Objective: Despite the high prevalence of type 2 diabetes mellitus (T2DM) and obesity in the region, reports are limited on genetic risk factors associated with T2DM risk in Kuwait. Our aim was to investigate the association of reported FTO and TCF7L2 T2DM genetic risk variants in Kuwaiti T2DM patients. Subjects and Methods:FTO rs9939609 and TCF7L2 rs7903146 variants were genotyped in 203 T2DM patients and 162 healthy controls. Data analysis included Fisher’s exact test, χ2 test, and linear and logistic regression analyses. Results:FTO rs9939609 (AA) and TCF7L2 rs7903146 (TT) genotypes associated with T2DM risk among Kuwaitis (p = 0.0016 and p < 0.0001; respectively). Both variants had the strongest association with T2DM risk in an autosomal recessive inheritance model (FTO rs9939609A: odds ratio (OR) 2.136, 95% confidence interval (CI): 1.21–3.67, p = 0.0075; TCF7L2 rs7903146T: OR 3.283, 95% CI: 1.92–5.76, p < 0.0001). Moreover, rs7903146T associated with risk of peripheral neuropathy (β = 0.735, 95% CI: 0.514–0.96, p < 0.001) and risk of myocardial infarction (β = 0.36, 95% CI: 0.024–0.7, p = 0.036) in T2DM patients. Conclusion: The increased susceptibility of Kuwaitis to T2DM is influenced by the same common genetic factors found in other T2DM populations. Further investigations of other T2DM genetic risk factors in Kuwait should refine and further support the clinical utility of a genetic risk score in predicting T2DM risk in a high-risk population such as Kuwait.

Highlights of the Study

  • FTO variant rs9939609A is associated with an increased risk of obesity but not of type 2 diabetes, among Kuwaitis.

  • TCF7L2 rs7903146T variant is associated with an increased risk of type 2 diabetes mellitus among Kuwaitis.

Type 2 diabetes mellitus (T2DM) is a chronic, complex, inflammatory, metabolic disorder in which glucose homeostasis and metabolism are impaired. According to the International Diabetes Federation, T2DM is estimated to affect 537 million individuals worldwide with projections showing an exponential increase in prevalence over the next 20 years [1]. In Kuwait, the prevalence of T2DM in adults was estimated to be 21.8%, and an increased incidence in children was also evident [2, 3]. Despite advances in treatment and management of T2DM and obesity to curtail T2DM, the incidence and burden of T2DM continue to increase. T2DM risk factors include modifiable and non-modifiable factors [4]. Modifiable factors include obesity, a sedentary lifestyle, high blood pressure, tobacco smoking, and an unhealthy diet [5]. Non-modifiable risk factors include genetics, age, and socioeconomic determinants of health. The identification of individuals at risk for T2DM has become a necessity to employ early interventions primarily by targeting modifiable risk factors. Genome-wide association studies (GWASs) conducted over the past decade have revealed many genetic aspects of T2DM risk, pathogenesis, and T2DM-related complications’ risk. Genetic risk factors reported for T2DM may have a clinical application in the prediction of risk of early T2DM, and the growing number of gene variants identified by GWAS have given rise to the possibility of constructing a polygenic risk score (PRS) for the early estimation of T2DM risk [6, 7]. While no clinical utility has been approved yet for T2DM PRS, many direct-to-consumer commercial genetic risk testing services for T2DM are available. However, these commercial tests have limited supporting clinical evidence and very low risk association [8]. A major limitation of such genetic tests is the lack of uniform T2DM risk association across different ethnic genetic backgrounds. Most of the reported T2DM genetic risk factors have been investigated in populations of European genetic background which makes their use in non-European or admixed populations of limited predictive value. For example, a meta-analysis of 11 primarily Asian studies conducted on the association of leptin receptor (LEPR) gene rs1137101 polymorphism concluded that homozygous rs1137101 is associated with a 1.5-fold increase in T2DM risk in Asians [9]. However, no association was found for rs1137101 with T2DM in Kuwait which is considered an Asian country in which the genetic background aligns 98% with European genome sequences [10]. Moreover, there is no reported evidence on the association of this variant with T2DM risk in European populations.

