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Discrimination of common inherited blood disorders using fluorescence spectra of premarital blood samples – A double blind study
*Corresponding author E-mail address: dsandhana@ksu.edu.sa (S Devanesan)
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Received: ,
Accepted: ,
Abstract
Blood plasma contains several amino acids and enzymes, some of which are fluorescent. In this study, synchronous fluorescence excitation spectroscopy (SFXS) was employed to detect inherited blood disorders, such as sickle cell trait (SCT), sickle cell disease (SCD), thalassemia trait (TT), and thalassemia disease (TD), in a batch of 67 blood samples enlisted for premarital screening. Spectral screening was performed by calculating the relative intensities of specific fluorescent biomarkers in the blood plasma of each participant. The four crucial biomarkers were tryptophan with a fluorescence excitation peak at approximately 290 nm, NADH at approximately 360 nm, FAD at 450 nm, and bile pigments at 520 nm. Because this was a double-blind study, half of the same set of blood samples underwent the conventional high-performance liquid chromatography (HPLC) detection procedure. On comparing these two blinded results, it was found that the detection of the spectral technique scored 5/5 for SCD and TD, 1/1 for TT, 1/3 for SCT, 56/57 for the normal group, and 1 spectral feature outside the expected. Thus, the SFXS technique showed 78% sensitivity, 98% specificity, and an overall accuracy of 88%. The above technique could be transformed into a simple, portable, inexpensive, and useful instrument for point-of-care and premarital screening of inherited blood disorders.
Keywords
Blood plasma
Fluorescent biomarkers
Inherited blood disorders
Synchronous fluorescence excitation spectra
1. Introduction
Among several hemoglobinopathies such as sickle cell disease (SCD), thalassemia disease (TD), hemophilia, platelet disorders, and thrombophilia, the first two are more debilitating and serious than others. Moreover, these two are mostly preventable as simple premarital screening could identify the carriers of these diseases, and counselling against marriage between the two carriers is the smartest way of avoiding future suffering for the children and parents. Therefore, premarital screening and counselling have become mandatory worldwide, particularly in Arabian, Asian, and African countries (Alkalbani, et al., 2022). According to a recent study, the prevalence rate of sickle cell trait (SCT) or disease (SCD) was comparatively stable; however, the number of newborns born with SCD has increased in the Caribbean and Western and Central Sub-Saharan Africa (Weatherall, et al., 2006; El Hasbani, et al., 2022; Gupta, et al., 2024; McGann, et al., 2017; GBD 2021). Worldwide, the prevalence of thalassemia has increased marginally in recent years (Lee, et al., 2022). In 2020, a high volume of cases (approximately 12-50% for α-thalassemia and up to 20% for β-thalassemia) have been recorded in Southeast Asia, the Mediterranean, the Indian subcontinent, and Africa (Goh, et al., 2020; Sayani and Kwiatkowski, 2015).
The general population in Saudi Arabia has a high prevalence of genetic disorders due to consanguineous marriages (Dahbi, et al, 2024). A recent study noted that the prevalence rate was higher in rural rather than in urban areas owing to the reduction in consanguineous marriages among the educated masses (Al-Shroby, et al., 2021; Hussain, 2004; Bittles, 2002). Common premarital screening laboratory tests are based on basic blood biochemistry measurements and electrophoresis, and because of expensive experimental specialties, many poor and developing countries have not been able to implement these premarital tests as per requirements (lmomani, et al., 2023, Mohd Nor, et al., 2022). We employed a simple and inexpensive fluorescence spectroscopy technique to diagnose blood disorders using fluorescent biomarkers. Fluorescence spectroscopy is an electromagnetic technique that plays a major role in the diagnosis of blood samples containing fluorescent biomolecules.
