A genetic study of FGG/FGA‎ mutations effect on D-dimer levels among COVID-19 patients in Jordan

doi:10.21203/rs.3.rs-3554593/v1

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A genetic study of FGG/FGA‎ mutations effect on D-dimer levels among COVID-19 patients in Jordan

https://doi.org/10.21203/rs.3.rs-3554593/v1

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Coronavirus disease (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus. This study aims to investigate the association between the single nucleotide polymorphisms (SNPs) of fibrinogen genes (FGG/FGA) monitored by the D-Dimer elevated levels in COVID-19 Jordanian patients. Blood samples were collected from 120 participants among which 90 were infected with COVID-19 while the rest 30 were used as healthy controls. The potential association between mutations in the fibrinogen gene and the elevated D-Dimer levels in COVID-19 patients was examined using Multiplex PCR and Sequencing. The results showed a correlation coefficient of 0.378 and a p-value of < 0.00 between D-Dimer levels and Covid-19 status. In addition, the results showed an escalation in COVID-19 incidence in the relevant age group of‏ ‏the study population (r = 0.209, ‎p < 0.022)‎. However, the current findings indicate that there is no link between D-Dimer levels and FGA/FGG mutation. These results suggest that the presence or absence of mutations in the FGA and FGG genes does not significantly affect D-Dimer levels in COVID-19 patients among the Jordanian population. Further study was required to examine the association between other factors and the D-Dimer elevated levels of COVID-19.

Coagulopathy

COVID-19

D-Dimer

Fibrinogen

FGA/FGG

Jordan

Coronavirus disease 2019 (COVID-19) which mainly targets the respiratory tract resulting in coughing, fever, and pneumonia,‎ has emerged as the most consequential global health crisis since the 1918 influenza epidemic [1, 2]. Globally, COVID-19 has had a catastrophic effect where more than 6 million people were dead [1]. Hospitalized COVID-19 patients were reported to have systemic multi-organ failure and thrombophilia disorders [3, 4]. D-dimer value on admission is considered an accurate biomarker for predicting mortality in patients with COVID-19 [5, 6]. Indeed, the structure and stability of a thrombus have an impact on the prevalence and mortality of thrombotic disorders [7]. In addition to D-dimer, individuals with COVID-19 have shown alterations in some coagulation parameters including factor III (also called tissue factor), factor V, fibrinogen gamma chain (FGG), and fibrinogen alpha chain (FGA). However, other factors may contribute to the etiology of COVID-19 through mutations and have been observed to cause thrombosis such as endothelial damage, antiphospholipid antibodies, inflammation, and hyperviscosity [8, 9].

Fibrinogen, a plasma glycoprotein that is essential for the formation of blood clots, is synthesized by hepatocytes with a molecular weight of 340 kDa [10]. Its molecules are 45nm long structures that are composed of two sets of three polypeptide chains: A alpha; B beta; and gamma[11]. Each of these chains is encoded by a separate gene namely, fibrinogen alpha (FGA), fibrinogen beta (FGB), and fibrinogen gamma (FGG), clustered in a region of approximately 50 kb on chromosome 4q31.3[12]. FGG and FGA are components of fibrinogen, which are soluble plasma proteins that coagulate into insoluble fibrin[10]. Mutations in these coagulation factors have been linked to thrombotic events in COVID-19 patients in numerous studies[13, 14]. Due to their association with a higher risk of arterial thrombosis, FGG and FGA mutations are significant in determining the etiology of the disease [15]. The study comprised COVID-19 patients and found that those with FGG mutations had significantly greater D-dimer levels than those without the mutation. These findings suggest that FGA mutations may have a major impact on the coagulopathy experienced by COVID-19 patients and may affect the prognosis and treatment[16].

