Association between periodontitis and uric acid levels in blood and oral fluids: A systematic review and meta-analysis

doi:10.21203/rs.3.rs-2251617/v1

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Association between periodontitis and uric acid levels in blood and oral fluids: A systematic review and meta-analysis

https://doi.org/10.21203/rs.3.rs-2251617/v1

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published 28 Mar, 2023

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Background

Uric acid, a formerly-known antioxidant that has recently been linked with many inflammatory diseases as a pro-inflammatory and -oxidative mediator in pathological conditions. It is imperative to reassess the association between periodontitis and uric acid in locally and systematically. The aim of this systematic review was to systemically evaluate the association of periodontitis with the uric acid (UA) levels in blood, saliva and gingival crevicular fluid (GCF).

Methods

Relevant clinical studies up to July 1, 2022 were identified and retrieved from electronic databases, with periodontitis, uric acid, hyperuricemia and gout as the keywords. Weighted (WMD) or standardized mean difference (SMD) was calculated using fixed- or random-effect models. Methodological heterogeneity was assessed.

Results

Fifteen eligible retrospective studies (blood, n = 7; saliva, n = 8; GCF, n = 1) were enrolled, which included 1302 patients with periodontitis and 916 controls. Meta-analysis demonstrated a statistically enhanced blood UA content (WMD = 0.49 mg/dL, 95% CI: 0.02 to 0.96, P = 0.042) but decreased salivary UA level (SMD = -0.95, 95% CI: -1.23 to -0.68, P < 0.001) in periodontitis versus control. Statistical heterogeneity was significant among studies involving blood (I² = 94.3%, P < 0.001) but not saliva (I² = 33.8%, P = 0.196).

Conclusions

Periodontitis is associated with higher UA levels in blood and lower UA levels in saliva. The indicative mechanisms need to be verified by further clinical and experimental studies. (Registration no. CRD42020172535 in Prospero).

Gout

hyperuricemia

periodontitis

purine

uric acid

Periodontitis is a multifactorial chronic inflammatory condition related to dysbiosis and characterized by progressive damage of tooth-supporting apparatus [1]. Severe periodontitis affects 11% of global population and can lead to tooth loss and low quality of life [2]. Impaired immune and metabolic response induced by periodontal pathogens is the critical feature in the pathogenesis of periodontitis [3, 4]. However, the underlying mechanisms remain unclear, which make an early prevention difficult.

Oxidative stress has been considered as an important mechanism in the progression of periodontitis [5]. It is formed when reactive oxygen species overproduced by immune cells under infection cannot be buffered by the antioxidant defense system, which would cause lipid, protein and DNA damage [6]. Of the antioxidant pools, uric acid (UA) used to be considered as an important antioxidant for scavenging radicals. However, its anti-oxidative roles seem to be limited and happen only in hydrophilic environments [7]. Recent studies have identified hyperuricemia (i.e., blood UA levels > 6.5 mg/dL) as risk factors for many inflammatory conditions such as gout, diabetes, metabolic syndrome and cardiovascular diseases [8–10]. Namely, UA can display pro-oxidative effects in specific environments. For instance, UA can react with peroxynitrite to form radicals [11, 12]. It can also enhance intracellular superoxide production by elevating nicotinamide adenine dinucleotide phosphate (NADPH) oxidase activity [13]. Hence, the current consensus accepts that a pathological elevation of UA levels (i.e., hyperuricemia) represents a pro-inflammatory, -oxidative and -osteoclastic state [7].

UA was recognized as an anti-oxidative parameter in previous research [14, 15] on periodontitis. Alterations of UA levels in blood have been associated with the presence or severity of periodontitis [16, 17]. Interventions with urate-lowering drugs have shown beneficial effects on animals with periodontitis [18, 19]. However, a re-assessment of their association is urgent because the findings in relevant studies are very conflicting. First, blood UA levels in periodontitis patients had been found to be either upregulated, downregulated or unchanged compared to controls [20–22]. There were contradictory findings in saliva as well [22, 23]. Second, UA levels tended to be increased in blood whereas decreased in saliva in the presence of periodontitis [24]. Third, periodontal treatment caused various changes in UA levels relative to baseline [25]. Therefore, a systematic review on previous findings would be imperative for integrating the paradoxical data. It would also be helpful in answering an unresolved question that whether there is a potential link between hyperuricemia and periodontitis [19, 25, 26]. The present systematic review and meta-analysis focus on the question that whether there are changed UA levels in blood, saliva or gingival crevicular fluid (GCF) in periodontitis patients versus controls.

The systematic review and meta-analysis have been registered in PROSPERO (no. CRD42020172535) and prepared according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement [27]. The present study aimed to test whether there is an association between blood/oral UA and periodontitis. Following the Population-Exposure-Comparators-Outcomes principles, the study focused on the differences in UA levels in blood/saliva/GCF between periodontitis patients and controls.