The major fluorescent biomarkers of blood samples are amino acids such as tyrosine and tryptophan, enzymes such as nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD), and hemoglobin decay products such as bile pigments (Li, et al., 2006; AlSalhi, et al., 2018; Masilamani, et al., 2020; Devanesan, et al., 2021; Masilamani, et al., 2016). The three aromatic amino acids, tyrosine, phenylalanine, and tryptophan, are involved in protein synthesis and transportation by the immune system (Shirahata et al., 1992.). NAD+/NADH coenzymes are involved in metabolic processes, particularly cellular pathways (Amjad. et al., 2021). FAD is a flavoprotein oxidoreductase involved in mitochondrial function and redox processes. Mitochondrial dysfunction leads to loss of homeostasis, which affects the internal stability of cells (Brand, et al., 2013). These fluorescent biomolecules are intimately involved in redox reactions during the maintenance and decay of blood components.
The first step of our investigation was to calibrate our instrument and standardize the spectral data, that is, to measure the relative proportion of the above four fluorescent biomarkers in known cases of inherited blood disorders and normal controls (Li, et al., 2006; AlSalhi, et al., 2018; Masilamani, et al., 2020; Devanesan, et al., 2021; Masilamani, et al., 2016). The objective of this study was to conduct a field test using unknown double-blinded sets. We analyzed premarital cases using blood plasma samples from the synchronous excitation spectra of each individual. The spectral deviations and relative intensity values of the aromatic amino acids, proteins, and coenzymes were calculated. Sample collection and blinding procedures were performed by a senior hematologist, and all analyses were performed on fresh samples on the same day.
2. Materials and Methods
Blood samples were collected from those seeking premarital screening at King Khalid University Hospital, Riyadh, who were apparently healthy, as per their own declaration and individual approvals. The renewed Institutional Review Board approval for this investigation was E-17−2267.
2.1 Sample collection and processing
A total of 67 double-blind blood samples were collected from individuals aged 19 to 35 years (35 men and 32 women). The samples were drawn into EDTA vials, gently rocked, and centrifuged at 3000 rpm for 15 min. The supernatant greenish-yellow blood plasma was pipetted off and collected in an Eppendorf tube without any disturbance to the buffy coat (which contains WBC) and the bottom RBC sediment. Fresh blood plasma was transferred in an icebox to a physics research lab in the other wing of the same university, without any mechanical disturbance, and the experiments were performed on the same day. Fresh blood plasma (1.5 mL) was poured into a fluorescent quartz cuvette, and the instrument was run at a chosen wavelength of 200-800 nm at a scan speed of 1000 nm/min. This set of parameters could present the relative intensities of the excitation spectra of all four relevant fluorescent biomarkers (tryptophan, NADH, FAD, and bile pigments) of blood plasma. The spectral data were interpreted according to the fluorescent biomarker concentrations in the premarital blood plasma samples.
2.2 Instrumentation
The crucial instrument was the LS55 fluorescence spectrophotometer made by PerkinElmer (USA), working with the WINLAB software. The instrument LS55 fluorescence spectrophotometer could carry out all the variants of fluorescence spectroscopy (emission, excitation, synchronous fluorescence emission spectra, and synchronous fluorescence excitation spectra- SFXS). This particular report pertains to the SFXS obtained with an offset wavelength of Δλ= 70 nm to obtain the fluorescence excitation band of every molecule in the predetermined wavelength range of 200-800 nm with a scan speed of 1000 nm/min. Light of a specified wavelength with a spectral width of 10 nm and a spot size of 3 by 2 mm was allowed to fall on the sample taken in the quartz cuvette. The power at the point of illumination was around 20 W, which was far too low to induce photo bleaching. This was confirmed by repeating the experiment in triplicate for each sample, wherein no spectral difference was observed (Alfano and Yang, 2003; Alfano, et al., 1984). The synchronous excitation spectra (Δλ=70 nm), as a more reliable observation, were recorded in the double-blinded samples.
2.3 Statistical performance
Spectral data were collected using the WINLAB software, plotted with Origin 2018, and analyzed with basic statistical calculations, including mean and standard deviation, with a significance level of p < 0.05.
