Jiang GH, Li S, Li HY, Xie LJ, Li SY, Yan ZT, Yu WQ, Luo J, Bai X, Kong LX, Lou YM, Zhang C, Li GC, Shan XF, Mao M, Wang X. Bidirectional associations among gallstone disease, non-alcoholic fatty liver disease, kidney stone disease. World J Gastroenterol 2024; 30(46): 4914-4928 [DOI: 10.3748/wjg.v30.i46.4914]
Corresponding Author of This Article
Xin Wang, PhD, Associate Professor, Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, South Renmin Road, Wuhou District, Chengdu 610041, Sichuan Province, China. wangxinmarine@126.com
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Guo-Heng Jiang, Sheng Li, Hong-Yu Li, Lin-Jun Xie, Shi-Yi Li, Zi-Tong Yan, Wen-Qian Yu, Jing Luo, Xuan Bai, Xin Wang, Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China
Ling-Xi Kong, Department of Pharmacy, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
Yan-Mei Lou, Department of Health Management, Beijing Xiaotangshan Hospital, Beijing 102211, China
Chi Zhang, Department of Prevention, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China
Guang-Can Li, Department of Pharmacy, The People’s Hospital of Kaizhou District, Chongqing 405400, China
Xue-Feng Shan, Department of Pharmacy, Bishan Hospital of Chongqing Medical University, Chongqing 402760, China
Min Mao, Department of Pediatric Pulmonology and Immunology, West China Second University Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China
Author contributions: Jiang GH, Li S and Li HY contributed equally to this paper. Jiang GH, Li S and Li HY contributed to conceptualization, investigation, writing original draft, and revision; Xie LJ, Li SY and Yan ZT contributed to methodology, assisted in the conceptualization, and contributed to the draft writing; Yu WQ, Luo J and Bai X contributed to software, imaging analysis, and revision; Kong LX, Lou YM, Zhang C, Li GC and Shan XF contributed to the methodology, source, and data curation; Wang X and Mao M review and revise, supervision, validation, data curation, project administration. All authors read and approved the final manuscript.
Supported byNational Natural Science Foundation of China, No. 81802508 and No. 81903398; Chongqing Natural Science Foundation Program, No. CSTC2019JCYJ-MSXMX0466 and No. CSTB2022NSCQ-MSX0206; The Research Start-up Fund for Introduction of Talents of Sichuan University, No. YJ2021112; Medical Youth Innovation Research Project of Sichuan Province, No. Q21016; Natural Science Foundation of Sichuan, No. 2023NSFSC1927; Sichuan Province Central Government Guide Local Science and Technology Development Project, No. 2023ZYD0097; and "From 0 to 1" Innovation Project of Sichuan University, No. 2023SCUH0026.
Institutional review board statement: The study was approved by the Ethics Committee of West China Fourth Hospital, West China School of Public Health, Sichuan University.
Informed consent statement: Informed consent was waived for this study.
Conflict-of-interest statement: The authors have no conflict of interest with the information presented.
Data sharing statement: Not applicable.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Xin Wang, PhD, Associate Professor, Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, South Renmin Road, Wuhou District, Chengdu 610041, Sichuan Province, China. wangxinmarine@126.com
Received: April 21, 2024 Revised: September 2, 2024 Accepted: September 27, 2024 Published online: December 14, 2024 Processing time: 214 Days and 3.6 Hours
Abstract
BACKGROUND
A body of evidence has suggested bidirectional relationships among gallstone disease (GSD), non-alcoholic fatty liver disease (NAFLD), and kidney stone disease (KSD). However, the results are inconsistent, and studies on this topic in China are relatively few. Our goal is to explore the bidirectional associations among these three diseases through a multicenter study, systematic review, and meta-analysis.
AIM
To explore the bidirectional associations among these three diseases through a multicenter study, systematic review, and meta-analysis. The results may help to investigate the etiology of these diseases and shed light on the individualized prevention of these three diseases.
METHODS
Subjects who participated in physical examinations in Beijing, Tianjin, Chongqing in China were recruited. Multivariable logistic regression was employed to explore the bidirectional relationships among GSD, KSD, and NAFLD. Systematic review and meta-analysis were initiated to confirm the epidemiologic evidence from previous observational studies. Furthermore, trial sequential analysis (TSA) was conducted to evaluate whether the evidence was sufficient and conclusive.
