A Pilot Study to Evaluate the Role of Obesity and Genetic Variants in Serum C-Reactive Protein Response to an Acute Fructose Load Open Access

In the past 3 decades, consumption of fructose has increased worldwide. It is believed that the change in the primary source of added sugars to high-fructose corn syrup in various food items may be a key reason for this increase in fructose consumption [1, 2]. Although the intake of added sugars has been reduced or stabilized in the past few years, it is still higher (∼14%) than the allowance recommended by the 2015–2020 Dietary Guidelines for Americans (10%) [1]. A monosaccharide, fructose occurs naturally in fresh fruits, honey, and vegetables. Few tissues, such as liver, kidney adipose tissue, and intestinal mucosa, can metabolize fructose. In the liver, kidney and intestine, it is metabolized and converted to triglycerides either directly through glyceraldehyde or indirectly through dihydroxyacetone phosphate via glycolysis [3‒5]. Increased intake of fructose has been linked to higher risk for various metabolic disorders such as obesity, metabolic syndrome, dyslipidemia, hyperuricemia, hypertension, non-alcoholic fatty liver disease, type 2 diabetes, and cardiovascular diseases [4‒7]. Fructose consumption, as compared to glucose consumption, has been shown to increase de novo lipogenesis, low-density concentrations of oxidized and small dense LDL, and apolipoprotein B (Apo B) [8‒14]. However, few studies found no association between fructose intake and risk for metabolic disorders [15‒17].

Fructose also contributes to the synthesis of free fatty acids in the liver whose metabolites may increase inflammation and the production of reactive oxygen species [18, 19]. C-reactive protein (CRP) is one of the major biomarkers for inflammatory conditions. It is produced in the liver in response to inflammation or infection in the body [20, 21]. Serum concentrations of CRP increase rapidly within 6–8 h of injury, inflammation, and related conditions [20‒25]. Elevated concentrations of circulating CRP are also associated with obesity, insulin resistance, and hyperglycemia [24, 25]. Intake of simple sugars such as glucose and fructose has been associated with increased levels of CRP [26, 27]. Jameel et al. [5] showed a steep increase in serum concentration of CRP within 30 min of fructose ingestion. In contrast, few studies have shown no effect of fructose on CRP concentrations or any other inflammatory biomarkers [15, 28]. These studies and reports show variability with respect to the effects of fructose on serum CRP, and are dependent on individuals’ age, sex, body weight and composition, and genetic makeup.

Serum CRP concentrations are impacted by both genes and the environment. They are heritable, with the heritability ranging between 25% and 60% in twin- and family-based studies [29‒31]. Candidate gene and genome-wide association studies (GWAS) have identified several loci that influence serum CRP concentrations in adults as well as children [29‒35]. However, scant research has been focused on the variability of CRP response to acute fructose, and on the factors that could influence this variability. In our study, we investigated if serum CRP concentrations change after fructose consumption, and whether genetic variants and obesity status influence this change.

The study protocol has been previously described [36]. In short, the study was conducted at the University of North Carolina at Chapel Hill (UNC) Nutrition Research Institute (NRI) in Kannapolis, North Carolina. Its objective was to investigate the effects of a fructose-rich sugar-sweetened beverage (SSB) on inflammation (Fig. 1). The participants were recruited from the Kannapolis, NC area. The participants were recruited from the community through flyers, advertisements, and the NRI website. Inclusion criteria included ages between 30 and 50 years, all sexes, self-reported as Black or White and those who are able to tolerate fructose without any GI distress. The exclusionary criteria included individuals who did not self-report as Black or White, and individuals with self-reported diabetes, chronic kidney disease, and fructose intolerance. Pregnant women were excluded to avoid any adverse effect that acute fructose ingestion might have on the health of the baby. This study was approved by the Institutional Review Board (IRB) of the University of North Carolina at Chapel Hill (IRB # 16-0876). All participants provided written informed consent to participate in the study before the start of the study.