3. Results
Fluorescence spectroscopy is a useful tool for the diagnosis of several diseases, particularly blood disorders. The method allows for the identification, quantification, and characterization of blood components, including bio-fluorophores. The instrument could be helpful to discriminate samples based on the fluorescent biomolecules. Fig. 1 shows a set of SFXS for known normal control samples. The four peaks for the four fluorescent blood components are consecutively at 290 nm, 360 nm, 450 nm, and finally a shoulder at 520 nm. The first peak (at 290 nm) was attributed to the essential amino acid tryptophan. It is an α-amino acid that is used in the biosynthesis of proteins. Tryptophan contains an α-amino group, α-carboxylic acid group, and a side chain indole, making it a polar molecule with a non-polar aromatic β-carbon substituent. The second peak at 360 nm was attributed to NADH. It is a universal coenzyme that plays a key role in cellular metabolism. It acts as a donor and acceptor of electrons in redox reactions within eukaryotic cells, and influences various enzymes and processes. The third peak at 450 nm was attributed to FAD. NADH and FAD are the two cofactors involved in cellular respiration. They are responsible for accepting “high-energy” electrons and carrying them ultimately to the electron transport chain, where they are used to synthesize ATP molecules. The last weak shoulder at 520 nm is attributed to bile pigments, such as biliverdin and bilirubin, which are tetrapyrrolic water-soluble compounds formed by the breakdown of heme.

- Synchronous excitation fluorescence spectra (Δλ=70 nm) of blood plasma of a normal control chosen from 56 samples.
A total of 67 blood plasma sample spectral features were recorded; of these, 56 had spectral features closely similar to those of normal controls. Spectra were extracted from the spectral features of each sample. These discriminations were based on relative intensity values, with a minimum of 200 a.u. and an average relative intensity of 283.25. The fluorescent values of tryptophan, NADH, FAD, and bile pigments were 283.25, 94.11, 45.10, and 17.22, respectively. Furthermore, the spectral ratio parameter intensity values were R1 = tryptophan/NADH, R2 = NADH/FAD, and R3 = FAD/bile pigments. The relative intensity values were R1 = 3.00 ± 0.84, R2 = 2.47 ± 0.41, and R3 = 2.6 ± 0.05.
The synchronous excitation spectra of blood disorder trait samples have been shown in Fig. 2. Out of the 67 double-blind samples, one sample had spectral features similar to the SCT (Fig. 2a) and was confirmed by a medical practitioner. It shows four peaks: one around 290 nm, next at 360 nm, then at 450 nm, and finally a shoulder at 520 nm, similar to the normal control but without the proportion of relative intensities R1 = 1.2 ± 0.15; R2 = 0.8 ± 0.02; R3 = 2.3 ±0.19; in addition, the intensities of all the peaks are many times lower than the normal. For example, the mean value of the 290-nm peak for the control was 283; in contrast, for SCT, it was only 120, almost 2.4 times lower. The glaring contrast between the normal and thalassemia trait (TT) groups, and between the SCT and TT groups, is well-discernible. Furthermore, four peaks similar to those observed for the control were observed; however, the spectrum was grossly distorted, as shown in Fig. 2b. Thus, the intensity at the 290 nm peak is four times lower than normal, and the ratio parameters are distinctly different with R1 = 3.00 ± 0.24; R2 = 0.17 ± 0.11; and R3 = 1.4 ± 0.52.

- Synchronous excitation fluorescence spectra (Δλ = 70) of blood samples of (a) SCT and (b) TT.
When we calibrated the spectral parameters from known cases of SCD or TD, the spectral shapes were distorted, as shown in Fig. 3. Fig. 3(a) shows that the SFXS of the SCD spectral features of disease samples were entirely different from those of the control and trait samples. The intensity values of tryptophan were drastically reduced, and those of the coenzyme were enhanced. For the SCD, the fluorescence spectra of tryptophan, NADH, FAD, and bile pigments were 16.1, 7.8, 14.1, and 14.0, respectively. The ratio parameter was set as R1 = 2. 10 ± 0.07; R2 = 0.52 ± 0.21; and R3 = 1.3 ± 0.09.

