Screening and Diagnosis of hemolytic anemia in North Indian population: Challenges faced

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Objective : This cross-sectional study aims to investigate epidemiological, clinical, and genetic aspects of hemolytic anemia in the antenatal population attending a tertiary care hospital in Delhi. Material and Method : A total of 7077 antenatal women were investigated over four years, revealing an overall prevalence of Beta Thalassemia Trait (BTT) of 4.55%. The screening algorithm involved complete blood count and High-Performance Liquid Chromatography (HPLC) for the women, followed by mutation testing using Multiplex ARMS PCR for four common mutations: IVS1-5, CD 41-42, CD 8-9, and Del 619 bp, additionally ARMS PCR, MPLA, and Sanger sequencing were also used. In cases where abnormal HPLC results were found, further testing of the husbands was done to guide counseling and decisions regarding prenatal testing. Results: IVS1-5 was identified as the most common mutation. CD 26 exhibited the lowest hemoglobin and highest HbA2 values among all mutations. The study underscores the challenges of using RBC indices, especially in cases with overlapping Nutritional Deficiency Anemia (NDA) and Hemolytic Anemia (HA). Similar challenges were observed with HbD and HbE due to their high MCV and MCH values, the algorithm for antenatal screening and diagnosis for LMIC was ascertained. Conclusion: The study provides data on the relative distribution of HA mutation in the antenatal population and emphasizes the importance of targeted screening strategies and genetic counseling to reduce the impact of hemoglobinopathies in the region effective. Beta thalassemia mutations of beta globin thalassemia screening barriers HBE hemolytic anemia Figures Figure 1 Figure 2 Figure 3 Introduction Hemoglobinopathies represent a significant group of inherited disorders affecting the red blood cells, imposing a substantial burden on families and healthcare systems worldwide 1 . Thalassemias are clinically categorized into Thalassemia Major (TM), Thalassemia Intermedia (TI) based on the severity. TM and severe TI require intensive management leading to a major disease burden. Thalassemia Minor, or ß Thalassemia Trait (BTT) is a carrier state where individuals are clinically asymptomatic. The pathogenesis of Thalassemia major and intermedia is based on the inheritance of abnormal ß thalassemia gene from both parents or one parent along with an abnormal variant hemoglobin gene (such as HbE or HbS). Common mutations prevalent in India include IVS 1–5(G→C), CD26 (HbE), CD8-9, CD41/42, 619 bp deletion 2 Hemolytic anemia (HA) is particularly prevalent and impactful in India, it has been estimated that in India annually approximately 10,000 to 15,000 babies with Thalassemia Major requiring lifelong treatment with blood transfusions and iron chelation therapy are born 1 . Antenatal screening is practically the most effective way to decrease the burden of disease in low- and middle-income countries (LMIC), antenatal screening with complete blood count (CBC) using RBC indices such as MCV, MCH, and RBC count has been advocated but the presence of Iron deficiency anemia due to poor nutrition, worm infestation, and frequent childbirths further complicates the diagnosis of thalassemia trait. High-performance liquid-based cytology (HPLC) in combination with CBC is practically the best test to screen for thalassemia. Nearly 200 different mutations have been implicated in causing the hemoglobinopathies. However, the five most common mutations account for 93.6% of the mutations 3 . The population of India is diverse, with people of different religions, origins, and regions, each having their own identity. Studies from Southern, western, and eastern parts of India have shown that the commonest mutations differ between the populations 4 , 5 . Migration has played an important role in shaping Delhi's population dynamics with approximately 68% of the migrants coming from the neighboring north Indian states like Uttar Pradesh, Bihar, Haryana, and Rajasthan 6 . The population of Delhi represents the microcosm of the northern Indian population. Hence this study aims to look into the epidemiological, clinical, and genetic aspects of Hemolytic anemia and to find out the relationship between the blood indices and Hemoglobin A2 values in different mutations in the antenatal population coming to the tertiary care hospital of Delhi. In this process, we wanted to explore the challenges faced due to coexisting nutritional anemia, lack of resources to diagnose mutations, and late evaluation of women during gestation. Material and Method It was a descriptive cross-sectional study and was done after prior approval from the Institutional Ethical and Research Committee (ECHR). The study was carried out from June 2020 to May 2024 after prior consent in the language they understood. All antenatal women coming to the antenatal clinic with unknown hemolytic disease status were included. Those who gave the history of receiving a blood transfusion in the past one month were excluded from the study. Clinical details like age, parity, gestational age, and religion were noted. All women underwent complete blood count (CBC) and high-performance liquid cytology (HPLC) tests. CBC profile included Hb level, MCV, MCH, MCHC, and RBC count. All women with HbA2 ≥ 3.5% or HbF > 1% were investigated further by DNA extraction followed by mutation testing using Multiplex ARMS PCR (MARMS PCR) for 4 mutations to begin with, they were IVS1-5, CD 41–42, CD 8–9 and Del 619 bp 2 . Subsequently by using ARMS PCR Cap A + 1, IVS1-1, CD 15, CD16 and CD17and sickle cell HbS mutation was done. For an unknown peak (HBD) we did PCR by RFLP and for high HBA2 (> 20%) HBE mutation was tested by PCR. For HBA2 ( 5%), Beta-delta deletion: Breakpoint A and Beta-delta deletion: Breakpoint B was looked for. In cases of the suspicion of hereditary persistence of fetal hemoglobin (HPFH), HPFH I, HPFH II, and HPFH III mutations were done. In women with anemia having normal HPLC reports, the serum ferritin levels, vitamin B12, and folic acid status were checked to confirm nutritional deficiency anemia (NDA). If the HPLC report of the antenatal women was abnormal, we performed HPLC testing on the husband to determine his hemolytic anemia status. If the husband’s HPLC was within normal limits, we did not do any further testing. If the husband’s HPLC was abnormal, we proceeded to molecular testing for mutation detection of the husband and subsequently counselled for prenatal testing to determine the status of the fetus. If the women’s sample did not show common mutations, and the husband’s HPLC was abnormal, we proceeded to Sanger sequencing and Multiplex ligation-dependent probe amplification (MLPA) of the HBB gene, before performing the prenatal sampling. The prenatal testing was done on chorionic villi (CV), obtained on CV sampling (CVS), in the instance when the gestation was beyond first trimester, amniotic fluid was used for testing. Testing for maternal cell contamination was done before mutation analysis. Post-test counselling was done after the prenatal test results and the couple was counselled regarding the option of medical termination of pregnancy (MTP) if the baby had both mutations from the father and mother. The collected data was entered into Microsoft Excel and statistically evaluated using the SPSS-25 version. Quantitative data was expressed by mean, and standard deviation with interquartile range, and the difference between the two groups was tested by student t test or Mann Whitney U test. Qualitative data was expressed in the percentages and difference between the proportions was tested by chi-square test or Fisher’s exact test. A ‘P’ value of less than 0.05 was considered statistically significant. Results Epidemiological profile of cases A total of 8161 antenatal women were screened for thalassemia and other hemoglobinopathies over 4 years, 828 of them were lost to follow-up and could not be completely investigated or followed. A total of 7077 of them were fully investigated and followed. The epidemiological profile of women in the study is given in Table 1 . The majority of women included in the study were young, most of them belonged to the age group of 23–27 years (2819/ 7077, 39.8%), not surprisingly, the majority of them were primigravida (2547/7077, 35.9%). Only a quarter of the subjects (1698/7077, 24%) were evaluated for thalassemia status in their first trimester of pregnancy, rest were investigated as late as the second or even in the third trimester. Anemia was seen in 58.3% of the cases, in the majority of them it was mild (2113/ 7077, 29.3%). A