T2DM genetic risk factors that have relatively high reproducibility across populations include fat mass obesity (FTO) gene polymorphism rs9939609 (T > A) and transcription factor 7-like 2 (TCF7L2) gene polymorphism rs7903146 (C > T), both of which associate with a moderate increase in T2DM risk [11‒13]. Moreover, an association between vitamin D receptor (VDR) gene polymorphism rs731236 (A > G) with T2DM risk was reported in the Kuwaiti population [10]. Given the substantial burden of T2DM, and obesity rates approaching 40% in the Kuwaiti population it has become critical to identify and refine early detection measures to thwart the progression of these two endemics by early interventions. Here, we investigated whether FTO rs9939609 and TCF7L2 rs7903146 associate with T2DM risk in an exclusively Kuwaiti case-control study, and their potential in distinguishing T2DM risk with the inclusion of nongenetic T2DM risk factors.

Study Cohorts

The diabetes sample depository biobank included 412 T2DM patient samples collected in the span of 5 years at Mubarak Al-Kabeer Hospital’s Physical Medicine and Rehabilitation Clinic. All deposited samples were collected according to the protocol approved by the Ethics Committees of the College of Medicine, Kuwait University, and the Ministry of Health both of which adhere to the declaration of Helsinki’s Ethical Principles for Medical Research Involving Human Subjects Guidelines. Verbal consent was obtained from all participants for samples in the sample depository. Inclusion criteria for this study were being a Kuwaiti citizen, having a confirmed diagnosis of diabetes, having a complete biochemical profile, evidence for diabetic neuropathy assessment, and being older than 17 years of age. Exclusion criteria were patients with neuropathy due to vitamin B12 deficiency, folic acid deficiency, patients with malignancy, renal failure, liver disease, inflammatory diseases, and patients with incomplete data. 203 Kuwaiti T2DM patients met the criteria of this study and were included.

The healthy control cohort included 162 healthy Kuwaiti controls recruited at Mubarak Al-Kabeer Hospital and by word of mouth and was subjected to anthropometric and demographic data collection. Exclusion criteria included being a non-Kuwaiti citizen, being younger than 18 years, and having a history of a neurological or a metabolic disorder. Fasting blood samples were collected in EDTA vacutainers for DNA extraction, and another blood sample was collected in red-top vacutainers for routine serum biochemical tests matching those performed for T2DM patients. All blood samples collected were fractionated into buffy coat and plasma/serum fractions for each patient and buffy coats were stored at −20°C until use. Anthropometric measurements included weight and height to determine body mass index. Biochemical tests included hemoglobin A1c, total cholesterol, total glycerides, high-density lipoprotein, low-density lipoprotein, apolipoprotein A, apolipoprotein B, alkaline phosphatase, alanine aminotransferase, aspartate aminotransferase, and serum creatinine.

DNA Extraction and Variant Genotyping

DNA extraction from T2DM patients’ frozen buffy coats and healthy control whole blood samples were performed using Qiagen DNA mini kit (Qiagen, CA, USA) using manufacturer standard protocol with minor modifications. Frozen buffy coat fractions were thawed in a 37°C water bath for 10 min, vortexed on low speed to mix, and 200 µL of sample was added to a microcentrifuge tube containing 20 µL proteinase K. AL buffer was added at an equal volume to sample, and vortexed for 10 s at high speed then incubated at 56°C for 25 min. After every 5 min vortexing was done at maximum speed for 5 s to ensure sample uniform digestion. The next protocol steps proceeded for both types of samples in accordance with the kit standard protocol. DNA concentration and integrity were determined using spectrophotometric and agarose gel electrophoresis. DNA samples of adequate quantity and quality were used for genotyping. Briefly, Taqman’s FTO rs9939609 and TCF7L2 rs7903146 genotyping assays (Applied Biosystems, CA, USA) were used to genotype all samples using Taqman genotyping master mix and 50 ng of sample DNA. Reactions were run on Applied Biosystems Fast 7,500 Real-time PCR system, and genotype calling was done using SDS software version 1.4.1 (Applied Biosystems, CA, USA).

Data Analysis

Allelic and genotype frequencies of individual variants were computed for both cohorts, and Hardy-Weinberg equilibrium (HWE) was ascertained for healthy controls using European variant frequencies. Allelic and genotypic frequencies were analyzed using Fisher’s exact test and χ2 test, respectively. The odds ratio (OR) was estimated for both variants, and autosomal dominant and recessive inheritance models were used to determine the inheritance model of penetrance. Linear regression analysis was performed to determine allele effect size (β coefficient). Logistic regression analysis was used to determine model performance metrics. Other parametric and nonparametric demographic and biochemical variables were analyzed using the student’s t test and Mann-Whitney test, respectively. Statistical analyses were performed using SPSS v.26 (IBM, NY, USA).

