Abstract
Nicotinamide adenine dinucleotide (NAD+) level is the protective factor of cardiovascular diseases (CVDs). In addition, anaemia is a risk factor of adverse cardiovascular outcomes in women. However, there are limited data about the association between NAD+ and anaemia. The aim of this study was to evaluate association of NAD+ with anaemia among women. A total of 727 females from Jidong community were included in the current analysis. NAD+ levels were tested by the cycling assay and HPLC assay using whole blood samples. Anaemia was determined by haemoglobin (Hb) concentration, and the subtypes of anaemia were further defined according to mean corpuscular volume (MCV) in blood. Multivariable logistic analysis was used to analyse the association between NAD+ levels and anaemia or its subtypes. The mean age of recruited subjects was 42.7 years. The proportion of anaemia by NAD+ levels quartiles were 19.7% (35/178), 4.8% (9/189), 3.4% (6/178) and 2.7% (5/182). Haematological parameters including haemoglobin (Hb), mean corpuscular volume (MCV), mean corpuscular haemoglobin (MCH), mean corpuscular haemoglobin concentration (MCHC) and red blood count (RBC) increased over NAD+ quartiles. Red cell volume distribution width (RDW) decreased over NAD+ quartiles. Compared with the lowest quartile of NAD+ levels (<27.6μM), the adjusted odds ratios with 95% confidence intervals of the top quartile were 0.15 (0.06–0.41) for anaemia, 0.05 (0.01–0.36) for microcytic anaemia and 0.37 (0.10–1.36) for normocytic anaemia respectively. Higher NAD+ levels were significantly associated with lower prevalence of anaemia among women, especially microcytic anaemia and normocytic anaemia. Haematological parameters might serve as a predictor of the blood NAD+ levels.
Keywords: cardiovascular diseases, hemoglobin, Nicotinamide adenine dinucleotide
1. INTRODUCTION
Nicotinamide adenine dinucleotide (NAD+) is a pivotal metabolite with a wide range of roles in cell survival, mitochondrial homeostasis, cellular bioenergetics, adaptive stress responses and genomic stability. 1 NAD+ is involved in over 500 enzymatic reactions in regulating almost all major biological processes. 2 Meanwhile, NAD+ is also a co‐substrate of regulatory enzymes, including sirtuins (SIRTs), poly (ADP‐ribose) polymerases (PARPs) and cyclic ADPR (cADPR) synthetases. 3 The association of NAD+ levels with cardiovascular diseases (CVDs) including endothelial, atherosclerosis and heart failure has been reported by a few studies. 4 , 5 , 6 , 7 Loss of NAD+ contents are implicated in the pathogenesis of multiple types of CVDs, and boosting NAD+ levels seems to be a strongly protective role of CVDs. 8 Moreover, NAD precursors have been suggested to delay the process of vascular aging and increase the span of cardiovascular health. 9
Anaemia is a worldwide health problem in the world, 10 , 11 , 12 , 13 particularly so in developing countries with children and women as the most affected population groups. 14 Approximately 1.9 billion individuals worldwide suffer from anaemia, which is nearly one‐quarter of the global population in 2013. 15 The World Health Organization (WHO) estimated that 32.4 million pregnant women and 496.3 million non‐pregnant women were anaemic across the world in 2011. 16 In addition, severe anaemia in pregnant and postnatal women strongly and independently contributes to maternal death. 17 Managing anaemia is one of the global health goals. 13 In China, whose population accounts for more than 18% of the world, the prevalence of anaemia is about 15.0% according to the fifth Chinese National Nutrition and Health Survey (CNNHS 2010–2012) and the anaemia prevalence for Chinese rural reproductive age women was 24.8% in 2012. 18 , 19 Anaemia was defined by WHO as a lower haemoglobin (Hb) content than normal in whole blood. 20 In addition, lower Hb is significantly and independently associated with adverse cardiovascular outcomes in women. 21 Anaemia is significantly correlated with severe complications of CVDs including stroke, arrhythmias and thromboembolics in the general population. It is also an independent predictor of cardiovascular mortalities. 22 , 23 , 24 NAD+ levels and anaemia are the protective factor and risk factor of CVDs respectively. However, the research on the associations between NAD+ contents in whole blood and subtypes of anaemia is still in scarcity. We assumed that NAD+ levels would be negatively correlated with anaemia. In our current study, we sought to understand the relationship of NAD+ levels with the anaemia and explore the associations of different types of anaemia with NAD+ levels.