total of 8.9% of women had severe anemia (Table 1 ). Table 1 Epidemiological profile of cases Variables Antenatal women in the study N = 7077 (%) Maternal Age in years 37 244(3.4) Gravidity 1 2547 (35.9) 2 2812 (39.7) 3 1137 (16.1) 4 581 (8.2) Abortion 0 4555 (64.3) 1 1962 (27.7) 2 561 (7.9) Religion Hindu 5854 (82.7) Muslim 1119 (15.8) Sikh 106 (1.5) Gestational age in weeks 24 3230 (45.6) Haemoglobin in gm/dl < 5 114 (1.6) 5-6.9 446 (6.3) 7-9.9 1454 (20.5) 10-10.9 2113 (29.8) 11 or more 2951 (41.7) Relative prevalence of beta-globin gene mutation The HPLC testing was abnormal in 392/7077(5.54%) cases, and husband’s HPLC was advised in them. The molecular testing was also done for all those who had abnormal HPLC reports (Fig. 1 ), mutations were detected in 315/7077(4.55%) cases. The relative distribution of the mutations detected in beta-globin gene is given in Fig. 2 . Ten common mutations of beta-globin gene were observed in 311 cases and rare mutations were found in four. More than half of the cases had IVS1-5 mutation (174/315, 55.1%), followed by HBE mutation (47/315, 14.9%), CD8-9 (32/315, 10.1%), and CD41-42 (17/315, 5.3%). The rare mutations were CD 30, CD 5, Cap + 1, and CD 126–131 comprised of one case each. The incidence of HBE was 0.7% and that of HBD was 0.2% in the study population. Comparison of RBC indices in NDA and HA Among those with normal HPLC reports, the serum ferritin levels, vitamin B12, and folic acid status were checked and nutritional deficiency anemia was diagnosed (3220/7077, 45.49%). Table 2 shows the hematological profile of women with NDA and those HA. Although the average hemoglobin level in HA and NDA was in the moderate anemia range, it was significantly higher in HA compared to NDA (p = 0.001). While the MCV levels were significantly lower in HA (p = 0.025), the MCH levels did not differ significantly between the two groups. The mean Mentzer index was 19.01 ± 4.36 among HA, which was significantly lower than that of NDA (20.2 ± 5.86) (p = 0.001) (Table 2 ). Table 2 Comparison of haematological profile of nutritional deficiency and BTT cases Nutritional deficiency anemia (n = 5220) BTT with known mutation (n = 315) P value Hemoglobin in gm/dl 8.4 ± 1.05 9.2 ± 1.73 0.001 Mean corpuscular volume (MCV) in fl 72.1 ± 11.3 70.49 ± 12.38 0.025 Mean corpuscular hemoglobin (MCH) in pg 23.0 ± 4.27 22.67 ± 4.84 0.227 Red cell distribution width (RDW) in fl 22.5 ± 11.51 17.3 ± 8.31 0.001 Red blood cell(RBC) count 10 9 / L 3.8 ± 0.82 4.82 ± 0.60 0.001 Mentzer index 20.2 ± 5.86 19.01 ± 4.36 0.001 Serum Ferritin in ng/ml 17.48 ± 12.45 40.65 + 34.56 0.001 Relationship of RBC indices and HBA2 with different mutations in Beta globin gene The relationship of different mutations with hematological indices is shown in Table 3 . The average hemoglobin levels were the lowest in the CD41-42 mutation (7.43 ± 1.13) and 619 BP mutation (8.26 ± 1.99). The mean hemoglobin of HBE cases (9.77 ± 1.20) were higher than general anemia cases (9.21 ± 1.73). The mean MCV levels in HBD (82.5 ± 6.22) and HBE (76.22 ± 6.04) were higher than average for HA (70.49 ± 12.38) and in those with anemia (70.35 ± 10.71). Similarly, the mean MCH levels in HBD (27.32 ± 0.63) and HBE (25.41 ± 3.32) were higher compared to mean for hemolytic anemia (22.67 ± 4.84). The Mentzer index also showed higher values, akin to cases with no anemia (20.67 ± 6.76) in HBD (27.44 ± 6.13) and HBE (21.58 ± 2.05). At the same time, it was at its lowest in CD 8–9 mutation (16.46 ± 4.10). Figure 3 shows the levels of HbA2 in different mutations of HA. For most of the mutations, the HbA2 levels were in the range of 5-9.9%. IVS 1–5 was the commonest mutation in the 3.5–4.9% HbA2 range while the cases with CD26 mutation showed very high levels of HbA2. The mean HBA2 levels in 619BP del and CD 8–9 mutation was 6.08 ± 0.68 and 5.92 ± 0.64 respectively which was higher compared to IVS 1–5 (5.19 ± 1.83). (Table 3 ). Table 3 Mean hematological parameters in all subjects and cases of 5 most common mutations detected Haematological parameter Hb MCV MCH MI HbA2 No anemia (N = 2951) 12.58 ± 12.1 86.24 ± 9.66 29.03 ± 5.42 20.67 ± 6.76 2.78 ± 0.33 Anemia (N = 4126) 9.25 ± 1.48 70.35 ± 10.71 26.48 ± 4.17 20.34 ± 11.36 3.10 ± 2.86 BTT Cases (N = 315) 9.21 ± 1.73 70.49 ± 12.38 22.67 ± 4.84 19.01 ± 4.36 8.04 ± 3.39 IVS1-5 (N = 115) 9.30 ± 1.52 69.71 ± 8.30 22.23 ± 3.96 17.38 ± 4.43 5.19 ± 1.83 CD8-9 (N = 18) 8.76 ± 0.74 62.0 ± 6.31 20.78 ± 4.92 16.46 ± 4.10 5.92 ± 0.64 CD26 (HBE) (N = 31) 9.77 ± 1.20 76.22 ± 6.04 25.41 ± 3.32 21.58 ± 2.05 31.92 ± 6.37 CD41-42 (N = 12) 7.43 ± 1.13 63.50 ± 5.84 20.17 ± 2.58 17.69 ± 2.99 5.82 ± 0.38 619BP del (N = 5) 8.26 ± 1.99 67.63 ± 6.22 21.50 ± 2.82 17.21 ± 4.21 6.08 ± 0.68 HBD (N = 7) 9.08 ± 2.04 82.5 ± 6.22 27.32 ± 0.63 27.44 ± 6.13 2.80 ± 0.2 With unknown peak Outcome of cases from confirmation of diagnosis to prenatal diagnosis The management of cases from screening to prenatal diagnosis is shown as flowchart in Fig. 1 . The HPLC of husband was abnormal in 38/392 (9.7%) cases. A total of 24 couples tested positive for mutations in both partners on ARMS PCR or RFLP PCR. In the rest ten cases, in which the mutation of only one partner was known, the Sanger sequencing /MLPA was done which revealed mutations in both partners in four additional couples. The prenatal testing with chorionic villus sampling or amniotic fluid aspiration for confirmation of mutation in the fetus was done in 26 cases, one case refused prenatal testing, and in the other, both partners had CD26 (HBE) mutation, which is not of much consequence even if homozygous, hence only counselling was done. One case had a diamniotic dichorionic twin pregnancy. The report of prenatal testing showed the fetus being affected in 7/27 (25.9%) cases and as trait or no mutation in 20/27 (74.1%). Post-test counselling was done in all cases, and MTP was opted in all 7 cases in which the report was thalassemia major. In one interesting case of dichorionic twin pregnancy, one baby was reported to be affected with thalassemia major while the other baby was trait. Selective reduction was done after consent. Discussion The highlight of the study was the analysis of mutations of the Beta thalassemia gene in a large number of antenatal women from a North Indian population. One in every twenty antenatal women was found to be HA carrier. The relationship of hematological parameters with different mutations of HA, and NDA was delved upon. Among beta thalassemia mutations, IVS1-5 was the most common. There was real-world implementation of a simple algorithm to provide prenatal diagnosis to the couples, which can be useful in low and middle-income countries (LMIC). For every 253 women tested, one with HA trait couple was identified. One thalassemia major case was prevented per 1000 women screened. The challenges faced in the LMIC and the tropical country set up ranged from high incidence of HA carriers in this part of the world to the presence of concomitant NDA cases making the diagnosis difficult. Delay in the antenatal booking was also a hurdle in the management. High incidence of HA carriers in the population The National Capital Territory (NCT) of Delhi is a largest metropolitan city in India and is densely populated with an estimated population of 18.6 million in 2016 6 . It has a heterogenous demographic profile significant representation from numerous ethnic groups and religious communities, such as Sindhis, Punjabis, Bengalis, Mahars, Kolis, Saraswats, Lohanas and Gaurs 6 . In the present study the incidence of carrier status of hemolytic anemia in antenatal women coming to the tertiary hospital of Delhi was 4.55%, which was higher than the pooled prevalence of beta-thalassemia carriers for Indian population (3.74%, 95% CI 2.52–4.97) and nearly same as its estimation among tribal groups (4.6%, 95% CI 3.2–6.2) 7 . The higher number of HA in the study may be accounted for by our hospital being a tertiary care center, and receiving many high-risk cases. The prevalence of β-thal trait in central India is estimated to range between 1.4 and 3.4% 8 , in South India, it is between 8.5% and 37.9% 9 . The Northern and Western Indian states have a higher thalassemic burden as it is more prevalent in ethnic communities 10 . Diagnosis of carrier state late in pregnancy Screening for HA should be done during adolescence or premaritally. However, due to lack of awareness and government commitment apart from many other sociodemographic reasons, premarital screening is still in its infancy in India. The antenatal period is considered to be the best practical time to screen as the population comes in contact with the hospital services during this time. It is also the final opportunity to