Abstract
Studies have found a positive association between metabolic risk factors, such as obesity and diabetes, and adenomatous polyps (APs). However, fewer studies have assessed the association between sessile serrated polyps (SSPs) or synchronous diagnosis of APs and SSPs (synch polyps). Study participants (N=1,370; ages 40–85) undergoing screening colonoscopy were enrolled between August 2016 and February 2020. Self-reported metabolic risk factors, including diabetes, hypertension, hyperlipidemia, and overweight/obesity, were evaluated for associations with new diagnoses of APs, SSPs, and synch polyps at the present colonoscopy. Average participant age was 60.73 ± 8.63 (SD) years; 56.7% were female and 90.9% white. In an assessment of individual metabolic risk factors adjusted for age, sex, race, and smoking status, increased BMI (overweight or obese vs normal BMI of <25 kg/m2) was associated with an increased odds for new onset of colon APs (p-value for trend, <0.001) as was a diagnosis of diabetes [aCOR=1.59 (1.10, 2.29)]. No associations were seen between the metabolic risk factors and onset of SSPs. Being obese or hypertensive each increased the odds of new onset of synch polyps with aCOR values of 2.09 (1.01, 4.32) and 1.79 (1.06, 3.02), respectively. Self-reported risk factors may help assess polyp type risk. Because SSPs and synch polyps are rare, larger studies are needed to improve our understanding of the contribution of these factors to polyp risk. These data lead us to hypothesize that differences in observed metabolic risk factors between polyp types reflect select metabolic impact on pathways to CRC.
Keywords: Colorectal polyps, obesity, epidemiology, metabolic risk factors, sessile serrated polyps
Introduction
Colorectal cancer (CRC) comprises a major portion of worldwide cancers; recent estimates rank CRC third in global cancer incidence (after lung and breast cancer) and second in mortality (1,2). Until recently, sporadic CRC was thought to predominantly arise from the cancerous precursor adenomatous polyps (APs), also known as conventional adenomas (3). Less is known about the risk factors for sessile serrated polyps (SSPs), also called sessile serrated adenomas, which are less common than APs and more difficult to detect during colonoscopy (3). Hyperplastic polyps (HPs) are considered benign serrated polyps. The distinction between SSPs and HPs was appreciated only recently as awareness of the cancerous potential of SSPs grew; less is known about risk factors specific to SSPs (3,4). Synchronous SSPs and APs (synch polyps) may signal increased risk for cancer progression (5,6) but risk factors for their co-occurrence need investigation.
Modifiable risk factors have been implicated for CRC and polyps (7,8). In men, up to 50% of colon cancers and 33% of distal colon adenomas are potentially preventable with a reduction of modifiable risk behaviors, including obesity, smoking, alcohol consumption, physical activity, red meat intake, and folic acid intake (7) and, in women, 37% of colon cancers are also estimated as preventable (8). Therefore, characterization of modifiable risk factors for precancerous lesions in various populations remains an important pursuit. While the metabolic risk factors associated with APs have been investigated, few studies have addressed SSPs or synch polyps in parallel with APs to understand the associations of these polyp types with metabolic risk factors.
CRC trends have evolved with some countries experiencing a decrease due to improved screening, awareness, and preventative measures and other countries, an increase, likely reflective of the adoption of less favorable lifestyle habits, such as a western diet (2,9). The prevalence of non-communicable diseases such as Metabolic Syndrome (MetS or MS), obesity, or diabetes have increased enhancing the potential for additional health complications (10). APs have been associated with increased weight (11–13) or variably with diabetes (14) or other conditions such as MetS (15). Studies of risk factors for SSPs and synch polyps have been infrequent and incomplete (3,6,16–18).
We investigated the relationship between metabolic risk exposures and APs, SSPs and synch polyps in a prospectively enrolled United States screening colonoscopy population. Herein, we assess the association of self-reported metabolic risk factors, including increased BMI, diabetes, hypertension, and hyperlipidemia, on the risk of histologically distinct colon polyps.
