Skip to main content
Egyptian Journal of Medical Human Genetics
Download PDF

Association of single nucleotide polymorphism at BMP2 gene with iron deficiency status among anaemic patients in Hospital Universiti Sains Malaysia

Egyptian Journal of Medical Human Genetics volume 25, Article number: 46 (2024) Cite this article

Abstract

Background

Iron deficiency contributes for over half of all anaemia cases, especially among women and children. Iron deficiency anaemia remains a serious public health concern worldwide. The aim of this study is to determine the association between the single nucleotide polymorphism rs235756 in the bone morphogenetic protein 2 (BMP2) gene and iron deficiency status.

Results

104 total anaemic samples were selected from Hospital Universiti Sains Malaysia. ARMS-PCR was performed to genotype the rs235756 SNP in the 104 samples. The genotype distribution of BMP2 rs235756 showed that AG genotypes had the highest frequency 51(86.4%) followed by GG 6(10.2%) and AA 2(3.4%) in IDA group, whereas AG 42(93.3%), AA 2(4.4%) and GG 1(2.2%) were found in the other anaemia group. The minor allele frequency in BMP 2 rs235756 from this study (0.514) was not similar to the East Asian (EAS) population (0.135); however, the allelic frequency showed significant association between these two. The mean of total iron binding capacity level differed significantly between homozygous-dominant AA and AG + GG genotypes (P < 0.05) but no significant difference for the mean of haematological parameter, ferritin and serum iron.

Conclusions

In future clinical settings, this finding can potentially be as a guide in the early prediction for IDA patients through the genetic testing.

Introduction

Anaemia has affected almost 30% of the world population and iron deficiency contributes about half of the cases [1]. The prevalence of iron deficiency anaemia (IDA) is highest in children less than 5 years old, pregnant women and women in reproductive age [2]. This condition occurs due to changing and increasing physiological needs among human according to sex and specific life stages development. The rate of the disease is also high in developing countries due to common situation in those countries such as lack of nutrients, chronic diseases and parasitic infection like malaria or intestinal worm colonization [3, 4], while for high income countries, those who are affected with IDA mostly due to certain eating habits such as vegetarian diet, heavy menstrual bleeding or malabsorption syndromes [5, 6]. A frequent blood donors and patients with chronic inflammatory conditions also have high risk of getting iron deficiency anaemia [7, 8].

IDA is usually associated with nutritional factors; however, recent research suggest that genetic variations may also contribute to this condition [9]. This is supported by genome-wide association study (GWAS) that has identified few single nucleotide polymorphisms (SNPs) of genes such as TMPRSS6, HAMP and BMP2 genes that are associated with iron imbalance by interfering the components in iron regulation [10,11,12].

Bone morphogenic protein 2 (BMP2) gene is located on chromosome 20, involved in hepcidin expression by activating the bone morphogenic protein 6 BMP/SMAD signalling pathway [13] with the action of haemojuvelin. Hepcidin is a protein synthesized in liver involved in iron homeostasis [14]. Low amount of hepcidin secretion causes iron overload that leads to haematochromatosis, while high amount of it causes anaemia [15, 16].

The presence of SNPs on BMP2 gene has been proven to affect the hepcidin regulation and cause haematochromatosis [17,18,19], while there were insufficient studies on the association between hepcidin regulation and iron deficiency anaemia [20]. The gold standard for iron deficiency diagnosis is serum ferritin level [21]. Thus, we aim to study the association between BMP2 rs235756 SNP and iron deficiency status among anaemic patients in Hospital USM using serum ferritin level as the indicator.

Materials and methods

This study involved 104 anaemic patients from Hospital Universiti Sains Malaysia (Hospital USM). Full blood count (FBC) parameters, such as RBC count, Hb, MCV, MCH, MCHC, and HCT, were determined using XN-1000 automated haematology analyser (Sysmex Corporation, Kobe, Japan) from Haematology Laboratory, School of Medical Science, USM. Serum ferritin, serum iron and TIBC level were measured using ARCHITECT automated chemistry analyser (Abbott, Illinois, USA).

The DNA samples were obtained from archived DNAs of the previous study [22]. The DNA concentrations were measured using NanoDrop 2000 spectrophotometer (Thermo Scientific, USA), and the DNA purity was evaluated by the absorbance ratios of A260/A280. Then, all DNA samples were stored at − 20 °C until use.