provide a prenatal diagnosis if both partners are traits. In the present study, only one-quarter of women came for antenatal check-up during the first trimester, leading to late diagnosis. Screening for HA should be done early in pregnancy as it requires an algorithm. A concentrated effort towards education and awareness of the coming generations is constantly needed in the complex and heterogeneous Indian population. Confrontation in diagnosis due to concurrent NDA The HbA 2 cut-off of 3.5% for HA carriers along with reduced MCV (< 80fl) and MCH (< 27pg) along with a relatively high RBC count and normal RDW is taken as HA. Due to high Iron deficiency anemia (IDA), the microcytosis and hypochromia due to IDA may blur the HA picture making the diagnosis based on the CBC report alone, a difficult task. In the present study, the majority of HA and NDA had moderate anemia, the MCV levels were significantly low in HA and was a better parameter compared to MCH, similar findings have been observed in other studies also 11 . HPLC testing is a useful adjunct as a screening modality of thalassemia, but CBC is needed additionally in cases with HPLC between 3.2–4.0% 11 , 12 . The RBC count and RDW provides vital information, hence, should be analyzed when HBA2 is in the borderline range. Limitations of RBC indices in HBD and HBE In HBD carriers, although the mean hemoglobin was found to be low, however, the MCV, MCH, and Mentzer index was in the normal range, hence could be diagnosed with certainty by HPLC only. Similarly, in HBE traits, the indices were lowered only marginally and could not be identified by the Mentzer index but could be diagnosed on HPLC due to the high HbA2 levels. For Beta thalassemia mutations, the Mentzer index was a good parameter to suspect the thalassemia trait. However, borderline/normal HbA 2 levels (3.0–3.9%) may often lead to a diagnostic dilemma. Previous studies have shown that borderline HbA 2 with near normal or reduced red cell indices is most often due to the cap site + 1 (A > C) mutation and the poly-A (T > C) mutation, several other β thalassemia carriers show borderline or normal HbA 2 levels common among them is the presence of δ gene mutations which could reduce HbA 2 levels significantly 13 . β genotyping should be done in a couple when one of the partners is a classical carrier of β thalassemia 13 . Logistics of screening and molecular test in LMIC The husband was called for HPLC and CBC only when the HPLC report of the wife was abnormal so the burden of doing the husband’s HPLC in all 7077 cases could be avoided and was instead performed in 392 cases only. Also, the mutations were required in the 38/7077(0.5%) couples when both partners had abnormal HPLC reports. The Sanger sequencing of beta-globin gene was needed only in 14/7077 (0.2%) couples, and in the rest 24 cases, the mutations could be ascertained on ARMS PCR which is cheaper alternative in terms of consumables and equipment. Relative distribution of HA mutation in the study population More than 350 different mutations of beta-globin gene have been reported so far 14 . However, Many studies have suggested that, the four most common mutations IVS I-5 (G→C), Codon 41/42 (- TCTT), 619-bp deletion and FS 8/9 (+ G) account for nearly 90% of the thalassemia mutations 2 , 12 , 15 . HbS is more frequently observed in the tribal populations, HbE in the eastern region, and HbD in Punjab 12 . It is also important to remember that couples at risk of having a baby with certain conditions like HbD-hereditary persistence of fetal hemoglobin (HPFH), HbD-β-thalassemia, and homozygous HbD or HbE disease do not require prenatal diagnosis as they would usually have a very mild clinical presentation and they can lead a normal life 16 . In our study also, the prenatal diagnosis was not done as both partners had HBE carrier status 10 . Strengths and weakness of the study The strength of the study was the, prospective inclusion of a large cohort of antenatal women. The detection of the genotype status of the carriers provided the data of the relative distribution of the HA mutations in the population. The weakness could be that the data was hospital based hence selective and thus not easily exploitable to estimate the true burden of the disease. Conclusion This study highlights the importance of early screening and diagnosis of the carrier status of hemoglobinopathies in antenatal women and their partners coupled with genetic counselling. Nearly one out of every twenty women was found to be the HA carrier, and IVS 1–5 was the most common mutation. In a developing country like India, high prevalence rates of nutrition deficiency anemia as well as hemoglobinopathies, makes the differentiation difficult. Similar challenges are encountered in the diagnosis of HbE and HbD mutations. Thus, following a targeted and systematic algorithm, is important for channelizing resources especially in low- and middle-income countries. Declarations Author Contribution MK , ED, VK were involved in planning the research workRG, SM, KB , MZ , MK were involved in execution of the research workMK, RY, RG did the overall supervision of the research and reviewed the manuscriptVK, KB, MK wrote the main manuscript Acknowledgment There is no conflict of interest among authors to declare. The study was funded by Department of Biotechnology, under the UMMID initiative. We thank Ms. Nisha and Mr. Preeti Negi for their support in the project. Data Availability the data will be provided if required References Chandy M. Developing a National Programme for India. In: Control and management of Thalassemia and other Hemoglobinopathies in the Indian Subcontinent_ Synoptic Views. Editor: Ghosh K, Colah R. Published by National institute of Immunohaematology, 2008. Mishra KK, Patel P, Bhukhanvala DS, Shah A, Ghosh K. A multiplex ARMS PCR approach to detection of common β-globin gene mutations. Anal Biochem. 2017 Nov 15;537:93–8. Varawalla NY, Old JM, Sarkar R, Venkatesan R, Weatherall DJ. The spectrum of beta-thalassaemia mutations on the Indian subcontinent: the basis for prenatal diagnosis. Br J Haematol. 1991 Jun;78(2):242–7. Bashyam MD, Bashyam L, Savithri GR, Gopikrishna M, Sangal V, Devi ARR. Molecular genetic analyses of beta-thalassemia in South India reveals rare mutations in the beta-globin gene. J Hum Genet. 2004;49(8):408–13. Shah PS, Shah ND, Ray HSP, Khatri NB, Vaghasia KK, Raval RJ, et al. Mutation analysis of β-thalassemia in East-Western Indian population: a recent molecular approach. Appl Clin Genet. 2017;10:27–35. https://ncrpb.nic.in/pdf_files/08modified_ch04_demographic_profile.pdf ; Pratik Singh, Samir Shaikh, Sagar Parmar & Reeshu Gupta. (2023) Current Status of β-Thalassemic Burden in India. Hemoglobin 47:5, pages 181-190. Sumedha, D., Anita, K. Prevalence of beta thalassemia carriers in India: a systematic review and meta-analysis. J Community Genet 14, 527–541 (2023). Yadav SS, Panchal P, Menon KC. Prevalence and Management of β-Thalassemia in India. Hemoglobin. 2022 Jan;46(1):27–32. Colah R, Italia K, Gorakshakar A. Burden of thalassemia in India: The road map for control. Pediatric Hematology Oncology Journal. 2017 Dec 1;2(4):79–84. Baliyan M, Kumar M, Nangia A, Parakh N. Can RBC Indices be Used as Screening Test for Beta-Thalassemia in Indian Antenatal Women? J Obstet Gynaecol India. 2019 Dec;69(6):495-500. S. Sinha, M.L. Black, S. Agarwal, R. Das, A.H. Bittles, M. Bellgard ThalInd, a β thalassemia and hemoglobinopathies database for India:defining a model country specific and disease centric bioinformatics resource . Hum Mutat, 32 (2011), pp. 887-893 Gorivale M, Sawant P, Mehta P, Nadkarni A, Ghosh K, Colah R. Challenges in prenatal diagnosis of b thalassemia: couples with normal HbA2 in one partner. Prenat Diagn 2015;35:1353e7. Kountouris P, Lederer CW, Fanis P, Feleki X, Old J, Kleanthous M. IthaGenes: an interactive database for haemoglobin variations and epidemiology. PLoS One 2014;9:e103020. Mohanty D, Colah RB, Gorakshakar AC, Patel RZ, Master DC, Mahanta J, et al. Prevalence of β-thalassemia and other haemoglobinopathies in six cities in India: a multicentre study. J Community Genet. 