, Jka /Jkb , Kna /Knb , Kpa /Kpb , M/N, S/s, Sda , Se, and Yta /Ytb , while some performed slightly worse: Fya /Fyb , K/k, Lua /Lub , and Vel ~99%-98% and CW and P1 ~96%. Genetic prediction identified 70 potential Vel negatives in our cohort, 64 of whom were confirmed correct using polymerase chain reaction (negative predictive value: 91.5%).

DISCUSSION

High genetic prediction accuracy in most blood groups demonstrated the viability of generating blood types using preexisting genotype data at no cost and successfully narrowed the pool of potential individuals with the rare Vel-negative phenotype from 180,000 to 70.

Blood group and ischemic stroke, myocardial infarction, and peripheral vascular disease: A meta-analysis of over 145,000 cases and 2,000,000 controls

OBJECTIVE

Cardiovascular illnesses have been associated to ABO blood types, specifically through an effect on von Willebrand factor and factor FVIII levels. We conducted a meta-analysis to comprehensively explore the relationship between blood groups and ischemic stroke, myocardial infarction, and peripheral vascular disease.

MATERIALS AND METHODS

A comprehensive meta-analysis was undertaken to investigate blood groups and ischemic stroke (IS), myocardial infarction (MI) and peripheral vascular disease (PVD). Odds ratios (OR) were used to assess the relationship between blood groups and disease. RevMan v5,4 was used to statistically analyse the results. Risk of bias was assessed using the Newcastle-Ottawa scale.

RESULTS

A total of 72 studies (18 ischemic stroke, 37 myocardial infarction, 17 peripheral vascular disease) met our search criteria, totalling 145,499 cases and 2,113,736 controls. Mean age ranged between 18 and 90 years. Compared to blood group-O, non-O blood group had an increased association with IS (OR=1.13, 95%Cl: 1.07-1.21, P < 0.001), MI (OR=1.17, 95%Cl: 1.11-1.24, P < 0.001) and PVD (OR=1.15, 95%Cl: 1.04-1.28, P=0.005). Compared to blood group-O, blood group A had a stronger statistically significant association to IS (OR=1.19, P=0.001), MI (OR=1.22, P < 0.001) and PVD (OR=1.15, P=0.03). Blood group-B has the lowest risk associated with MI (OR=1.09, P=0.01). In addition, blood groups AB had a stronger statistically significant association to IS (OR=1.24, P=0.01), and MI (OR=1.20, P < 0.001) compared with the other blood groups.

CONCLUSIONS

Compared to blood group-O, groups A and AB are strongly associated to ischemic stroke, myocardial infarction, and peripheral vascular disease.

Deep Learning Algorithms for Estimation of Demographic and Anthropometric Features from Electrocardiograms

The electrocardiogram (ECG) has been known to be affected by demographic and anthropometric factors. This study aimed to develop deep learning models to predict the subject's age, sex, ABO blood type, and body mass index (BMI) based on ECGs. This retrospective study included individuals aged 18 years or older who visited a tertiary referral center with ECGs acquired from October 2010 to February 2020. Using convolutional neural networks (CNNs) with three convolutional layers, five kernel sizes, and two pooling sizes, we developed both classification and regression models. We verified a classification model to be applicable for age (<40 years vs. ≥40 years), sex (male vs. female), BMI (<25 kg/m² vs. ≥25 kg/m²), and ABO blood type. A regression model was also developed and validated for age and BMI estimation. A total of 124,415 ECGs (1 ECG per subject) were included. The dataset was constructed by dividing the entire set of ECGs at a ratio of 4:3:3. In the classification task, the area under the receiver operating characteristic (AUROC), which represents a quantitative indicator of the judgment threshold, was used as the primary outcome. The mean absolute error (MAE), which represents the difference between the observed and estimated values, was used in the regression task. For age estimation, the CNN achieved an AUROC of 0.923 with an accuracy of 82.97%, and a MAE of 8.410. For sex estimation, the AUROC was 0.947 with an accuracy of 86.82%. For BMI estimation, the AUROC was 0.765 with an accuracy of 69.89%, and a MAE of 2.332. For ABO blood type estimation, the CNN showed an inferior performance, with a top-1 accuracy of 31.98%. For the ABO blood type estimation, the CNN showed an inferior performance, with a top-1 accuracy of 31.98% (95% CI, 31.98-31.98%). Our model could be adapted to estimate individuals' demographic and anthropometric features from their ECGs; this would enable the development of physiologic biomarkers that can better reflect their health status than chronological age.