ARMS-PCR was performed and optimized to detect rs235756 using following primers:

  • Forward outer: 3’ CATAGAGCAGGGCCCAGAAGCT 5’

  • Reverse outer: 3’TCAGGGTACTCACGAAAGAGAGA 5’

  • Forward inner (G allele): 3’ GAAGACTAAGAATTCTAGAATCCTCTCG 5’

  • Reverse inner (A allele): 3’ AAGATTTTCCTTTGGGCACCTGTTGGT 5’

Amplification was performed in a 20 μl reaction volume containing 50 ng genomic DNA, 0.4 μM of each primer, 250 μM dNTPs, 1.5 mM MgCl2 and 1U Taq DNA polymerase. PCR amplification was performed with a 5-min initial denaturation step at 95 °C followed by 30 s at 94 °C for denaturation, 30 s at 59 °C for annealing, 30 s at 72 °C for extension, and a final extension step at 72 °C for 5 min. The PCR was performed for 30 cycles. 2% agarose was used to separate the products [20].

All statistical analyses were performed using SPSS software version 24.0 (IBM Corporation, Armonk, NY, USA).

Results

Demographic distribution of patients

A total of 104 anaemic patient samples with Hb level < 12.0 g/dL and < 13.0 g/dL for male and female, respectively, were selected for this study as shown in Table 1.

Table 1 Demographic data of patients
Full size table

Genotyping of rs235756 via ARMS-PCR

The gel electrophoresis of ARMS-PCR of the genotyping is shown in Fig. 1. The homozygous dominant or wild type (AA) was predicted to produce bands at 140 base pair and mutant-type homozygous recessive (GG) at 184 base pair (bp), and heterozygous (AG) would produce bands at both 140 bp and 184 bp as well as internal control band of 270 bp (Fig. 1).

Fig. 1
figure 1

ARMS-PCR gel electrophoresis for SNP rs235756 genotyping. Lane 5: homozygous dominant (AA), Lane 1–4, 7: heterozygous AG, Lane 6: homozygous recessive (GG). (Abbreviations: bp: base pair, LD: ladder, NTC: non-template control)

Full size image

Genotype distribution of BMP2 rs235756 gene polymorphism

Out of 104 total anaemic samples, only 59 samples fulfilled the criteria of iron deficiency anaemia, following the guideline of the indicator serum ferritin level which is below 15 ng/mL [1]. The overall frequency of the SNP genotyping result for all the patients before classification into iron deficiency anaemia and other types of anaemia was calculated (Table 2).

Table 2 Genotypes distribution of BMP2 (rs235756) polymorphism in iron deficiency anaemia and other anaemia group
Full size table

Analysis of population genetics of BMP2 rs235756

The data obtained from the study were used to analyse the comparison of MAF and HWE P value between the current study and reference population (East Asian) at https://gene-calc.pl/hardy-weinberg-page as shown in Table 3. MAF is the frequency of the second most common allele which is G allele BMP2 rs235756 that occurs in a population. The current study showed a higher value of MAF (0.514) compared to reference study (0.135). However, the HWE P value of the current study (< 0.001) was not statistically significant for consistent distribution with Hardy–Weinberg law (P > 0.05) as compared to the reference population (0.559).

Table 3 MAF and HWE P value comparison between observed and reference study from genotype frequency of BMP2 (rs235756)
Full size table

The allelic frequency of BMP2 (rs235756) between observed and reference study was analysed using Pearson’s chi-squared test (Table 4). At a significance level 0.05, the P value obtained for the A and G allele frequency from both studies was statistically significant (P < 0.001) and thus could be concluded that there was association between both alleles frequency with observed and reference study.

Table 4 Comparison of allelic frequency of BMP2 (rs235756) between observed and reference study
Full size table

The mean difference of haematological and biochemical parameters between the genotype

The mean difference of Hb, RBC, MCV, MCH, MCHC, HCT, ferritin iron and TIBC level of patients is between homozygous-dominant AA and heterozygous AG + homozygous GG. The mean difference was analysed using independent t test. There was a significant difference for the mean of TIBC level between homozygous-dominant AA and heterozygous AG + homozygous GG genotypes (P < 0.05) but there is no significant difference for the mean of Hb, RBCs, MCV, MCH, MCHC, HCT, ferritin and iron (P > 0.05) summarized in Table 5.

Table 5 Mean difference of haematological and biochemical parameters between the genotype
Full size table

Discussion

Anaemia has always become a burden in the world population, and iron deficiency contributes half of the cases. In the past, iron deficiency was thought to be associated with dietary diet and environmental factors only. This condition always occurs especially among people who have strict diet, vegetarian, have problems with iron absorption in the body and among women who are pregnant and having heavy menstruation [23, 24]. Environmental factor such as poor sanitation also can increase the infection rate and affect the ability of body to absorb iron, thus leading to this condition [25]. These factors are believed to be the main cause; however, with the advancement of the technologies and the understanding of the underlying mechanism about iron metabolism disorder, it is revealed that genetic factors also can partially contribute to iron deficiency development [26, 27]. This is supported by the studies that have been done across the population around the globe, where the geographic and ethnicity differences have affected the genetic variation that involves in iron deficiency, especially in Asia and African populations [28].