2013 Jan;4(1):33–42. N. Madan, S. Sharma, S.K. Sood, R. Colah, H.M. Bhatia. Frequency of β thalassemia trait and other hemogl obinopathies in northern and western India . Indian J Hum Genet, 16 (2010), pp. 16-25 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4828384","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":347992356,"identity":"18c7ed5a-f83d-4344-9e37-ef85420e9659","order_by":0,"name":"Manisha Kumar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5UlEQVRIie3PLQsCMRjA8Y0HdoadVsWXbyAMBicW/SqKdVhMYlA4mF9HyzDesXBFsQoWX6rlguA1d2IwnYuC+4eNwfNjG0Iu148W4YVZPYRPZqNlewIIWE6I1TVvQqr54StpL3dxnG16rQ7QYHoXvQZBcL4cCkiwHQ+0vx3xbkiDY1ONzMMI56KIRIJpLGG40obUFBhCSb2Q7G8szuT8RSY1NbcgB8EiX+oXwanSNuTGtC8TzjSZ1LFKKIFvf9kLnmZy1mJJuE4zNetXvPB8LSIflRjQfAe78TzvhB/20y6Xy/VHPQEP3EgA7iMIcQAAAABJRU5ErkJggg==","orcid":"","institution":"Lady Hardinge Medical College","correspondingAuthor":true,"prefix":"","firstName":"Manisha","middleName":"","lastName":"Kumar","suffix":""},{"id":347992357,"identity":"c6f24048-ff17-477d-a96a-d3d746d614d7","order_by":1,"name":"Rajeev Goel","email":"","orcid":"","institution":"Lady Hardinge Medical 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College","correspondingAuthor":false,"prefix":"","firstName":"Kirti","middleName":"","lastName":"Balyan","suffix":""},{"id":347992361,"identity":"7ded7f5d-bb5f-43c4-8cb6-ff51ca749b74","order_by":5,"name":"Mahrukh Zaidi","email":"","orcid":"","institution":"Lady Hardinge Medical College","correspondingAuthor":false,"prefix":"","firstName":"Mahrukh","middleName":"","lastName":"Zaidi","suffix":""},{"id":347992362,"identity":"e7d3a1d8-b758-42d0-a065-112cf681ef6c","order_by":6,"name":"Vani Kargwal","email":"","orcid":"","institution":"Lady Hardinge Medical College","correspondingAuthor":false,"prefix":"","firstName":"Vani","middleName":"","lastName":"Kargwal","suffix":""},{"id":347992363,"identity":"fa3165af-8a9f-4b48-bb5f-6e2df34a579a","order_by":7,"name":"Reena Yadav","email":"","orcid":"","institution":"Lady Hardinge Medical College","correspondingAuthor":false,"prefix":"","firstName":"Reena","middleName":"","lastName":"Yadav","suffix":""}],"badges":[],"createdAt":"2024-07-30 11:24:56","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4828384/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4828384/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":64568344,"identity":"177301f9-0e44-4744-a74e-074a1bc05f82","added_by":"auto","created_at":"2024-09-16 00:39:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":90609,"visible":true,"origin":"","legend":"\u003cp\u003eThe algorithm of the outcome of the study cohort from screening to prenatal diagnosis\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4828384/v1/fe94df897e1983c3cf9c6cdd.png"},{"id":64568343,"identity":"6324b4b3-ca9c-4bcc-ba99-0a0c660de23d","added_by":"auto","created_at":"2024-09-16 00:39:53","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":64659,"visible":true,"origin":"","legend":"\u003cp\u003eThe relative distribution of the mutations detected in beta-globin gene.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4828384/v1/0eebe5d30603038f3b1905cf.png"},{"id":64568345,"identity":"efc5e4de-a9dd-41dd-8460-80e85bc990d7","added_by":"auto","created_at":"2024-09-16 00:39:53","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":54157,"visible":true,"origin":"","legend":"\u003cp\u003eThe levels of HbA2 in different mutations of hemolytic anemia.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4828384/v1/a0754493fb9f49b5e980cf45.png"},{"id":66007528,"identity":"c270b568-7658-41fd-892a-02e3c2aff718","added_by":"auto","created_at":"2024-10-06 10:08:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":846176,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4828384/v1/b933de4f-1502-4829-b920-d827b941c765.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Screening and Diagnosis of hemolytic anemia in North Indian population: Challenges faced","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHemoglobinopathies represent a significant group of inherited disorders affecting the red blood cells, imposing a substantial burden on families and healthcare systems worldwide \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Thalassemias are clinically categorized into Thalassemia Major (TM), Thalassemia Intermedia (TI) based on the severity. TM and severe TI require intensive management leading to a major disease burden. Thalassemia Minor, or \u0026szlig; Thalassemia Trait (BTT) is a carrier state where individuals are clinically asymptomatic. The pathogenesis of Thalassemia major and intermedia is based on the inheritance of abnormal \u0026szlig; thalassemia gene from both parents or one parent along with an abnormal variant hemoglobin gene (such as HbE or HbS). Common mutations prevalent in India include IVS 1\u0026ndash;5(G\u0026rarr;C), CD26 (HbE), CD8-9, CD41/42, 619 bp deletion\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eHemolytic anemia (HA) is particularly prevalent and impactful in India, it has been estimated that in India annually approximately 10,000 to 15,000 babies with Thalassemia Major requiring lifelong treatment with blood transfusions and iron chelation therapy are born \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Antenatal screening is practically the most effective way to decrease the burden of disease in low- and middle-income countries (LMIC), antenatal screening with complete blood count (CBC) using RBC indices such as MCV, MCH, and RBC count has been advocated but the presence of Iron deficiency anemia due to poor nutrition, worm infestation, and frequent childbirths further complicates the diagnosis of thalassemia trait. High-performance liquid-based cytology (HPLC) in combination with CBC is practically the best test to screen for thalassemia. Nearly 200 different mutations have been implicated in causing the hemoglobinopathies. However, the five most common mutations account for 93.6% of the mutations \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe population of India is diverse, with people of different religions, origins, and regions, each having their own identity. Studies from Southern, western, and eastern parts of India have shown that the commonest mutations differ between the populations \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Migration has played an important role in shaping Delhi's population dynamics with approximately 68% of the migrants coming from the neighboring north Indian states like Uttar Pradesh, Bihar, Haryana, and Rajasthan \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. The population of Delhi represents the microcosm of the northern Indian population.\u003c/p\u003e \u003cp\u003eHence this study aims to look into the epidemiological, clinical, and genetic aspects of Hemolytic anemia and to find out the relationship between the blood indices and Hemoglobin A2 values in different mutations in the antenatal population coming to the tertiary care hospital of Delhi. In this process, we wanted to explore the challenges faced due to coexisting nutritional anemia, lack of resources to diagnose mutations, and late evaluation of women during gestation.\u003c/p\u003e"},{"header":"Material and Method","content":"\u003cp\u003eIt was a descriptive cross-sectional study and was done after prior approval from the Institutional Ethical and Research Committee (ECHR). The study was carried out from June 2020 to May 2024 after prior consent in the language they understood. All antenatal women coming to the antenatal clinic with unknown hemolytic disease status were included. Those who gave the history of receiving a blood transfusion in the past one month were excluded from the study.\u003c/p\u003e \u003cp\u003eClinical details like age, parity, gestational age, and religion were noted. All women underwent complete blood count (CBC) and high-performance liquid cytology (HPLC) tests. CBC profile included Hb level, MCV, MCH, MCHC, and RBC count. All women with HbA2\u0026thinsp;\u0026ge;\u0026thinsp;3.5% or HbF\u0026thinsp;\u0026gt;\u0026thinsp;1% were investigated further by DNA extraction followed by mutation testing using Multiplex ARMS PCR (MARMS PCR) for 4 mutations to begin with, they were IVS1-5, CD 41\u0026ndash;42, CD 8\u0026ndash;9 and Del 619 bp \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Subsequently by using ARMS PCR Cap A\u0026thinsp;+\u0026thinsp;1, IVS1-1, CD 15, CD16 and CD17and sickle cell HbS mutation was done. For an unknown peak (HBD) we did PCR by RFLP and for high HBA2 (\u0026gt;\u0026thinsp;20%) HBE mutation was tested by PCR. For HBA2 (\u0026lt;\u0026thinsp;20%) Hb Lepore mutation was tested by PCR. In those with high HbF (\u0026gt;\u0026thinsp;5%), Beta-delta deletion: Breakpoint A and Beta-delta deletion: Breakpoint B was looked for. In cases of the suspicion of hereditary persistence of fetal hemoglobin (HPFH), HPFH I, HPFH II, and HPFH III mutations were done.\u003c/p\u003e \u003cp\u003eIn women with anemia having normal HPLC reports, the serum ferritin levels, vitamin B12, and folic acid status were checked to confirm nutritional deficiency anemia (NDA). If the HPLC report of the antenatal women was abnormal, we performed HPLC testing on the husband to determine his hemolytic anemia status. If the husband\u0026rsquo;s HPLC was within normal limits, we did not do any further testing. If the husband\u0026rsquo;s HPLC was abnormal, we proceeded to molecular testing for mutation detection of the husband and subsequently counselled for prenatal testing to determine the status of the fetus.