RESULTS
Significant bidirectional associations were detected among the three diseases, independent of potential confounding factors. The pooled results of the systematic review and meta-analysis also corroborated the aforementioned results. The combined evidence from the multicenter study and meta-analysis was significant [pooled odds ratio (OR) = 1.42, 95%CI: 1.16-1.75, KSD → GSD; pooled OR = 1.48, 95%CI: 1.31-1.67, GSD → KSD; pooled OR = 1.31, 95%CI: 1.17-1.47, GSD → NAFLD; pooled OR = 1.37, 95%CI: 1.26-1.50, NAFLD → GSD; pooled OR = 1.28, 95%CI: 1.08-1.51, NAFLD → KSD; pooled OR = 1.21, 95%CI: 1.16-1.25, KSD → NAFLD]. TSA indicated that the evidence was sufficient and conclusive.
CONCLUSION
The present study presents relatively sufficient evidence for the positive bidirectional associations among GSD, KSD, and NAFLD. The results may provide clues for investigating the etiology of these three diseases and offer a guideline for identifying high-risk patients.
Core Tip: Recent reports have suggested significant associations among gallstone disease, non-alcoholic fatty liver disease, and kidney stone disease, but the results were inconsistent. Therefore, we first explored the reciprocal relationships among these three diseases using multicenter cross-sectional studies with a large sample size in the Chinese population. We then comprehensively assessed epidemiologic evidence from conventional observational studies regarding the strengths and the directions of associations among the three diseases using systematic review and meta-analysis. The results may help to investigate the etiology of these diseases and shed light on the individualized prevention of these three diseases.
Citation: Jiang GH, Li S, Li HY, Xie LJ, Li SY, Yan ZT, Yu WQ, Luo J, Bai X, Kong LX, Lou YM, Zhang C, Li GC, Shan XF, Mao M, Wang X. Bidirectional associations among gallstone disease, non-alcoholic fatty liver disease, kidney stone disease. World J Gastroenterol 2024; 30(46): 4914-4928
Gallstone disease (GSD) is a prevalent gastrointestinal disorder, affecting 10% to 20% of adults globally[1]. Non-alcoholic fatty liver disease (NAFLD) has reached epidemic proportions, with an estimated global prevalence of approximately 25.2%, ranging from 13.5% in Africa to 31.8% in the Middle East[2]. The prevalence of kidney stone disease (KSD) has been risen continuously rising on a global scale over the past decades and varies across different countries, ranging from 0.1% to 18.5%[3]. These three diseases have been reported to significantly increase the risk of all-cause mortality, imposing a severe socio-economic and public health burden[4-6]. Previous studies have identified that GSD, NAFLD, and KSD share common risk factors such as obesity, type 2 diabetes, dyslipidemia, metabolic syndrome, and oxidative stress (OxS)[1,7-12]. Recent reports have indicated significant associations among these three diseases, and evaluating these relationships plays a crucial role in disease prevention and treatment[13-16]. Previous studies have suggested that bidirectional relationships between GSD and KSD were found in prospective cohort studies[13]. It has also been reported that GSD and NAFLD have reciprocal associations in young and middle-aged Asian people[14]. Moreover, positive correlations between NAFLD and KSD have also been discovered in Asian and other populations[15,16]. However, the findings from previous publications have varied significantly across studies[17-20]. The sample sizes of prior research were also limited, and few studies have been conducted on the Chinese population.
The bidirectional associations among GSD, NAFLD and KSD have significant clinical significance. Recognizing the bidirectional connections of these three diseases helps formulate more comprehensive chronic disease prevention and control strategies and provides important clues for early intervention. At the same time, it can expand the identification range of high-risk populations and formulate personalized prevention strategies. Finally, it can also provide a new perspective for in-depth exploration of the disease pathogenesis, discover new therapeutic targets.
This study comprised three steps (Figure 1). Firstly, we explored the bidirectional relationships among GSD, KSD, and NAFLD by utilizing multicenter cross-sectional studies with a large sample size in the Chinese population. Subsequently, we conducted a systematic review and meta-analysis to comprehensively assess the epidemiologic associations among these three diseases. Furthermore, trial sequential analysis (TSA) was also employed to evaluate whether the evidence from observational studies was sufficient and conclusive[21].
Figure 1 Flow chart of the study design.
GSD: Gallstone disease; KSD: Kidney stone disease; NAFLD: Non-alcoholic fatty liver disease.
MATERIALS AND METHODS
Multicenter cross-sectional study
Data source and study participants: Adult subjects who visited the physical examination center at the First Affiliated Hospital of Chongqing Medical University Jinshan Hospital (in the urban area of Chongqing), the People’s Hospital of Kaizhou District of Chongqing (in the rural area of Chongqing), Beijing Xiaotangshan Hospital, and Tianjin Medical University Cancer Institute and Hospital between January 2015 and May 2020 were recruited for this study. The most recent data were selected. This study was conducted in accordance with the Helsinki declaration and was approved by the ethical committees of these four hospitals. All patients provided written informed consent. Additionally, this study was approved by the Ethics Board of the Ethics Committee of West China Fourth Hospital and West China School (Gwll2021055).