Many studies have been done to study the association between SNPs that locate on the specific gene with the increasing risk of iron metabolism disorder. There are few genes that involve in iron metabolism pathways such as TMPRSS6, FTL, HAMP, and BMP2 gene that associate with different kinds of diseases [19]. BMP2 gene, that is located on chromosome 20, involves in hepcidin regulation that plays a big role in iron metabolism. Over-induced hepcidin can lead to anaemia, and lack of hepcidin can cause iron overload. Thus, variant of BMP2 gene is linked to most hemochromatosis cases, as it indirectly involves in C282Y mutation that modifies the HFE [18]. Other than that, study by Milet and colleagues found a significant association between the SNP of BMP2 gene (rs235756) with the pre-therapeutic serum ferritin level [29]. However, the association was related to hemochromatosis disease and not iron deficiency anaemia [17, 19, 30]. As there were lacks of studies between rs235756 on BMP2 gene with serum ferritin level and iron deficiency anaemia, therefore, this study investigated the association between this SNP with the iron deficiency status among anaemic patients in Hospital USM, Kubang Kerian, Kelantan, Malaysia.

According to this study, taken serum ferritin level as the indicator for iron deficiency, there was no significant association between BMP2 gene rs235756 with serum ferritin level, and no association with increased risk of iron deficiency in the 104 anaemic subjects. Generally, there was also no association between the homozygous GG genotype and recessive G allele with the serum ferritin level. This finding is consistent with previous study done by An and colleagues [31], where there was no association between BMP2 rs235756 with serum ferritin and risk of iron deficiency. However, this finding is contradicted with another study done by Milet and colleagues [17], where there was a significant association between increased risk of iron deficiency anaemia with serum ferritin even though there was no association between the iron deficiency risk with BMP2 rs235756.

This result may be affected by the existence of interactions with other genetic variation, demographics, or clinical factors that will affect the genotype and phenotype of the polymorphism. In this study, the demographic data including the sex, age, and ethnicity are completely difference with the previous study that has been done. In this study, 52.9% of the subjects were male. The age mean of the subject is 24.82 (SEM: 2.531) years with 95% of them being Malays. However, studies by Al-Amer et al. [20] and An et al. [31] showed that all their subjects were female, where the age of the subjects in Al-Amer et al. studies was between young females, while An et al. use elder female in their study. Female may be chosen because they are prone to have low ferritin level due to iron deficiency that is caused by multiple factors such as menstruation, diets and others. Low level of oestrogen level in female also may affect the hepcidin regulation that cause abnormalities in serum ferritin especially in menopause elder female [32], thus supporting the study by An et al. According to the study by Yusof and team, in Malaysia, Indian has the highest prevalence of anaemia (45%), followed by Malay and Chinese, respectively [33]. However, our data only consist of 98.1% and 1.9% of Malays and Chinese due to the distribution rate of the population around Hospital USM. If the Indian race was present in the study, as one of the major races that exhibit the highest prevalence towards the disease, it may contribute to different genotype distributions compared to the result that was obtained in the study.

Individuals are considered anaemic when the haemoglobin level is less than 13.0 g/dL in male, and 12.0 g/dL in female generally [34]. Apart from that, other haematological parameters such as RBCs count, MCV, MCH, MCHC and Hct level also contribute to anaemia identification. Iron deficiency anaemia has certain characteristics of haemoglobin parameters, such as microcytic (MCV < 80fL), hypochromia (MCH < 27 pg/cell) and anisocytosis (RDW > 15.2%) [35, 36]. It also possesses certain abnormalities in biochemical parameters that involve in iron markers such as serum ferritin, serum iron and TIBC level [35, 36]. Among anaemic samples, serum ferritin level is the best indicator for iron deficiency and low ferritin level is widely used for iron deficiency anaemia diagnosis [35]. Ferritin is very sensitive to iron deficiency, so it can be detected when the iron stores start to exhaust and before the amount of serum iron starts to deplete [37]. Thus, even though the serum iron and TIBC still remain normal, decreases in ferritin level indicate an acute phase of iron deficiency anaemia [38].

In this study, we analysed all the anaemic samples collected generally without grouping it into their respective types and determine the association between haematological and biochemical parameters with the anaemic status. This study demonstrated the mean of Hb was 10.29 ± 0.17 g/dL, RBC was 4.59 ± 0.1 × 1012/L and haematocrit was 31.81 ± 0.56%; all below the normal value indicate the samples are anaemic. The mean MCV was 70.52 ± 1.04 fL, and MCH was 21.82 ± 0.37 pg/cell. Low MCV below 83.0 fL and low MCH below 27 pg/cell are defined as hypochromic microcytic anaemia. The expression of the parameters is due to low amount of stored iron that reduces the concentration of haemoglobin, thus producing a paler red blood cell, and insufficient amount of haemoglobin reduces the size of newly produced red blood cells [39]. These are proved by studies by Johnson Wimbley and Graham [40], Tong et al. [41] and Rabindrakumar et al. [42] that show the same parameters value with our study.