\u003c/p\u003e \u003cp\u003eIf the women\u0026rsquo;s sample did not show common mutations, and the husband\u0026rsquo;s HPLC was abnormal, we proceeded to Sanger sequencing and Multiplex ligation-dependent probe amplification (MLPA) of the HBB gene, before performing the prenatal sampling. The prenatal testing was done on chorionic villi (CV), obtained on CV sampling (CVS), in the instance when the gestation was beyond first trimester, amniotic fluid was used for testing. Testing for maternal cell contamination was done before mutation analysis. Post-test counselling was done after the prenatal test results and the couple was counselled regarding the option of medical termination of pregnancy (MTP) if the baby had both mutations from the father and mother.\u003c/p\u003e \u003cp\u003eThe collected data was entered into Microsoft Excel and statistically evaluated using the SPSS-25 version. Quantitative data was expressed by mean, and standard deviation with interquartile range, and the difference between the two groups was tested by student t test or Mann Whitney U test. Qualitative data was expressed in the percentages and difference between the proportions was tested by chi-square test or Fisher\u0026rsquo;s exact test. A \u0026lsquo;P\u0026rsquo; value of less than 0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eEpidemiological profile of cases\u003c/h2\u003e \u003cp\u003eA total of 8161 antenatal women were screened for thalassemia and other hemoglobinopathies over 4 years, 828 of them were lost to follow-up and could not be completely investigated or followed. A total of 7077 of them were fully investigated and followed. The epidemiological profile of women in the study is given in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe majority of women included in the study were young, most of them belonged to the age group of 23\u0026ndash;27 years (2819/ 7077, 39.8%), not surprisingly, the majority of them were primigravida (2547/7077, 35.9%). Only a quarter of the subjects (1698/7077, 24%) were evaluated for thalassemia status in their first trimester of pregnancy, rest were investigated as late as the second or even in the third trimester. Anemia was seen in 58.3% of the cases, in the majority of them it was mild (2113/ 7077, 29.3%). A total of 8.9% of women had severe anemia (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEpidemiological profile of cases\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAntenatal women in the study N\u0026thinsp;=\u0026thinsp;7077 (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal Age in years\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1863 (26.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u0026ndash;27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2819(39.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28\u0026ndash;32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1718(24.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e33\u0026ndash;37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e433(6.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e244(3.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGravidity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2547 (35.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2812 (39.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1137 (16.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e581 (8.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAbortion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4555 (64.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1962 (27.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e561 (7.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHindu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5854 (82.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMuslim\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1119 (15.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSikh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e106 (1.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGestational age in weeks\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1698 (24.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u0026ndash;18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1071 (15.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u0026ndash;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1079 (15.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3230 (45.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHaemoglobin in gm/dl\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e114 (1.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5-6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e446 (6.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7-9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1454 (20.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10-10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2113 (29.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11 or more\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2951 (41.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eRelative prevalence of beta-globin gene mutation\u003c/h2\u003e \u003cp\u003eThe HPLC testing was abnormal in 392/7077(5.54%) cases, and husband\u0026rsquo;s HPLC was advised in them. The molecular testing was also done for all those who had abnormal HPLC reports (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), mutations were detected in 315/7077(4.55%) cases.\u003c/p\u003e\u003cp\u003eThe relative distribution of the mutations detected in beta-globin gene is given in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Ten common mutations of beta-globin gene were observed in 311 cases and rare mutations were found in four. More than half of the cases had IVS1-5 mutation (174/315, 55.1%), followed by HBE mutation (47/315, 14.9%), CD8-9 (32/315, 10.1%), and CD41-42 (17/315, 5.3%). The rare mutations were CD 30, CD 5, Cap\u0026thinsp;+\u0026thinsp;1, and CD 126\u0026ndash;131 comprised of one case each. The incidence of HBE was 0.7% and that of HBD was 0.2% in the study population.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eComparison of RBC indices in NDA and HA\u003c/h2\u003e \u003cp\u003eAmong those with normal HPLC reports, the serum ferritin levels, vitamin B12, and folic acid status were checked and nutritional deficiency anemia was diagnosed (3220/7077, 45.49%). Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the hematological profile of women with NDA and those HA. Although the average hemoglobin level in HA and NDA was in the moderate anemia range, it was significantly higher in HA compared to NDA (p\u0026thinsp;=\u0026thinsp;0.001). While the MCV levels were significantly lower in HA (p\u0026thinsp;=\u0026thinsp;0.025), the MCH levels did not differ significantly between the two groups. The mean Mentzer index was 19.01\u0026thinsp;\u0026plusmn;\u0026thinsp;4.36 among HA, which was significantly lower than that of NDA (20.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.86) (p\u0026thinsp;=\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of haematological profile of nutritional deficiency and BTT cases\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNutritional deficiency anemia\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;5220)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBTT with known mutation\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;315)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin in gm/dl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e8.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean corpuscular volume (MCV) in fl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e72.1\u0026thinsp;\u0026plusmn;\u0026thinsp;11.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.49\u0026thinsp;\u0026plusmn;\u0026thinsp;12.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean corpuscular hemoglobin (MCH) in pg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e23.0\u0026thinsp;\u0026plusmn;\u0026thinsp;4.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.67\u0026thinsp;\u0026plusmn;\u0026thinsp;4.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.227\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRed cell distribution width (RDW) in fl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e22.5\u0026thinsp;\u0026plusmn;\u0026thinsp;11.