2.1 Eligibility criteria

The studies should be prospective/retrospective cohort, cross-sectional/case-control study, or randomized/non-randomized controlled trials. The excluded studies were case reports/series, animal/in-vitro study, narrative/systematic review, conference abstract, editorial, letter and comment. And as for full-text review, the selecting criteria were as follows.

2.1.1 Definition of periodontitis and periodontal health control

Periodontitis should be diagnosed as plaque-induced periodontal destruction, which was measured by periodontal probing or radiography. In epidemiological view, periodontal healthy control concerned in the present study would include not only clinical periodontal health but also mild (Stage I) or localized periodontitis.

2.1.2 Inclusion criteria

a) Periodontitis should be clearly defined or stated;

b) periodontitis and control groups should have UA levels in blood, saliva or GCF measured;

c) participants in systemic health or with gout/hyperuricemia but without systemic complications (e.g., renal dysfunction including abnormal glomerular filtration rate);

and d) participants in interventional studies should have baseline/pre-treatment UA levels recorded.

2.1.3 Exclusion criteria

a) studies without periodontitis patients or control groups;

b) female subjects during pregnancy;

c) subjects with potential comorbidities shared by hyperuricemia and periodontitis, such as cardiovascular diseases, diabetes, osteoporosis, chronic kidney disease, metabolic syndrome and obesity [25];

d) subjects with other potential conditions associated with altered purine/UA metabolism such as inflammatory bowel diseases [28, 29], hyperparathyroidism [30] and vitamin D deficiency [31];

e) subjects with significant systemic diseases or conditions such as cancers, liver cirrhosis, organ transplantation, etc.;

and f) subjects receiving antibiotics or anti-inflammatory or urate-lowering drugs or have had periodontal treatment in the past three months.

2.2 Information sources and search strategy

Highly sensitive electronic search was conducted in four databases, including the PubMed, Scopus, Web of Science and Embase with no language restriction (update to July 1, 2022). The following search model was accomplished using Boolean operators. For exposure, “periodontal diseases” and “periodontitis” were used, with “apical periodontitis” excluded. Regarding samples tested for UA, the keywords “blood”, “serum”, “plasma”, “circulation”, “GCF”, “gingival crevicular fluid” and “saliva” were used. As for outcome, the keywords “UA”, “urate”, “purine”, “hyperuricemia”, “gout” and “antioxidant” were used. The advanced search was based on each database-specific search strategies (see the Supporting Information). The search terms employed were either medical subject headings (MeSH) terms or keywords classified under general category (title/abstract/keywords).

2.3 Study selection

Initial assessment of titles and abstracts was conducted by two independent reviewers (L.Y. and L. Z.), followed by full-text screening for the eligible articles. Disagreement was discussed until reaching a consensus or through arbitration by the supervisor (T. Y.). During the process, any study that failed to meet the eligibility criteria was excluded and the reason would be formally recorded in detail. Inter-examiner agreement for the full-text screening between the two reviewers was assessed by κ test (κ values > 0.75 and < 0.4 indicated high and weak consistency, respectively [32].

2.4 Quality assessment

Newcastle-Ottawa Scale (NOS) (Wells et al., 2001) and the Agency for Healthcare Research and Quality (AHRQ) methodology checklist were used to assess the methodological quality of case-control study and cross-sectional study, respectively. Quality assessment was conducted by two reviewers independently (L. Y. and L. Z.).

For Newcastle-Ottawa Scale, the total score of quality ranged from 0 to 9 stars (7 to 9, 5 to 6 and < 5 stars indicated high, moderate and low quality, respectively) [33]. Regarding ARHQ, studies with 8 to 11, 4 to 7 and 0 to 3 points were recognized as high, moderate and low quality, respectively [34]. Any disagreement would be discussed with a third reviewer (T. Y.).

2.5 Data extraction

Once these studies were identified, two reviewers independently extracted the information including bibliometric information (the names, e-mail addresses and institutions of authors, publication date and journals of articles, etc.), characteristics of study design (study place/type, diagnostic criteria of periodontitis/control groups and sample size, etc.), demographics of participants (sex, age, race and smoking habit [35, 36], periodontal parameters (probing pocket depth, gingival/plaque index, bleeding on probing, clinical attachment loss, radiological alveolar bone loss, etc.), collection methods for saliva (resting/stimulated) or blood (plasma/serum) or GCF (paper strip/point), detection methods for UA (enzyme-based colorimetric method or gas chromatography/mass spectrometer, etc.), statistics for UA levels (means and standard deviations (SDs)/errors (SEs)) in periodontitis and control groups. Corresponding authors of the included articles were contacted by e-mail for three times to request for the raw data including the sex and age of the participants. Unresponsive or undelivered mails were considered as no response.