Demographics, clinical characteristics, and measured biochemical parameters of T2DM patients and healthy controls included in this study are shown in Table 1. Allelic and genotypic frequencies of FTO rs9939609 TCF7L2 rs7903146 in healthy controls and T2DM patients are shown in Table 2. Genotype frequencies of healthy controls for both variants were used to ascertain whether our sampled Kuwaiti population is in HWE with European frequencies. FTO rs9939609 was in HWE with European frequencies (p = 0.453) as was TCF7L2 rs7903146 (p = 0.107). It should be noted that TCF7L2 rs7903146(T) allele frequency in our sampled healthy Kuwaiti population was higher than any population-specific frequencies recorded in the National Center for Biotechnology Information (NCBI) database of Genotypes and Phenotypes (dbGaP) Allele Frequency Aggregator (ALFA) project. FTO rs9939609 allelic distribution did not differ between T2DM and healthy control cohorts, whereas its genotype frequencies were significantly different between the two cohorts (p = 0.0016). FTO rs9939609 genotype AA associated with T2DM risk in an autosomal recessive model of inheritance (OR 2.136, 95% confidence interval [CI]: 1.21–3.67, p = 0.0075). TCF7L2 rs7903146 allelic and genotypic frequencies showed significantly different distributions between healthy controls and T2DM patients. TCF7L2 rs7903146 genotype TT associated with T2DM risk in an autosomal recessive model of inheritance (OR 3.382, 95% CI: 1.99–5.92, p < 0.0001).

Table 1.

Demographics and clinical characteristics of type 2 diabetes and healthy controls

CriteriaType 2 diabetics (n = 203)Healthy controls (n = 162)p value
Gender, n (%) 
 Male 60 (29.6) 51 (31.5) 0.73 
 Female 143 (70.4) 111 (68.5)  
Age, years 57.3 (±10.16) 40.3 (±9.8) 0.06 
Body mass index 33.57 (±6.93) 29.03 (±7.76) <0.0001 
Smokers, n (%) 28 (13.8) 26 (16.05) 0.55 
Peripheral neuropathy, n (%) 72 (35.5) 
Diabetic retinopathy, n (%) 60 (29.5) 
History of myocardial infarct, n (%) 32 (15.7) 
HbA1c, % 9.71 (±2.5) 5.7 (±0.84) <0.0001 
Total cholesterol, mmol/L 4.82 (±1.18) 4.51 (±0.75) 0.084 
Triglycerides, mmol/L 1.73 (±1.02) 1.02 (±0.6) <0.0001 
HDL, mmol/L 1.08 (±0.28) 1.25 (±0.43) 0.001 
Cholesterol: HDL ratio 4.67 (±1.48) 3.87 (±1.15) <0.0001 
LDL, mmol/L 2.95 (±0.99) 2.83 (±0.65) 0.653 
APOB, g/L 1.05 (±0.29) 0.87 (±0.22) <0.0001 
APOA, g/L 1.43 (±0.28) 1.42 (±0.29) 0.59 
APOB:APOA ratio 0.75 (±0.26) 0.63 (±0.19) 0.0001 
ALP, IU/L 85.27 (±43.4) 76.8 (±40.4) 0.014 
AST, IU/L 21.84 (±8.87) 20.22 (±5.7) 0.37 
ALT, IU/L 24.56 (±12.3) 21.9 (±13.6) 0.006 
Serum creatinine, µmol/L 76 (±76.9) 61.47 (±17.3) 0.14 
CriteriaType 2 diabetics (n = 203)Healthy controls (n = 162)p value
Gender, n (%) 
 Male 60 (29.6) 51 (31.5) 0.73 
 Female 143 (70.4) 111 (68.5)  
Age, years 57.3 (±10.16) 40.3 (±9.8) 0.06 
Body mass index 33.57 (±6.93) 29.03 (±7.76) <0.0001 
Smokers, n (%) 28 (13.8) 26 (16.05) 0.55 
Peripheral neuropathy, n (%) 72 (35.5) 
Diabetic retinopathy, n (%) 60 (29.5) 
History of myocardial infarct, n (%) 32 (15.7) 
HbA1c, % 9.71 (±2.5) 5.7 (±0.84) <0.0001 
Total cholesterol, mmol/L 4.82 (±1.18) 4.51 (±0.75) 0.084 
Triglycerides, mmol/L 1.73 (±1.02) 1.02 (±0.6) <0.0001 
HDL, mmol/L 1.08 (±0.28) 1.25 (±0.43) 0.001 
Cholesterol: HDL ratio 4.67 (±1.48) 3.87 (±1.15) <0.0001 
LDL, mmol/L 2.95 (±0.99) 2.83 (±0.65) 0.653 
APOB, g/L 1.05 (±0.29) 0.87 (±0.22) <0.0001 
APOA, g/L 1.43 (±0.28) 1.42 (±0.29) 0.59 
APOB:APOA ratio 0.75 (±0.26) 0.63 (±0.19) 0.0001 
ALP, IU/L 85.27 (±43.4) 76.8 (±40.4) 0.014 
AST, IU/L 21.84 (±8.87) 20.22 (±5.7) 0.37 
ALT, IU/L 24.56 (±12.3) 21.9 (±13.6) 0.006 
Serum creatinine, µmol/L 76 (±76.9) 61.47 (±17.3) 0.14 