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.3\u0026thinsp;\u0026plusmn;\u0026thinsp;8.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRed blood cell(RBC) count 10\u003csup\u003e9\u003c/sup\u003e/ L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e3.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMentzer index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e20.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.01\u0026thinsp;\u0026plusmn;\u0026thinsp;4.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum Ferritin in ng/ml\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e17.48\u0026thinsp;\u0026plusmn;\u0026thinsp;12.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.65\u0026thinsp;+\u0026thinsp;34.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eRelationship of RBC indices and HBA2 with different mutations in Beta globin gene\u003c/h2\u003e \u003cp\u003eThe relationship of different mutations with hematological indices is shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The average hemoglobin levels were the lowest in the CD41-42 mutation (7.43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.13) and 619 BP mutation (8.26\u0026thinsp;\u0026plusmn;\u0026thinsp;1.99). The mean hemoglobin of HBE cases (9.77\u0026thinsp;\u0026plusmn;\u0026thinsp;1.20) were higher than general anemia cases (9.21\u0026thinsp;\u0026plusmn;\u0026thinsp;1.73). The mean MCV levels in HBD (82.5\u0026thinsp;\u0026plusmn;\u0026thinsp;6.22) and HBE (76.22\u0026thinsp;\u0026plusmn;\u0026thinsp;6.04) were higher than average for HA (70.49\u0026thinsp;\u0026plusmn;\u0026thinsp;12.38) and in those with anemia (70.35\u0026thinsp;\u0026plusmn;\u0026thinsp;10.71). Similarly, the mean MCH levels in HBD (27.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63) and HBE (25.41\u0026thinsp;\u0026plusmn;\u0026thinsp;3.32) were higher compared to mean for hemolytic anemia (22.67\u0026thinsp;\u0026plusmn;\u0026thinsp;4.84). The Mentzer index also showed higher values, akin to cases with no anemia (20.67\u0026thinsp;\u0026plusmn;\u0026thinsp;6.76) in HBD (27.44\u0026thinsp;\u0026plusmn;\u0026thinsp;6.13) and HBE (21.58\u0026thinsp;\u0026plusmn;\u0026thinsp;2.05). At the same time, it was at its lowest in CD 8\u0026ndash;9 mutation (16.46\u0026thinsp;\u0026plusmn;\u0026thinsp;4.10).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the levels of HbA2 in different mutations of HA. For most of the mutations, the HbA2 levels were in the range of 5-9.9%. IVS 1\u0026ndash;5 was the commonest mutation in the 3.5\u0026ndash;4.9% HbA2 range while the cases with CD26 mutation showed very high levels of HbA2. The mean HBA2 levels in 619BP del and CD 8\u0026ndash;9 mutation was 6.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68 and 5.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64 respectively which was higher compared to IVS 1\u0026ndash;5 (5.19\u0026thinsp;\u0026plusmn;\u0026thinsp;1.83). (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean hematological parameters in all subjects and cases of 5 most common mutations detected\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHaematological parameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHb\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMCV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMCH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHbA2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNo anemia\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(N\u0026thinsp;=\u0026thinsp;2951)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e12.58\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e86.24\u0026thinsp;\u0026plusmn;\u0026thinsp;9.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e29.03\u0026thinsp;\u0026plusmn;\u0026thinsp;5.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e20.67\u0026thinsp;\u0026plusmn;\u0026thinsp;6.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnemia\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(N\u0026thinsp;=\u0026thinsp;4126)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e9.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e70.35\u0026thinsp;\u0026plusmn;\u0026thinsp;10.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e26.48\u0026thinsp;\u0026plusmn;\u0026thinsp;4.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e20.34\u0026thinsp;\u0026plusmn;\u0026thinsp;11.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.10\u0026thinsp;\u0026plusmn;\u0026thinsp;2.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBTT Cases\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(N\u0026thinsp;=\u0026thinsp;315)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e9.21\u0026thinsp;\u0026plusmn;\u0026thinsp;1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e70.49\u0026thinsp;\u0026plusmn;\u0026thinsp;12.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e22.67\u0026thinsp;\u0026plusmn;\u0026thinsp;4.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e19.01\u0026thinsp;\u0026plusmn;\u0026thinsp;4.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.04\u0026thinsp;\u0026plusmn;\u0026thinsp;3.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIVS1-5\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(N\u0026thinsp;=\u0026thinsp;115)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e9.30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e69.71\u0026thinsp;\u0026plusmn;\u0026thinsp;8.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e22.23\u0026thinsp;\u0026plusmn;\u0026thinsp;3.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e17.38\u0026thinsp;\u0026plusmn;\u0026thinsp;4.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.19\u0026thinsp;\u0026plusmn;\u0026thinsp;1.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCD8-9\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(N\u0026thinsp;=\u0026thinsp;18)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e8.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e62.0\u0026thinsp;\u0026plusmn;\u0026thinsp;6.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e20.78\u0026thinsp;\u0026plusmn;\u0026thinsp;4.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e16.46\u0026thinsp;\u0026plusmn;\u0026thinsp;4.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCD26 (HBE)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(N\u0026thinsp;=\u0026thinsp;31)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e9.77\u0026thinsp;\u0026plusmn;\u0026thinsp;1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e76.22\u0026thinsp;\u0026plusmn;\u0026thinsp;6.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e25.41\u0026thinsp;\u0026plusmn;\u0026thinsp;3.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e21.58\u0026thinsp;\u0026plusmn;\u0026thinsp;2.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.92\u0026thinsp;\u0026plusmn;\u0026thinsp;6.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCD41-42\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(N\u0026thinsp;=\u0026thinsp;12)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e7.43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e63.50\u0026thinsp;\u0026plusmn;\u0026thinsp;5.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e20.17\u0026thinsp;\u0026plusmn;\u0026thinsp;2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e17.69\u0026thinsp;\u0026plusmn;\u0026thinsp;2.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e619BP del\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(N\u0026thinsp;=\u0026thinsp;5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e8.26\u0026thinsp;\u0026plusmn;\u0026thinsp;1.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e67.63\u0026thinsp;\u0026plusmn;\u0026thinsp;6.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e21.50\u0026thinsp;\u0026plusmn;\u0026thinsp;2.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e17.21\u0026thinsp;\u0026plusmn;\u0026thinsp;4.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHBD\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(N\u0026thinsp;=\u0026thinsp;7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e9.08\u0026thinsp;\u0026plusmn;\u0026thinsp;2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e82.5\u0026thinsp;\u0026plusmn;\u0026thinsp;6.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e27.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e27.44\u0026thinsp;\u0026plusmn;\u0026thinsp;6.