2.6 Data conversion and preprocessing

The UA levels could be documented in mg/dL, µmol/L, mmol/L or relative units. In the present systematic review, the unit was reported in mg/dL (1 mg/dL = 59.48 µmol/L) [37]. According to the new classification for periodontal diseases [38], chronic and aggressive periodontitis are no longer distinguished from each other and the data here were synthesized. The data of UA in periodontitis at different stages or in one kind of sample with different collection methods were also combined based on the means, SDs and sample size in corresponding subgroups. If some studies reported SEs instead of SDs, the formers were converted to SDs (SD = SE×\(\surd n\)) [39]. If the data of UA in a study were shown in bar charts without detailed values, the heights were measured for three repeats using a digital ruler (v1.8.0, Image J, National Institutes of Health, Bethesda, MD, USA) to calculate the absolute values.

2.7 Statistical analyses

Statistical analyses were conducted with a commercial software (v 14.0, STATA, Stata Corporation, College Station, TX). The UA levels is presented as means ± SDs. The distribution of potential confounders (i.e., sex and age) that may modify the UA levels were compared[40]. Meta-analyses are displayed as forest plots. For continuous outcomes, it would be calculated as weighted mean differences (WMDs) or standardized mean differences (SMDs). Statistical heterogeneity was estimated by Cochrane’s Q test and Higgins’s I² test (I² = 0, no heterogeneity; I² < 50%, low heterogeneity; I² < 75%, moderate heterogeneity; I² > 75%, high heterogeneity) [41]. If a statistically significant heterogeneity was found, a random-effect model was used; otherwise, a fixed-effect model was applied. Subgroup analysis was conducted based on collection methods of testing samples (i.e., serum vs. plasma). P < 0.05 was considered statistically significant. Publication bias was assessed by Egger’s tests [42]. If publication bias was detected, the Duval and Tweedie trim-and-fill method was used for adjustment [43]. If statistical heterogeneity was indicated, sensitivity analysis was conducted by excluding the studies one by one to observe whether the heterogeneity was dramatically changed.

3.1 Study selection

A total of 348 potentially eligible records were found through the highly sensitive electronic search, of which 221 were included for abstract review and 66 included for full-text evaluation. Finally, 15 articles [17, 20–23, 44–53] were retained for systematic review. Characteristics of the 15 included studies are presented in Table 1. The selection flow for included studies was presented in Fig. 1. The reasons for excluded studies were recorded (Table S1). Additionally, the κvalue of agreement between the two reviewers during the full-text review showed good consistency (κ = 0.84).