Damaged cells release tissue factor III, which triggers the extrinsic route. After ‎‎interacting with tissue factor VII in the bloodstream, tissue factor III acts into the last ‎‎stage of the common route, where factor X converts prothrombin into thrombin [10].‎The potential relationship between the D-dimer and factor III mutation has ‎been investigated in a study comprised of COVID-19 patients [11]. It was proposed that ‎it might start the coagulation cascade that results in the development of fibrin clots ‎when its expression rises in response to tissue damage or inflammation. The 261 ‎COVID-19 patients who participated in the previous study showed that individuals with ‎the factor III mutation had significantly higher D-dimer levels than those without the ‎mutation‏ ‏‎[12]. Patients who had the factor III mutation were more likely to pass away ‎than those who did not have the mutation. These findings proposed that the mutations in ‎factor III might have a role in the development of coagulopathy reported in COVID-19 ‎patients and may have implications for patient prognosis [13, 16]. In this context, the ‎association between Factor V, a cofactor that helps to convert prothrombin into ‎thrombin and is essential for stable fibrin clot formation, and D-dimer in COVID-19 ‎patients was investigated. Patients with factor V mutations had significantly higher D-‎dimer levels than patients without the mutation[14, 15].‎

This study aimed to determine the association of FGA/FGG genetic mutations with the risk of developing thrombosis among COVID-19 patients. The outcomes might discover FGA/FGG genotypes that may serve as a biomarker for the early detection and diagnosis of COVID-19 infection and the prevention of associated complications.

Study Sample and Ethical Consideration

A total of 120 participants participated in this study during three months from May to August 2022 who were informed that participation is voluntary, and the information is highly confidential. 2.5 ml of blood samples were collected from the participants in K3-EDTA vacuum tubes from Gardens Hospital and Consulting Medical Laboratories in Jordan Amman. Data were obtained from the patient's clinical outcome records and patient files after each patient gave his informed consent. It consisted of two parts; the first one includes sociodemographic information like age and sex and the second part includes the D-Dimer test and stored at -25°C. This study was approved by Al-Balqa Applied University’s Institutional Review Board (IRB) has approved the ‎study (26-3-1781).

DNA Extraction

All blood samples, collected from both infected and non-infected participants were subjected to DNA extraction processing using (AllGene, South Korea). It should be noted that the DNA extraction process was performed according to the manufacturer's instructions for the AllGene kit. First, the lysis solution and GEN Xtract resin were left to reach room temperature while a 100 µl blood sample was pipetted into a 1.5 ml microtube with a screw cap. After that, the lysis solution was left at room temperature for 15 minutes and then mixed with the sample. The mixture was then centrifuged (Dragon, China) for 5 minutes at a speed of 3000 rpm, followed by careful removal of the supernatant. This step was repeated by adding 1ml of lysis solution for 5 minutes under a speed of 12,000 rpm, removing the supernatant, and keeping 50 µl to a soft pellet. Next, 200 µl of GEN Xtract resin was added, and the solution was vortexed (Dragon, China) for 10 seconds after the incubation stage was completed. Centrifugation (Dragon, China) was conducted at a speed of 12,000 rpm in a microcentrifuge for 5 minutes, and the sample was kept on ice for 5 minutes. The final supernatant contained DNA was used for PCR analysis in the subsequent steps and was frozen at -20°C.

The concentration of nucleic acid at 260 nm by using the 260/280 absorbance ratio is used to determine DNA purity and detect the presence of contaminants. A NanoDrop™ One (Thermo Fisher Scientific, USA) [17]. To assess the quality and the integrity of DNA extracted from the blood samples, gel electrophoresis was performed using a 1% Ultra-Pure agarose gel (Invitrogen, USA). The gel was run by using a power pack (Bio-Rad, USA) at 100 volts for 45 minutes and visualized under UV light.

Primer Design

The primers of the target gene Factor V have been designed using the Primer-BLAST tool on the NCBI website (https://www.ncbi.nlm.nih.gov/tools/primer-blast. For the SNPs located in FGA/FGG, the primers were able to amplify the regions containing the SNPs at position 100. Table 1 shows the primer sequence for FGA/FGG. The primers were manufactured by Macrogen Company, (South Korea).

