Hemoglobin variants in India: A referral center-based descriptive analysis using high-performance liquid chromatography

Objectives

• To determine the prevalence of various Hb variants among patients referred for screening at a tertiary care center

• To analyze the demographic characteristics and regional distribution patterns of hemoglobinopathies

• To compare our findings with existing literature from other regions of India.

Study design and setting

This retrospective observational study was conducted at Asian Institute of Gastroenterology hospitals, a tertiary healthcare center in Hyderabad, Telangana, over a period of 5 years from October 2019 to October 2024. Asian Institute of Gastroenterology Hospitals is an 800-bed multi-specialty hospital serving as a referral center for patients from across South India and neighboring states.

Ethical approval

This study was declared exempt by the Institutional Ethics Committee (Approval number: AIG/IEC – Post BH and R 64/11.2024-01, dated December 19, 2024). Patient confidentiality was maintained throughout the study, and data were anonymized before analysis.

Study population

Sample size

A total of 3,052 patients were screened during the study period, who met the inclusion criteria and were included in the final analysis.

Sample collection and processing

Whole blood samples (3–5 mL) were collected in ethylenediaminetetraacetic acid-coated vacutainers following standard phlebotomy protocols. Samples were processed within 4–6 h of collection and stored at 2–8°C until analysis.

HPLC analysis screening of Hb variants by HPLC was performed on the Bio-Rad D-10 using the dual kit extended program. This system utilizes cation-exchange chromatography principles for the separation and quantification of Hb fractions.

Principle

HPLC operates by exchanging charged groups on an ion-exchange material with those on the Hb molecule. Hemoglobins were identified based on their retention time, which refers to the duration (in minutes) from sample injection to the peak elution point. The quantification of Hbs was achieved by measuring the area under the corresponding peak in the elution profile.

Quality control

• Daily calibration using Bio-Rad control materials (normal and abnormal levels)

• Participation in external quality assurance programs

• Regular instrument maintenance as per the manufacturer’s guidelines.

Interpretation criteria

Based on the different percentages of HbA, HbA2, HbF, and the presence of other variant peaks, a presumptive diagnosis of various Hb variants was made using the following reference ranges:

• Patients with low HbA2 (<2.0%) suspected to have iron deficiency anemia were confirmed by checking serum ferritin, iron studies, and other relevant parameters from EMR

• Borderline high HbA2 (3.5–4.0%) suspected to have megaloblastic anemia were confirmed by checking vitamin B12, folate levels, and peripheral blood smear findings from EMRs.

Data collection

The following data were collected from EMRs:

• Demographic information: Age, gender, geographic origin, ethnicity

• Clinical information: Presenting symptoms, family history, consanguinity

• Laboratory parameters: Complete blood count (Hb, mean corpuscular volume, mean corpuscular hemoglobin, mean corpuscular hemoglobin concentration), peripheral smear findings, iron studies, vitamin B12, folate levels

• HPLC results: HbA, HbA2, HbF percentages, and variant peak identification.

Statistical analysis

Data were analyzed using the Statistical Package for the Social Sciences version 26.0/R version 4.x. Categorical variables were expressed as frequencies and percentages.

Continuous variables were expressed as mean ± standard deviation or median with interquartile range, depending on data distribution. Chi-square test was used for comparing categorical variables. P < 0.05 was considered statistically significant.

Demographic characteristics

A total of 3052 patients were included in the study. The mean age was (36) ± (16) years (range: 6–70 years). 62.1% were males and 37.9% were females [Table 1]. The majority of patients were from West Bengal (39.8%), followed by Telangana (18.9%), Assam (17.0%), Andhra Pradesh (5.0%), Jharkhand (5.0%), and other states.