Table 1

Detailed characteristics of included studies.
Citations	Study location	Study type	Diagnosis of periodontitis	Statement on periodontal controls	Sample size [P (M/F) vs. C (M/F)]	Age (years; P vs. C) ^†	Periodontal parameters (mm, P vs. C) ^†	Sample/Collection method	Detection method for UA	UA levels (P vs. C) ^†	Quality assessment
Gharbi et al., 2019	Africa (Tunisia)	Case control	AAP criteria	Periodontal health	80 (33/47) vs. 50 (25/25)	42 ± 13.6 vs. 44.8 ± 12.6	PPD: 5.3 (2.5–7.5) vs. 1 (0.5-2)	Blood/Plasma	EBCM	5.22 ± 0.91 vs. 4.13 ± 1.11(mg/dL) ^‡	NOS:8
Banu et al., 2015	Asia (India)	Case control	Clinically ≥ 4 teeth in each jaw; PPD ≥ 5 mm; CAL ≥ 4 mm; ≥ 80% BOP + at proximal sites; presence of ABL in ≥ 2 quadrants of the dentition; interproximal ABL ≥ 50%	Without periodontitis	40 (14/26) vs. 20 (9/11)	40–65	PPD: 5.55 ± 0.29 vs. 2.28 ± 0.13	Blood/Plasma	EBCM	5.32 ± 0.95 vs. 4.42 ± 0.68 (mg/dL)	NOS:8
Mourão et al., 2015	South America (Brazil)	Case control	AAP criteria	PPD < 3 mm in all tooth sites and absence of CAL	20 (8/12) vs. 20 (8/12)	54.3 ± 10.02 vs. 50.2 ± 8.79	NM	Blood/Plasma	EBCM	6.45 ± 1.44 vs. 4.77 ± 0.81 (mg/dL)	NOS:7
Narendra et al., 2018	Asia (India)	Cross-sectional	AAP criteria	NM	78 (40/38) vs. 50 (33/17)	38.34 ± 12.08 vs. 36.56 ± 6.26	CAL: 4.60 ± 0.51 vs. 1.49 ± 0.25	Blood/Serum	EBCM	5.10 ± 0.31 vs. 5.11 ± 0.54 (mg/dL)	AHRQ:6
Sreeram et al., 2015	Asia (India)	Cross-sectional	≥ 14 teeth; BOP + at ≥ 30% periodontal sites with PPD = 1–3 mm; BOP + and CAL ≥ 3 mm at ≥ 30% of all sites	≥ 14 teeth; BOP + at༜30% sites with PPD = 1–3 mm; BOP + and CAL ≥ 3 mm at ༜ 30% of all sites	150 (114/36) vs. 150 (120/30)	41.0 ± 12.2 vs. 34.2 ± 12.0	NM	Blood/Serum	EBCM	4.29 ± 1.15 vs. 4.93 ± 0.87 (mg/dL)	AHRQ:7
Brotto et al., 2011	South America (Brasil)	Case control	≥ 14 teeth including third molars; at least 4 different teeth had at least one site with PPD = 3–5 mm, and at least 4 others different teeth had at least one site with PPD = 6–10 mm; the proportion of all sites were considered to be AL > 2 mm and PPD > 2 mm.	≥ 14 teeth including third molars; BOP + at < 30% sites with PPD = 1–3 mm, only 2 isolated sites with PPD = 4 mm and BOP-, and CAL ≥ 3 mm at < 30% of all sites	30 (16/14) vs. 30 (16/14)	46 ± 6 vs. 43 ± 5	PPD: 2.25 (1.39–3.62) vs. 1.00 (1.00-1.40) CAL: 2.58 (1.45–4.50) vs. 1.00 (1.00-2.27)	Blood/Serum	EBCM	4.9 ± 2.1 vs. 4.3 ± 1.7 (mg/dL)	NOS:6
Tsai et al., 2021	Asia (China)	Cross-sectional	Localized stage II/III periodontitis	Periodontally healthy or stage I periodontitis	295(269/26) vs. 828༈726/102༉	30.88 ± 5.35 vs. 29.38 ± 5.56	PPD: 3.03 ± 0.04 vs.2.92 ± 0.05 CAL: 3.07 ± 0.06 vs. 2.93 ± 0.06	Blood/Serum	EBCM	6.73 ± 1.45 vs. 6.49 ± 1.41 (md/dL)	AHRQ:7
Sakanaka et al., 2017	Asia (Japan)	Case control	PISA > 215	PISA < 215	35 vs. 15	NM	PISA: 490.8 (200.5-1238.5) vs. 199.3 (155.5-252.8)	Saliva/Resting	Gas Chromatography - Mass Spectrometry	112.32 ± 66.02 vs. 155.83 ± 82.69 (Intensity)^§?	NOS:6
Novakovic et al., 2014	Europe (Serbia)	Case control	≥ 3 teeth per quadrant; at least one pocket PPD > 5 mm with BOP + per quadrant; and ABL > 30%	Periodontally healthy	42 (28/14) vs. 21 (14/7)	39.0 ± 11.81 vs. 35.2 ± 7.1	PPD: 3.38 ± 0.58 vs. 2.11 ± 1.67; CAL: 3.00 ± 1.00 vs. 0	Saliva/Resting	EBCM	153.93 ± 40.88 vs. 198.43 ± 87.73 (relative level)	NOS:6
Miricescu et al., 2014	Europe (Romania)	Cross-sectional	Gingival inflammation; at least six sites with PPD ≥ 4 mm; and ABL > 30%	NM	25 (11/14) vs. 25 (5/20)	51.26 ± 7.4 vs. 18.66 ± 2	PPD: 4.41 ± 0.42 vs. 0	Saliva/Resting	EBCM	2.41 ± 0.27 vs. 3.12 ± 0.85 (mg/mg albumin)	AHRQ:4
Mathur et al., 2013	Asia (India)	Case control	CPITN > 2	CPITN ≤ 2	30 vs. 10	NM	NM	Saliva/Resting	EBCM	2.34 ± 0.4 vs. 5.19 ± 0.8 (relative level)	NOS:4
Fatima G et al., 2016	Asia (India)	Case control	PPD = 6mm or presence of CAL	No periodontal pockets as assessed by Williams periodontal probe	10 (4/6) vs. 10 (4/6)	46.30 ± 8.62 vs. 27.30 ± 4.37	NM	Saliva/Resting	EBCM	3.01 ± 0.68 vs. 5.39 ± 1.49 (mg/dL)	NOS:7
Sharma et al., 2018	Asia (India)	Cross-sectional	Russell’s periodontal index and a panoramic radiograph	Russell’s periodontal index, and a panoramic radiograph	25 vs. 25	34.32 vs. 30.68	NM	Saliva/Resting	EBCM	1.95 ± 0.42 vs. 3.72 ± 1.02(mg/dL)	AHRQ:7
Senouci et al., 2021	Africa (Algeria)	Case control	stage III– IV, grade C periodontitis	without clinical signs of periodontal disease as measured by PPD or any CAL	29 (6/23) vs. 28 (7/21)	24.06 ± 6.09 vs. 24.73 ± 1.38	PPD: 7 ± 1.68 vs. 1.7 ± 0.3; CAL: 7.81 ± 1.79 vs. 1.4 ± 0.2	Saliva/Resting	EBCM	1.43 ± 0.93 vs. 2.78 ± 1.60(mg/dL)	NOS:8
Diab-Ladki et al., 2003	Asia	Case control	Severe periodontitis (with tooth mobility, gingival recession and up to one-half of ABL)	Apparently healthy gingiva	17 vs. 20	30–45	NM	Saliva/Stimulated	EBCM	2.41 ± 2.32 vs. 2.68 ± 2.46 (mg/dL) ^‡§?	NOS:2
Narendra et al., 2018	Asia	Cross-sectional	AAP criteria	NM	78 (40/38) vs. 50 (33/17)	38.34 ± 12.08 vs. 36.56 ± 6.26	CAL: 4.60 ± 0.51 vs. 1.49 ± 0.25	GCF/Paper strip	EBCM	4.87 ± 0.36 vs. 5.11 ± 0.53 (mg/dL)	AHRQ:6
The AAP criteria for diagnosis of periodontitis are determined by measuring PPD, gingival bleeding index and plaque index, chronic periodontitis were those with BOP⁺ and PPD ≥ 4 mm in at least 30% of the total sites before implant placement [54]. PISA is a calculated index based on BOP⁺, CAL and gingival recession to reflect periodontal inflammation. PISA score for an individual tooth = percentage of BOP⁺ sites × (attachment loss surface area - recession surface area). The PISA scores of total teeth in a mouth were summed to get a total PISA value for a patient (Nesse et al., 2008). The CPITN is an index with five degrees according to BOP, presence of dental calculus and PPD (0, normal; 1, gingivitis with BOP⁺; 2, presence of calculus; 3, PPD ≥ 3.5 mm; and 4, PPD ≥ 5.5 mm) (Ainamo et al., 1982). †, the data of periodontal parameters, age and UA levels are presented as means ± standard deviations or medians (interquartile range);‡, For uric acid, 1 mg/dL = 59.48 µmol/L; §, Standard errors were converted to standard deviations; ?, Data of UA in bar charts without numerical display were measured using a digital ruler; AAP, American Academy of Periodontology; ABL, alveolar bone loss; AHRQ, Agency for Healthcare Research and Quality; BOP, bleeding on probing; CAL, clinical attachment loss; CPITN, community periodontal index of treatment needs; EBCM, enzymatic colorimetric methods; GCF, gingival crevicular fluid; NM, not mentioned; NOS, Newcastle-Ottawa Scale; M/F, male/female; P vs. C, periodontitis vs. control; PPD, probing pocket depth; PISA, periodontal inflamed surface area.