Table 1

Primer Sequences used in the PCR reaction.
Primer		Sequence (5'->3')	Primer Length	Tm	Product size (bp)
FGA\|FGG	Forward	GGTTTTTCCACGCAGTACCT	20	58.4	183
FGA\|FGG	Reverse	CCATATGGTGACAGCCTTCCA	21	59.69	183

<<Table 1>>

Amplification Reaction

Multiplex PCR reactions were conducted using the I-MAX II 2xPCR Master mix Solution (iNtRON Biotechnology, South Korea) and a QIAGEN Rotor-Gene instrument, Model 6 Plex (Hilden, Germany). The reactions were carried out under the thermal profile following conditions: 94º C initial denaturation for 2 minutes, followed by 33 cycles of 20 seconds at 94º C denaturation, 20 seconds at 56º C annealing, and 1 minute at 72º C extension, followed by a final extension step of 72º C for 10 minutes and holding at 4º C. The volume of the reaction was (1.25 µl) primer, 12.5 µM working solution, 2 µl of template DNA, and an appropriate amount of nuclease-free water to reach a final volume of 25 µl.

PCR Product Purification

The PCR product purification protocol achieves rapid and efficient removal of short primers, dNTPs, enzymes, short-failed PCR products, and salts from PCR fragments > 100 bp, typically in less than 10 minutes by adding 5 volumes of Buffer PB (Hydrochloride and isopropanol) to 1 volume of the PCR sample to remove mineral oil or kerosene. Followed by adding 10 µl of 3 M sodium acetate with mixing. The color of the mixture will turn yellow. Place a QIAquick (Qiagen, Germany) spin column in a provided 2 ml collection tube. Centrifuge for 30–60 seconds. After that discard the flow-through, add 0.75 ml Buffer PE (Hydrochloride and isopropanol) to the QIAquick column and centrifuge for 30–60 seconds again discard the flow-through and place the QIAquick column back in the same tube finally centrifuge the column for an additional 1 minute.

DNA Sequencing

The South Korean company Macrogen performed DNA Sequencing and the process was performed according to the following procedure: A total of 120 samples were analyzed for single nucleotide polymorphisms using the BigDye Terminator v3.1 Cycle Sequencing Kit (Thermofisher, USA). Each sample was tested for one single SNP. To produce enough templates for sequencing, the DNA template was isolated and purified from each sample before PCR amplification. Purified PCR products were combined with the BigDye Terminator v3.1 mix, which includes fluorescently labeled dideoxynucleosides, Taq DNA polymerase, and buffer. Thermal cycling was used to enable the Taq polymerase to incorporate the fluorescently labeled dideoxynucleosides into the growing DNA strand, resulting in a collection of DNA fragments of varying lengths, each labeled with a different fluorescent color. The generated data was analyzed using GC software and the DNA sequence was screened and exported as a Word file.

D-Dimer

The measurement of the D-dimer level was performed according to the vendor's instructions (Qdaisat, 2019). A volume of 10 µl of human whole blood was used as a transfer pipette to a tube containing the detection buffer used for the D-dimer level. By using the sandwich immunodetection method, this buffer contains the binding site for the D-dimer antigen of the sample, leading to antigen-antibody complexes. The complex will transfer onto nitrocellulose matrix to be captured by the other immobilized antibody on the test strip and then the mixture is mixed up and shaken about 10 times Pipette out 75 µl of a sample mixture on the cartridge. After that samples were incubated at room temperature for 12 minutes this process is carried out using the iChroma™ II instrument (Boditech company, South Korea) which is a diagnostic device that uses immunochromatographic technology to provide rapid and accurate test results for a range of clinical applications, including D-dimer level measurement.