2. METHOD
2.1. Study design and population
The population in this community‐based study was from Jidong community in Tangshan City, Hebei Province, China. From 2019 to 2020, a total of 1723 participants were originally recruited into the study. We excluded 802 males and 191 participants with incomplete information. Finally, 727 females were included in the final analysis (Figure 1). All participants gave written informed consent, and the study was conducted according to the guidelines of the Helsinki Declaration.
FIGURE 1.
Flow chart of this study
2.2. Data collection
In this study, basic information of subjects was obtained from standardized questionnaires, laboratory tests and clinical examinations. 25 Face‐to‐face interviews were performed by well‐trained examiners. Information on demographic characteristics including age, income and education level was collected by standardized questionnaires. The average monthly income was divided into ‘≤¥3000’, or ‘>¥3000’. Education levels were categorized as ‘Middle school or below’ or ‘collegeor above’. Body mass index (BMI) was categorized as ‘<18.5 kg/m2’, ‘18.5–23.9 kg/m2’, ‘24.0–27.9 kg/m2’ and ‘>28.0 kg/m2’. Previous history of hyperlipidaemia, hypertension and diabetes mellitus was recorded directly by self‐reports of participants.
2.3. Measurement of NAD+ levels
Blood samples were collected from the large antecubital veins after overnight fasting. All blood samples were stored in vacuum tubes containing EDTA (ethylene diamine tetraacetic acid), and NAD+ levels were determined by the cycling assay and LC‐MS/MS analysis in the laboratories. 26 , 27 , 28 , 29 (see Supplementary Material 1 and Figure S1).
NAD+ levels were stratified into 4 categories: Q1 (<27.6), Q2 (27.6–31.0), Q3 (31.0–34.5) and Q4 (≥34.5), which were based on the quartiles of NAD+ levels. In addition, the participants in Q2, Q3 and Q4 were grouped into Q2‐4, whose NAD+ level was in 2th‐4th NAD+ quartile (25th percentile‐100th percentile).
2.4. Determination of haematology parameters
Haematology parameters including haemoglobin (Hb), mean corpuscular volume (MCV), mean corpuscular haemoglobin (MCH), mean corpuscular haemoglobin concentration (MCHC), red cell distribution width (RDW) and red blood count (RBC) were measured by autoanalyzer (Hitachi 747; Hitachi,) in the central laboratory of the Staff Hospital of the Jidong Oilfield.
2.5. Diagnosis of anaemia
According to World Health Organization (WHO), anaemia was defined as Hb concentration lower than 120 mg/dl for women. 20 According to MCV, anaemia was further classified into three types: microcytic anaemia if MCV was lower than 80 fl, normocytic anaemia if MCV was from 80 to 100 fl, and macrocytic anaemia if MCV was higher than 100 fl. 30
2.6. Statistical analysis
The normality distributions of continuous variables were evaluated by the Kolmogorov–Smirnov test. Continuous variables are expressed as the mean ± standard deviation (SD) and were compared using one‐way ANOVA or t‐test, as appropriate. Categorical variables are presented as proportions and frequencies and were compared by chi‐squared tests. Multivariable logistic regression models were used to assess the association between NAD+ quartiles and anaemia or its different types. We adjusted 4 covariates which were thought to be potential confounder of the risk factors for anaemia: age, BMI, UA and RBC. All statistical tests were 2‐sided, and p values of less than 0.05 were considered to be significant. Statistical analyses were conducted with SAS software, version 9.4 (SAS Institute Inc.,).
3. RESULTS
3.1. Baseline Characteristics in eligible participants
Baseline characteristics of participants according to NAD+ quartiles are summarized in Table 1. Of 727 females finally included, the mean age was 42.7 years and there were only 6 smokers and 5 drinkers. BMI distributions were different among the quartiles of NAD+. The levels of UA increased along with the levels of NAD+. Analysis of haematological parameters in different NAD+ quartiles is also presented in Table 1. The levels of Hb, MCV, MCH, MCHC and RBC increased along with the quartiles of NAD+, while the levels of RDW decreased along with the quartiles of NAD+. Age, income, education level, history of smoke, history of drink, salt intake, eGFR, history of hyperlipidaemia, hypertension and diabetes were not significantly different among the quartiles. Baseline characteristics of male and females has been provided. (see Table S2).
TABLE 1.