The mean value of ferritin was 138.90 ± 18.42 ng/mL ranging from 0.9 to 732.10 ng/mL. The mean value was quite high due to the wide range of ferritin level among the samples. The limitation of serum ferritin is that it is an acute phase protein. Its value can remain normal or elevate in a response of infections and inflammation such as inflammatory bowel disease, chronic kidney disease and other conditions [43]. The correlation between serum ferritin with other clinical parameters shows that there was statistically significant negative correlation between ferritin with Hb, RBCs, haematocrit and TIBC, and not statistical significance with MCV, MCH and serum iron. These findings contradict with the theory as ferritin level must have positive correlation with Hb, RBCs, haematocrit, MCV, MCH and negative correlation with TIBC [44]. Previous study also reported a statistically significant positive correlation (P < 0.05) between ferritin level and each of Hb, RBCs, haematocrit, MCV and MCH values [45].

ARMS-PCR was used in determining the BMP2 rs235756 genotypes in the sample. This method can amplify the specific allele of interest and is time efficient, so it is suitable to be used due to limited time frame allocated for this study. The observed genotype distribution in this study showed that 89.4% of the patients had heterozygous AG followed by 6.7% and 3.8% for homozygous-recessive GG and homozygous-dominant AA, respectively. This finding is comparable with Al-Amer et al. [20] where they found that 88% had heterozygous AG followed by 5% for both for homozygous-recessive GG and homozygous-dominant AA, respectively, in their study. However, comparing the minor allele frequency (MAF) and HWE P value between this studies with reference population obtained from Ensembl genome study showed obvious difference between the genotype distribution. In reference population, homozygous AA comprises 75.4% of the population followed by 22.2% of heterozygous AG and 2.4% of homozygous-recessive GG.

MAF is the second most frequent allele occurs in a given population, which is allele G, while HWE stands for Hardy–Weinberg equilibrium is used to estimate the number of homozygous and heterozygous variant carriers based on its allele frequency in populations that are not evolving [46]. Our observed MAF (0.514) is higher compared to reference MAF of East Asia (0.135). SNPs with MAF frequency more than 5% are classified as a common variant in the population and are suitable to be used in disease research [47]. HWE P value analysis of the reference population is 0.559 and shows consistent distribution (P > 0.05), as they are not likely to represent genotyping errors. However, our data have HWE P value less than 0.05. This may be due to imbalance genotype distribution of our sample where the heterozygous genotypes are the highest, compared to the reference population [48]. If the HWE P value of the reference population also do not meet the criteria of P > 0.05, the gene allele frequencies may change and the population may evolve for that gene [49]. Comparison between allele A and G between this study and the reference population shows a statistically significant association (P < 0.05) between both.

The patients were divided into two groups: iron deficiency anaemia (n = 59) and other types of anaemia (n = 45), according to the serum ferritin level of the patients. The distribution of the genotype is likely the same with overall genotype distribution. The only difference is that iron deficiency anaemia group has higher frequency of homozygous-recessive GG (11.9%) compared to other type of anaemia group (2.2%). The higher frequency of homozygous-recessive GG genotype in iron deficiency groups compared to other may indicate that this minor genotype involves in susceptibility of the disease. This value is supported again by the study done by Al-Amer et al., where the homozygous-recessive GG of the iron deficiency group (13.79%) was higher than normal group (2%) and found association between the major allele with the disease in both group (P < 0.05). In study done by Milet et al. [17], major A allele of BMP2 rs235756 has association with higher ferritin level even though it is a study about hemochromatosis.

Study by Al-Amer et al. [20] shows that the OR 95% CI for the homozygous-recessive GG of rs235756 in BMP2 was 29.3 (1.494–575.401) and there was a significant association (P < 0.026) between the gene with increased risk of iron deficiency anaemia in female students in the study. However, in this study, the association between the risks of iron deficiency with the genotype cannot be identified. This is because the risk of a disease in a research can only be calculated based on a study that has two different groups which are group that have exposed with the disease and other is not [50]. This study consists of two groups; however, both groups were already exposed with the disease (anaemia) so only frequency of the genotype distribution across the groups could be identified. The distribution of the dominant and recessive allele among clinical parameters also shows no significant association except TIBC with P < 0.03. The distribution for G allele exceeds the major allele A because of the genotype distribution that has high frequency of heterozygous AG.