Statistical Analysis

The result data underwent various statistical tests using the Statistical Package for the Social Sciences (SPSS) software (version 26). The variables including Factor III, Factor V, and FGA/FGG will be investigated for any correlation and relationships. Multiple tests were used including one-way ANOVA and T-tests (both independent and dependent ways) to thoroughly analyze the data and draw meaningful conclusions, Excel was also used to generate most of the charts and Figures in this study.

The 120 participants in the current study had remarkably different D-dimer levels between the different demographic groups. The mean D-dimer level was 2643 ng/ml for the study population; the 90 positive COVID-19 patients showed significantly higher D-dimer levels than the 30 non-infected COVID-19 participants as the mean D-dimer level was 3353 ng/ml versus 513 ng/ml p > 0.001, respectively, the demographic data are summarized in Table 2. Regardless of gender, there was no significant difference in D-dimer levels among males and females. In addition, there was no significant difference in D-dimer levels according to the factor FGA|FGG mutation among the study population.

Table 2

The levels of D-dimer according to the study demographic variables
		Frequency	Percent	Valid Percent	Cumulative Percent	D Dimer	p-Value
Factor FGA\|FGG	Wild type	97	80.2	80.8	80.8	2589	0.71
Factor FGA\|FGG	Mutation	23	19	19.2	100	2872	0.71
Gender	Male	68	56.2	56.7	56.7	2655	0.243
Gender	Female	52	43	43.3	100	2628	0.243
Age	< 20	12	9.9	10	10	1363	0.716
	< 40	40	33.1	33.3	43.3	2799
	< 60	29	24	24.2	67.5	2869
	< 80	28	23.1	23.3	90.8	2670
	> 80	11	9.1	9.2	100	2809
Covid-19	Negative	30	24.8	25	25	513	0.001
Covid-19	Positive	90	74.4	75	100	3353	0.001
D-dimer level	< 500 ng/ml	31	25.6	25.8	25.8	126	0.001
D-dimer level	> 500 ng/ml	89	73.6	74.2	100	3464
Total		120	100			2643

<<Table 2>>

However, 72% of the high D-dimer levels (more than 500 ng/ml) are wild-type Factor FGA|FGG ‎samples, and in return, 83% of the Factor FGA|FGG‎ mutant patients showed high D-dimer levels. This confirms that there was no significant direct correlation between COVID-19 incidence in the study population and Factor FGA|FGG ‎mutation (Table 3).

Table 3

The prevalence of Factor FGA|FGG Mutation according to D-dimer levels
Factor FGA\|FGG ‎	Total Population	D-dimer > 500 ng/ml N. (%)	D-dimer > 500 ng/ml Mean (%)	D-dimer < 500 ng/ml N. (%)	D-dimer < 500 ng/ml Mean (%)	p-Value
Wild type	97	70 (72%)	3447.01	27 (28%)	363.967	0.71
Mutation	23	19 (83%)	3404.91	4 (17%)	342.92	0.71
Total	120 (100%)	89 (74%)		31 (26%)

<<Table 3>>

Moreover, there was an escalation in D-dimer levels in relevance to the increase in age of the study population (r = 0.21, p < 0.022) as well as there was an escalation in COVID-19 incidence in the relevance age group of the study population (r = 0.209, p < 0.022) (Table 4).

Table 4

The correlation between the demographic variables with D-dimer and Factor FGA|FGG
		Age	Age group	Gender	Covid-19	D Dimer	FGA \| FGG
Age	Pearson Correlation	1
Age	Sig. (2-tailed)
Age group	Pearson Correlation	0.122	1
Age group	Sig. (2-tailed)	0.186
Gender	Pearson Correlation	-0.057	-0.072	1
Gender	Sig. (2-tailed)	0.538	0.433
Covid-19	Pearson Correlation	0.080	.209^*	-0.117	1
Covid-19	Sig. (2-tailed)	0.383	0.022	0.205
D Dimer	Pearson Correlation	.210^*	0.064	-0.004	.378^**	1
D Dimer	Sig. (2-tailed)	0.022	0.485	0.965	0.000
FGA \| FGG	Pearson Correlation	-0.051	0.068	0.001	0.086	0.034	1
FGA \| FGG	Sig. (2-tailed)	0.581	0.461	0.988	0.353	0.710
Bold = statistically significant, = p < 0.05, *=p < 0.001