Baseline characteristics of participants according to NAD+ quartiles
| Characteristics | Overall (n = 727) | Q1 (<27.6) (n = 178) | Q2 (27.6–31.0) (n = 189) | Q3 (31.0–34.5) (n = 178) | Q4 (≥34.5) (n = 182) | p value |
|---|---|---|---|---|---|---|
| Age (years) | 42.7 ± 11.3 | 41.4 ± 9.3 | 43.5 ± 12.4 | 42.9 ± 11.5 | 42.9 ± 11.7 | 0.33 |
| Income,¥/month (n,%) | 0.33 | |||||
| ≤¥3000 | 52 (7.8) | 8 (5.0) | 13 (7.7) | 17 (10.6) | 14 (8.1) | |
| >¥3000 | 613 (92.2) | 152 (95.0) | 157 (92.4) | 177 (89.4) | 160 (92.0) | |
| Education level (n,%) | 0.57 | |||||
| Middle school or below | 254 (34.9) | 63 (35.4) | 73 (38.6) | 60 (33.7) | 58 (31.9) | |
| College or above | 473 (65.1) | 115 (64.6) | 116 (61.4) | 118 (66.3) | 124 (68.1) | |
| Body mass index (kg/m2) | <0.05 | |||||
| <18.5 | 99 (13.6) | 23 (12.9) | 25 (13.2) | 29 (16.3) | 22 (12.1) | |
| 18.5–23.9 | 395 (54.3) | 97 (54.5) | 108 (57.1) | 98 (55.1) | 92 (50.6) | |
| 24.0–27.9 | 178 (24.5) | 53 (29.8) | 43 (22.8) | 31 (17.4) | 51 (28.0) | |
| ≥28.0 | 55 (7.6) | 5 (2.8) | 13 (6.9) | 20 (11.2) | 17 (9.3) | |
| Smoking (n,%) | 6 (0.9) | 0 (0.0) | 3 (1.8) | 2 (1.2) | 1 (0.6) | 0.43 |
| Drinking (n,%) | 5 (0.8) | 2 (1.3) | 0 (0.0) | 2 (1.2) | 1 (0.6) | 0.46 |
| Salt intake (n,%) | 0.49 | |||||
| Low | 218 (32.8) | 55 (34.4) | 53 (31.2) | 49 (30.4) | 61 (35.1) | |
| Medium | 370 (55.6) | 81 (50.6) | 101 (59.4) | 96 (59.6) | 92 (52.9) | |
| High | 77 (11.6) | 24 (15.0) | 16 (9.4) | 16 (9.9) | 21 (12.1) | |
| Hyperlipidaemia (n,%) | 256 (38.4) | 56 (35.0) | 59 (34.7) | 60 (37.0) | 81 (46.6) | 0.08 |
| Hypertesion (n,%) | 107 (16.1) | 19 (11.9) | 26 (15.3) | 26 (16.1) | 36 (20.7) | 0.18 |
| Diabetes (n,%) | 35 (5.3) | 7 (4.4) | 6 (3.5) | 8 (4.9) | 14 (8.1) | 0.26 |
| eGFR (mL/min/1.73m2) | 121.4 ± 24.3 | 121.0 ± 23.3 | 124.1 ± 24.4 | 118.7 ± 24.4 | 121.9 ± 24.7 | 0.28 |
| UA (μmol/L) | 289.9 ± 66.2 | 281.9 ± 61.4 | 283.1 ± 61.7 | 296.1 ± 68.8 | 298.6 ± 71.2 | <0.05 |
| Haematological parameters | ||||||
| Hb (g/L) | 136.0 ± 12.1 | 130.1 ± 15.6 | 135.6 ± 11.0 | 138.4 ± 9.4 | 139.8 ± 9.2 | <0.0001 |
| MCV (fL) | 91.9 ± 6.4 | 89.9 ± 8.7 | 91.6 ± 6.5 | 93.1 ± 4.7 | 93.1 ± 4.2 | <0.0001 |
| MCH (pg) | 30.9 ± 2.5 | 30.1 ± 3.4 | 30.6±2.5 | 31.4 ± 1.7 | 31.4 ± 1.5 | <0.0001 |
| MCHC (g/L) | 335.6 ± 8.8 | 334.2 ± 10.1 | 334.1 ± 8.4 | 337.0 ± 7.5 | 337.2 ± 8.4 | <0.0001 |
| RDW (%) | 12.2 ± 1.5 | 12.6 ± 2.1 | 12.2 ± 1.6 | 12.0 ± 1.1 | 12.0 ± 1.0 | <0.01 |
| RBC (10^12/L) | 4.4 ± 0.3 | 4.3 ± 0.4 | 4.4 ± 0.3 | 4.4 ± 0.3 | 4.5 ± 0.3 | <0.01 |
| PLT (10^9/L) | 229.7 ± 57.8 | 235.6 ± 61.5 | 235.6 ± 58.9 | 219.5 ± 50.1 | 227.8 ± 59.1 | <0.05 |
| WBC (10^9/L) | 6.3 ± 1.5 | 6.3 ± 1.6 | 6.3 ± 1.5 | 6.3 ± 1.5 | 6.4 ± 1.6 | 0.77 |
Abbreviations: BMI, body mass index; eGFR, estimated glomerular filtration rate; UA, uric acid; NAD+, nicotinamide adenine dinucleotide; Hb, haemoglobin; MCV, mean corpuscular volume; MCH, mean corpuscular; MCHC, mean corpuscular haemoglobin concentration; RDW, red cell volume distribution width; RBC, red blood cell; PLT, platelet count; WBC, white blood cell.