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 With unknown peak\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eOutcome of cases from confirmation of diagnosis to prenatal diagnosis\u003c/h2\u003e \u003cp\u003eThe management of cases from screening to prenatal diagnosis is shown as flowchart in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The HPLC of husband was abnormal in 38/392 (9.7%) cases. A total of 24 couples tested positive for mutations in both partners on ARMS PCR or RFLP PCR. In the rest ten cases, in which the mutation of only one partner was known, the Sanger sequencing /MLPA was done which revealed mutations in both partners in four additional couples.\u003c/p\u003e \u003cp\u003eThe prenatal testing with chorionic villus sampling or amniotic fluid aspiration for confirmation of mutation in the fetus was done in 26 cases, one case refused prenatal testing, and in the other, both partners had CD26 (HBE) mutation, which is not of much consequence even if homozygous, hence only counselling was done. One case had a diamniotic dichorionic twin pregnancy. The report of prenatal testing showed the fetus being affected in 7/27 (25.9%) cases and as trait or no mutation in 20/27 (74.1%). Post-test counselling was done in all cases, and MTP was opted in all 7 cases in which the report was thalassemia major. In one interesting case of dichorionic twin pregnancy, one baby was reported to be affected with thalassemia major while the other baby was trait. Selective reduction was done after consent.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe highlight of the study was the analysis of mutations of the Beta thalassemia gene in a large number of antenatal women from a North Indian population. One in every twenty antenatal women was found to be HA carrier. The relationship of hematological parameters with different mutations of HA, and NDA was delved upon. Among beta thalassemia mutations, IVS1-5 was the most common. There was real-world implementation of a simple algorithm to provide prenatal diagnosis to the couples, which can be useful in low and middle-income countries (LMIC). For every 253 women tested, one with HA trait couple was identified. One thalassemia major case was prevented per 1000 women screened. The challenges faced in the LMIC and the tropical country set up ranged from high incidence of HA carriers in this part of the world to the presence of concomitant NDA cases making the diagnosis difficult. Delay in the antenatal booking was also a hurdle in the management.\u003c/p\u003e\n\u003ch3\u003eHigh incidence of HA carriers in the population\u003c/h3\u003e\n\u003cp\u003eThe National Capital Territory (NCT) of Delhi is a largest metropolitan city in India and is densely populated with an estimated population of 18.6\u0026nbsp;million in 2016 \u003csup\u003e6\u003c/sup\u003e. It has a heterogenous demographic profile significant representation from numerous ethnic groups and religious communities, such as Sindhis, Punjabis, Bengalis, Mahars, Kolis, Saraswats, Lohanas and Gaurs \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. In the present study the incidence of carrier status of hemolytic anemia in antenatal women coming to the tertiary hospital of Delhi was 4.55%, which was higher than the pooled prevalence of beta-thalassemia carriers for Indian population (3.74%, 95% CI 2.52\u0026ndash;4.97) and nearly same as its estimation among tribal groups (4.6%, 95% CI 3.2\u0026ndash;6.2) \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. The higher number of HA in the study may be accounted for by our hospital being a tertiary care center, and receiving many high-risk cases. The prevalence of β-thal trait in central India is estimated to range between 1.4 and 3.4% \u003csup\u003e8\u003c/sup\u003e, in South India, it is between 8.5% and 37.9% \u003csup\u003e9\u003c/sup\u003e. The Northern and Western Indian states have a higher thalassemic burden as it is more prevalent in ethnic communities \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDiagnosis of carrier state late in pregnancy\u003c/h2\u003e \u003cp\u003eScreening for HA should be done during adolescence or premaritally. However, due to lack of awareness and government commitment apart from many other sociodemographic reasons, premarital screening is still in its infancy in India. The antenatal period is considered to be the best practical time to screen as the population comes in contact with the hospital services during this time. It is also the final opportunity to provide a prenatal diagnosis if both partners are traits. In the present study, only one-quarter of women came for antenatal check-up during the first trimester, leading to late diagnosis. Screening for HA should be done early in pregnancy as it requires an algorithm. A concentrated effort towards education and awareness of the coming generations is constantly needed in the complex and heterogeneous Indian population.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eConfrontation in diagnosis due to concurrent NDA\u003c/h2\u003e \u003cp\u003eThe HbA\u003csub\u003e2\u003c/sub\u003e cut-off of 3.5% for HA carriers along with reduced MCV (\u0026lt;\u0026thinsp;80fl) and MCH (\u0026lt;\u0026thinsp;27pg) along with a relatively high RBC count and normal RDW is taken as HA. Due to high Iron deficiency anemia (IDA), the microcytosis and hypochromia due to IDA may blur the HA picture making the diagnosis based on the CBC report alone, a difficult task. In the present study, the majority of HA and NDA had moderate anemia, the MCV levels were significantly low in HA and was a better parameter compared to MCH, similar findings have been observed in other studies also \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. HPLC testing is a useful adjunct as a screening modality of thalassemia, but CBC is needed additionally in cases with HPLC between 3.2\u0026ndash;4.0% \u003csup\u003e11\u003c/sup\u003e, \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. The RBC count and RDW provides vital information, hence, should be analyzed when HBA2 is in the borderline range.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eLimitations of RBC indices in HBD and HBE\u003c/h2\u003e \u003cp\u003eIn HBD carriers, although the mean hemoglobin was found to be low, however, the MCV, MCH, and Mentzer index was in the normal range, hence could be diagnosed with certainty by HPLC only. Similarly, in HBE traits, the indices were lowered only marginally and could not be identified by the Mentzer index but could be diagnosed on HPLC due to the high HbA2 levels. For Beta thalassemia mutations, the Mentzer index was a good parameter to suspect the thalassemia trait. However, borderline/normal HbA\u003csub\u003e2\u003c/sub\u003e levels (3.0\u0026ndash;3.9%) may often lead to a diagnostic dilemma. Previous studies have shown that borderline HbA\u003csub\u003e2\u003c/sub\u003e with near normal or reduced red cell indices is most often due to the cap site\u0026thinsp;+\u0026thinsp;1 (A\u0026thinsp;\u0026gt;\u0026thinsp;C) mutation and the poly-A (T\u0026thinsp;\u0026gt;\u0026thinsp;C) mutation, several other β thalassemia carriers show borderline or normal HbA\u003csub\u003e2\u003c/sub\u003e levels common among them is the presence of δ gene mutations which could reduce HbA\u003csub\u003e2\u003c/sub\u003e levels significantly \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. β genotyping should be done in a couple when one of the partners is a classical carrier of β thalassemia \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eLogistics of screening and molecular test in LMIC\u003c/h2\u003e \u003cp\u003eThe husband was called for HPLC and CBC only when the HPLC report of the wife was abnormal so the burden of doing the husband\u0026rsquo;s HPLC in all 7077 cases could be avoided and was instead performed in 392 cases only. Also, the mutations were required in the 38/7077(0.5%) couples when both partners had abnormal HPLC reports. The Sanger sequencing of beta-globin gene was needed only in 14/7077 (0.2%) couples, and in the rest 24 cases, the mutations could be ascertained on ARMS PCR which is cheaper alternative in terms of consumables and equipment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eRelative distribution of HA mutation in the study population\u003c/h2\u003e \u003cp\u003eMore than 350 different mutations of beta-globin gene have been reported so far \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. However, Many studies have suggested that, the four most common mutations IVS I-5 (G\u0026rarr;C), Codon 41/42 (- TCTT), 619-bp deletion and FS 8/9 (+\u0026thinsp;G) account for nearly 90% of the thalassemia mutations \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. HbS is more frequently observed in the tribal populations, HbE in the eastern region, and HbD in Punjab \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. It is also important to remember that couples at risk of having a baby with certain conditions like HbD-hereditary persistence of fetal hemoglobin (HPFH), HbD-β-thalassemia, and homozygous HbD or HbE disease do not require prenatal diagnosis as they would usually have a very mild clinical presentation and they can lead a normal life \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. In our study also, the prenatal diagnosis was not done as both partners had HBE carrier status \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and weakness of the study\u003c/h2\u003e \u003cp\u003eThe strength of the study was the, prospective inclusion of a large cohort of antenatal women. The detection of the genotype status of the carriers provided the data of the relative distribution of the HA mutations in the population. The weakness could be that the data was hospital based hence selective and thus not easily exploitable to estimate the true burden of the disease.