<<Table 4>>

Sequencing analysis of FGA/FGG

Gel electrophoresis was conducted to examine the product size and number. The samples were of high quality, and the bands were well-defined (Fig. 1). All DNA samples fulfilled the requirements of quality approval for the 230/ 260 ratio and the 260/280 ratio the ratios were higher than 1.8 and less than 2.4.

<<Figure 1>>

Sequencing data for PCR products were analyzed for single nucleotide polymorphisms in FGA/FGG Factor. The data revealed variations in the SNPs for the factor of interest in the patient. Specifically, the FGA/FGG SNP (rs13109457) had an A variant instead of the wild-type G allele, with G/A/T. The specific variants identified in the sequencing data for each factor were further analyzed using the GWAS Catalog. Figure 2 displays the sequencing analysis for FGA/FGG and its corresponding ‎mutations A instead of G (red star). The figure provides a visual representation of the single ‎nucleotide polymorphisms (SNPs) found for the factor of interest and serves to enhance ‎our understanding of the genetic variations present in the patient population studied.‎

<<Figure 2>>

In this study, the D-dimer levels correlate with COVID-19 patients as a reliable prognostic marker. Notably, there was a higher tendency to have an intravascular coagulopathy in the COVID-19 patients as the Odds Ratio was 3.949, p < 0.001 for COVID-19 patients with high D-dimer > 500 ng/ml. Indeed, COVID-19 infections increased the D-dimer average level to six times higher than the non-infected samples. The relationship between D-dimer and COVID-19 infection is particularly important in severe cases, where elevated levels of D-dimer can contribute to the development of venous thromboembolism and other clotting disorders[18–20]. In this regard, a previous report demonstrates that patients with COVID-19 frequently have increased fibrinogen. Further, data revealed that in COVID-19 patients, high levels of fibrinogen are correlated with severe illness, exaggerated inflammation, and ICU hospitalization [21]. Additional recent research has demonstrated the significance of using inflammatory markers, such as serum ferritin and D-dimer, to predict the prognosis of COVID-19 patients. These markers have a strong correlation with disease mortality, ICU admission, and the requirement for mechanical ventilation, all of which aid in the early identification of case risk of progression and, ultimately, improve outcomes [22, 23]. Interestingly, Aydin and Golcuk found that the third and fourth months of the post-COVID-19 period had the highest rate of D-dimer increase [24].