3.2. Association between NAD+ levels and anaemia
The anaemia occurred in 19.7%, 4.8%, 3.4% and 2.7% in each NAD+ quartile respectively (Figure 2). Crude and adjusted odds ratios (OR) with 95% confidence intervals (CI) of NAD+ levels for anaemia status are shown in Table 2. In general, lower NAD+ levels were associated with higher prevalence of anaemia. Compared with the first quartile of NAD+, proportion rates of anaemia in the 2th‐4th NAD+ quartile (25th percentile‐100th percentile) was also much lower. The NAD+ levels between anaemic and non‐anaemic group have been provided. (see Table S3).
FIGURE 2.
Proportions of anaemia status according to NAD+ quartiles
TABLE 2.
Association between quartiles of NAD+ levels and anaemia among women
| NAD+ Quartiles | Subjects with anaemia (n,%) | Unadjusted OR (95% CI) | Adjusted OR (95% CI) | |
|---|---|---|---|---|
| Q1 | 35 (4.8) | 1 (Reference) | 1 (Reference) |
|
| Q2 | 9 (1.2) | 0.20 (0.10–0.44) | 0.25 (0.11–0.55) | |
| Q3 | 6 (0.8) | 0.14 (0.06–0.35) | 0.17 (0.07–0.43) | |
| Q4 | 5 (0.7) | 0.12 (0.04–0.30) | 0.15 (0.06–0.41) | |
| Q2‐4 | 20 (2.8) | 0.15 (0.09–0.28) | 0.19 (0.10–0.35) | |
Covariates included age, BMI, UA and RBC.
Abbreviations: CI, confidence interval; OR, odds ratio.
3.3. Association between quartiles of NAD+ levels and types of anaemia
Rates of types of anaemia according to quartiles of NAD+ levels are presented in Table 3. The proportion of microcytic anaemia and normocytic anaemia was 4.1% and 3.5%. Both of them decreased by NAD+ quartiles. The proportion of macrocytic anaemia was just 0.1% (N = 2), so macrocytic anaemia was not further analysed in the logistic regression model due to few events. As shown in Table 4, the prevalence decreased with the higher NAD+ levels in microcytic anaemia and normocytic anaemia respectively; compared with the first quartiles of NAD+, the adjusted ORs and 95% CI of the fourth NAD+ quartile were 0.05 (0.01–0.36) for microcytic anaemia and 0.37 (0.10–1.36) for normocytic anaemia, and the adjusted ORs and 95% CI of the 2th~4th NAD+ quartile (25th percentile‐100th percentile) were 0.16 (0.07–0.36) for microcytic anaemia and 0.20 (0.07–0.56) for normocytic anaemia. The haematological parameters in each type of anaemia have been provided. (see Table S1).
TABLE 3.
Rates of types of anaemia according to quartiles of NAD+ levels among women
| NAD+ Quartiles, μM | ||||||
|---|---|---|---|---|---|---|
| Type of anaemia | Overall | Q1 (<27.6) | Q2 (27.6–31.0) | Q3 (31.0–34.5) | Q4 (≥34.5) | p value |
| microcytic anaemia | 29 (4.1) | 18 (2.6) | 7 (1.0) | 3 (0.4) | 1 (0.1) | <0.0001 |
| normocytic anaemia | 24 (3.5) | 15 (2.2) | 2 (0.3) | 3 (0.4) | 4 (0.6) | <0.001 |
TABLE 4.