- Synchronous excitation spectra of (Δλ= 70) of blood plasma of (a) SCD and (b) TD.
The typical SFXS of blood disorders in TD have been shown in Fig. 3(b). The similarities between the two spectra were unmistakable, and the latter was found to be correct using conventional analysis. The tryptophan level was < 12, and the band for NADH was almost absent. FAD and bile pigment levels were elevated 15-fold compared to NADH and were 2-fold higher than tryptophan levels. The ratio parameters were: R1 = 12.00 ± 0.06; R2 = 0.007 ± 0.01; and R3 = 1.55 ± 0.04.
Another special case that is rarely encountered was the combination of SCD and TD. Fig. 4 shows the spectra of one individual that we correctly identified as SCD + TD using our calibrated data. The tryptophan intensity values were reduced to 6, and the entire spectrum was dominated by emissions from FAD and bile pigments. The intensity values for tryptophan, NADH, FAD, and bile pigments were 5.80, 4.41, 41.85, and 18.15, respectively.

- Synchronous excitation spectra of (Δλ= 70) of blood plasma both symptoms of SCD/TD.
The histogram in Fig. 5 shows the intensity of tryptophan in the normal control, SCT, TT, SCD, TD, and SCD/TD groups. The results clearly exhibited significant differences in each case. The spectral intensities of the fluorescent biomolecules obtained from known cases and employed for identification in the blinded set have been listed in Table 1.

- Histogram image from Synchronous excitation fluorescence spectra (Δλ =70 nm) of blood plasma of normal control, SCT, TT, SCD, TD and SCD/TD.
| Sample | Tryptophan | NADH | FAD | Bile pigments |
|---|---|---|---|---|
| Normal | 283.25 | 94.11 | 45.10 | 17.22 |
| SCT | 117.50 | 98.50 | 123.00 | 54.00 |
| TT | 87.50 | 29.00 | 139.50 | 71.00 |
| SCD | 16.00 | 7.60 | 14.50 | 11.00 |
| TD | 9.15 | 0.15 | 19.40 | 12.50 |
| SCD/TD | 5.80 | 4.41 | 41.85 | 18.50 |
With these parameters as the guidelines for our field trial and double-blind study, we had analyzed a total of 67 samples over a period of 3 months. On comparing these two blinded results, we found that detection of inherited blood disorder for premarital screening by spectral technique scored 5/5 for SCD and TD, 1/1 for TT, and 1/3 for SCT. Sensitivity and specificity were calculated; Sensitivity = TP/(TP + FN) = 7/9 = 78%; and Specificity = TN/(TN + FP)= 56/57 = 98%) and overall accuracy = (78+98)/2 = 88%. The conventional method (high-performance liquid chromatography: HPLC) of the 67 tested samples has been reported in Table 2. After comparison of HPLC and spectral data, the SFXS technique is reliable for discriminating blood disorders in premarital cases.