Measurements: Information regarding demographic characteristics, drinking habits, medical history, and medication history was collected through a questionnaire. Physical examinations, including measurements of body weight, height, waist circumference, diastolic blood pressure (DBP), and systolic blood pressure (SBP), were conducted by trained staff using standardized procedures. Fasting plasma glucose, serum levels of total cholesterol, triglyceride, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-C), fasting blood glucose, alanine transaminase, and uric acid (UA) were measured using venous blood samples. All these biochemical indexes were measured independently in each physical examination center in accordance with the international standard protocol. According to the JNC 7 guideline, hypertension was ascertained when SBP ≥ 140 mmHg or DBP ≥ 90 mmHg[22]. Fasting plasma glucose (FPG) was classified into three categories: FPG < (5.6 mmol/L) = normal fasting glucose, FPG (5.6–6.9 mmol/L) = impaired fasting glucose, and FPG ≥ (7.0 mmol/L) = provisional diagnosis of diabetes[23]. The body mass index (BMI) was calculated as weight (kg) divided by the square of height (m) (kg/m2). Based on the criteria of the Working Group on Obesity in China, the participants were categorized into four groups according to their BMI values: Underweight (BMI ≤ 18.49 kg/m2), normal weight (BMI: 18.50-23.99 kg/m2), overweight (BMI: 24.00-27.99 kg/m2), and obese (BMI ≥ 28.00 kg/m2)[24].
Ascertainment of GSD, NAFLD, and KSD: All three diseases were diagnosed by experienced radiologists through abdominal ultrasonography.
Definition of GSD: GSD was diagnosed based on any of the following criteria: (1) The presence of one or more echogenic structures in the gallbladder lumen accompanied by acoustic shadowing; and (2) In patients with a history of cholecystectomy due to gallstones, the non-visualization of the gallbladder[25].
Definition of NAFLD: NALFD was diagnosed according to the following criteria: Enhanced hepatic echogenicity (bright) with evident contrast between the liver and the kidney, attenuated far-field echo, and bright vessel walls and gallbladder wall[26]. Those with a history of excessive drinking (alcohol intake > 30 g/day for men and > 20 g/day for women), or with positivity detection of hepatitis C virus antibodies or hepatitis B surface antigen, or suffering from other specific diseases known to cause fatty liver, or with a history of using hepatotoxic drugs that can lead to fatty liver were excluded[27].
Definition of KSD: KSD was diagnosed when there was one or more echogenic structures, sometimes accompanied by a dark distal shadow in abdominal ultrasound[28].
Systematic review and meta-analysis
Search strategy: The systematic review and meta-analysis adhered to the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines[29]. PubMed and EMBASE were searched from their inception to August 2022. The entire search strategies are presented in Supplementary Table 1. Eligible observational studies (cohort studies, nested case-control studies, case-control studies, and cross-sectional studies) were included in the meta-analysis. The related citations of these studies were carefully screened to identify additional publications. This meta-analysis was registered in the International Prospective Register of Systematic Reviews (PROSPERO; registration ID: CRD42020215117) in November 2020.
Inclusion and exclusion criteria: Two independent authors reviewed each piece. Data extraction was conducted using a standard data-extraction form (Supplementary Table 2). Studies with adjusted risk estimates [such as relative risk, hazard ratio, odds ratio (OR), or regression coefficient] and 95%CIs or SEs, or with sufficient data to calculate the effect size with a 95%CI, were included. For studies with the population reported more than once, we included the most recent one or the one with the largest sample size.
Statistical analysis
SPSS 23.0 (SPSS Inc., Chicago, IL, United States) was utilized for the statistical analyses of multicenter cross-sectional studies. The demographic and clinical characteristics of participants were mainly described as categorical variables by the number and percentage (n%), and the age of patients was presented as mean ± SD. Patients from each hospital were stratified into two groups according to the median age. Multivariable logistic regression analyses were performed to calculate the OR with a 95%CI among GSD (including gallstones and cholecystectomy), NAFLD, and KSD in each center, adjusted for demographic characteristics and associated clinical indicators. The results from the four hospitals were then pooled using meta-analysis by STATA, version 16 (Stata, College Station, TX, United States).