Association between quartiles of NAD+ levels and types of anaemia among women
| Type of anaemia | Unadjusted OR (95% CI) | Adjusted OR (95% CI) | |
|---|---|---|---|
| Microcytic anaemia |
|
||
| Q2 VS Q1 | 0.31 (0.13–0.76) | 0.28 (0.11–0.71) | |
| Q3 VS Q1 | 0.14 (0.04–0.48) | 0.14 (0.04–0.50) | |
| Q4 VS Q1 | 0.05 (0.01–0.34) | 0.05 (0.01–0.36) | |
| Q2‐4 VS Q1 | 0.17 (0.08–0.36) | 0.16 (0.07–0.36) | |
| Normocytic anaemia | |||
| Q2 VS Q1 | 0.11 (0.02–0.47) | 0.13 (0.03–0.67) | |
| Q3 VS Q1 | 0.17 (0.05–0.59) | 0.15 (0.03–0.69) | |
| Q4 VS Q1 | 0.22 (0.07–0.66) | 0.37 (0.10–1.36) | |
| Q2‐4 VS Q1 | 0.16 (0.07–0.38) | 0.20 (0.07–0.56) | |
Covariates included age, BMI, UA and RBC.
Abbreviations: CI, confidence interval; OR, odds ratio.
4. DISCUSSION
In this community‐based study, individuals with the low NAD+ quartile were associated with high risk of anaemia among women. Anaemia subtype analysis in our study showed that this association was also evident in microcytic anaemia and normocytic anaemia among women. Besides, we observed a positive association between NAD+ levels and haematological parameters including Hb, MCV, MCH, MCHC and RBC. Our results provide evidence for the relationship between NAD+ levels and anaemia among women.
Most of the existing studies focused on the association between NAD+ contents in RBCs and sickle cell disease (SCD). Studies about the association between SCD and NAD+ contents in RBCs are controversial. Sickle RBCs had an increased NAD+ content, and this increase in NAD+ may be the reason of adverse metabolic consequences in sickle RBCs. 31 However, a study reported that the levels of NAD+ in sickle RBCs were similar to the levels in normal RBCs. 32 As reported, among patients with anaemia, 50%–80% are iron deficiency anaemia (IDA) which is highly prevalent among women throughout their lives. 33 A study in rhesus monkey found that the NAD metabolites were similar between IDA and control groups, and NAD pathway components nearly doubled after the treatment of IDA. 34 Another study in male chicks found that iron deficiency reduced the utilization of tryptophan with which de novo biosynthesis of NAD starts. 35 , 36 Haemolytic anaemia could be induced by medications along with other causes, whose late diagnosis could be fatal. 37 Nicotinamide mononucleotide adenylyltransferase 3 (Nmnat3) is considered a NAD synthesis enzyme involved in de novo and salvage pathways. Deficiency of Nmnat3 in mice can cause haemolytic anaemia. 38 In our study, the anaemia subtypes distinguished by pathogeny like IDA and haemolytic anaemia could not be judged and anaemia was classified into three subtypes by MCV. NAD+ levels were detected in whole blood instead of just in RBCs. We found that low NAD+ quartile was associated with high risk of anaemia among women. The prevalence of microcytic anaemia and normocytic anaemia decreased with increase of NAD+ level. The specific impact of NAD+ levels on anaemia warrants further research.
Elevated Hb was related to Sirtuin 1 (SIRT1) levels, which was the activation of NAD‐dependent deacetylase. 39 A study in mice found that replenishing NAD had a positive effect on the most primitive blood stem cells and protected patients from haematological failure. 40 These findings indicated that NAD+ might be a protective factor of anaemia and also provided a possible theoretical support for our findings. In our study, there were positive associations between NAD+ levels and haematological parameters including Hb, MCV, MCH, MCHC and RBC. Our result implied that, NAD+ might be a new indicator for anaemia among women, especially in microcytic anaemia and normocytic anaemia.
The study has several potential limitations. First, we were unable to determine subtype of anaemia according to the pathogeny due to the limited data. Thus, the associations of anaemia subtypes according to the pathogeny with NAD+ levels need to be further investigated in a subsequent study. Second, the cross‐sectional study made it difficult to infer the causal effect relationship between anaemia and NAD+ contents. Third, the participants were mainly from an urban city in North China; therefore, the findings might not be generalized to other ethnics and male. Finally, given the characteristics of observational study, there might be some unmeasured or residual confounding effects that could not be adjusted.