In this study, the impact of ferritin on the recessive allele G was determined and the findings show that there is no significant association between serum ferritin levels with minor genotype studied (AG + GG) compared to major genotype AA with P value > 0.05. So, it can be concluded that the rs235756 BMP2 does not affect the level of serum ferritin in the body. Very little research has been done to study the relation between rs235756 BMP2 with low serum ferritin and iron deficiency. The only studies that show the association between allele and the serum ferritin level in iron deficiency are as always mentioned before, by Al-Amer et al. [20] and Milet et al. [29]. The insignificant result in this study may be affected by the imbalanced genotype distribution. Based on the reference population of rs235756 BMP2 in Ensembl genome, it is showed that the dominant genotype AA and major allele A have the highest frequency, followed by heterozygous AG and minor allele G and homozygous GG genotype are the least. However, this study showed heterozygous AG as the most common genotype compared to dominant genotype AA causing the difference between the distribution in this study as compared to the reference population.

Conclusion

The current study demonstrates the substantial roles BMP2 polymorphic variant rs235756 in iron deficiency status among anaemic patients in Hospital USM. In the future research, we hope that with detail preparation and improvement from this study, we may find a significant result that can help in the early prediction for iron deficiency through the genetic testing.

Availability of data and materials

The data presented in this study are available on request from the corresponding author.

References

  1. World Health Organization (2001) Iron Deficiency Anemia Assessment, Prevention and Control. A guide for programme managers (Document WHO/NHD/01.3); Geneva, Switzerland

  2. World Health Organization (2015) THE GLOBAL PREVALENCE OF ANAEMIA IN 2011; Geneva, Switzerland

  3. Camaschella C (2015) Iron-deficiency anemia. N Engl J Med 372:1832–1843. https://doi.org/10.1056/NEJMRA1401038

    Article  PubMed  Google Scholar 

  4. Kassebaum NJ, Jasrasaria R, Naghavi M, Wulf SK, Johns N, Lozano R, Regan M, Weatherall D, Chou DP, Eisele TP et al (2014) A systematic analysis of global anemia burden from 1990 to 2010. Blood 123:615–624. https://doi.org/10.1182/BLOOD-2013-06-508325

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Cappellini MD, Musallam KM, Taher AT (2020) Iron deficiency anaemia revisited. J Intern Med 287:153–170. https://doi.org/10.1111/JOIM.13004

    Article  CAS  PubMed  Google Scholar 

  6. Fraser IS, Mansour D, Breymann C, Hoffman C, Mezzacasa A, Petraglia F (2015) Prevalence of heavy menstrual bleeding and experiences of affected women in a European patient survey. Int J Gynaecol Obstet 128:196–200. https://doi.org/10.1016/J.IJGO.2014.09.027

    Article  PubMed  Google Scholar 

  7. Goldman M, Uzicanin S, Scalia V, O’Brien SF (2014) Iron deficiency in Canadian blood donors. Transfusion 54:775–779. https://doi.org/10.1111/TRF.12380

    Article  CAS  PubMed  Google Scholar 

  8. Vos T, Abajobir AA, Abbafati C, Abbas KM, Abate KH, Abd-Allah F, Abdulle AM, Abebo TA, Abera SF, Aboyans V et al (2017) Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the global burden of disease study 2016. Lancet (London, England) 390:1211–1259. https://doi.org/10.1016/S0140-6736(17)32154-2

    Article  Google Scholar 

  9. McLean E, Cogswell M, Egli I, Wojdyla D, De Benoist B (2009) Worldwide prevalence of anaemia, WHO vitamin and mineral nutrition information system, 1993–2005. Public Health Nutr 12:444–454. https://doi.org/10.1017/S1368980008002401

    Article  PubMed  Google Scholar 

  10. Jallow MW, Cerami C, Clark TG, Prentice AM, Campino S (2020) Differences in the frequency of genetic variants associated with iron imbalance among global populations. PLoS ONE 15:e0235141. https://doi.org/10.1371/JOURNAL.PONE.0235141

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Pei SN, Ma MC, You HL, Fu HC, Kuo CY, Rau KM, Wang MC, Te LC (2014) TMPRSS6 Rs855791 polymorphism influences the susceptibility to iron deficiency anemia in women at reproductive age. Int J Med Sci 11:614–619. https://doi.org/10.7150/IJMS.8582

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Timmer T, Tanck MWT, Huis in ’t Veld EMJ, Veldhuisen B, Daams JG, de Kort WLAM, van der Schoot CE, van den Hurk K (2019) Associations between single nucleotide polymorphisms and erythrocyte parameters in humans: a systematic literature review. Mutat Res Mutat Res 779:58–67. https://doi.org/10.1016/J.MRREV.2019.01.002