Materials and Methods
The Johns Hopkins Biofilm Colonoscopy Study
Data for this study come from The Johns Hopkins Biofilm Colonoscopy Study approved by the Johns Hopkins Medical Institute (JHMI) Institutional Review Board (IRB) for human research, IRB00094020 (Principal investigators: CL Sears, FM Giardiello). Eligible participants were prospectively enrolled by written informed consent prior to colonoscopy between August, 2016 and February, 2020 at three sites: Digestive Diseases Associates in Wyomissing, Pennsylvania; Greenspring Station Endoscopy Center in Lutherville, MD and the Johns Hopkins White Marsh Endoscopy Center in Baltimore, Maryland. From August, 2016 to February, 2020, 2091 individuals were enrolled in the study; of these, 40 were withdrawn from the study (38 had consent withdrawn by the supervising physician, one had a cancelled colonoscopy at visit, and one participant withdrew consent); thus, 2051 individuals were evaluated for inclusion in the current study. The design of the study is described elsewhere (19). Patient studies were conducted under the ethical guidelines outlined in the Belmont Report and U.S. Common Rule.
Participants included in this analysis were adults (ages 40–85) enrolled in the Johns Hopkins Biofilm Colonoscopy Study who had an intact colon and complete colonoscopy with visualization to the cecum. Participants with exclusively hyperplastic polyps, missing pathology on polyps, having rare pathological outcomes, or missing information on some of the covariates of interest were removed from the analysis. Participants with no polyps at study visit, but with a reported history of polyps were also excluded. The Johns Hopkins Biofilm Colonoscopy Study excluded pregnant women, prisoners, individuals with inflammatory bowel disease, and individuals on blood thinners or antiplatelet drugs. Figure 1 shows the participant flow and reasons for exclusion from this analysis. Final study population included in this analysis was 1,370.
Figure 1.
Participant inclusion in metabolic risk factor data analysis.
Case and Control Definitions
Polyp diagnoses at the current colonoscopy were abstracted from the medical record to classify study participants. The precise location, size, diagnosis and other characteristics of the colorectal polyps were collected from colonoscopy and pathology reports. To standardize polyp diagnosis, histopathology reports of all extracted or biopsied polyps were systematically reviewed by one gastroenterology physician member of the study team (SR). Polyp cases were classified according to the presence, number, and synchronicity of HPs, SSPs and APs. AP cases had one or more tubular, tubulovillous, or villous AP with or without dysplasia and with or without synchronous HPs. The SSP cases had one or more SSPs, with or without synchronous HPs. The synchronous cases have both APs and SSPs with or without synchronous HPs. HPs were considered benign. Advanced polyps were defined as polyps that were greater than or equal to 1 cm in size, contained villous components and/or dysplasia. Advanced synchronous polyps were defined as having an advanced polyp of at least one AP or one SSP or both.
Controls were individuals without any evidence of polyps and without a reported history of polyps.
Metabolic Risk Factors
Participants were defined as having diabetes mellitus, hypertension, or hyperlipidemia if they self-reported these conditions in their medical histories. These medical histories were collected or confirmed at study visit by a member of the healthcare team. No information on the severity or length of these conditions was available. Height and weight measurements, either self-reported, abstracted from the medical record, or measured at enrollment, were used to calculate BMI. BMI categories utilized in analysis were <25 kg/m2, ≥25–<30 kg/m2, and ≥30 kg/m2 defined as normal weight, overweight, and obese, respectively.
Covariate Definition
At colonoscopy, study participants were administered a questionnaire including information about socio-demographic factors such as race and employment status, medical and surgical history, basic dietary patterns, medication use (including antibiotics, nonsteroidal anti-inflammatory drugs (NSAIDs), proton pump inhibitors), risk factors for colorectal cancer (CRC) including family history of CRC, smoking history, alcohol use, physical activity, and history of prior colonoscopy with pertinent findings.