All participants were asked to report to NRI between 06:45 and 08:00 a.m., following a 12-h overnight fast. We also asked all participants not to consume alcoholic beverages the previous night. A single staff member took all the anthropometric measurements to reduce measurement variation and margin of error. We assessed body composition by bioelectric impedance analysis using the Tanita Dual Frequency Total Body Composition Analyzer (DC-430U, Tokyo, Japan). We measured the individual’s weight in a standing position, with participants wearing light clothing and without shoes. The height was measured to the nearest 0.1 cm by using a stadiometer situated against the wall in an upright standing position. We then calculated body mass index (BMI) from height and weight as kg/m². We categorized the participants as normal weight (BMI: 18.5–24.9 kg/m²), overweight (BMI: 25.0–29.9 kg/m²), or obese (BMI ≥30 kg/m²). We measured waist circumference using stretch-resistance tape at the midpoint between the lower margin of the last rib and the top of the iliac crest to the nearest 0.1 inch.

We asked the participants to consume the fructose-rich SSB within 15 min. We prepared the drink by dissolving 60 g of fructose (Now Foods, Bloomingdale, IL, USA) and 15 grams of glucose (Now Foods, Bloomingdale, IL, USA) in 300 mL of water, which provided 300 kcal. The dose of 75 g of sugars was based on an oral glucose tolerance test [37]. We made the drink containing 80% fructose and the rest glucose. This ratio of fructose to glucose (80:20) was determined based on Akhavan and Anderson’s study [38]. The addition of glucose was to alleviate symptoms of gastrointestinal discomfort caused by pure fructose and help with the absorption of fructose [39, 40].

We also asked the participants to fill out a questionnaire on demographic information, medical history, 24-h food recall, and food frequency information. A trained phlebotomist drew the blood at baseline before the drink consumption, and at 30 min, 60 min, 120 min, and 180 min after the fructose ingestion. The blood was collected through venous puncture using 6-mL ethylenediaminetetraacetic acid (EDTA)-coated tubes and serum tubes (BD Vacutainer, Becton, Dickson & Company, Franklin Lakes, NJ, USA). EDTA tubes were placed on wet ice and centrifuged at 3,000 g for 15 min at 4°C within 2 h of collection. We aliquoted and stored serum, plasma, and buffy coat at −80°C until further analysis.

We measured CRP in serum at baseline and at 60, 120, and 180 min after fructose ingestion using ELISA (High-sensitivity, DPCR00, R&D Systems, Minneapolis, MN, USA) as per manufacturer’s instructions. We measured optical density at wavelengths of 450 nm and 540 nm, using a BioTek Synergy 2 Multi-Mode plate reader (BioTek, Winooski, VT, USA) and we generated a four-parameter logistic regression curve as a standard curve to calculate the CRP of serum samples. We analyzed all samples in duplicates and the coefficient of variation (CV) was <5%.

We isolated DNA from the buffy coat (WBC) using the QIAamp DNA Blood Mini Kit (Qiagen Sciences, Valencia, CA, USA) as per manufacturers’ instructions. We measured the concentration of genomic DNA and assessed its quality using a NanoDrop Spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA).

A total of 11 single nucleotide polymorphisms (SNPs) were selected based on previously published reports of associations between CRP concentrations and SNPs located within CRP and other genes [29‒35, 41]. Eight polymorphisms were chosen due to the association with baseline CRP level or their role in CRP. rs2794521 was selected based on its interaction between obesity and high CRP level. Finally, rs17700633 was included because it is related to obesity, a factor that highly influences serum CRP levels [29‒35, 41]. Details about these SNPs, their gene locations and functional consequences are provided in online supplementary Table 1 (for all online suppl. material, see https://doi.org/10.1159/000544832). These SNPs were selected from a set of genotypes included in the genotyping array, the Multi-Ethnic Global Array (MEGA 8) (Illumina Inc., San Diego, CA, USA). The protocol has been described elsewhere [36, 42]. In short, the DNA samples were first amplified and then fragmented by a controlled enzymatic process. After alcohol precipitation and DNA resuspension, the Bead Chip was prepared for hybridization in the capillary flow-through chamber; samples were applied to Bead Chips and incubated overnight. The DNA samples were then annealed to locus-specific 50-mers covalently and hybridized. After hybridization, allelic specificity was conferred by enzymatic base extension. Products were subsequently fluorescently stained. The intensities of the beads’ fluorescence were detected and are, in turn, analyzed using Illumina software for automated genotype calling. Cluster calls were checked for accuracy and genotypes were exported as text files for further use in data analysis. Replicate samples were included as controls for genotyping and allele calling consistencies. DNA samples with known genotypes were used as positive controls. Genotypes were called using Illumina Genome Studio. Samples and SNPs were evaluated based on multiple quality values calculated by Genome Studio and were excluded or further reviewed if they failed with preset standards. Prior to the analysis, individuals were excluded if their genetic sex could not be determined and/or if their missing rate per person was >5%. SNPs with a call rate of <95%, and minor allele frequency <1% were also excluded.