3.2 General characteristics of included studies

Detailed characteristics of the 15 included studies are presented in Table 1. The identified 15 studies were published between the years 2003 and 2021. Nine studies were conducted in Asia, two in Europe, two in South America and two in Africa. There were nine case-control studies, five cross-sectional studies and one RCT. A total of 2218 participants were included (916 patients with periodontitis vs. 1302 healthy controls). The participants generally aged between 20 and 50. Most (11/15) of the studies have a balanced gender composition between periodontitis and control groups. The sample size in the studies ranged from 20 to 1123. Three sample types were involved for UA detection including blood (seven studies), saliva (eight studies) and GCF (one study). Fourteen studies detected the UA levels with enzymatic colorimetric methods, while one analyzed the UA content using gas chromatography-mass spectrometry.

3.3 Definition of periodontitis and control

Regarding the exposure factor, six studies gave clear but different criteria on definition of periodontitis. Four studies used the criteria of American Academy of Periodontology (AAP) in 1999 [54], two used the new classification for periodontal diseases in 2018, and one used Community Periodontal Index of Treatment Needs (CPITN). Besides, one study distinguished periodontitis from control according to periodontal inflamed surface area (a secondary index calculated from clinical attachment loss, gingival recession and bleeding on probing). The remaining eight studies either gave an unclear definition of periodontitis (7/8) or only included severe periodontitis without clear diagnostic criteria (1/8).

The controls for periodontitis in the included studies were not clearly defined. Only four studies claimed clinical periodontal health as controls. Five studies gave clear criteria on definition of controls. That is, one used CPITN ≤ 2 (0, normal; 1, gingivitis with bleeding on probing; 2, presence of calculus) as controls, one used periodontal inflamed surface area (PISA) < 215. Besides, in the control groups, two studies allowed the presence of localized periodontitis and another one combined healthy periodontium with stage I periodontitis. As for the remaining studies, four gave an unclear definition of controls and two did not mention the controls at all.

As potential confounders, sex and age were two candidate variables for subgroup analysis, which, however, could not be conducted due to missing data. Furthermore, smokers were rejected clearly in most studies (12/15). Two studies did not mention whether they included smokers or not. None of the studies mentioned body mass index.