All quantitative variables are represented as mean ± standard deviation unless otherwise indicated.

HDL, high-density lipoprotein; LDL, low-density lipoprotein; APOA, apolipoprotein A; APOB, apolipoprotein B; ALP, alkaline phosphatase; ALT, alanine aminotransferase; AST, aspartate aminotransferase; HbA1c, hemoglobin A1c.

Table 2.

Allelic and genotype distributions of FTO and TCF7L2 variants in the two cohorts

Genetic variantType 2 diabetics (n = 203)Healthy controls (n = 162)p value
FTO rs9939609 
 Allelic 
  A 172 (42.4) 129 (39.8) 0.405 
  T 234 (57.6) 195 (60.2)  
 Genotypic 
  AA 49 (24.1) 21 (13.0) 0.0016 
  AT 74 (36.5) 87 (53.7)  
  TT 80 (39.4) 54 (33.3)  
TCF7L2 rs7903146 
 Allelic 
  C 197 (48.5) 204 (63.0) 0.0001 
  T 209 (51.5) 120 (37.0)  
 Genotypic 
  CC 62 (30.5) 63 (38.9) <0.0001 
  CT 73 (36.0) 78 (48.1)  
  TT 68 (33.5) 21 (13.0)  
Genetic variantType 2 diabetics (n = 203)Healthy controls (n = 162)p value
FTO rs9939609 
 Allelic 
  A 172 (42.4) 129 (39.8) 0.405 
  T 234 (57.6) 195 (60.2)  
 Genotypic 
  AA 49 (24.1) 21 (13.0) 0.0016 
  AT 74 (36.5) 87 (53.7)  
  TT 80 (39.4) 54 (33.3)  
TCF7L2 rs7903146 
 Allelic 
  C 197 (48.5) 204 (63.0) 0.0001 
  T 209 (51.5) 120 (37.0)  
 Genotypic 
  CC 62 (30.5) 63 (38.9) <0.0001 
  CT 73 (36.0) 78 (48.1)  
  TT 68 (33.5) 21 (13.0)  

All allelic and genotype distributions are presented as n (%).