The Newcastle-Ottawa quality assessment scale (NOS), consisting of 9 scores, was employed to evaluate the methodology quality of cohort and case-control studies included in the systematic review and meta-analysis[30]. A final score of 0-3, 4-6, and 7-9 was respectively regarded as low, moderate, and high quality. The Agency for Healthcare Research and Quality (AHRQ) scale, comprising 11 questions, was utilized to assess the study quality of cross-sectional studies[31]. A total score of 0-3, 4-7, and 8-11 indicated low, moderate, and high quality. Meta-analysis for observational studies was conducted using STATA, version 16 (Stata, College Station, TX, United States). Cochran’s Q test and I2 statistics were performed to evaluate the heterogeneities between studies[32]. Meta-analysis was conducted using a fixed-effect model, and a random-effects model was selected in case of evident statistical heterogeneity (defined as I2 > 50% and/or Cochran’s Q test P < 0.10)[33]. Pooled OR with corresponding 95%CIs were calculated for each outcome. Subgroup analyses were carried out by geographic region, GSD subtype, study design, and study quality stratification to explore the source of heterogeneities. Egger’s and Begg’s tests were also applied to investigate small-study effects and potential publication bias (P < 0.05 was considered significant)[34]. The trim-and-fill method was utilized to adjust the estimated overall effect size to reduce small-study effects and potential publication bias[34]. Sensitivity analyses were performed to measure the impact of one study on the pooled results and assess the robustness of the results[33]. Statistical tests were two-sided, and significant levels were set at P < 0.05.
Furthermore, the TSA was employed to evaluate whether the evidence in the meta-analysis was sufficient[21]. If the cumulative Z-curve crossed the TSA monitoring boundary line or the required information size (RIS) line for the research, the research results were considered stable and conclusive. Otherwise, it was believed that the evidence of current results was insufficient, and further research is needed to verify the findings[21,35]. The TSA for cross-sectional studies was performed by STATA, version 16 (Stata, College Station, TX, United States), and the TSA for cohort studies was conducted using TSA program version 0.9 beta[36].
RESULTS
Multicenter cross-sectional study
The demographic and clinical characteristics of the included subjects from four centers are presented in Table 1. We selected 81158 individuals from Beijing, among whom 59.2% were males and 40.8% were females. The mean age was 43.88 ± 13.97 years. From the urban area of Chongqing, 170038 individuals were included, with 54.7% males and 45.3% females. The mean age was 41.79 ± 13.45 years. From the rural area of Chongqing, 372289 individuals were enrolled, with 53.4% males and 46.6% females. The mean age was 43.97 ± 13.14 years. From Tianjin, 10940 individuals were collected, with 44.0% males and 56.0% females. The mean age was 43.47 ± 13.63 years.
Table 1 Demographic and clinical characteristics distribution of the included subjects, n (%)/mean ± SD.
GSD and KSD: As demonstrated in Figure 2, the pooled analysis indicated bidirectional relationships between KSD and GSD (pooled OR = 1.33, 95%CI: 1.02-1.75, KSD → GSD; pooled OR = 1.32, 95%CI: 1.01-1.74, GSD → KSD). These significant relationships were observed in data derived from Beijing, the urban area of Chongqing, and the rural area of Chongqing, although the results varied in centers. When stratified by the subtype of GSD (gallstones vs cholecystectomy), bidirectional correlations were found between gallstones and KSD (pooled OR = 1.44, 95%CI: 1.06-1.95, KSD → gallstones; pooled OR = 1.41, 95%CI: 1.02-1.95, gallstones → KSD), while no relationship was observed between cholecystectomy and KSD (pooled OR = 1.04, 95%CI: 0.96-1.11, KSD for cholecystectomy; pooled OR = 1.05, 95%CI: 0.97-1.13, cholecystectomy for KSD) (Supplementary Figure 1).
Figure 2 Multivariable logistic regression analyses of the associations among kidney stone disease, gallstone disease, and non-alcoholic fatty liver disease.
GSD: Gallstone disease; KSD: Kidney stone disease; NAFLD: Non-alcoholic fatty liver disease; OR: Odds ratio.
GSD and NAFLD: There were significantly bidirectional correlations between GSD and NAFLD (pooled = OR 1.39, 95%CI: 1.24-1.57, GSD → NAFLD; pooled = OR 1.38, 95%CI: 1.23-1.55, NAFLD → GSD) (Figure 2). Subgroup analysis suggested positive associations between gallstones and NAFLD (pooled OR = 1.29, 95%CI: 1.19-1.40, gallstones → NAFLD; pooled OR = 1.29, 95%CI: 1.20-1.39, the NAFLD → gallstones). Meanwhile, positive relationships were also found for cholecystectomy and NAFLD (pooled OR = 1.41, 95%CI: 1.22-1.64, cholecystectomy → NAFLD; pooled OR = 1.44, 95%CI: 1.19-1.74, the NAFLD → cholecystectomy) (Figure 2).