The study aim was to investigate the association between NAD+ level and the prevalence of anaemia subtypes distinguished by MCV and the correlation of NAD+ with haematological parameters among women. Due to the limited data, the association between NAD+ level and specific anaemia subtypes according to the pathogeny could not be analysis. Whether NAD+ is involved in the occurrence and development of anaemia, has core effect or just was accompanied by appearance, still need to be studied in future research.
In summary, the high NAD+ level in whole blood was associated with a low prevalence of anaemia among women, especially microcytic anaemia. Besides, haematological parameters including Hb, MCV, MCH, MCHC and RBC were positively associated with NAD+ contents. Haematological parameters might serve as a predictor for lack of NAD+ in whole blood among women.
CONFLICT OF INTEREST
The authors declare no competing interests.
AUTHOR CONTRIBUTIONS
Yong Zhou: Funding acquisition (equal); Project administration (lead). Fan Yang: Data curation (lead); Formal analysis (equal); Methodology (supporting); Writing – original draft (supporting); Writing – review & editing (supporting). Xuguang Zhang: Data curation (supporting); Formal analysis (supporting); Methodology (supporting); Project administration (supporting); Writing – review & editing (supporting). Feifei Hu: Data curation (equal); Formal analysis (equal); Methodology (supporting); Project administration (supporting); Writing – original draft (lead); Writing – review & editing (lead). Ye Yu: Data curation (equal); Writing – review & editing (equal). Lei Luo: Data curation (supporting); Formal analysis (supporting); Methodology (supporting); Project administration (supporting). Xuan Deng: Data curation (supporting); Methodology (supporting); Project administration (supporting). Yuzheng Zhao: Data curation (supporting); Methodology (supporting); Project administration (supporting). Bo Pan: Data curation (supporting); Methodology (supporting); Project administration (supporting). Jin‐ping Zheng: Data curation (supporting); Methodology (supporting); Project administration (supporting). Yugang Qiu: Data curation (supporting); Methodology (supporting); Project administration (supporting). Feng Xiao: Data curation (supporting); Funding acquisition (supporting); Methodology (supporting); Project administration (supporting). Zhenyu Ju: Data curation (equal); Formal analysis (equal); Funding acquisition (equal); Methodology (equal); Project administration (equal); Writing – review & editing (equal). Jun Guo: Methodology (supporting); Validation (supporting). Xiaomei Xie: Data curation (supporting); Investigation (supporting).
Supporting information
Supplementary Material
ACKNOWLEDGMENTS
This work is supported by the National Key R&D Program of China (2018YFC2000705 and 2021YFC2500500), National Natural Science Foundation of China (81973112, 92049302, 92049304) and Nutritional Science Research Foundation of BY‐HEALTH Co. Ltd. We thank members of the Ju group for their technical assistance for detecting NAD+ levels. We thank many volunteers in this study.
Yang F, Zhang X, Hu F, et al. Association between NAD+ levels and anaemia among women in community‐based study. J Cell Mol Med. 2022;26:2698–2705. doi: 10.1111/jcmm.17281
Fan Yang, Xuguang Zhang, Feifei Hu, and Ye Yu contributed equally to this paper.
Contributor Information
Zhenyu Ju, Email: zhenyuju@163.com.
Yong Zhou, Email: yongzhou78214@163.com.