3.4 Risk of bias and methodological quality

The results of assessment on the risk of bias were shown in the Table S2 and S3. Of the nine case-control studies assessed by NOS, five had good quality (7 to 8 scores), two showed moderate (6 scores) and two exhibited low (2 and 4 scores) (Table S2). The five cross-sectional studies had moderate quality (4 to 7 scores) in the AHRQ checklist (Table S3).

3.5 Are UA levels changed in blood in periodontitis vs. control?

To answer whether periodontitis patients have changed UA levels in blood compared to control, seven studies (693 periodontitis patients vs. 1148 controls) were included. Of them, three used plasma and the other four used serum as testing samples. Five studies found increased UA levels in blood in periodontitis vs. control, one found a decrease and the remaining ones showed no significant change. Meta-analysis using a random-effect model showed that periodontitis and control groups had statistically comparable UA content in blood (WMD = 0.49 mg/dL, 95% CI: 0.02 to 0.96, P = 0.042) (Fig. 2). Whereas, the statistical heterogeneity between the studies was high (I² = 94.3%, P < 0.001). Sensitivity analysis failed to found any obvious influence of individual study on the pooled risk estimates (Figure S1). Next, subgroup analysis was performed based on the blood collection methods (plasma vs. serum). It showed that periodontitis patients had significantly higher UA levels in plasma (WMD = 1.13 mg/dL, 95% CI: 0.77 to 1.48, P < 0.001) but comparable UA content in serum (WMD = -0.04 mg/dL, 95% CI: -0.47 to 0.39, P = 0.847) as compared to controls (Figure S2). In this case, the plasma subgroup had low statistical heterogeneity (I² = 40.1%, P = 0.188), while that in the serum subgroup was high (I² = 91.6%, P < 0.001).

3.6 Are UA levels changed in saliva in periodontitis vs. control?

The second question is “whether periodontitis patients have altered UA levels in saliva compared to the control?” Eight studies with 213 patients versus 154 controls were included. Unlike the content of UA in blood, those in saliva could not be unified in the enrolled studies due to various units (four used mg/dL and the other four gave semi-quantitative data). Whereas, the eight studies consistently showed decreased levels of salivary UA in periodontitis vs. control. Meta-analysis with a random-effect model demonstrated that salivary UA content was significantly reduced in periodontitis versus control (SMD = -1.52, 95% CI: -2.25 to -0.79, P < 0.001) (Figure S3). There was a high heterogeneity among the studies (I² = 88.6%, P < 0.001). Sensitivity analysis (Figure S4) helped to obtain a low heterogeneity (I² = 33.8%, P = 0.196) by removing three studies [45, 47, 52]. In this case, periodontitis was still associated with a reduction of UA levels in saliva as compared to the control (SMD = -0.95, 95% CI: -1.23 to -0.68, P < 0.001) in a fixed-effect model (Fig. 3).

3.7 Association of UA in GCF with periodontitis

There was only one cross-sectional study (78 vs. 50, periodontitis patients vs. controls) reporting UA levels in GCF (Table 1). The study was assessed as high quality (5 scores) (Table S2). GCF in the study was collected with paper strip and UA content was detected by enzymatic colorimetric methods. Similar to the findings in saliva, the outcome showed a significant decrease of UA levels by 4.93% in periodontitis versus control [4.87 ± 0.36 vs. 5.11 ± 0.53 (mg/dL)].

3.8 Publication bias

Publication bias cannot be ruled out given the limited number (< 10) of studies. Mandatory analysis with Egger's test showed no publication bias for studies detecting blood UA (P = 0.166, n = 7) but potential bias for those involving salivary UA (P = 0.024, n = 8).

The present study explored the association of oral/blood UA with periodontitis using systematic review and meta-analysis. We found a positive correlation between periodontitis and blood UA content. The increased blood UA might result from accelerated purine degradation in both periodontal tissues and systemic organs. In periodontium, accelerated purine catabolism and enhanced xanthine oxidoreductase expression have been observed in periodontitis patients [24, 55]. Enhanced secretion of UA has been found in immune cells stimulated with periodontal pathogens [55, 56], as well as in gingiva in periodontitis mice [4]. Given that ubiquitous xanthine oxidoreductase was sensitive to inflammation and oxidative stress [57], a low-grade systemic inflammation induced by periodontitis might accelerate purine catabolism in distant organs. For instance, periodontal infection is associated with increased UA content in liver and feces in rodents [58, 59]. However, it should be noted that the present study only supported a positive association between blood UA and periodontitis in the context of normouricemia. UA has been considered as a potent antioxidant in blood, especially at a physiological level [7, 60, 61]. However, such theory has not been strictly tested in the field of periodontology. Namely, whether an elevated UA levels in circulation or periodontal vessel in a state of normouricemia is a beneficial or harmful response for periodontitis is unknown.