Questionnaire-based exposome-wide association studies (ExWAS) reveal expected and novel risk factors associated with cardiovascular outcomes in the Personalized Environment and Genes Study

While multiple factors are associated with cardiovascular disease (CVD), many environmental exposures that may contribute to CVD have not been examined. To understand environmental effects on cardiovascular health, we performed an exposome-wide association study (ExWAS), a hypothesis-free approach, using survey data on endogenous and exogenous exposures at home and work and data from health and medical histories from the North Carolina-based Personalized Environment and Genes Study (PEGS) (n = 5015). We performed ExWAS analyses separately on six cardiovascular outcomes (cardiac arrhythmia, congestive heart failure, coronary artery disease, heart attack, stroke, and a combined atherogenic-related outcome comprising angina, angioplasty, atherosclerosis, coronary artery disease, heart attack, and stroke) using logistic regression and a false discovery rate of 5%. For each CVD outcome, we tested 502 single exposures and built multi-exposure models using the deletion-substitution-addition (DSA) algorithm. To evaluate complex nonlinear relationships, we employed the knockoff boosted tree (KOBT) algorithm. We adjusted all analyses for age, sex, race, BMI, and annual household income. ExWAS analyses revealed novel associations that include blood type A (Rh-) with heart attack (OR[95%CI] = 8.2[2.2:29.7]); paint exposures with stroke (paint related chemicals: 6.1[2.2:16.0], acrylic paint: 8.1[2.6:22.9], primer: 6.7[2.2:18.6]); biohazardous materials exposure with arrhythmia (1.8[1.5:2.3]); and higher paternal education level with reduced risk of multiple CVD outcomes (stroke, heart attack, coronary artery disease, and combined atherogenic outcome). In multi-exposure models, trouble sleeping and smoking remained important risk factors. KOBT identified significant nonlinear effects of sleep disorder, regular intake of grapefruit, and a family history of blood clotting problems for multiple CVD outcomes (combined atherogenic outcome, congestive heart failure, and coronary artery disease). In conclusion, using statistics and machine learning, these findings identify novel potential risk factors for CVD, enable hypothesis generation, provide insights into the complex relationships between risk factors and CVD, and highlight the importance of considering multiple exposures when examining CVD outcomes.

Effect of Different Blood Groups on Long-Term Outcomes of Surgical Revascularisation

BACKGROUND

ABO blood groups are considered to be associated with cardiovascular disease. Nonetheless, the definite effect of ABO blood groups on the clinical outcome of coronary artery bypass graft surgery (CABG) is still undetermined. We evaluated whether ABO blood groups can predict long-term major adverse cardiocerebrovascular events (MACCE) in CABG patients.

METHOD

In this retrospective cohort study, we retrieved the clinical files of eligible patients treated with isolated CABG in our hospital between March 2007 and March 2016. We divided the patients into four ABO subgroups. The primary study endpoints were the occurrence of all-cause mortality and MACCE during long-term follow-ups. We used Cox regression survival analysis to define the association of ABO blood groups with the occurrence of MACCE.

RESULTS

Of 17,892 patients who underwent isolated CABG, 17,713 (mean age, 61.19±9.47 years, 74.6% male) were successfully followed, and their data used in the final analysis. Our multivariable analysis demonstrated that patients with different blood groups had similar 5-year mortality and 5-year MACCE.

CONCLUSIONS

Our findings suggest that in patients who underwent CABG, ABO blood groups were not associated with long-term MACCE.

The association between ABO blood groups and TASC II classification in patients with peripheral artery disease

OBJECTIVE

The aim of this study was to investigate the association between blood groups and severity of peripheral artery disease (PAD) using TASC II classification.

METHODS

The patients who were diagnosed with PAD were retrospectively analyzed. The patients with 50% or more stenosis in the aorto-iliac or femoro-popliteal region detected by conventional or CT angiography were included in the study. These patients were divided into TASC II A, B, C, and D groups considering the severity of PAD. All patients' blood groups were recorded and compared between TASC II groups.

RESULTS

While 38% of the study population was O blood group, 61% were non-O group. On the other hand, 90% of the entire study population were RH positive and 10% were RH negative. Non-O blood ratio was found to be significantly higher in patients with higher TASC II groups. (TASC IIA 51.6% vs. TASC IIB 57.9% vs. TASC IIC 61.3% vs. TASC IID 76.6%, p< .001) However, the frequencies of Rh types were similar in all groups. Multiple logistic regression analysis was applied for determining the predictors of severity and complexity of PAD (TASC II C and TASC II D lesions).