    Article  CAS  Google Scholar 

  13. Xiao X, Alfaro-Magallanes VM, Babitt JL (2020) Bone morphogenic proteins in iron homeostasis. Bone. https://doi.org/10.1016/J.BONE.2020.115495

    Article  PubMed  PubMed Central  Google Scholar 

  14. Yiannikourides A, Latunde-Dada GO (2019) A short review of iron metabolism and pathophysiology of iron disorders. Medicines 6:85. https://doi.org/10.3390/MEDICINES6030085

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Papanikolaou G, Tzilianos M, Christakis JI, Bogdanos D, Tsimirika K, MacFarlane J, Goldberg YP, Sakellaropoulos N, Ganz T, Nemeth E (2005) Hepcidin in iron overload disorders. Blood 105:4103. https://doi.org/10.1182/BLOOD-2004-12-4844

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. D’Angelo G (2013) Role of hepcidin in the pathophysiology and diagnosis of anemia. Blood Res 48:10. https://doi.org/10.5045/BR.2013.48.1.10

    Article  PubMed  PubMed Central  Google Scholar 

  17. Milet J, Déhais V, Bourgain C, Jouanolle AM, Mosser A, Perrin M, Morcet J, Brissot P, David V, Deugnier Y et al (2007) Common variants in the BMP2, BMP4, and HJV Genes of the hepcidin regulation pathway modulate HFE hemochromatosis penetrance. Am J Hum Genet 81:799. https://doi.org/10.1086/520001

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Pagani A, Pettinato M, Colucci S, Dulja A, Rauner M, Nai A, Camaschella C, Altamura S, Muckenthaler MU, Silvestri L (2020) Hemochromatosis proteins are dispensable for the acute hepcidin response to BMP2. Haematologica 105:e493. https://doi.org/10.3324/HAEMATOL.2019.241984

    Article  PubMed  PubMed Central  Google Scholar 

  19. Radio FC, Majore S, Aurizi C, Sorge F, Biolcati G, Bernabini S, Giotti I, Torricelli F, Giannarelli D, De Bernardo C et al (2015) Hereditary hemochromatosis type 1 phenotype modifiers in Italian patients the controversial role of variants in HAMP, BMP2, FTL and SLC40A1 genes. Blood Cells Mol Dis 55:71–75. https://doi.org/10.1016/J.BCMD.2015.04.001

    Article  CAS  PubMed  Google Scholar 

  20. Al-Amer OM, Oyouni AAA, Alshehri MA, Alasmari A, Alzahrani OR, Aljohani SAS, Alasmael N, Theyab A, Algahtani M, Al Sadoun H et al (2021) Association of SNPs within TMPRSS6 and BMP2 genes with iron deficiency status in Saudi Arabia. PLoS ONE 16:e0257895. https://doi.org/10.1371/JOURNAL.PONE.0257895

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Daru J, Colman K, Stanworth SJ, De La Salle B, Wood EM, Pasricha SR (2017) Serum ferritin as an indicator of iron status: What do we need to know? Am J Clin Nutr 106:1634S-1639S. https://doi.org/10.3945/AJCN.117.155960

    Article  PubMed  PubMed Central  Google Scholar 

  22. Ghani M, Assyuhada SN, Bahar R, Zulkafli Z (2021) Characterization of β-globin gene cluster deletions using multiplex-gap polymerase chain reaction (PCR) and multiplex ligation-dependent probe amplification (MLPA) elucidating the role of dendritic cells and b cells in imiquimod (IMQ)-Induced psoriasis-like mouse model view project RBC alloimmunization view project. Artic Bangladesh J Med Sci. https://doi.org/10.3329/bjms.v20i3.52804

    Article  Google Scholar 

  23. Sebastiani G, Barbero AH, Borrás-Novel C, Casanova MA, Aldecoa-Bilbao V, Andreu-Fernández V, Tutusaus MP, Martínez SF, Roig MDG, García-Algar O (2019) The effects of vegetarian and vegan diet during pregnancy on the health of mothers and offspring. Nutrients. https://doi.org/10.3390/NU11030557

    Article  PubMed  PubMed Central  Google Scholar 

  24. Means RT (2020) Iron deficiency and iron deficiency anemia: implications and impact in pregnancy, fetal development, and early childhood parameters. Nutrients 12:447. https://doi.org/10.3390/NU12020447

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Coffey D, Geruso M, Spears D (2018) Sanitation, disease externalities and anaemia: evidence from Nepal. Econ J (London) 128:1395. https://doi.org/10.1111/ECOJ.12491

    Article  PubMed  Google Scholar 

  26. Camaschella C (2017) New insights into iron deficiency and iron deficiency anemia. Blood Rev 31:225–233. https://doi.org/10.1016/J.BLRE.2017.02.004