REFERENCES
- 1. Lautrup S, Sinclair DA, Mattson MP, Fang EF. NAD(+) in brain aging and neurodegenerative disorders. Cell Metab. 2019;30:630‐655. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Biefer HRC, Elkhal A, Cesarovic N, Emmert MY. NAD+ the disregarded molecule in cardiac metabolism. Eur Heart J. 2020;41:983‐986. [DOI] [PubMed] [Google Scholar]
- 3. Zou Y, Wang A, Huang L, et al. Illuminating NAD(+) metabolism in live cells and in vivo using a genetically encoded fluorescent sensor. Dev Cell. 2020;53:240‐252. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Matasic DS, Brenner C, London B. Emerging potential benefits of modulating NAD(+) metabolism in cardiovascular disease. Am J Physiol Heart Circ Physiol. 2018;314:H839‐H852. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Song P, Zou MH. Regulation of NAD(P)H oxidases by AMPK in cardiovascular systems. Free Radic Biol Med. 2012;52:1607‐1619. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Borradaile NM, Pickering JG. NAD(+), sirtuins, and cardiovascular disease. Curr Pharm Des. 2009;15:110‐117. [DOI] [PubMed] [Google Scholar]
- 7. Alefishat E, Alexander SP, Ralevic V. Effects of NAD at purine receptors in isolated blood vessels. Purinergic Signal. 2015;11:47‐57. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Kane AE, Sinclair DA. Sirtuins and NAD(+) in the development and treatment of metabolic and cardiovascular diseases. Circ Res. 2018;123:868‐885. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Csiszar A, Tarantini S, Yabluchanskiy A, et al. Role of endothelial NAD(+) deficiency in age‐related vascular dysfunction. Am J Physiol Heart Circ Physiol. 2019;316:H1253‐H1266. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Eisele L, Dürig J, Broecker‐Preuss M, et al. Prevalence and incidence of anemia in the german heinz nixdorf recall study. Ann Hematol. 2013;92:731‐737. [DOI] [PubMed] [Google Scholar]
- 11. Mugisha JO, Baisley K, Asiki G, Seeley J, Kuper H. Prevalence, types, risk factors and clinical correlates of anaemia in older people in a rural Ugandan population. PLoS One. 2013;8:e78394. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Alsaeed AH. An analysis of hematological parameters to assess the prevalence of anemia in elderly subjects from Saudi Arabia. Genet Test Mol Biom. 2011;15:697‐700. [DOI] [PubMed] [Google Scholar]
- 13. Jalambo MO, Karim NA, Naser IA, Sharif R. Prevalence and risk factor analysis of iron deficiency and iron‐deficiency anaemia among female adolescents in the Gaza Strip, Palestine. Public Health Nutr. 2018;21:2793‐2802. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Kassebaum NJ, Jasrasaria R, Naghavi M, et al. A systematic analysis of global anemia burden from 1990 to 2010. Blood. 2014;123:615‐624. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Kassebaum NJ. The global burden of anemia. Hematol Oncol Clin North Am. 2016;30:247‐308. [DOI] [PubMed] [Google Scholar]
- 16. Elmardi KA, Adam I, Malik EM, et al. Prevalence and determinants of anaemia in women of reproductive age in Sudan: analysis of a cross‐sectional household survey. BMC Public Health. 2020;20:1125. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Daru J, Zamora J, Fernandez‐Felix BM, et al. Risk of maternal mortality in women with severe anaemia during pregnancy and post partum: a multilevel analysis. Lancet Glob Health. 2018;6:e548‐e554. [DOI] [PubMed] [Google Scholar]
- 18. Ma QY, Zhang SK, Liu J, et al. [Anemia status of Chinese rural women of reproductive age in 2012]. Zhonghua Yi Xue Za Zhi. 2018;98:2115‐2119. [DOI] [PubMed] [Google Scholar]
- 19. Hu Y, Li M, Wu J, et al. Prevalence and risk factors for anemia in non‐pregnant childbearing women from the chinese fifth national health and nutrition survey. Int J Environ Res Public Health. 2019;16(7):1290. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. McLean E, Cogswell M, Egli I, Wojdyla D, de Benoist B. Worldwide prevalence of anaemia, WHO vitamin and mineral nutrition information system, 1993–2005. Public Health Nutr. 2009;12:444‐454. [DOI] [PubMed] [Google Scholar]
- 21. Arant C, Wessel T, Olson M, et al. Hemoglobin level is an independent predictor for adverse cardiovascular outcomes in women undergoing evaluation for chest pain: results from the national heart, lung, and blood institute women's ischemia syndrome evaluation study. J Am Coll Cardiol. 2004;43:2009‐2014. [DOI] [PubMed] [Google Scholar]
- 22. Sarnak MJ, Tighiouart H, Manjunath G, et al. Anemia as a risk factor for cardiovascular disease in the atherosclerosis risk in communities (ARIC) study. J Am Coll Cardiol. 2002;40:27‐33. [DOI] [PubMed] [Google Scholar]