KSD and NAFLD: Multivariable logistic regression analyses indicated significant bidirectional relationships between NAFLD and KSD in all centers (Figure 2). According to the combined results, patients with NAFLD were 1.21 times more likely to develop KSD (pooled OR = 95%CI: 1.16-1.25), and there was also a 1.21-fold increase in the risk of NAFLD among patients with KSD (pooled OR = 95%CI: 1.17-1.26).
Systematic review and meta-analysis
The selection procedure is listed in the flowchart in Supplementary Figure 2. A total of 2,574 observational articles were identified from the initial search. After excluding 517 duplicated articles, the remaining articles were reviewed by title and abstract, and 45 were left for full-text screening. Finally, 25 eligible publications (49 studies) were selected for data collection, including 30 cross-sectional and 19 cohort studies. The majority of studies were conducted in Asia (n = 28), followed by America (n = 16) and Europe (n = 5). The characteristics of the eligible articles are presented in Supplementary Table 2. The quality assessment results are shown in Supplementary Table 3 and Supplementary Table 4. The average quality score was 7.38 by the NOS for included cohort studies and 5.28 for cross-sectional studies according to the AHRQ scale. The subsequent analyses excluded two studies with low quality (< 4 for NOS or AHRQ)[37]. Sensitivity analyses were performed to assess the robustness of this meta-analysis by sequentially omitting each single study (see Supplementary Figure 3). In total, four studies were excluded for having a significant impact on the overall results[38,39].
GSD and KSD: The results of the meta-analysis are presented in Table 2. KSD was significantly associated with the development of GSD (random effect pooled OR = 1.44; 95%CI, 1.14-1.81, P < 0.001), and conversely, the presence of KSD increased the risk of GSD (random effect pooled OR = 1.50; 95%CI: 1.32-1.71, P < 0.001). The significant relationships between GSD and the risk of KSD were not modified after stratifying by geographic background, subtypes of GSD, study design, and quality. According to subgroup analysis, KSD was significantly correlated with the risk of GSD in the studies conducted in America, the studies of cohort design, and the studies with high quality. Moreover, KSD was only associated with the increased risk of cholecystectomy. The Begg’s and Egger’s tests suggested no significant publication bias in these included studies (P for Begg’s test = 1.000 and P for Egger’s test = 0.741, KSD → GSD, P for Begg’s test = 1.000 and P for Egger’s test = 0.210, GSD → KSD).
Table 2 Pooled results for meta-analyses assessing the bidirectional associations among gallstone disease, kidney stone disease, non-alcoholic fatty liver disease.
Type of groups
Sample size
Pooled OR (95%CI)
I2 (%)
P for Begg’s test
P for Egger’s test
No. of filled data
Trim and fill adjusted pooled OR (95%CI)
Number of studies
KSD-GSD
Overall
363960
1.44 (1.14-1.81)
94.4
1.000
0.741
0
1.44 (1.14-1.81)
5
Subgroups
Geographic background
America
245690
1.32 (1.15-1.52)
82.7
0.296
0.276
0
1.32 (1.15-1.52)
3
Asia
118270
1.71 (0.97-3.02)
37.2
1.000
NA
0
1.71 (0.97-3.02)
2
Type of GSD
KSD-cholecystectomy
97185
1.17 (1.06-1.29)
NA
NA
NA
0
1.17 (1.06-1.29)
1
KSD-gallstones
118270
1.71 (0.97-3.02)
37.2
1.000
NA
0
1.71 (0.97-3.02)
2
Study design
0
Cross-sectional study
195
0.94 (0.30-2.97)
NA
NA
NA
0
0.94 (0.30-2.97)
1
Cohort study
363765
1.46 (1.15-1.85)
95.7
1.000
0.383
0
1.46 (1.15-1.85)
4
Study quality
Moderate