Statistical analyses were performed using STATA software version 17 (College Station, TX, USA). Stepwise linear regression analysis was run with baseline CRP as the dependent variable. Logistic regression analysis was performed to determine the role of selected SNPs in the response of CRP to acute fructose ingestion. The cohort was divided into individuals with and without obesity (BMI >30 kg/m² vs. <30 kg/m²). The analysis used an additive model which was adjusted for race, gender, and age. Proportion test, t test, and Wilcoxon test (non-parametric test) were performed to analyze how age, race, gender, BMI, waist circumference, percent body fat, and baseline CRP level differ between individuals with and without obesity. All results were considered significant at p < 0.05 for non-genetic analysis. For association analysis, we used an additive model in which homozygous genotypes were denoted as 0 or 2 based on their association with CRP in the literature. If an allele was linked with elevated serum CRP, genotype homozygous for that allele was given a score of 2 and homozygous of the other allele was given a score of 0. Heterozygous genotypes for all SNPs were given a score of 1. For SNP association analysis, the significance was set at <0.005 considering multiple tests. A post hoc power analysis was conducted to detect a significant change in CRP post fructose ingestion (p < 0.05). Using the Students’ t test, we showed that a sample size of 57 provided a power of 72% to detect significant differences in CRP between the two obesity groups.

A total of 57 participants, with 20 self-reported as Black, were enrolled and completed the acute fructose challenge. At baseline, participants had an average (mean ± standard deviation) age of 39.23 ± 6.8 years, a BMI of 29.78 ± 7.5 kg/m², and a CRP of 0.36 ± 0.5 mg/dL (Table 1). We categorized participants based on their obesity status (BMI ≥30 kg/m² vs. others). At baseline, CRP concentrations were higher in women (n = 40) than in men (n = 17) (0.40 [0.6] vs. 0.27 [0.4] mg/dL) and White participants (n = 20) than Black participants (n = 37) (0.65 [0.8] vs. 0.21 [0.2] mg/dL). We further dichotomized participants into those with obesity and those without (Fig. 2). Individuals with obesity had higher mean values of weight, waist circumference, % body fat, BMI, and serum CRP concentrations as compared to those without obesity (p < 0.009) (Table 1). Women had slightly higher mean CRP levels at all time points compared to men. Participants identifying as White showed consistently higher mean CRP levels across all five-time points compared to those identifying as Black. Additionally, participants with obesity had higher mean CRP levels at all time points compared to those with weight in the normal and overweight range (Table 1; Fig. 2). Pearson’s correlation analysis showed significant correlations between baseline CRP concentrations and body composition measures (p < 0.005). Similar correlations were also observed for changes in CRP from baseline to 30 min. However, as more time elapsed since the fructose ingestion, the correlations were no longer significant (Table 2).

The effect allele frequencies (EAFs) and summary statistics of the associations between the 11 SNPs and baseline CRP levels are shown in (Table 3). All SNPs were in Hardy-Weinberg equilibrium (HWE) (Table 3). The allele frequencies were different between races (online suppl. Table 2) groups. The regression-based association revealed that two SNPs, rs1417938 and rs2794521, which both reside in the CRP gene, were significantly associated with CRP concentrations. Further stratification by obesity status showed that these SNPs maintained their significance only in individuals without obesity (Table 3). Table 4 presents data on SNPs and their associations with changes in serum CRP concentrations across time intervals (0–30 min, 30–60 min, 60–120 min, and 120–180 min). We found that the effect of SNPs on CRP concentrations was primarily observed only at the 120- and 180-min timepoint post-ingestion. The CRP SNP rs2794521 showed a significant association with change in CRP in the overall population beta = −0.05, SE = 0.02, p = 0.004) and in individuals without obesity (beta = −0.07, SE = 0.02, p = 0.001) during the 60–120-min interval. Another CRP SNP rs3093062 was associated with the changes from 120- and 180-min time points, but only in the overall population (beta = −0.45, SE = 0.16, p = 0.006) (Table 4). Online supplementary Table 3 shows the genotype-specific means of serum CRP for the three SNPs that had significant association with baseline or serum CRP changes in response to fructose ingestion.