To study the association between colorectal polyps and metabolic risk factors, covariates considered for adjustment were family history of CRC, dietary patterns of meat (including poultry) and alcohol consumption, use of NSAIDs, age, sex, race, smoking history, physical activity at work, and current physical activity. Smoking measures were assessed in pack years from participant report of the average number of cigarettes they smoked per day during the number of years that they reported smoking. An average was used to calculate pack years if participant provided a range. Pack-years smoking was then categorized into no pack-years, >0–10 pack-year smoker, 10–20 pack-year smoker, and >20 pack-year smoker. Lastly, individuals who mentioned having exclusively smoked something other than cigarettes (cigars, pipe, marijuana, hookah) were combined into one category, though this list may not be exhaustive as this question was not explicitly asked. For NSAID usage, reports of regular usage of aspirin or other NSAIDs were combined.
Statistical Analysis
For Table 1, stratification was performed by polyp type to compare included and potential covariates. Choice of considered predictors for adjustment were selected from prior studies of risk factors for colon polyps. For final selection of adjustment variables, results from univariate analysis, log likelihoods, and the Akaike information criterion (AIC) were considered (20). Final adjustment covariates selected were age, sex, race, and smoking history.
Table 1.
Demographics of Study Participants by Polyp Type
| Control | Cases | ||||
|---|---|---|---|---|---|
| No polyp and no history of polyp (554) |
AP (645) |
SSP (101) |
Synchronous (70) |
Total (n=1,370) |
|
| Age, Mean (SD) | 58.1 (8.2) | 62.9 (8.6) | 60.4 (7.6) | 62.7 (8.3) | 60.7 (8.6) |
| Age, Median (IQR) | 58.4 (12.5) | 63.5 (12.1) | 60.7 (11.1) | 62.0 (13.4) | 60.9 (13.4) |
| N (%) | N (%) | N (%) | N (%) | N (%) | |
| Sex | |||||
| Male | 191 (34.5) | 325 (50.4) | 37 (36.6) | 40 (57.1) | 593 (43.3) |
| Female | 363 (65.5) | 320 (49.6) | 64 (63.4) | 30 (42.9) | 777 (56.7) |
| Race | |||||
| White | 488 (88.1) | 592 (91.8) | 97 (96.0) | 68 (97.1) | 1,245 (90.9) |
| Black | 49 (8.8) | 33 (5.1) | 1 (1.0) | 2 (2.9) | 85 (6.2) |
| Other | 17 (3.1) | 20 (3.1) | 3 (3.0) | 0 (0) | 40 (2.9) |
| Smoking | |||||
| Never smoker | 357 (64.4) | 330 (51.2) | 57 (56.4) | 38 (54.3) | 782 (57.1) |
| Cigar, pipe, hookah or marijuana smoker | 4 (0.7) | 21 (3.3) | 1 (1.0) | 3 (4.3) | 29 (2.1) |
| >0–10 pack-year smoker | 103 (18.6) | 111 (17.2) | 28 (27.7) | 12 (17.1) | 254 (18.5) |
| 10–20 pack-year smoker | 53 (9.6) | 77 (11.9) | 3 (3.0) | 4 (5.7) | 137 (10.0) |
| > 20 pack-year smoker | 37 (6.7) | 106 (16.4) | 12 (11.9) | 13 (18.6) | 168 (12.3) |
| NSAID intake (tablets per week) | |||||
| 0 | 298 (53.8) | 289 (44.8) | 52 (51.5) | 38 (54.3) | 677 (49.4) |
| 1–2 | 42 (7.6) | 46 (7.1) | 9 (8.9) | 2 (2.9) | 99 (7.2) |
| 3–5 | 52 (9.4) | 47 (7.3) | 3 (3.0) | 3 (4.3) | 105 (7.7) |
| 6–14; 15+ | 162 (29.2) | 263 (40.8) | 37 (36.6) | 27 (38.6) | 489 (35.7) |
| Job Activity | |||||
| Mostly sedentary or light activity | 226 (40.8) | 195 (30.2) | 36 (35.6) | 29 (41.4) | 486 (35.5) |
| Mostly medium activity | 163 (29.4) | 153 (23.7) | 22 (21.8) | 15 (21.4) | 353 (25.8) |
| Mostly intense activity | 14 (2.5) | 22 (3.4) | 7 (6.9) | 1 (1.4) | 44 (3.2) |
| Unemployed/ retired/disabled | 151 (27.3) | 275 (42.6) | 36 (35.6) | 25 (35.7) | 487 (35.6) |
| Current Physical Activity¥ | |||||