195
0.94 (0.30-2.97)
NA
NA
NA
0
0.94 (0.30-2.97)
1
High
363765
1.46 (1.15-1.85)
95.7
1.000
0.383
0
1.46 (1.15-1.85)
4
GSD-KSD
Overall
496094
1.50 (1.32-1.71)
84.7
1.000
0.210
0
1.50 (1.32-1.71)
7
Subgroups
Geographic background
America
266252
1.34 (1.24-1.45)
0.0
0.462
0.847
0
1.34 (1.24-1.45)
5
Asia
229842
1.79 (1.56-2.05)
82.4
1.000
NA
0
1.79 (1.56-2.05)
2
Type of GSD
Cholecystectomy-KSD
95537
1.26 (1.10-1.45)
NA
NA
NA
0
1.26 (1.10-1.45)
1
Gallstones-KSD
229842
1.79 (1.56-2.05)
82.4
1.000
NA
0
1.79 (1.56-2.05)
2
Study design
Cross-sectional study
12161
1.54 (1.31-1.81)
NA
NA
NA
0
1.54 (1.31-1.81)
1
Cohort study
483933
1.49 (1.28-1.73)
87.1
1.000
0.269
0
1.49 (1.28-1.73)
6
Study quality
Moderate
12161
1.54 (1.31-1.81)
NA
NA
NA
0
1.54 (1.31-1.81)
1
High
483933
1.49 (1.28-1.73)
87.1
1.000
0.269
0
1.49 (1.28-1.73)
6
NAFLD-GSD
Overall
352255
1.38 (1.25-1.54)
56.3
0.005
0.014
3
1.26 (1.12-1.41)
11
Subgroups
Geographic background
Asia
351249
1.35 (1.21-1.51)
57.8
0.009
0.057
2
1.26 (1.11-1.43)
9
Europe
1006
1.60 (1.24-2.06)
1.9
1.000
NA
0
1.60 (1.24-2.06)
2
Type of GSD
NAFLD-cholecystectomy
283446
1.10 (0.96-1.26)
NA
NA
NA
0
1.10 (0.96-1.26)
1
NAFLD-gallstones
326887
1.43 (1.22-1.67)
67.3
0.060
0.083
0
1.43 (1.22-1.67)
6
Study design
Cross-sectional study
56313
1.49 (1.26-1.76)
62.0
0.035
0.017
2
1.27 (1.06-1.52)
8
Cohort study
295942
1.25 (1.18-1.34)
0.0
0.296
0.517
0
1.25 (1.18-1.34)
3
Study quality
Moderate
57609
1.47 (1.27-1.69)
56.9
0.029
0.012
2
1.32 (1.12-1.55)
9
High
294646
1.24 (1.16-1.32)
0.0
1.000
NA
0
1.24 (1.16-1.32)
2
GSD-NAFLD
Overall
474151
1.29 (1.14-1.47)
66.7
0.230
0.060
0
1.29 (1.14-1.47)
7
Subgroups
Geographic background
America
12232
1.56 (1.27-1.91)
NA
NA
NA
0
1.56 (1.27-1.91)
1
Asia
457130
1.19 (1.07-1.33)
54.5
0.089
0.060
0
1.19 (1.07-1.33)
4
Europe
4789
1.39 (0.82-2.35)
58.7
1.000
NA
0
1.39 (0.82-2.35)
2
Type of GSD
Cholecystectomy-NAFLD
252772
1.37 (1.00-1.87)
86.0
0.308
0.590
0
1.37 (1.00-1.87)
4
Gallstones-NAFLD
248690
1.15 (1.08-1.22)
0.0
0.296
0.681
0
1.15 (1.08-1.22)
3
Study design
Cross-sectional study
34869
1.46 (1.17-1.83)
0.589
0.462
0.392
0
1.46 (1.17-1.83)
5
Cohort study
439282
1.15 (1.08-1.22)
0.0
1.000
NA
0
1.15 (1.08-1.22)
2
Study quality
Moderate
34869
1.46 (1.17-1.83)
0.589
0.462
0.392
0
1.46 (1.17-1.83)
5
High
439282
1.29 (1.14-1.47)
0.0
1.000
NA
0
1.29 (1.14-1.47)
2
NAFLD-KSD
Overall
439933
1.37 (1.04-1.81)
86.1
0.099
0.354
0
1.37 (1.04-1.81)
7
Subgroups
Geographic background
America
11859
1.29 (1.02-1.63)
NA
NA
NA
0
1.29 (1.02-1.63)
1
Asia
428074
1.41 (1.00-1.99)
88.3
0.133
0.429
0
1.41 (1.00-1.99)
6
Study type
Cross-sectional study
22777
1.64 (0.94-2.88)
88.2
0.221
0.548
0
1.64 (0.94-2.88)
5
Cohort study
417156
1.08 (0.90-1.30)
68.4
1.000
NA
0
1.08 (0.90-1.30)
2
Study quality
Moderate
22777
1.64 (0.94-2.88)
88.2
0.221
0.548
0
1.64 (0.94-2.88)
5
High
417156
1.08 (0.90-1.30)
68.4
1.000
NA
0
1.08 (0.90-1.30)
2
GSD and NAFLD: Meta-analysis suggested bidirectional associations between GSD and NAFLD (random effect pooled OR = 1.29, 95%CI: 1.14-1.47, P for Begg’s test = 0.230 and P for Egger’s test = 0.060, GSD → NAFLD; pooled OR = 1.38, 95%CI: 1.25-1.54, P for Begg’s test = 0.005 and P for Egger’s test = 0.014, NAFLD → GSD). These associations were consistent when stratified by the subtype of GSD, study design, and study quality. Begg’s and Egger’s tests indicated significant publication bias among the studies of NAFLD and the risk of GSD. Therefore, trim and fill methods were applied in the random effect model (adjusted OR: 1.26; 95%CI: 1.12-1.41) (Table 2).