    Article  CAS  PubMed  Google Scholar 

  27. Pasricha SR, Tye-Din J, Muckenthaler MU, Swinkels DW (2021) Iron deficiency. Lancet 397:233–248. https://doi.org/10.1016/S0140-6736(20)32594-0

    Article  CAS  PubMed  Google Scholar 

  28. Finberg KE (2009) Iron-refractory iron deficiency anemia. Semin Hematol 46:378–386. https://doi.org/10.1053/J.SEMINHEMATOL.2009.06.006

    Article  CAS  PubMed  Google Scholar 

  29. Milet J, Le Gac G, Scotet V, Gourlaouen I, Thèze C, Mosser J, Bourgain C, Deugnier Y, Férec C (2010) A common SNP near BMP2 Is associated with severity of the iron burden in HFE p.C282Y homozygous patients: a follow-up study. Blood Cells Mol Dis 44:34–37. https://doi.org/10.1016/J.BCMD.2009.10.001

    Article  CAS  PubMed  Google Scholar 

  30. Pelucchi S, Mariani R, Calza S, Fracanzani AL, Modignani GL, Bertola F, Busti F, Trombini P, Fraquelli M, Forni GL et al (2012) CYBRD1 as a modifier gene that modulates iron phenotype in HFE p.C282Y homozygous patients. Haematologica 97:1818–1825. https://doi.org/10.3324/HAEMATOL.2012.062661

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. An P, Wu Q, Wang H, Guan Y, Mu M, Liao Y, Zhou D, Song P, Wang C, Meng L et al (2012) TMPRSS6, but not TF, TFR2 or BMP2 variants are associated with increased risk of iron-deficiency anemia. Hum Mol Genet 21:2124–2131. https://doi.org/10.1093/HMG/DDS028

    Article  CAS  PubMed  Google Scholar 

  32. Seong JM, Yoon YS, Lee KS, Bae NY, Gi MY, Yoon H (2017) Gender difference in relationship between serum ferritin and 25-hydroxyvitamin D in Korean adults. PLoS ONE. https://doi.org/10.1371/JOURNAL.PONE.0177722

    Article  PubMed  PubMed Central  Google Scholar 

  33. Yusof M, Awaluddin SM, Omar M, Ahmad NA, Abdul Aziz FA, Jamaluddin R, Aris T, Tan MP (2018) Prevalence of anaemia among the elderly in Malaysia and its associated factors: does ethnicity matter? J Environ Public Health. https://doi.org/10.1155/2018/1803025

    Article  PubMed  PubMed Central  Google Scholar 

  34. Chaparro CM, Suchdev PS (2019) Anemia epidemiology, pathophysiology, and etiology in low- and middle-income countries. Ann N Y Acad Sci 1450:15–31. https://doi.org/10.1111/NYAS.14092

    Article  PubMed  PubMed Central  Google Scholar 

  35. Bouri S, Martin J (2018) Investigation of iron deficiency anaemia. Clin Med (Northfield Il) 18:242. https://doi.org/10.7861/CLINMEDICINE.18-3-242

    Article  Google Scholar 

  36. Constantino BT (2013) Red cell distribution width, revisited. Lab Med 44:e2–e9. https://doi.org/10.1309/LMZ1GKY9LQTVFBL7

    Article  Google Scholar 

  37. Firkin F, Rush B (1997) Interpretation of biochemical tests for iron deficiency: diagnostic difficulties related to limitations of individual tests. Aust Prescr 20:74–76. https://doi.org/10.18773/AUSTPRESCR.1997.063

    Article  Google Scholar 

  38. Wang W, Gao J, Li N, Han S, Wu L, Zhang Y, Han T, Shan R, Li Y, Sun C et al (2021) Dietary iron and vitamins in association with mortality. Clin Nutr 40:2401–2409. https://doi.org/10.1016/J.CLNU.2020.10.038

    Article  CAS  PubMed  Google Scholar 

  39. Chaudhry HS, Kasarla MR (2022) Microcytic hypochromic anemia. StatPearls, Treasure Island

    Google Scholar 

  40. Johnson Wimbley TD, Graham DY (2011) Diagnosis and management of iron deficiency anemia in the 21st century. Ther Adv Gastroenterol 4:177. https://doi.org/10.1177/1756283X11398736

    Article  Google Scholar 

  41. Tong TYN, Key TJ, Gaitskell K, Green TJ, Guo W, Sanders TA, Bradbury KE (2019) Hematological parameters and prevalence of anemia in white and British Indian vegetarians and nonvegetarians in the UK biobank. Am J Clin Nutr 110:461. https://doi.org/10.1093/AJCN/NQZ072