- 23. Kuhn V, Diederich L, Keller TCS. Red blood cell function and dysfunction: redox regulation, nitric oxide metabolism, anemia. Antioxid Redox Signal. 2017;26:718‐742. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Honda Y, Watanabe T, Otaki Y, et al. Gender differences in the impact of anemia on subclinical myocardial damage and cardiovascular mortality in the general population: the yamagata (Takahata) study. Int J Cardiol. 2018;252:207‐212. [DOI] [PubMed] [Google Scholar]
- 25. Zhang Q, Zhou Y, Gao X, et al. Ideal cardiovascular health metrics and the risks of ischemic and intracerebral hemorrhagic stroke. Stroke. 2013;44:2451‐2456. [DOI] [PubMed] [Google Scholar]
- 26. Kanamori K, de Oliveira G, Auxiliadora‐Martins M, Schoon R, Reid J, Chini E. Two different methods of quantification of oxidized nicotinamide adenine dinucleotide (NAD) and reduced nicotinamide adenine dinucleotide (NADH) intracellular levels: enzymatic coupled cycling assay and ultra‐performance liquid chromatography (UPLC)‐mass spectrometry. Bio Protoc. 2018;8:undefined. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Liu L, Cui Z, Deng Y, Dean B, Hop CECA, Liang X. Analytical technologies in the biomedical and sciences l. Surrogate analyte approach for quantitation of endogenous NAD(+) in human acidified blood samples using liquid chromatography coupled with electrospray ionization tandem mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci. 2016;1011:69‐76. [DOI] [PubMed] [Google Scholar]
- 28. Trammell S, Schmidt M, Weidemann B, et al. Nicotinamide riboside is uniquely and orally bioavailable in mice and humans. Nat Commun. 2016;7:12948. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Ying W, Sevigny M, Chen Y, Swanson RA. Poly(ADP‐ribose) glycohydrolase mediates oxidative and excitotoxic neuronal death. Proc Natl Acad Sci U S A. 2001;98:12227‐12232. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Hershko C, Ronson A, Souroujon M, Maschler I, Heyd J, Patz J. Variable hematologic presentation of autoimmune gastritis: age‐related progression from iron deficiency to cobalamin depletion. Blood. 2006;107:1673‐1679. [DOI] [PubMed] [Google Scholar]
- 31. Zerez CR, Lachant NA, Lee SJ, Tanaka KR. Decreased erythrocyte nicotinamide adenine dinucleotide redox potential and abnormal pyridine nucleotide content in sickle cell disease. Blood. 1988;71:512‐515. [PubMed] [Google Scholar]
- 32. Detterich JA, Liu H, Suriany S, et al. Erythrocyte and plasma oxidative stress appears to be compensated in patients with sickle cell disease during a period of relative health, despite the presence of known oxidative agents. Free Radic Biol Med. 2019;141:408‐415. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33. Mirza F, Abdul‐Kadir R, Breymann C, Fraser Ian S, Taher Ali. Impact and management of iron deficiency and iron deficiency anemia in women’s health. Expert Rev Hematol. 2018;11:727‐736. [DOI] [PubMed] [Google Scholar]
- 34. Sandri BJ, Lubach GR, Lock EF, et al. Correcting iron deficiency anemia with iron dextran alters the serum metabolomic profile of the infant Rhesus Monkey. Am J Clin Nutr. 2021;113:915‐923. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Oduho GW, , Han Y, Baker DH. Iron deficiency reduces the efficacy of tryptophan as a niacin precursor. J Nutr. 1994;124:444‐450. [DOI] [PubMed] [Google Scholar]
- 36. Tannous C, Booz G, Altara R, et al. Nicotinamide adenine dinucleotide: biosynthesis, consumption and therapeutic role in cardiac diseases. Acta Physiol. 2021;231:e13551. [DOI] [PubMed] [Google Scholar]
- 37. Afra F, Mehri M, Namazi S. Bosentan‐induced immune hemolytic anemia in 17 years old man. a case report. DARU J Pharm Sci. 2021;29:211‐215. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38. Hikosaka K, Ikutani M, Shito M, et al. Deficiency of nicotinamide mononucleotide adenylyltransferase 3 (Nmnat3) causes hemolytic anemia by altering the glycolytic flow in mature erythrocytes. J Biol Chem. 2014;289:14796‐14811. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39. Esmayel IM, Hussein S, Gohar EA, Ebian HF, Mousa MM. Plasma levels of sirtuin‐1 in patients with cerebrovascular stroke. Neurol Sci. 2021;42(9):3843‐3850. [DOI] [PubMed] [Google Scholar]
- 40. Vannini N, Campos V, Girotra M, et al. The NAD‐booster nicotinamide riboside potently stimulates hematopoiesis through increased mitochondrial clearance. Cell Stem Cell. 2019;24(3):405‐418. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplementary Material