Distribution of specific Hb variants [Figure 1]

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Figure 1:

Overall distribution of hemoglobin patterns distribution of hemoglobin (Hb) patterns among 3,052 patients screened using high-performance liquid chromatography at AIG Hospitals, Hyderabad, Telangana (October 2019–October 2024). The pie chart demonstrates that 48.53% of the study population had abnormal Hb patterns. Beta Thalassemia Trait was the most common variant (36.39%), followed by HbE Homozygous (20.66%) and HbE Heterozygous (14.44%). The high prevalence of hemoglobinopathies reflects both the referral nature of the tertiary care center and the geographic diversity of the patient population, particularly from endemic regions of Eastern India.

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• Beta thalassemia trait: 36.39% (most common variant)

• Characterized by HbA2 >3.5% with or without elevated HbF

• HbE disease:

  • Homozygous: 20.66%

  • Heterozygous: 14.44%

  • Total HbE prevalence: 35.10%

• Sickle cell disease: 2.43%

• Predominantly HbSS genotype

• Sickle cell trait: 2.76%

• HbAS genotype

• Other variants: 19.82% (including HbD Punjab, HbQ India, and rare variants).

Regional distribution

Beta thalassemia trait and HbE disease

Higher prevalence observed in patients from West Bengal and Assam. This correlates with known endemic zones in Eastern India [Figures 2 and 3].^[13,14]

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Figure 2:

Regional distribution of Beta Thalassemia Trait among 539 identified cases. West Bengal showed the highest prevalence (43.78%, n = 236), followed by Telangana (17.07%, n = 92) and Assam (10.39%, n = 56). This distribution reflects the known endemic zones of beta thalassemia in Eastern and Southern India. The high concentration in West Bengal is consistent with previous studies reporting prevalence rates ranging from 3.92% to 57.5% in various populations of West Bengal. The geographic clustering emphasizes the need for region-specific screening programs and genetic counselling services, particularly in high prevalence areas.

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Figure 3:

Regional distribution of hemoglobin E (HbE) variants (homozygous and heterozygous) showing marked concentration in Eastern India. Both HbE homozygous and HbE heterozygous cases were predominantly found in West Bengal (homozygous: 64.94%, n = 200; heterozygous: 51.87%, n = 111) and Assam (homozygous: 29.87%, n = 92; heterozygous: 37.38%, n = 80). Together, these two states account for over 90% of all HbE cases in the study. This distribution is consistent with the known high prevalence of HbE in north-eastern regions of India, where carrier frequencies range from 5% to 50%, and certain communities in Assam show prevalence rates as high as 41.1–66.7%. The geographic clustering highlights the importance of HbE screening in Eastern Indian populations and counseling for HbE-beta thalassemia risk.

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Sickle cell disease and trait

Sickle cell disease and sickle cell trait were more frequently observed among patients referred from Odisha, Jharkhand, and Telangana. This distribution aligns with the known predominance of sickle hemoglobinopathies in the tribal belt regions of Central and Eastern India [Figure 4].

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Figure 4:

Regional distribution of sickle cell disease (SCD) and sickle cell trait (SCT) showing higher concentration in the central Indian tribal belt. SCD was notably higher in Odisha (17.14%), Jharkhand (20.00%), and Telangana (22.86%), while SCT showed considerable presence in Chhattisgarh (31.71%) and Telangana (26.83%). This distribution aligns with the known “sickle cell belt” extending across peninsular southern, south-eastern, central, and south-western India, particularly affecting tribal populations. The geographic pattern underscores the importance of targeted screening in high-prevalence regions and implementation of comprehensive sickle cell disease management programs, including hydroxyurea therapy, vaccination, and patient education.

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Statistical significance

Regional variations in Hb variant distribution were statistically significant (P < 0.001), reflecting the ethnic and geographic diversity of the Indian population. “These findings represent proportions among referred patients and are not indicative of population-level prevalence.”

“Note: Data reflect referral bias and may include related individuals. Findings should be interpreted accordingly.”