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study highlights the importance of early screening and diagnosis of the carrier status of hemoglobinopathies in antenatal women and their partners coupled with genetic counselling. Nearly one out of every twenty women was found to be the HA carrier, and IVS 1\u0026ndash;5 was the most common mutation. In a developing country like India, high prevalence rates of nutrition deficiency anemia as well as hemoglobinopathies, makes the differentiation difficult. Similar challenges are encountered in the diagnosis of HbE and HbD mutations. Thus, following a targeted and systematic algorithm, is important for channelizing resources especially in low- and middle-income countries.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eMK , ED, VK were involved in planning the research workRG, SM, KB , MZ , MK were involved in execution of the research workMK, RY, RG did the overall supervision of the research and reviewed the manuscriptVK, KB, MK wrote the main manuscript\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAcknowledgment\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is no conflict of interest among authors to declare. The study was funded by Department of Biotechnology, under the UMMID initiative. We thank Ms. Nisha and Mr. Preeti Negi for their support in the project.\u0026nbsp;\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003ethe data will be provided if required\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChandy M. Developing a National Programme for India. In: Control and management of Thalassemia and other Hemoglobinopathies in the Indian Subcontinent_ Synoptic Views. Editor: Ghosh K, Colah R. Published by National institute of Immunohaematology, 2008.\u003c/li\u003e\n\u003cli\u003eMishra KK, Patel P, Bhukhanvala DS, Shah A, Ghosh K. A multiplex ARMS PCR approach to detection of common \u0026beta;-globin gene mutations. Anal Biochem. 2017 Nov 15;537:93\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eVarawalla NY, Old JM, Sarkar R, Venkatesan R, Weatherall DJ. The spectrum of beta-thalassaemia mutations on the Indian subcontinent: the basis for prenatal diagnosis. Br J Haematol. 1991 Jun;78(2):242\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eBashyam MD, Bashyam L, Savithri GR, Gopikrishna M, Sangal V, Devi ARR. Molecular genetic analyses of beta-thalassemia in South India reveals rare mutations in the beta-globin gene. J Hum Genet. 2004;49(8):408\u0026ndash;13.\u003c/li\u003e\n\u003cli\u003eShah PS, Shah ND, Ray HSP, Khatri NB, Vaghasia KK, Raval RJ, et al. Mutation analysis of \u0026beta;-thalassemia in East-Western Indian population: a recent molecular approach. Appl Clin Genet. 2017;10:27\u0026ndash;35.\u003c/li\u003e\n\u003cli\u003ehttps://ncrpb.nic.in/pdf_files/08modified_ch04_demographic_profile.pdf ; \u003c/li\u003e\n\u003cli\u003ePratik Singh, Samir Shaikh, Sagar Parmar \u0026amp; Reeshu Gupta. (2023) Current Status of \u0026beta;-Thalassemic Burden in India. Hemoglobin 47:5, pages 181-190.\u003c/li\u003e\n\u003cli\u003eSumedha, D., Anita, K. Prevalence of beta thalassemia carriers in India: a systematic review and meta-analysis. J Community Genet 14, 527\u0026ndash;541 (2023).\u003c/li\u003e\n\u003cli\u003eYadav SS, Panchal P, Menon KC. Prevalence and Management of \u0026beta;-Thalassemia in India. Hemoglobin. 2022 Jan;46(1):27\u0026ndash;32.\u003c/li\u003e\n\u003cli\u003eColah R, Italia K, Gorakshakar A. Burden of thalassemia in India: The road map for control. Pediatric Hematology Oncology Journal. 2017 Dec 1;2(4):79\u0026ndash;84. \u003c/li\u003e\n\u003cli\u003eBaliyan M, Kumar M, Nangia A, Parakh N. Can RBC Indices be Used as Screening Test for Beta-Thalassemia in Indian Antenatal Women? J Obstet Gynaecol India. 2019 Dec;69(6):495-500. \u003c/li\u003e\n\u003cli\u003eS. Sinha, M.L. Black, S. Agarwal, R. Das, A.H. Bittles, M. Bellgard ThalInd, a \u0026beta; thalassemia and hemoglobinopathies database for India:defining a model country specific and disease centric bioinformatics resource . Hum Mutat, 32 (2011), pp. 887-893\u003c/li\u003e\n\u003cli\u003eGorivale M, Sawant P, Mehta P, Nadkarni A, Ghosh K, Colah R. Challenges in prenatal diagnosis of b thalassemia: couples with normal HbA2 in one partner. Prenat Diagn 2015;35:1353e7.\u003c/li\u003e\n\u003cli\u003eKountouris P, Lederer CW, Fanis P, Feleki X, Old J, Kleanthous M. IthaGenes: an interactive database for haemoglobin variations and epidemiology. PLoS One 2014;9:e103020. \u003c/li\u003e\n\u003cli\u003eMohanty D, Colah RB, Gorakshakar AC, Patel RZ, Master DC, Mahanta J, et al. Prevalence of \u0026beta;-thalassemia and other haemoglobinopathies in six cities in India: a multicentre study. J Community Genet. 2013 Jan;4(1):33\u0026ndash;42.\u003c/li\u003e\n\u003cli\u003eN. Madan, S. Sharma, S.K. Sood, R. Colah, H.M. Bhatia. Frequency of \u0026beta; thalassemia trait and other hemogl obinopathies in northern and western India . Indian J Hum Genet, 16 (2010), pp. 16-25\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Beta thalassemia, mutations of beta globin, thalassemia screening, barriers, HBE, hemolytic anemia","lastPublishedDoi":"10.21203/rs.3.rs-4828384/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4828384/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eHemoglobinopathies are a common group of inherited disorders responsible for a significant global healthcare burden in low- and middle-income countries (LMIC).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e: This cross-sectional study aims to investigate epidemiological, clinical, and genetic aspects of hemolytic anemia in the antenatal population attending a tertiary care hospital in Delhi.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterial and Method\u003c/strong\u003e: A total of 7077 antenatal women were investigated over four years, revealing an overall prevalence of Beta Thalassemia Trait (BTT) of 4.55%. The screening algorithm involved complete blood count and High-Performance Liquid Chromatography (HPLC) for the women, followed by mutation testing using Multiplex ARMS PCR for four common mutations: IVS1-5, CD 41-42, CD 8-9, and Del 619 bp, additionally ARMS PCR, MPLA, and Sanger sequencing were also used. In cases where abnormal HPLC results were found, further testing of the husbands was done to guide counseling and decisions regarding prenatal testing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003eIVS1-5 was identified as the most common mutation. CD 26 exhibited the lowest hemoglobin and highest HbA2 values among all mutations. The study underscores the challenges of using RBC indices, especially in cases with overlapping Nutritional Deficiency Anemia (NDA) and Hemolytic Anemia (HA). Similar challenges were observed with HbD and HbE due to their high MCV and MCH values, the algorithm for antenatal screening and diagnosis for LMIC was ascertained.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003eThe study provides data on the relative distribution of HA mutation in the antenatal population and emphasizes the importance of targeted screening strategies and genetic counseling to reduce the impact of hemoglobinopathies in the region effective.\u003c/p\u003e","manuscriptTitle":"Screening and Diagnosis of hemolytic anemia in North Indian population: Challenges faced","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-16 00:39:48","doi":"10.21203/rs.3.rs-4828384/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5d8eae56-a9a9-4a97-9f0f-65cfd0da3e65","owner":[],"postedDate":"September 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-06T10:08:10+00:00","versionOfRecord":[],"versionCreatedAt":"2024-09-16 00:39:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4828384","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4828384","identity":"rs-4828384","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}