Trends in the Development of Diagnostic Tools for Red Blood Cell-Related Diseases and Anemias

Abstract

In the recent years, the progress in genetic analysis and next-generation sequencing technologies have opened up exciting landscapes for diagnosis and study of molecular mechanisms, allowing the determination of a particular mutation for individual patients suffering from hereditary red blood cell-related diseases or anemia. However, the huge amount of data obtained makes the interpretation of the results and the identification of the pathogenetic variant responsible for the diseases sometime difficult. Moreover, there is increasing evidence that the same mutation can result in varying cellular properties and different symptoms of the disease. Even for the same patient, the phenotypic expression of the disorder can change over time. Therefore, on top of genetic analysis, there is a further request for functional tests that allow to confirm the pathogenicity of a molecular variant, possibly to predict prognosis and complications (e.g., vaso-occlusive pain crises or other thrombotic events) and, in the best case, to enable personalized theranostics (drug and/or dose) according to the disease state and progression. The mini-review will reflect recent and future directions in the development of diagnostic tools for red blood cell-related diseases and anemias. This includes point of care devices, new incarnations of well-known principles addressing physico-chemical properties, and interactions of red blood cells as well as high-tech screening equipment and mobile laboratories.

Keywords: artificial intelligence; functional screening; mobile laboratory; personalized medication; physico-chemical properties; point of care; sickle cell disease.

FIGURE 1

Analysis of RBC membrane disorders and other rare haemolytic anaemias by ektacytometry analysis. (A) Image of the Laser Optical Rotational Red Cell Analyzer (LoRRca Maxsis RR Mechatronics, Netherlands). (B) List of key parameters analyzed by the instruments. (C) Osmoscan profile in normal subjects and parameters analyzed: the Omin value represents the 50% of the RBCs hemolysis in conventional osmotic fragility assays, reflecting mean cellular surface-to volume ratio; the Elongation Index (EI) max corresponds to the maximal deformability obtained near the isotonic osmolality and is an expression of the membrane surface; the Ohyper reflects mean cellular hydration status; the AUC correspond to the area under the curve beginning from a starting point in the hypo-osmolar region and an ending point in the hyper-osmolar region. (D) Examples of typical osmoscan profiles in hemolytic anemias resulting from the analysis of 202 patients affected by congenital hemolytic anemia of different etiology. Continuous line represents a daily control and shaded area the control range curve. (a) HS = hereditary spherocytosis, (b) HE = hereditary elliptocytosis, (c) HSt = hereditary stomatocytosis: HSt-PIEZO1 (hereditary xerocytosis) (dotted line), HSt-KCNN4 (Gardos channelopathy) (dashed line), (d) CDAII = congenital diserythropoietic anemia type II, (e) RBC enzymopathies (pyruvate kinase deficiency), (f) other rarer RBC enzymopathies (glucosephosphate isomerase deficiency). Panels (A) and (C) are reproduced with permission from RR Mechatronics. Panels (D) is reproduced from Zaninoni et al. (2018).

FIGURE 2

Diagnosis of a novel PIEZO mutation with automated patch-clamp technology. (A) Image of the SyncroPatch device (Nanion Technologies, Munich, Germany). (B) List of key parameters of the SyncroPatch. (C) Illustration of a novel mutation (R2110W) of the Piezo 1 ion channel. Although detected per se, it was unknown if the mutation has a functional effect on the red blood cells. Orange areas represent regions affected by previously reported mutations. (D) Raw data traces of a red blood cell recording for illustration. Yoda1 is a specific activator of Piezo 1. The gray bar depicts the time point (= membrane potential), which was used for the statistical analysis. (E) Statistical analysis of all measured cells (R2110W mutation vs. control) to exemplify the functional impact of the mutation. n gives the number of successful measured and analyzed cells. (A) Reproduced with permission from Nanion Technologies. (C–E) Reproduced from Rotordam et al. (2019) with permission of the Ferrata Storti Foundation.