Prevalence of Hb variants

Our study demonstrates that 48.5% of patients referred for Hb variant screening had abnormal patterns. This high prevalence is consistent with India’s status as one of the countries with the highest burden of hemoglobinopathies globally [Tables 2, 3 and Table S1].^[6,15]

Beta thalassemia trait (36.39%)

Beta thalassemia trait was the most prevalent variant in our study, affecting nearly one in six screened patients. This finding aligns with previous studies from Northern and Western India reporting prevalence rates of 1.8–17% in various populations.^[16,17] The high carrier frequency emphasizes the critical need for premarital screening and genetic counseling programs to prevent births of children with beta thalassemia major, which requires lifelong transfusion therapy.

HbE disease (35.10% combined)

The high frequency of HbE homozygotes relative to heterozygotes is atypical and likely reflects referral bias, where symptomatic individuals are more likely to be tested. Similarly, the observed regional clustering of variants aligns with known epidemiological patterns but should be interpreted cautiously due to the non-random nature of the sample [Figure 3].

The substantial prevalence of HbE disease (20.66% homozygous and 14.44% heterozygous) in our cohort is noteworthy. HbE is particularly common in populations from Eastern India and Southeast Asia.^[13,14] The high proportion of patients from West Bengal and Assam in our study likely explains this elevated prevalence. HbE trait is generally asymptomatic, but homozygous HbE disease can cause mild to moderate hemolytic anemia. Sickle cell disease and trait (5.2% combined) [Figure 1].

Sickle cell disease and trait

The prevalence of sickle cell disease (2.43%) and trait (2.76%) in our study reflects the endemic nature of this condition in Central India, particularly among tribal populations. The geographic clustering in patients from Odisha, Jharkhand, and Telangana is consistent with the known “sickle cell belt” extending across these states [Figures 4 and 5]. Early identification is crucial for implementing preventive strategies, including hydroxyurea therapy, vaccination, and patient education to reduce morbidity and mortality.

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Figure 5:

Comparison of hemoglobin (Hb) variant prevalence between the present hospital-based study and national population-level estimates. The higher prevalence of Beta Thalassemia Trait (17.66% vs. 3.5% national estimate) and HbE Disease (17.10% vs. 7.5% national estimate) in our study reflects referral bias, as patients with suspected hemoglobinopathies are more likely to be referred to tertiary care centers. In addition, the geographic representation of our study population, with higher proportions from endemic regions such as West Bengal and Assam, contributes to elevated prevalence rates. Sickle cell disease prevalence (1.15%) is comparable to the national estimate (1.17%), while sickle cell trait (1.34%) is lower than the national estimate (5.9%), possibly due to underrepresentation of specific tribal communities in our hospital-based cohort. These findings emphasize the importance of distinguishing between hospital-based and population-based prevalence estimates when planning public health interventions

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Regional variations

The significant regional variations observed in our study reflect India’s remarkable genetic diversity. Historical migration patterns, endogamous marriage practices, and selective evolutionary pressure from malaria have contributed to distinct geographic distributions of Hb variants.^[6,18] The higher prevalence of HbE in Eastern Indian populations and sickle cell disease in Central Indian tribal communities highlights the importance of region-specific screening strategies and public health interventions [Figures 3 and 4].

Our findings are broadly consistent with previous studies from different regions of India: Shrivastav et al.^[8] reported hemoglobinopathies in Western India with similar prevalence patterns, Mondal and Mandal^[14] documented high HbE prevalence in Eastern India (119,336 cases over 10 years), and Chaudhury et al.^[13] reported spectrum of variants in Eastern India (14,145 cases). Recent studies from Karnataka by Putchen et al.^[19] showed comparable regional distributions. However, variations in study populations, screening criteria, and geographic coverage limit direct comparisons [Table 4].

Clinical implications

Public health perspective

Integration of hospital-based surveillance data with national health programs is crucial for mapping disease burden and high-prevalence regions, planning resource allocation for specialized treatment centers, developing targeted prevention strategies, and monitoring program effectiveness [Figure 5]. The National Health Mission’s initiatives for hemoglobinopathy control would benefit from systematic data collection from tertiary care centers like ours.

Strengths and limitations