Almost no evidence has directly explored the association of periodontitis with hyperuricemia or gout. One cross-sectional study identified hyperuricemia as a protecting factor for periodontitis [26]. However, the outcome was measured by questionnaire and only represented a retrospective history of periodontitis. Gouty patients generally have increased abundance of periodontal pathogens (e.g., Prevotella Intermedia) [62]. Given that the highly prevalent hyperuricemia is considered an emerging risk factor for many inflammatory comorbidities of periodontitis (e.g., cardiovascular disease, diabetes, and chronic kidney disease) [63], its association with periodontitis would be an interesting research topic. Recent research has indicated a pathological role of UA in periodontitis. For instance, systemic injection of UA aggravated the alveolar bone loss in periodontitis mice [19]. A urate-lowering drug febuxostat alleviated experimental periodontitis induced by molar ligation in rats [18]. Moreover, non-surgical periodontal treatment in periodontitis seemed to have a urate-lowering effect in circulation [64]. Taken together, increased blood UA at a pathological level appears to contribute to the progression of periodontitis.

Interestingly, the change of UA in saliva shows an opposite trend compared to that in blood in periodontitis patients versus controls. UA has been considered as a major antioxidant in saliva, accounting for ~ 70% of total antioxidant capacity [65]. However, the content of antioxidants including UA in saliva does not seem to mirror those in blood [14]. A reduced level of salivary UA in periodontitis might be due to either increased consumption or decreased production. Increased consumption of salivary UA might be due to the enhanced oxidative stress induced by periodontal infection. In the presence of oxidative stress, UA might be oxidized by reactive oxygen species into allantoin in the absence of uricase [66]. Additionally, UA can be used as substrate for the synthesis of bacterial components [25], such process might be accelerated with increased dental plaque accumulation. Decreased production of salivary UA might result from some substances that can inhibit the purine oxidation activity of the UA-producing enzyme (i.e., xanthine oxidoreductase). For instance, there is an increased demand of nitrate and its downstream products nitrite and nitric oxide in saliva for killing bacteria and limiting inflammation in periodontitis [67]. These substances might competitively inhibit the purine-oxidizing activity of xanthine oxidoreductase, considering that xanthine oxidoreductase also has a nitrate/nitrite reductase activity [68, 69]. In summary, the mechanisms underlying the reduction of salivary UA in periodontitis are unclear, and further investigation is warranted.

The present systematic review included only one article that found a decreased level of UA in GCF in periodontitis patients. The result was consistent with the findings from some studies left out [24, 70]. The changes of UA in GCF appeared to mirror those in saliva. Different from saliva that comes from salivary glands, GCF is serum transudate during periodontal health or inflammatory exudate during periodontal diseases [71]. In the context of periodontitis with an increased UA content in blood, it was not likely that there was decreased exudation of UA from circulation into GCF. A more likely scenario, similar to that of saliva, would be that the consumption of UA might be enhanced by subgingival microbiota. Moreover, it should be noticed that some urate transporters (SLC2A9 and SLC22A12) showed increased gene expressions in gingival tissues from periodontitis patients [72], which could be a potential contributor or confounder for a changed UA content in periodontal pockets.

There were some potential confounders that might influence the applicability of the present study. The data of sex, age and smoking, which have been associated with hyperuricemia or altered tissular UA in the past studies [73–75], were partly missing. We failed to obtain the original data from the corresponding authors in relevant studies. However, it could be seen that the distribution of age and sex was even in most or all of the studies (age, 6/11; sex, 11/11). Smoking was not likely to have a significant impact on the results given that most (12/15) of the studies had excluded smokers. The data of body mass index (a common confounder), which has been reported to significantly impact blood UA [76, 77], were completely missing. Hence, it was unclear how much and to what extent the impact of body mass index has on the results.

Definition of periodontitis and control could be another source of bias. A variety of definitions on periodontitis were likely to weaken the comparability between the included studies. The control groups in many studies not only included healthy periodontium, but might also be mixed with gingivitis, mild periodontitis and even localized moderate-to-severe periodontitis. Such mixture might make the difference of UA levels between periodontitis and control underestimated. Additionally, the severity of periodontitis seems also to be associated with UA levels in blood or saliva [16, 25, 78, 79]. For instance, patients with severe periodontitis had higher blood UA levels than those with mild or moderate periodontitis [16]. Thus, severe periodontitis might be more related to altered UA levels. It is suggested that researchers use a uniform criterion on periodontitis and control, i.e., the new classifications of periodontal diseases in 2018, in future studies.