The two variants were analyzed by linear regression to determine their allele effect size or log-additive inheritance model with and without adjustment for other demographic T2DM risk factors assessed inclusive of age and BMI. FTO rs9939609A did not associated with T2DM risk (β = 0.029, 95% CI: −0.042–0.101, p = 0.417) alone. Adjusting for age or BMI or both did not reveal any T2DM risk association. However, rs9939609A did associate with high BMI in the total sampled population (β = 1.84, 95% CI: 0.66–3.01, p = 0.002) and in the healthy controls alone (β = 0.026, 95% CI: 0.008–0.043, p = 0.004) but not in T2DM patients (p = 0.061). None of the other assessed clinical and biochemical variables associated with rs9939609 genotypes in either the total sampled population or T2DM and healthy controls cohorts when analyzed separately. TCF7L2 rs7903146T associated with T2DM risk without any adjustments (β = 0.115, 95% CI: 0.047–0.183, p < 0.001). The association remained significant when adjusted for age (p = 0.009), BMI (p < 0.001), and both (p = 0.008) with minimal change in effect size. Rs7903146T showed no association with BMI in the two cohorts when analyzed separately. TCF7L2 rs7903146T associated in the total sampled population positively with increased levels of glycated hemoglobin A1c levels (β = 0.074, 95% CI: 0.04–0.11, p < 0.001), and with triglyceride levels (β = 0.131, 95% CI: 0.03–0.23, p = 0.011). These associations were not sustained when analyzed in the case and healthy control cohorts separately. In T2DM, rs7903146T associated with risk of peripheral neuropathy when adjusted for age and BMI (β = 0.735, 95% CI: 0.514–0.96, p < 0.001), and risk of myocardial infarction (β = 0.32, 95% CI: 0.004–0.63, p = 0.04) which remained significant when adjusted for age and BMI (β = 0.36, 95% CI: 0.024–0.7, p = 0.036). The predictive potential of TCF7L2 rs7903146T in accurately classifying T2DM patients in the total cohort was assessed using logistic regression. When considering demographic and BMI factors alone, the model explained 65.5% (Nagelkerke R2) of the variance in T2DM and correctly classified (accuracy) 88.8% of cases with a positive predictive value (PPV) of 90.5% and a negative predictive value (NPV) of 84.2%. Only increasing age (p < 0.001) and BMI (p = 0.041) had a statistically significant influence on the model but not sex (p = 0.126). The sensitivity of the model was 93.8% and 77.1% specificity. The inclusion of TCF7L2 rs7903146T resulted in refinement of the model, explaining 68.3% of the variance in T2DM patients and correctly classifying 89.8% of cases with a PPV of 91.7% and an NPV of 85.1%. TCF7L2 rs7903146T addition slightly enhanced the sensitivity of the model (94.1%) and its specificity (79.7%). The inclusion of VDR rs731236 G as a previously reported Kuwaiti T2DM genetic risk factor into the model further enhanced its performance metrics (accuracy 90.2%, PPV 92.1%, NPV 85.3%, sensitivity 94.1%, specificity 81%).

More than 700 genetic risk factors for T2DM have been reported from GWAS and case-control studies conducted in the past 2 decades in different populations, the majority being of European and East Asian ancestries [14, 15]. Despite the rising number of reported genetic variants associated with T2DM risk, their contribution in explaining T2DM heritability is estimated to be approximately 18% [16]. Replication studies worldwide ensued with inconsistent reports of association of discovered variants which led to tapered interest in the clinical utility of these variants in T2DM risk prediction and highlighted the influence of ethnicity or genetic background on effect sizes of these T2DM risk variants [17, 18]. In the Middle East, the risk of developing T2DM and obesity is high, presumably due to socioeconomic and environmental factors that have altered the lifestyle and diet of these populations toward adopting practices that increase T2DM risk, such as low-fiber obesogenic diets and a sedentary lifestyle. Although numerous case-control studies from the Middle East have reported variants associated with T2DM risk, these reports are inconsistent across Middle Eastern populations [19]. In Kuwait, genetic risk factors for T2DM have been sporadically investigated. Among the globally established T2DM genetic risk factors, variants in FTO and TCF7L2 are the most consistently reported and uniformly accepted T2DM risk genetic variants [20]. We found FTO rs9939609A to associate with T2DM risk in Kuwaitis only when in homozygosity for the risk allele. The association of FTO rs9939609A with BMI was only noted in the total population sample and healthy controls but not in T2DM patients. This suggests that though FTO rs9939609A associates with an increased risk for obesity, its contribution to obesity predisposing to T2DM is not substantial since among FTO rs9939609T allele T2DM patients; 19 (25.7%) were categorically overweight and 50 (67.6%) were obese, while only 6.7% had average weight. In addition, it has been shown that the influence of FTO rs9939609A in T2DM impacts food choices or appetite independent of BMI, favoring high-fat and low-fiber foods suggesting the association of FTO rs9939609A with T2DM is modifiable [21]. Moreover, a meta-analysis of multiethnic studies revealed that FTO rs9939609A only had a small association with T2DM risk in the overall cohort (OR = 1.15, 95% CI: 1.11–1.19, p < 0.001); however, in North America and Europe the associations were lost after BMI adjustment [22]. Taken together, this indicates that the association of this variant with T2DM is because of its strong association with obesity, and therefore it is expected that its association with T2DM would be lost in our population where there is a high prevalence of obesity in the general population.