| Sample no. | Spectral observation | Medical records | True/False |
|---|---|---|---|
| 1 | Normal | Medical free | True |
| 2 | SCD/TD | Sickle-β-thalassemia disease | True |
| 3 | Normal | Medical free (Hypertension) | True |
| 4 | Normal | Medical free | True |
| 5 | Normal | Medical free (hypothyroidism) | True |
| 6 | Normal/IDA | Medical free (Iron-deficiency anemia) | True |
| 7 | Normal | Medical free (Gestational diabetes mellitus (GDM)) | True |
| 8 | Normal | Medical free | True |
| 9 | Normal | Medical free (Hypothyroidism) | True |
| 10 | Normal | Medical free | True |
| 11 | Normal | Medical free | True |
| 12 | Normal | Medical free | True |
| 13 | Normal | Medical free | True |
| 14 | Normal | Medical free | True |
| 15 | Normal | Medical free | True |
| 16 | Normal | Medical free | True |
| 17 | Normal | Medical free | True |
| 18 | Normal | Medical free | True |
| 19 | Normal | Medical free | True |
| 20 | Normal | Medical free | True |
| 21 | TD | Thalassemia Disease | True |
| 22 | Normal | Medical free | True |
| 23 | Normal | Medical free | True |
| 24 | Normal | Medical free | True |
| 25 | Normal | Medical free (Iron deficiency anemia | True |
| 26 | Normal | Medical free | True |
| 27 | Normal | Medical free | True |
| 28 | Out of spectral features | Medical free (HYPOTHYROIDISM & polycystic ovary syndrome)- | NA |
| 29 | Normal | Medical free | True |
| 30 | Normal | Medical free (Gestational diabetes) | True |
| 31 | Normal | Medical free (Hypothyroidism) | True |
| 32 | Normal | Medical free | True |
| 33 | Normal | Medical free | True |
| 34 | Normal | Medical free | True |
| 35 | SCD | Sickle Cell Disorder | True |
| 36 | TT | Medical free - a heavy smoker | FALSE |
| 37 | SCT | Sickle cell trait | True |
| 38 | Normal | Sickle cell trait | FALSE |
| 39 | Normal | Medical free -high Hemoglobin C level | True |
| 40 | Normal | Sickle cell trait | FALSE |
| 41 | SCD/TD | Sickle beta -thalassemia disease | True |
| 42 | TD | Thalassemia Disease | True |
| 43 | Normal | Medical free | True |
| 44 | Normal | Medical free (Iron-deficiency anemia) | True |
| 45 | Normal | Medical free | True |
| 46 | Normal | Medical free | True |
| 47 | Normal | Medical free | True |
| 48 | Normal | Medical free | True |
| 49 | Normal | Medical free | True |
| 50 | Normal | Medical free | True |
| 51 | Normal | Medical free | True |
| 52 | Normal | Medical free | True |
| 53 | Normal | Medical free | True |
| 54 | Normal | Medical free | True |
| 55 | Normal | Medical free | True |
| 56 | Normal | Medical free | True |
| 57 | Normal | Medical free | True |
| 58 | Normal | Medical free | True |
| 59 | Normal | Medical free | True |
| 60 | Normal | Medical free | True |
| 61 | Normal | Medical free | True |
| 62 | Normal | Medical free | True |
| 63 | Normal | Medical free | True |
| 64 | Norma | Medical free | True |
| 65 | Normal | Medical free | True |
| 66 | Normal | Medical free | True |
| 67 | Normal | Medical free | True |
4. Discussion
Over the past few decades, many efforts have been taken worldwide to prevent blood disorders (Al-Shroby, et al., 2021; Fareed, & Afzal, 2017; Rouh AlDeen, et al., 2021; Memish, & Saeedi, 2011). These programs were initiated to develop new and innovative techniques for diagnosing blood diseases and reducing the number of new cases (Almasmoum, et al., 2022). Premarital diagnosis plays a major role in avoiding high-risk in developing countries worldwide. Several countries lack infrastructure for conventional techniques, owing to high expenses and limited availability of equipped laboratories (Chakravorty, & Dick, 2019).
Spectral observations of the normal control, SCT, TT, SCD, TD, and SC/TD samples showed reduced relative intensity values compared to normal controls, indicating the decomposition of biomolecules. Fluorescent biomolecule level elevations and decay products were present in the abnormal blood samples. The trait samples showed 50% lower fluorescence intensity than the normal control, whereas the diseases were >200-fold lower in the spectral region 290-305 nm (tryptophan). A similar technique was reported to differentiate between healthy individuals and those with Alzheimer’s disease (Dos Santos, et al., 2022.). Moreover, Resonance Raman spectroscopy could be useful for observing oxidative phosphorylation levels in blood disorders (Dybas, et al., 2020.). Another study reported a spectrofluorimetric method to quantify fluorescent biomolecules using spectral wavelengths of 295 and 431 nm in human plasma (Hassan, et al., 2023).