| No regular physical activity | 124 (22.4) | 151 (23.5) | 22 (21.8) | 11 (15.9) | 308 (22.6) |
| Mostly moderate activity | 267 (48.3) | 338 (52.6) | 46 (45.5) | 35 (50.7) | 686 (50.2) |
| Mostly vigorous activity | 162 (29.3) | 154 (24.0) | 33 (32.7) | 23 (33.3) | 372 (27.2) |
| Alcohol intake in current age range¥ | |||||
| Never or less than once per month | 79 (14.3) | 101 (15.7) | 17 (16.8) | 5 (7.1) | 202 (14.7) |
| < once per week | 190 (34.3) | 191 (29.7) | 28 (27.7) | 18 (25.7) | 427 (31.2) |
| ≥ once per week | 285 (51.4) | 352 (54.7) | 56 (55.5) | 47 (67.1) | 740 (54.1) |
| Prior history of polyps | |||||
| No | 554 (100.0) | 255 (39.5) | 39 (38.6) | 31 (44.3) | 879 (64.2) |
| Yes | 0 (0) | 379 (58.8) | 62 (61.4) | 38 (54.3) | 479 (35.0) |
| Unsure | 0 (0) | 11 (1.7) | 0 (0) | 1 (1.4) | 12 (0.9) |
| Family history of colon cancer¥ | |||||
| No | 455 (82.1) | 525 (81.4) | 79 (78.2) | 61 (87.1) | 1,120 (81.8) |
| Yes | 99 (17.9) | 120 (18.6) | 22 (21.8) | 9 (12.9) | 250 (18.3) |
The total N in the category differs from the total adjusted sample size of N=1,370 because of missing data.
The association of each metabolic risk exposure of interest with the polyp outcome was assessed individually using multinomial logistic regression to derive adjusted conditional odds ratios (aCOR) and 95% confidence intervals (95% CI) as an estimate of effect size.
Analysis of the relationship of the metabolic risk factors with advanced polyps was also assessed using an individual multinomial logistic regression for each polyp type, where the outcomes were no polyps, non-advanced polyps <1cm, or at least 1 advanced polyp of >1cm.
In the present study, sex was adjusted for as a covariate and then a stratified analysis by sex was performed to test if any differences were observed.
In the final analyses, a p-value of <0.05 was considered statistically significant. All analyses were performed using Stata version 15.1.
Results
Of 2,051 individuals completing the first study visit, 1,370 (66.8%) participants were included in the data analysis. Table 1 shows demographic characteristics of study participants, based on polyp classification. Of the 1,370 participants studied, there were 554 control participants without polyps and without a reported or unknown history of polyps, including 191 males and 363 females; 645 participants (47.1%) with APs, 325 males and 320 females; 101 participants (7.4%) with SSPs, 37 males and 64 females; and 70 participants (5.1%) with synch polyps, 40 males and 30 females. APs and synch polyps were more prevalent in males than in females (APs: 54.8% vs 41.2%; synch: 6.7% vs. 3.9%). SSPs were more prevalent in females than in males (8.2% vs 6.2%). At a power of 0.80 and a two-sided alpha of 0.05, the minimally detectable odds ratios for this study are 1.52, 2.58, 3.34 for adenomatous polyps, sessile serrated polyps, and synch polyps respectively.
Metabolic risk exposures included 39.9% of participants with hypertension (546 participants), 16.9% with hyperlipidemia (232 participants) and 13.3% with diabetes (182 participants). BMI measurements revealed 36.0% were overweight (493 participants), and 39.9% were obese (546 participants). Only 17.2% of participants had no metabolic risk factors whereas 38.5% of participants had one metabolic risk factor, 28.4%, two, 13.0%, three, and 2.9%, all four of the metabolic risk factors examined (BMI>25kg/m2, hypertension, hyperlipidemia, diabetes). The differential impact of these risk factors on APs, SSPs, and synch polyps are described below.
