Gene Mutation Spectrum among Alpha-Thalassaemia Patients in Northeast Peninsular Malaysia

Multi-criteria decision making to validate performance of RBC-based formulae to screen [Formula: see text]-thalassemia trait in heterogeneous haemoglobinopathies

BACKGROUND

India has the most significant number of children with thalassemia major worldwide, and about 10,000-15,000 children with the disease are born yearly. Scaling up e-health initiatives in rural areas using a cost-effective digital tool to provide healthcare access for all sections of people remains a challenge for government or semi-governmental institutions and agencies.

METHODS

We compared the performance of a recently developed formula SCS[Formula: see text] and its web application SUSOKA with 42 discrimination formulae presently available in the literature. 6,388 samples were collected from the Postgraduate Institute of Medical Education and Research, Chandigarh, in North-Western India. Performances of the formulae were evaluated by eight different measures: sensitivity, specificity, Youden's Index, AUC-ROC, accuracy, positive predictive value, negative predictive value, and false omission rate. Three multi-criteria decision-making (MCDM) methods, TOPSIS, COPRAS, and SECA, were implemented to rank formulae by ensuring a trade-off among the eight measures.

RESULTS

MCDM methods revealed that the Shine & Lal and SCS[Formula: see text] were the best-performing formulae. Further, a modification of the SCS[Formula: see text] formula was proposed, and validation was conducted with a data set containing 939 samples collected from Nil Ratan Sircar (NRS) Medical College and Hospital, Kolkata, in Eastern India. Our two-step approach emphasized the necessity of a molecular diagnosis for a lower number of the population. SCS[Formula: see text] along with the condition MCV[Formula: see text] 80 fl was recommended for a higher heterogeneous population set. It was found that SCS[Formula: see text] can classify all BTT samples with 100% sensitivity when MCV[Formula: see text] 80 fl.

CONCLUSIONS

We addressed the issue of how to integrate the higher-ranked formulae in mass screening to ensure higher performance through the MCDM approach. In real-life practice, it is sufficient for a screening algorithm to flag a particular sample as requiring or not requiring further specific confirmatory testing. Implementing discriminate functions in routine screening programs allows early identification; consequently, the cost will decrease, and the turnaround time in everyday workflows will also increase. Our proposed two-step procedure expedites such a process. It is concluded that for mass screening of BTT in a heterogeneous set of data, SCS[Formula: see text] and its web application SUSOKA can provide 100% sensitivity when MCV[Formula: see text] 80 fl.

Characterization of New Alpha Zero (α0) Thalassaemia Deletion (--GB) among Malays in Malaysian Population

Malaysia is a multicultural and multiethnic country comprising numerous ethnic groups. From the total population of 32.7 million, Malays form the bulk of the Bumiputera in Malaysia comprise about 69.9%, followed by Chinese 22.8%, Indian 6.6%, and others 0.7%. The heterogeneous population and increasing numbers of non-citizens in this country affects the heterogeneity of genetic diseases, diversity, and heterogeneity of thalassaemia mutations. Alpha (α)-thalassaemia is an inherited haemoglobin disorder characterized by hypochromic microcytic anaemia caused by a quantitative reduction in the α-globin chain. A majority of the α-thalassaemia are caused by deletions in the α-globin gene cluster. Among Malays, the most common deletional alpha thalassaemia is -α3.7 deletion followed by --SEA deletion. We described the molecular characterization of a new --GB deletion in our population, involving both alpha genes in cis. Interestingly, we found that this mutation is unique among Malay ethnicities. It is important to diagnose this deletion because of the 25% risk of Hb Bart's with hydrops fetalis in the offspring when in combination with another α0- thalassaemia allele. MLPA is a suitable method to detect unknown and uncommon deletions and to characterize those cases which remain unresolved after a standard diagnostic approach.