KSD and NAFLD: NAFLD was significantly associated with KSD risk (random effect pooled OR = 1.37; 95%CI: 1.04-1.81, P = 0.024). Significant associations were also observed in studies conducted in all geographic regions. Publication bias analysis suggested no substantial significance in the meta-analysis of the associations between these two diseases (P for Begg’s test = 0.099 and P for Egger’s test = 0.354, NAFLD → KSD). However, no study has been published to investigate the associations between KSD and the risk of NAFLD.
Combined results of multicenter cross-sectional studies and previous publications
The results of current studies and the systematic review and meta-analysis are depicted in Figure 3. A significant bidirectional association among GSD, KSD, and NAFLD was found. These relationships remained consistent across studies with different geographic regions and study designs. However, no association was observed between KSD and cholecystectomy or between NAFLD and the risk of cholecystectomy. The TSA revealed that the Z-curves crossed the TSA monitoring boundary line or the RIS line (Supplementary Figure 4), suggesting that the evidence from observational studies is sufficient and conclusive.
Figure 3 Forest plots of combined results of observational studies.
GSD: Gallstone disease; KSD: Kidney stone disease; NAFLD: Non-alcoholic fatty liver disease; OR: Odds ratio.
DISCUSSION
This article conducts a multicenter cross-sectional study, systematic review, and meta-analysis based on the data of subjects from Jinshan Hospital of the First Affiliated Hospital of Chongqing Medical University (in urban Chongqing), Kaizhou District People's Hospital of Chongqing (in rural Chongqing), Beijing Xiaotangshan Hospital, and Tianjin Medical University Cancer Institute and Hospital. It explores the pairwise relationships among GSD, NAFLD, and KSD. The results show that there are bidirectional connections among these three diseases. TSA is used to further confirm that the associations among the three diseases are fully reliable. The research results have important clinical value for chronic disease prevention and control, identification of high-risk populations, and exploration of disease pathogenesis.
Shared multiple common risk factors among these diseases, including obesity, type 2 diabetes, dyslipidemia, metabolic syndrome, and OxS, could partly explain these associations[1,7]. Obesity might increase the risk of urinary tract infections and affect kidney function. It can also promote chronic systemic inflammation and OxS conditions, increase the expression of adipokines and alter the state of inflammatory molecules (IL-6 and TNF-α), leading to tissue immune cell infiltration, and thus promoting the formation of renal stones[40-42]. The presence of obesity could also facilitate the development of gallstones through hepatic cell injury and cholesterol excretion[43]. Moreover, obesity and insulin resistance are linked with the initial fat accumulation in the hepatocyte, particularly fatty acid and triglycerides (TG), and might further lead to hepatic steatosis[44]. Furthermore, one of the renal manifestations of insulin resistance is reported to be low urine pH, which could further determine the formation of UA stones[45]. Insulin resistance could also favor the development of gallstones by inducing the excretion of hepatic cholesterol, the supersaturation of biliary cholesterol[46], and disturbing the motility of the gallbladder[47]. The specific mechanism includes the down-regulation of the farnesoid X receptor (FXR) gene of the nuclear heterodimer receptor, reducing the corresponding receptor expression and decreasing bile acid transporters Abcb11 and phospholipid transporter Abcb4[48]. At the same time, the up-regulated cholesterol secretion genes ABCG5 and ABCG8 promote more expression of cholesterol transporters and ultimately increase cholesterol secretion, ultimately leading to cholesterol supersaturation and inducing GSD[49]. High blood sugar can increase the secretion of urinary calcium, UA, phosphorus and oxalate. Insulin resistance can lead to a decrease in urinary ammonium and pH value. Both of these will lead to the formation of kidney stones[50]. It is well established that dyslipidemia has significant associations with the occurrence of NAFLD and cholesterol GSD[1,7]. Recent reports have also suggested that a low level of LDL-C and a high level of TG are correlated with lower urinary pH levels, which could further contribute to renal stone formation[51]. Another plausible explanation involves OxS, which results from the imbalance between the production and accumulation of reactive oxygen species (ROS) and antioxidant defenses[10,11,52]. OxS might have implications for metabolic alteration and the expression of the pro-inflammatory transcription factor (IL-6, IL-10, IL-12 and IL-13), thereby initiating hepatic steatosis and affecting the progression to fibrosis[53,54]. Studies in multi-regional populations also show that elevated serum high-sensitivity C-reactive protein levels are an independent risk factor for gallstones[55,56]. Experimental data also indicated that patients diagnosed with NAFLD/non-alcoholic steatohepatitis had higher ROS and lipid peroxidation products and presented fewer antioxidant enzymes as well as antioxidant compounds[57]. Increased production of ROS and toxic products generated by lipid peroxidation (such as malondialdehyde) has also been observed in serum samples of patients with gallstones, thereby inducing DNA damage and OxS response[58]. Insulin resistance can also act as a promoter of pro-inflammatory cytokine signaling and OxS. In this pro-inflammatory and pro-oxidative environment, mitochondrial dysfunction, the presence of adipokines, the secretion of pro-inflammatory cytokines, and endoplasmic reticulum stress can all lead to excessive production of ROS and induce NAFLD[59]. Meanwhile, under the condition of OxS, bilirubin could interact with free radicals and generate oxidized bilirubin free radicals in polymeric form, resulting in nucleation as well as the deposition of stones[60]. Evidence has also supported that OxS could promote intrarenal crystal deposition and retention (especially calcium oxalate, CaOX) via tissue damage and inflammatory response[12].