The most significant finding of this study is that two of the eleven CRP genetic variants were associated with serum CRP concentrations at baseline and changes in CRP in response to an acute fructose challenge. We observed that these associations are more pronounced in individuals without obesity than those with obesity.

Each individual’s metabolic response to nutrients varies due to factors such as genetic makeup, epigenetics and microbiome profile, and social environment. In our study, we investigated if serum CRP concentrations change after fructose consumption, and whether genetic variants and obesity status influence this variation. Previous studies have shown that fructose consumption increases inflammation [4, 5, 26, 27]. Jameel et al. [5] studied the acute effects of glucose, fructose, or sucrose on metabolic syndrome risk factors and found that fructose was the most effective of the three sugars in modulating CRP and lipids. In a cross-sectional study of 6,858 men from the Health Professionals Follow-up Study, a 20 g/day increase in total fructose intake was associated with about 2% higher concentrations of pro-inflammatory biomarkers. When separated by the source of fructose, they found that fruit fructose was associated with lower concentrations of CRP as compared to other sources [26]. In a clinical trial, 7 patients with type 2 diabetes (T2D) and six healthy participants underwent six interventions with isocaloric drinks. They received fructose in two doses, Coca-Cola, fructose plus glucose, blueberry, and a drink containing fructose, glucose, and sucrose. Some of these drinks were combined with a pizza slice. None of the drinks by themselves increased inflammatory markers. The authors noticed a trend toward higher interleukin 6 (IL6) in the group when given a fructose drink or Coca-Cola with a pizza slice. However, this response was observed only in healthy participants, not in T2D participants [19]. A similar study that investigated the differential effects of acute ingestion of fructose or glucose found a significant increase in CRP concentrations [27]. Additionally, studies investigating other markers of inflammation such as monocyte chemoattractant protein-1 (MCP-1), tumor necrosis factor-alpha (TNFα), or plasminogen activator inhibitor-1 (PAI-1), have shown an increase in these markers as a result of fructose consumption ranging from a few days to weeks [16, 43]. Although CRP concentrations take longer time to peak, a previous study by Jameel et al. [5] did show that fructose has the ability to increase CRP within 30 min of ingestion. Although the duration of response was short (3 h) in our intervention, it is interesting to note that this short response was also affected by genetic variants or obesity status.

In our study, participants with obesity had higher baseline CRP levels; however, their responses to fructose in the 3-h intervention period followed the same trend as those who were healthy or overweight. The differences in individuals with and without obesity were demonstrated in the variability in their responses. Individuals without obesity did not have much variability in their responses as compared to those with obesity. There are not many studies investigating the role of obesity in CRP responses to fructose ingestion. However, other studies have shown that obesity tends to change responses to nutrients [44‒46], which we believe might be the case in our study.

Next, we examined the association of CRP-related SNPs with baseline CRP concentration as well as CRP response to an acute fructose challenge. Allele frequencies of several of these SNPs were different between Blacks and Whites which need to be checked in a larger sample. Genetic studies have shown serum CRP concentrations to be significantly heritable, with the heritability ranging between 25 and 60% [29‒31]. Several polymorphisms, particularly those in the CRP gene, have been associated with circulating concentrations of CRP [29‒36, 42]. This is replicated by our study where all the observed significant associations were between CRP-related SNPs and CRP concentrations at baseline and changes between two time points. Genetic polymorphisms have also been linked to CRP and fructose independently; however, to the best of our knowledge, there are no genetic studies linked to CRP changes in response to fructose, or any sugar, ingestion. A cross-sectional study of 1,043 adult participants of the Framingham Offspring Study cohort investigated the interaction between genetic risk for inflammation and SSB consumption. They analyzed 806 SNPs from 218 linkage disequilibrium (LD) blocks previously shown to be associated with cardiovascular disease and found significant interactions between 38 LD blocks and SSB intake on circulating CRP concentrations [47]. In another study, carbohydrate, glucose, and omega-6 to omega-3 fatty acid ratios have been shown to interact with CRP SNPs to affect CRP concentrations [48].