TCF7L2 rs7903146T is one of the oldest reported T2DM risk factors [23]. Since its initial report, numerous replication studies have established its strong association with increased T2DM risk, and functional studies proved its influence on impaired insulin secretion [11, 24]. In addition, a recent multiethnic GWAS revealed that this variant is the strongest T2DM genetic risk factor among all detected susceptibility variants [25]. In our study, TCF7L2 rs7903146T sustained its strong association with T2DM risk which is consistent with results from other countries in the region such as the United Arab Emirates and Sultanate of Oman but not the Kingdom of Saudi Arabia [26‒28]. In addition, our results show TCF7L2 rs7903146T to be associated with diabetic neuropathy and myocardial infarction risks which is a novel finding. Limited evidence from a single study suggested a role for this variant in diabetic peripheral nerve function, albeit not with nerve conduction or latency [29]. Another study suggested TCF7L2 rs7903146T is associated with cardiovascular autonomic neuropathy in diabetic patients [30]. This suggests that rs7903146T may have a potential prediction clinical application not only for T2DM risk but also for T2DM-related complications which is valuable for disease monitoring and early management.

Complex disorders such as T2DM involve a gene-environment interplay that predisposes to disease. This fact must be considered when estimating a population’s risk for complex disorders. We have shown that though a model including sex, BMI, and age has a moderate predictive potential for T2DM, these factors taken alone may not be suitable in a clinical setting. For example, advanced age is not a valuable factor when risk estimation is conducted in a young individual. Moreover, the major limitation of our study is the lack of T2DM age-matched elderly healthy controls which may have created bias in our model. Recruitment of the elderly age group is extremely hard in our population since the elderly tend to become sedentary and have a reduced social lifestyle as imposed by local traditions. In addition, females in our region are more sedentary than males and that is evident in the high percentage of obese females (73.4%) compared to males (50%) in our T2DM cohort. However, this situation may not be true for other populations and thus detracts from the value of this factor in predicting T2DM risk [31]. Therefore, the inclusion of genetic factors as non-modifiable factors into a T2DM predictive model is valuable to achieve predictive accuracy, specificity, and sensitivity applicable to the Kuwaiti T2DM population. It is clear from our results that the inclusion of two T2DM risk variants in our population enhanced all aspects of the predictive performance of our model. However, the enhancement of our predictive model by genetic factors was mild, most likely because more variants are required to explain T2DM heritability and/or the fact that heritability in T2DM is suggested to be marginal with modifiable factors such as obesity playing a larger role. Ultimately, a suitable T2DM risk model should account for the interplay between genetic and environmental factors relevant to the population being assessed, a fact that should be adapted into reality in the development of a T2DM predictive risk models for clinical use.

T2DM is a complex disorder with a heritability component that is yet to be fully determined in our high-risk population. The most consistent T2DM risk variant TCF7L2 rs7903146T is associated with T2DM risk in the Kuwaiti population whereas FTO rs9939609A is not. TCF7L2 rs7903146T T2DM risk association may be extended to T2DM complications, primarily the risk of peripheral neuropathy and myocardial infarction. A risk predictive model for T2DM of clinical application should include a combination of genetic and non-genetic T2DM risk factors to greatly improve its potential in early identification of patients at risk of T2DM paving the way for early interventions.

Samples used in this study were collected through a previous project that was approved by the Joint Committee for the Protection of Human Subjects at Kuwait University’s Health Sciences Center, and the Ethical Review Committee of the Ministry of Health in the State of Kuwait.

The authors have no conflicts of interest to declare.

Nawal Chaudhary performed FTO variant genotyping. Faye Alawadhi performed TCF7L2 variant genotyping. Ahmad Al-Serri provided genotyping assays and reviewed the manuscript and statistical analyses Rabeah Al-Temaimi designed the experiments and the project concept, extracted DNA from samples, trained students in experimental techniques, analyzed the data, and drafted the manuscript. All authors approved and reviewed this manuscript.

All data generated or analyzed during this study are included in this article. Further inquiries can be directed to the corresponding author.

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