CONCLUSIONS

Our study results revealed a clear association between ABO blood groups and severity of peripheral arterial disease. Non-O blood group was found to be the independent predictor of severe and complex PAD.

Associations between smoking and blood-group, and the risk of dyslipidaemia amongst French women

Dyslipidaemia is a major risk factor for cardio-vascular disease, as it promotes atherosclerosis. While cross-sectional studies have identified higher serum cholesterol amongst individuals with the A blood group, there is less evidence from prospective studies whether this translates into a higher risk of dyslipidaemia that requires treatment, nor if this genetic factor interacts with smoking status. This study aimed to prospectively determine potential associations between smoking, ABO blood groups, and risk of incident dyslipidaemia requiring treatment, and to assess associations over strata of blood ABO group. We assessed associations between blood ABO group, smoking and dyslipidaemia in 74,206 women participating in the E3N cohort. We included women who did not have cardiovascular disease at baseline. Logistic regression was used to determine associations between ABO group, smoking and prevalent dyslipidaemia at baseline. Cox proportional hazard models were then used to determine if blood ABO group and smoking were associated with the risk of incident dyslipidaemia, amongst women free of dyslipidaemia at baseline. At baseline 28,281 women with prevalent dyslipidaemia were identified. Compared to the O-blood group, the non-O blood group was associated higher odds of with prevalent dyslipidaemia (OR_non-O = 1.09 [1.06: 1.13]). Amongst the women free of dyslipidaemia at baseline, 6041 incident cases of treated dyslipidaemia were identified during 454,951 person-years of follow-up. The non-O blood groups were associated with an increased risk of dyslipidaemia when compared to the O-group (HR_non-O = 1.16 [1.11: 1.22]), specifically the A blood-group (HR_A = 1.18 [1.12: 1.25]). Current smokers were associated with an increased risk of incident dyslipidaemia (HR _smokers = 1.27 [1.16: 1.37]), compared to never-smokers. No evidence for effect modification between smoking and ABO blood group was observed (p-effect modification = 0.45), although the highest risk was observed among AB blood group women who smoked (HR = 1.76 [1.22: 2.55]). In conclusion, the non-O blood groups, specifically the A group were associated with an increased risk of dyslipidaemia. Current smokers were associated with a 30% increased risk of dyslipidaemia. These results could aid in personalised approaches to the prevention of cardiovascular risk-factors.

An Unknown Risk Factor for Sepsis in Very Low Birth Weight Preterms: ABO Blood Groups (BGaPS Study)

OBJECTIVE

There is insufficient study of the association of blood groups with neonatal diseases. The aim of this study was to evaluate the blood groups associated with sepsis and blood groups in preterm infants.

STUDY DESIGN

This retrospective study was conducted between January 1, 2010 and November 31, 2018 in the neonatal intensive care unit (NICU). This study was done in single-center tertiary NICU. Infants born at gestational age (GA) <32 weeks with birth weight (BW) <1,500 g were included in the study.

RESULTS

A total of 2,548 infants were included. The culture-proven sepsis ratio (30.2%) was the lowest in the O blood group and the highest in the AB blood group (37.5%) (p = 0.045). Meningitis ratio (6.5%) was significantly higher, and hospital stay (64.1 ± 33.9 days) was significantly longer in B blood group (respectively, p = 0.005, p < 0.001). In the AB blood group, GA (27.68 ± 1.12 weeks) was the lowest and early onset sepsis (EOS) (40.1%) and mortality (28.9%) ratio were found to be statistically higher (p < 0.001 for all groups). The AB group was significantly related to higher frequency of EOS (odds ratio [OR] = 2.93, 95% confidence interval [CI] = 1.68-5.12, p = 0.000), in addition to mortality (OR = 1.1, 95% CI = 0.55-2.19, p = 0.001). The O group was found to be associated with lower risk of late onset sepsis (LOS) (OR = 1.67, 95% CI = 1.06-3.058, p = 0.003) according to the model with corrected risk factor including GA, BW, and time of hospitalization.

CONCLUSION

Our study was the first study showing a relationship between certain blood groups and EOS/LOS in premature infants as well as meningitis.