Adenomatous polyps
Being obese or overweight or having diabetes were associated with an increased odds of APs compared to those with a normal BMI [aCOR for overweight and obese, 1.54 (1.11, 2.13) and 2.09 (1.52, 2.88), respectively] (Figure 2A). The p-value for trend for the association of increased BMI with APs was p<0.001. Having diabetes vs. no diabetes resulted in an aCOR of 1.59 (1.10, 2.29) (Figure 2A). Hypertension or hyperlipidemia were not statistically significantly associated with an increased risk of APs (Figure 2A).
Figure 2.
Forest plots displaying aCOR and 95% CI from multinomial logistic regression for the odds of metabolic risk factors with APs (A), SSPs (B), and synch polyps (C). Statistically significant findings are highlighted with an asterisk.
After stratification by polyp size, advanced APs were associated with obesity [aCOR of 3.10 (1.53, 6.26)] and with hypertension [aCOR of 2.32 (1.38, 3.91)]. The association with hypertension was not seen when the polyp sizes were combined. Advanced APs were not associated with having diabetes or being overweight. (Table 2)
Table 2.
aCOR and 95% CI from multinomial logistic regression for non-advanced versus advanced adenomas
| Adenomatous Polyps | Sessile Serrated Polyps | Synchronous Polyps | ||||
|---|---|---|---|---|---|---|
| Polyp Size | Nonadvanced Polyps <1cm |
Advanced Polyps >1cm | Nonadvanced Polyps <1cm |
Advanced Polyps >1cm | Nonadvanced Polyps <1cm |
Advanced Polyps >1cm |
| N (%) | 572 (88.68) | 73 (11.32) | 87 (86.14) | 14 (13.86) | 53 (75.71) | 17 (24.29) |
| Metabolic Risk Factor | aCOR | aCOR | aCOR | |||
| BMI <25 kg/m2 | refǂ | refǂ | refǂ | refǂ | refǂ | refǂ |
| BMI 25–30 kg/m2 | *1.57 (1.13, 2.20) | 1.46 (0.67, 3.20) | 0.83 (0.46, 1.49) | 0.52 (0.13, 2.00) | 1.37 (0.62, 3.05) | 9.00 (0.89, 91.25) |
| BMI >30 kg/m2 | *1.99 (1.43, 2.77) | *3.40 (1.64, 7.03) | 1.00 (0.57, 1.77) | 0.45 (0.11, 1.80) | 1.44 (0.64, 3.24) | *13.84 (1.37, 139.74) |
| Hypertension (yes vs no) | 1.12 (0.86, 1.46) | *2.24 (1.32, 3.79) | 1.42 (0.88, 2.29) | 1.44 (0.46, 4.54) | 1.53 (0.84, 2.79) | *3.83 (1.25, 11.7) |
| Hyperlipidemia (yes vs no) | 1.05 (0.74, 1.48) | 1.46 (0.78, 2.73) | 1.42 (0.79, 2.56) | 1.59 (0.41, 6.12) | 1.24 (0.58, 2.67) | 1.45 (0.44, 4.82) |
| Diabetes (yes vs no) | *1.63 (1.12, 2.37) | 1.43 (0.72, 2.87) | 0.44 (0.15, 1.27) | 1.86 (0.38, 9.11) | 1.21 (0.25, 5.86) | 0.81 (0.29, 2.25) |
The reference group is the baseline group to which the other BMI categories of overweight and obese are compared to.
Statistically significant findings are highlighted with an asterisk.
When stratified by sex (Figure 3), diabetes was only associated with APs in females [aCOR of 1.83 (1.15, 2.93)] whereas an overweight BMI was only associated with APs in males [aCOR of 2.35 (1.38, 3.99)]. An obese BMI was associated with APs in both males and females [aCOR values of 3.01 (1.75, 5.20) and 1.76 (1.20, 2.60), respectively] (Figure 3A).