The collection and testing methods of samples might be potential confounders of interest. Some studies found no difference in UA levels detected by enzymatic colorimetric methods between plasma and serum [80, 81]. Another study showed a higher UA content in plasma with 1.59 folds of that in serum as detected by gas chromatography-mass spectrometry [82]. Such discrepancy might be attributed to the differences in technological sensitivity [83]. The present study did not calibrate the UA levels from the two types of blood samples because all of the included studies detected the UA content using enzymatic colorimetric methods. Notably, subgroup analysis on studies involving blood UA showed that the statistical heterogeneity was much smaller in plasma subgroup than that in serum one. A better homogeneity in the plasma subgroup might be partly due to that anticoagulant (e.g., ethylenediamine tetracetic acid) inhibit xanthine oxidoreductase activity and thus reduce UA production from undesired sources [84], while sustained purine degradation might still occur in serum. Another anticoagulant heparin sodium, however, does not appear to affect xanthine oxidoreductase activity [85]. Hence, plasma with specific anticoagulants might be a favorable sample type over serum for comparing the results of blood UA content across different studies. Whether collection methods influence the results of UA levels in saliva would be another concern. Resting saliva seems to have a higher UA content than stimulated saliva [65]. However, the resting to stimulated ratios were found to be approximate (around 2:1) in both periodontitis and control participants. Moreover, the final meta-analysis ruled out the studies involving stimulated saliva. Thus, collection method of saliva might not be a significant confounder in the present meta-analysis.

The present systematic review and meta-analysis had some limitations. Firstly, the number and sample size of included studies (especially those involving saliva and GCF) were limited. The findings should be interpreted with caution before conformation by large-scale studies. Secondly, the findings were mainly derived from retrospective studies which should be tested further by prospective and interventional studies. Finally, the raw data of some potential confounders (i.e., age, smoking and body mass index) were not available and the impacts of them (especially body mass index) on the results were unknown. It might be a source of statistical heterogeneity in the present meta-analysis. Taken together, high-quality studies, especially prospective cohort study and interventional (e.g., periodontal or urate-lowering treatments) studies, are needed to elucidate the association of periodontitis with UA in blood and oral fluids.

Within the limitations of the present study, it would be concluded that:

1) Periodontitis is related to an increased blood UA content in the context of normouricemia. Whether periodontitis and hyperuricemia/gout are correlated remains to be validated.

2) In contrast to the change of UA in blood, the content of UA in saliva and GCF seems to be reduced in the presence of periodontitis. The potential mechanisms need further explorations.

And 3) The findings are mainly based on a small number of observational studies with a small sample size and significant methodological heterogeneity which might impact the reliability of the conclusions. High-quality studies including large-scale prospective cohort studies and interventional ones are required to further validate the findings.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Availability of data and materials

The datasets for this study can be made available on reasonable request to [email protected].

Competing Interests

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

Funding

This work was supported by Natural Science Foundation of Guangdong Province, China (Grant 2022A1515010497); Guangzhou Science, Technology and Innovation Commission; Guangdong Medical Research Foundation (Grant B2020209); and National Natural Science Foundation of China (Grant 81700985).

Author contributions

Ting Yu contributed to research concept and design. Lu-wen Ye, Li Zhao and Ze-song Mei contributed to literature search. Lu-wen Ye, Li Zhao and Ting Yu contributed to data analysis and interpretation. Lu-wen Ye, Li Zhao and Ze-song Mei contributed to manuscript preparation and editing. Ting Yu and Ying-hong Zhou contributed to critical revision of the article. Ting Yu contributed to funding acquisition. Lu-wen Ye, Li Zhao and Ze-song Mei have contributed equally to this work and share first authorship. The authors have read and approved the final version of the manuscript.

Acknowledgements

The authors would like to thank Dr Salima Senouci (Ahmed Ben Bella Faculty of Medicine, Department of Pharmacy, University of Oran1, Algeria), Dr Gen-Min Lin (Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taiwan), Dr Meenakshi Sreeram (Department of Physiology and Biochemistry, MGV's KBH Dental College and Hospital, India), Dr Shaheena Banu (Sri Jayadeva Institute of Cardiovascular Science and Research, Department of Biochemistry, India) and Dr Antonio Canabarro (Department of Periodontology, School of Dentistry, Veiga de Almeida University, Brazil) for providing the raw data of their clinical studies during the stage of quality assessment.

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No competing interests reported.

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Association between periodontitis and uric acid levels in blood and oral fluids: A systematic review and meta-analysis

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Abstract

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1 Introduction

2 Materials And Methods

2.1 Eligibility criteria

2.1.1 Definition of periodontitis and periodontal health control

2.1.2 Inclusion criteria

2.1.3 Exclusion criteria

2.2 Information sources and search strategy

2.3 Study selection

2.4 Quality assessment

2.5 Data extraction

2.6 Data conversion and preprocessing

2.7 Statistical analyses

3 Results

3.1 Study selection

3.2 General characteristics of included studies

3.3 Definition of periodontitis and control

3.4 Risk of bias and methodological quality

3.5 Are UA levels changed in blood in periodontitis vs. control?

3.6 Are UA levels changed in saliva in periodontitis vs. control?

3.7 Association of UA in GCF with periodontitis

3.8 Publication bias

4 Discussion

5 Conclusions

Declarations

References

Additional Declarations

Supplementary Files

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