The mechanism underlying the increase in CRP or general inflammation from elevated fructose intake appears to operate at multiple cellular levels. In endothelial cells, fructose induces inflammation by stimulating the inflammatory molecule intercellular adhesion molecule-1 (ICAM-1) and reducing endothelial nitric oxide levels [49]. One study reports that fructose may increase mammalian target of rapamycin complex 1 (mTORC1) activity, which can translate to an increase in inflammation [50]. Indirectly, fructose contributes to inflammation by increasing reactive oxygen species, serum urate concentrations, liver fat content and fibrosis, and expression of inflammation-related genes [51‒53].

The change in inflammatory biomarkers in response to fructose has not been observed by all the studies. A double-blind crossover design dietary intervention study in 24 adults with healthy weight and obesity found no change in CRP concentrations after an 8-day ingestion of 4 servings/day of fructose [28]. Additionally, a meta-analysis and a systematic review of 13 studies involving 1,141 participants have shown that dietary fructose, either by itself or as part of high-fructose corn syrup, may not increase subclinical inflammation more than any other dietary sugar [15]. Similarly, in our study, although baseline CRP concentrations varied between men and women, Black and White participants, and individuals with and without obesity, their CRP response to fructose was of the same magnitude. Overall, our study shows that the mean CRP did not increase with acute fructose challenge. However, there was considerable variability in baseline CRP and responses in CRP which were associated with CRP SNPs. Additionally, we found that these associations were more prominent in individuals without obesity. Our study’s small sample size and the short observation period may have limited our ability to detect the effect of fructose on serum CRP. There is a need for studies that aim to unravel genetic association, influencing the responses to nutrient intake. The role of factors such as sex, obesity status, ethnicity or genetics in variability in responses to nutrient intake is understudied. Studies, like our pilot study, provide data and a basis for the variability in responses, and justification for such studies in large samples, similar to Nutrition for Precision Health and others [54, 55]. Additionally, since our sample size was small, we focused on SNPs from candidate genes which have been associated with CRP before. It is also not clear if the acute changes in CRP have clinical and health significance except in individuals who drink SSBs every 3 h or more often. However, these results do suggest the immediate effect of fructose-rich drink on CRP. Therefore, associations need to be interpreted with caution and need to be replicated in a larger population for a longer length of time. Additionally, a genome-wide scan beyond the 11 SNPs will likely yield more findings. Despite these limitations, the observed variability in CRP responses and the significant SNP associations at various post-ingestion time points suggest that further research is warranted. These findings also underscore the importance of specific alleles in influencing nutrient response, shedding light on potential avenues for personalized nutritional intervention approaches.

We thank the participants of the Fructose Challenge Study for their participation.

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of the University of North Carolina at Chapel Hill (IRB protocol # 16-0876). Written informed consent was obtained from all participants to participate in the study.

The authors declare that this study was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

This research was funded partially by NIH/NIDDK-P30DK056350 and partially by a University of North Carolina Junior Faculty Development Award to V.S.V.

Conceptualization, resources, data curation, and funding acquisition: V.S.V.; methodology: B.B.M., X.Z., and V.S.V.; formal analysis: S.S.V., V.T., R.S., G.V., and V.S.V.; investigation: S.S.V., X.Z., and V.S.V.; software, validation, writing – original draft preparation, writing – review and editing, visualization, and supervision: S.S.V. and V.S.V.; and project administration: X.Z. and V.S.V. All authors have read and agreed to the published version of the manuscript.

Data supporting the findings of this study are not publicly available due to privacy reasons, but are available from the corresponding author upon reasonable request with the corresponding author.