    Article  PubMed  PubMed Central  Google Scholar 

  42. Rabindrakumar MSK, Pujitha Wickramasinghe V, Gooneratne L, Arambepola C, Senanayake H, Thoradeniya T (2018) The role of haematological indices in predicting early iron deficiency among pregnant women in an urban area of Sri Lanka. BMC Hematol 18:1–7. https://doi.org/10.1186/S12878-018-0131-2/TABLES/3

    Article  Google Scholar 

  43. Dignass A, Farrag K, Stein J (2018) Limitations of serum ferritin in diagnosing iron deficiency in inflammatory conditions. Int J Chronic Dis 2018:1–11. https://doi.org/10.1155/2018/9394060

    Article  Google Scholar 

  44. Svenson N, Bailey J, Durairaj S, Dempsey-Hibbert N (2021) A simplified diagnostic pathway for the differential diagnosis of iron deficiency anaemia and anaemia of chronic disease. Int J Lab Hematol 43:1644–1652. https://doi.org/10.1111/IJLH.13666

    Article  PubMed  Google Scholar 

  45. Sezgin G, Monagle P, Loh TP, Ignjatovic V, Hoq M, Pearce C, McLeod A, Westbrook J, Li L, Georgiou A (2020) Clinical thresholds for diagnosing iron deficiency: comparison of functional assessment of serum ferritin to population based centiles. Sci Rep 10:1–12. https://doi.org/10.1038/s41598-020-75435-5

    Article  CAS  Google Scholar 

  46. Abramovs N, Brass A, Tassabehji M (2020) Hardy–Weinberg equilibrium in the large scale genomic sequencing era. Front Genet 11:210. https://doi.org/10.3389/FGENE.2020.00210/BIBTEX

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Gorlov IP, Gorlova OY, Sunyaev SR, Spitz MR, Amos CI (2008) Shifting paradigm of association studies: value of rare single-nucleotide polymorphisms. Am J Hum Genet 82:100. https://doi.org/10.1016/J.AJHG.2007.09.006

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Eynard SE, Windig JJ, Leroy G, Van Binsbergen R, Calus MPL (2015) The effect of rare alleles on estimated genomic relationships from whole genome sequence data. BMC Genet. 16:1–12. https://doi.org/10.1186/S12863-015-0185-0/TABLES/6

    Article  Google Scholar 

  49. Chen B, Cole JW, Grond-Ginsbach C (2017) Departure from Hardy Weinberg equilibrium and genotyping error. Front Genet 8:167. https://doi.org/10.3389/FGENE.2017.00167/BIBTEX

    Article  PubMed  PubMed Central  Google Scholar 

  50. Viera AJ (2008) Odds ratios and risk ratios: what’s the difference and why does it matter? South Med J 101:730–734. https://doi.org/10.1097/SMJ.0B013E31817A7EE4

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We would like to thank all the staff at the Universiti Sains Malaysia, Kubang Kerian, Kelantan.

Funding

This research was funded by the Ministry of Higher Education Malaysia for Fundamental Research Grant Scheme. Project Code: [FRGS/1/2019/SKK06/USM/02/8].

Author information

Authors and Affiliations

  1. Department of Haematology, School of Medical Sciences, Health Campus, Universiti Sains Malaysia, 16150, Kubang Kerian, Kelantan, Malaysia

    Zefarina Zulkafli

  2. School of Health Sciences, Health Campus, Universiti Sains Malaysia, 16150, Kubang Kerian, Kelantan, Malaysia

    Nur Ain Azman, Nur Salwani Bakar, Mat Ghani Siti Nor Assyuhada & Siti Nur Nabeela A’ifah Mohammad

  3. Hospital Universiti Sains Malaysia, 16150, Kubang Kerian, Kelantan, Malaysia

    Zefarina Zulkafli

Authors
  1. Nur Ain Azman
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zefarina Zulkafli
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nur Salwani Bakar
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mat Ghani Siti Nor Assyuhada
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Siti Nur Nabeela A’ifah Mohammad
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

NAA and NSB contributed to conceptualization; NAA, NSB, SNAMG and SNNAM were involved in methodology; NAA, ZZ and NSB contributed to writing—original draft preparation; NAA, ZZ and NSBr were involved in writing—review and editing; and all authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Zefarina Zulkafli.

Ethics declarations

Ethics approval and consent to participate

This study has been approved by the Research Ethics Committee (Human) Universiti Sains Malaysia with code USM/JEPeM/19090552 and patient consented to participate.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Azman, N.A., Zulkafli, Z., Bakar, N.S. et al. Association of single nucleotide polymorphism at BMP2 gene with iron deficiency status among anaemic patients in Hospital Universiti Sains Malaysia. Egypt J Med Hum Genet 25, 46 (2024). https://doi.org/10.1186/s43042-024-00511-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s43042-024-00511-8

Keywords