Association between the dynamics of the COVID-19 epidemic and ABO blood type distribution

The coronavirus disease 2019 (COVID-19) pandemic is currently the most critical challenge in public health. An understanding of the factors that affect severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection will help fight the COVID-19 pandemic. This study sought to investigate the association between SARS-CoV-2 infection and blood type distribution. The big data provided by the World Health Organization (WHO) and Johns Hopkins University were used to assess the dynamics of the COVID-19 epidemic. The infection data in the early phase of the pandemic from six countries in each of six geographic zones divided according to the WHO were used, representing approximately 5.4 billion people around the globe. We calculated the infection growth factor, doubling times of infection and death cases, reproductive number and infection and death cases in relation to the blood type distribution. The growth factor of infection and death cases significantly and positively correlated with the proportion of the population with blood type A and negatively correlated with the proportion of the population with blood type B. Compared with the lower blood type A population (<30%), the higher blood type A population (⩾30%) showed more infection and death cases, higher growth factors and shorter case doubling times for infections and deaths and thus higher epidemic dynamics. Thus, an association exists between SARS-CoV-2 and the ABO blood group distribution, which might be useful for fighting the COVID-19 pandemic.

Evaluation of ABO blood group in subjects with CVD risk factors in a population sample from northeastern Iran

BACKGROUND AND AIMS

The ABO blood group system is a genetic polymorphism which can affect the clearance of von Willebrand factor. We aimed to assess the levels of newer biomarkers of cardiovascular disease (CVD) risk; pro-oxidant-antioxidant balance (PAB), high sensitivity C-reactive protein (hs-CRP) and anti-heat-shock protein27 (anti-Hsp27) antibody titers in subjects with various blood groups (A, B, AB and O) and with or without traditional CVD risk factors.

METHODS

The cross-sectional study comprised 6910 subjects. Antigen-antibody agglutination was evaluated by the slide test method for identification of ABO blood groups.

RESULTS

Among three markers, only Serum anti-Hsp27 titers significantly differed between the four blood groups and showed the highest and lowest values in AB and O blood groups (0.26 ± 0.22 and 0.23 ± 0.18 OD, respectively; P < 0.05). Serum anti-Hsp27 was higher in individuals with an AB blood group with metabolic syndrome (MetS), dyslipidemia, hypertension (HTN) and obesity and it was lower in subjects with O blood group; though, two other biomarkers, serum PAB and hs-CRP, were not significantly different between the ABO blood groups. However, they were not different among blood groups in participants with or without diabetes mellitus (DM) (P > 0.05).

CONCLUSION

Individuals with an AB blood group and high levels of anti-Hsp27 antibody titers may be predisposed to CVDs that can be mediated through the traditional CVD risk factors among middle-aged subjects from northeastern Iran. The fact that differences in anti Hsp27 are only found in the subgroup with other risk factors suggest that the difference between ABO blood groups is a consequence rather than a cause.

Relationship between ABO blood groups and cardiovascular disease in type 1 diabetes according to diabetic nephropathy status

Background

ABO blood groups have previously been associated with cardiovascular disease (CVD) in the general population. This study aimed to investigate the potential relationship between ABO blood groups and CVD in individuals with type 1 diabetes according to diabetic nephropathy (DN) status.

Methods

Adults with type 1 diabetes (4531 individuals) from the FinnDiane Study were evaluated. DN was determined by two out of three measurements of urinary albumin excretion rate. Albuminuria was defined as an excretion rate above 20 µg/min. CVD events were identified by linking the data with the Finnish Care Register for Health Care and the Finnish Cause of Death Register. Follow-up ranged from the baseline visit until a CVD event, death or the end of 2017. The impact of ABO blood groups on CVD risk was estimated by multivariable Cox-regression analyses adjusted for traditional risk factors.

Results

At baseline, the median age was 38.5 (IQR 29.2–47.9) years, 47.5% were female and median duration of diabetes was 20.9 (11.4–30.7) years. There were 893 incident ischemic heart disease (IHD) events, 301 ischemic strokes (IS), and 415 peripheral artery disease (PAD) events during a median follow up of 16.5 (IQR 12.8–18.6) years. The A blood group showed the highest risk of IHD versus the O blood group, when microalbuminuria was present. Comparing the population with microalbuminuria with those with normoalbuminuria, only the A blood group elevated the risk of IHD. This increased risk was neither explained by the FUT2 secretor phenotype nor by the A-genotype distribution. The risk of IS or PAD was no different among the ABO blood groups regardless of diabetic nephropathy stage.

Conclusion

The A blood group is a risk factor for IHD in individuals with type 1 diabetes and microalbuminuria.