The NADH volume quantified in normal controls was 94.11, whereas TT was 3.25-fold lower, SCT was closer, and SCD and SC/TD cases were > 20-fold lower; furthermore, TD cases were almost absent (> 100-fold lower). In thalassemia cases, NADH levels are highly reduced owing to the high demand to inhibit oxidative action (Ogasawara, et al., 2008). Owing to hemolysis in the SCT, SCD, and SCD/TD cases, NADH intensity was reduced. The extracellular fluorophore FAD was quantified, and the relative intensity volume was highly elevated in SCT, TT, SCD, TD, and SCD/TD cases owing to excess damage in red blood cells exposed to decay products in the blood plasma (Salem, et al., 2023.). FAD was highly affected in patients with blood disorders than in normal controls due to the excess stimulation of FAD-dependent glutathione reductase with minimal activity (Anderson, et al., 1989.). The FAD levels at 450 nm were not much reduced in SCT or TT as compared to the normal (all peaks around 120–150), but the NADH level was significantly lower for TT (140 for normal and 20 for TT). What is remarkable for TT is the dramatic elevation of the spectra at approximately 500 nm owing to bile pigments (biliverdin and bilirubin), which are well-known fluorophore markers for RBC degeneration (Aessopos, et al., 2007).
The decrease in tryptophan level and NADH was enhanced many times in the spectra of TD plasma. In contrast, the situation for SCD is worse than that for SCT, but not as alarming as that of TD. From the above results, it is evident how effectively we can discriminate among the four common cases of blood disorders. The process involves collecting blood from participants, centrifuging it to separate the plasma, transferring the plasma into a quartz cuvette, and performing a spectral scan. If the intensity at 290 nm is > 200, then it is normal; < 150, it is SCT; < 100, it is TT; < 20, it may be SCD; and < 10, it may be TD. The large non-overlapping gap in the intensity values is notable. Then, the emission of tryptophan can be measured using a portable compact grating coupled with a charge-coupled device (CCD) detector in a compact laser-based spectrometer equipped with a laser diode operating at 300-320 nm, where tryptophan exhibits strong absorption at approximately 350-370 nm. This setup would enable the detection of these disorders within a few minutes, even in the homes of the individuals being screened. The fluorescence intensities of the four cases were visualized as follows: ≥ 200, normal; 120-180, SCT; 50-100, TT; 20-40, SCD; and < 20, TD.
5. Conclusion
In the past few decades, numerous efforts have been taken to prevent blood disorders worldwide, leading to the development of new and innovative techniques to diagnose blood diseases and reduce the number of new cases. Premarital diagnosis plays a major role in avoiding high-risk pregnancies in developing countries. However, several countries lack such screening programs because of high expenses and limited availability of equipped laboratories. The current study, with limited samples, performed as a proof of concept, showed remarkable sensitivity and specificity for SCT, TT, SCD, TD, SCD/TD, and normal control blood plasma samples. A wider multicenter study could prove the efficacy of this technique. If proven reliable, the bulky instrument could be replaced by a set of laser diodes and a CCD-grating combination packed into a portable unit. It is expected to be inexpensive, and a large number of individuals suffering in poor African and Asian countries, and individuals belonging to indigenous tribes can be tested, and their quality of life can be improved.
Acknowledgment
This Project was funded by the National Plan for Science, Technology and Innovation (MAARIFAH), King Abdulaziz City for Science and Technology, Kingdom of Saudi Arabia, Award Number (3-17-05-001-0056).
CRediT authorship contribution statement
Sandhanasamy Devanesan: Conceptualization, experiments, data collection, writing – original draft, review and editing; Karim Hamda Farhat: Sample collection, data collection, review and editing; Masilamani Vadivel: Conceptualization, writing – original draft; Fatmah Alqahtany: Software, data analysis, review and editing; Mohamed Alsalhi: Software, data analysis, review and editing.
Declaration of competing interest
The authors declare that they have no competing financial interests or personal relationships that could have influenced the work presented in this paper
Declaration of Generative AI and AI-assisted technologies in the writing process
The authors confirm that there was no use of artificial intelligence (AI)-Assisted technology for assisting in the writing or editing of the manuscript and no images were manipulated using AI.
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