Significant correlation between COVID-19 and age group was also demonstrated. In comparison to younger individuals, older populations were more likely to experience unfavorable consequences. Healthcare providers ought to focus mostly on patients in that risk category [25]. However, a previous report from India demonstrated that the most vulnerable age group was 21–30 years[26]. This could be related to the fact that this group represents the most active worker group even during the pandemic lockdown. Likewise, age can be an indirectly influential variable that affects D-dimer levels, according to our previous findings that have been evaluated in our lab (Aburayyan, 2023 unpublished data). In this context, the study population's odds ratio for age on D-dimer levels was 1.579. This means that an increased risk of expressing one of the coagulation events such as Deep Vein Thrombosis (DVT), pulmonary embolism, or heart attack will raise the release of fibrin degradation products as the bloodstream's D-dimer level rises. Other age-related conditions, such as renal function impairment because of aging, may also have an indirect impact on D-dimer levels. The kidneys are responsible for reducing D-dimer from the blood [27]. This indicates that D-dimer levels may have a minor propensity to rise with aging. However, the effects of aging on D-dimer levels are multifaceted and can be influenced by a range of factors, such as lifestyle decisions and underlying medical disorders. In a previous study (Aburayyan, 2023 unpublished data), a significantly positive correlation between the escalations in D-dimer levels in older people and young patients. The mean D-dimer levels exceeding 500 ng/ml were shown to have approximately 1.12 ODD, particularly in the age group of 35 to 60. The age range of the infected sample included newborns to elderly individuals, with 33.3% of infected samples being under 35 and two-thirds being over 35. This suggests that those in the mid-aged and older group had a higher risk of contracting the infection. According to a 2022 study by Statsenko et al., older patients had a higher risk of being hospitalized in the critical care unit and were more vulnerable to severe COVID-19 instances than their younger counterparts [28]. Bruine de Bruin who concluded that older adults have higher risks for mortality due to coagulopathy conducts another study that emphasizes the same result [29]. The World Health Organization (WHO) states that age is a risk factor for COVID-19 infection and that older people are more susceptible to serious disease outcomes. Age was directly correlated with the risk of getting COVID-19 severity and death, according to several researches conducted during the epidemic [28, 30, 31] [27, 29–31].

The current research has also evaluated the relationship between mutation in the FGA/FGG Factor and elevated D-dimer in COVID-19 patients. The results revealed that no impact between higher levels of D-dimer in COVID-19 patients and mutation of the FGA/FGG Factor. Likewise, a study published by Abu-Farha et al., 2020 has aroused the potential effect of rs13109457-A (G_A)‎ ‎FGG/FGA ‎Factor mutation on escalating D-dimer levels[32]. In a previous study conducted by Nicholas L., Smith, 2011 reported no proved evidence on the association of FGG locus mutation and the D-dimer levels in hospital admitted patients [33]. The non-significant effect of FGG mutation could be attributed to several reasoning among them the ethnicity, Lu-Chen Weng, 2014 reported a significant effect for the FGG mutation in African American population whereas there was no significant effect among the Asian, and Hispanic populations [34]. Inversely, several studies showed that individuals with a mutation on other factors such as Factor V Leiden (FVL) had higher levels of D-dimer compared to individuals without the mutation. Indeed, the mutation on FVL exaggerates the threat of thrombus formation through the activation of Factor Va and VIIIa by 10 folds [35].

This study spots the importance of the use of D-dimer in predicting the outcome of COVID-19 subjects. In addition, the current study also provides proof for the association between Covid-19 infection and age groups as well as the correlation between elevated levels of D-dimer and age. Further research is required to examine the underlying mechanisms and therapeutic effects of the observed correlation.

Author Contributions

O’la Ahmad AL-Fawares designed the study, wrote, edit and ‎supervised the overall project; Walid AbuRayyan designed the study, and edit the manuscript; M. M. Albalbaki collected the samples and conducted the experiments; Nesrin Seder has performed data analysis and interpretation; Mohammad Nazeeh Shatnawi edits the manuscript.‎ All authors drafted the manuscript and approved the final version.

Declaration of Conflicting Interests

The authors declare that they have no conflict of interest.

Ethical Approval

Al-Balqa Applied University’s Institutional Review Board (IRB) has approved the study (26- 3-1781).

Funding

The study was performed on behalf of the researcher's cost.

Availability of data and materials

Data available on request from the authors.

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A genetic study of FGG/FGA‎ mutations effect on D-dimer levels among COVID-19 patients in Jordan

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Abstract

Figures

Introduction

Materials and Methods

Study Sample and Ethical Consideration

DNA Extraction

Primer Design

<<Table 1>>

Amplification Reaction

PCR Product Purification

DNA Sequencing

D-Dimer

Statistical Analysis

Results

<<Table 2>>

<<Table 3>>

<<Table 4>>

Sequencing analysis of FGA/FGG

<<Figure 1>>

<<Figure 2>>

Discussion

Conclusions

Declarations

References

Status:

Version 1