The bidirectional relationship remained significant after accounting for commonly shared factors, indicating that pathways independent of these important risk factors might link the three diseases. A set of possible molecular mechanisms supported the relationships between GSD and NAFLD. Fibroblast growth factor 19 (FGF19) could mediate the negative feedback regulation of bile salt synthesis. However, this upregulation of bile acid homeostasis is reported to be defective in GSD[61]. Decreased FGF19 might favor the development of hepatic steatosis due to its effect on lipid synthesis and TG accumulation in the liver. It promotes the synthesis of cholesterol 7-alpha-hydroxylase to synthesize bile acids through the mitogen-activated protein kinase pathway[62,63]. In patients with NAFLD, the expression of aquaporin 8 mediated by hypoxia-inducible factor-1α is abnormally low, which affects the gene expression of oxygen transfer, cell growth and redox homeostasis, thus inducing gallstones[64]. Dysfunction of FXR signaling is also one of the factors leading to disorders of carbohydrate and lipid metabolism. It promotes bile acids, enterohepatic circulation and insulin resistance by inhibiting hepatic peroxisome proliferator activated receptor-alpha, limiting very low-density lipoprotein clearance, and inhibiting phosphoenolpyruvate carboxy kinase and glucose-6 phosphatase, and finally induces gallstones and NAFLD[65]. Furthermore, intestinal malabsorption might affect the enterohepatic circulation of bile acids and enhance urinary oxalate level, thereby playing a role in the pathogenesis of cholesterol gallstones and renal stones[66]. Meanwhile, water or ion channels act as mediators in processing bile and urine, and the transport alteration of water or ion could further promote bile and urinary concentration, leading to stone formation in the gallbladder and kidney[13,67]. Hyperuricemia is a prominent risk factor for UA stones, and UA is also found to induce fat accumulation in hepatocytes[68]. Additionally, fructose could promote lipogenesis, and hyperuricemia might also enhance the risk for NAFLD through stimulating fructose-dependent lipogenesis in hepatocytes[69].
The present study has several limitations that should be acknowledged. Firstly, ultrasound detection could not distinguish cholesterol stones from pigment stones, which have different pathogenesis. Secondly, Significant heterogeneity was observed among the study results. This could be attributed to varying study characteristics such as the source of the population, follow-up period, and different measurements of diseases. However, due to a relatively small number of studies, we could not fully detect the sources of heterogeneity. Thirdly, Observational studies also have disadvantages such as being unable to determine causal relationships, being easily affected by confounding factors, having sample selection biases, information biases, and lacking intervention controls. Based on the above defects, further research is warranted to infer causality and clarify these biological pathways.
CONCLUSION
In summary, the present study discovered significant bidirectional associations among GSD, KSD, and NAFLD. These results may assist in investigating the etiology of these disease and shed light on individualized prevention strategies. Patients diagnosed with any one of these three diseases should be recommended to undergo multidisciplinary screening to develop individualized prevention strategies for the other two diseases.
ACKNOWLEDGEMENTS
We are extremely grateful to the first Affiliated Hospital of Chongqing Medical University Jinshan Hospital, the People’s Hospital of Kaizhou District of Chongqing, Beijing Xiaotangshan Hospital, and Tianjin Medical University Cancer Institute for providing data for our research.
Footnotes
Provenance and peer review: Unsolicited article; Externally peer reviewed.
Peer-review model: Single blind
Specialty type: Gastroenterology and hepatology
Country of origin: China
Peer-review report’s classification
Scientific Quality: Grade A, Grade B
Novelty: Grade B, Grade B
Creativity or Innovation: Grade B, Grade B
Scientific Significance: Grade A, Grade B
P-Reviewer: Alshammary RAA; Chisthi MM S-Editor: Liu H L-Editor: A P-Editor: Cai YX
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