Figure 3.
Forest plots displaying sex-stratified aCOR and 95% CI from multinomial logistic regression for the odds of metabolic risk factors with APs (A), SSPs (B), and synch polyps (C). Statistically significant findings are highlighted with an asterisk.
Sessile serrated polyps
No statistically significant associations between the metabolic risk exposures and SSPs were detected herein. This was true in an individual assessment of each metabolic risk factor (Figure 2B), or when stratified by polyp size (Table 2), or by sex (Figure 3B).
Synchronous polyps
Lastly, the odds of synch polyps increased in participants with hypertension versus those without hypertension [aCOR of 1.93 (1.14, 3.25)] and in those with obesity vs a normal BMI [aCOR of 2.18 (1.06, 4.48)]. Hyperlipidemia, diabetes, or being overweight were not associated with an increased risk of synch polyps in this population (Figure 2C).
Stratifying synch polyps by size revealed that only advanced synch polyps were associated with hypertension [aCOR of 3.83 (1.25, 11.7)] or an obese BMI [aCOR of 13.84 (1.37, 139.74)]. Non-advanced polyps did not display associations with the metabolic risk factors examined (Table 2).
No statistically significant associations were seen for synch polyps when stratified by sex (Figure 3C).
Discussion
Elucidating the risk factors associated with different polyp types may help in identifying individuals at greater risk clinically for these polyps and assist physicians in conversations encouraging patients to undergo screening colonoscopy. Our study used well-defined polyp categories to elucidate differences in four metabolic risk factors for three types of polyps. We identified that associations of metabolic risk exposures differed between histologically distinct polyp types when assessing each exposure independently adjusted for age, sex, race, and smoking status. Being overweight, obese, or diabetic independently associated with APs, while hypertension associated exclusively with advanced APs. Metabolic risk factors were not significantly associated with SSPs, suggesting that metabolic risk factors impact AP but not SSP development. Consistent with the AP alone data, obesity or hypertension increased the risk of synch polyps, in particular, advanced synch polyps. Thus, synch polyps behaved more like APs versus SSPs, but possibly with stronger risk.
Herein increased BMI, and particularly obesity, was a strong risk factor for APs. Although the associations for BMI and APs vary in the literature, our results are consistent with assessment via meta-analyses (11–13) whether using physician-measured BMI (11) or self-reported measures (12,13). Our study assessed BMI mostly using self-reported medical histories. As compared to those with normal weight, being overweight increased the odds of APs by ~50% and being obese more than doubled the odds of APs (~100% increase) (p-value for trend <0.001). This dose-response relationship was also seen in the meta-analysis by Okabayashi et al., which included self-reported measures, but not seen in the meta-analysis by Wong et al., which included studies with only physician-measured BMI (11,12). In contrast, in the meta-analysis by Ben et al., adenoma risk increased only with obese BMI but not overweight BMI (13). Our effect estimations for BMI were higher than in the meta-analyses despite similar categorization of BMI although the confidence intervals overlapped (11–13). One reason our estimates may differ include the decision to remove individuals with a reported history of polyps from our control group, potentially diminishing homogeneity between our cases and controls and strengthening the association between obesity and APs.
Additional differences among the studies exist. In the Wong et al. meta-analysis, the odds of APs was higher in females with a BMI>25 kg/m2 (versus females with a normal BMI) (11), whereas we found males to have a higher odds of APs for both overweight and obese BMI. The meta-analysis by Ben et al. found no significant differences in the associations by sex (13), and the meta-analysis by Okabayashi et al. found overweight and obesity to be significant risk factors only for females (12). While it is not clear why AP risk differed by sex in our population, menopausal status, not explicitly collected in our study, may play a role, with a potentially greater adenoma risk being seen in premenopausal women (12).
Our study associated diabetes with APs [aCOR of 1.59 (1.11, 2.13)]. This association was not seen for advanced APs herein, and stratified analysis by sex found this association only in females. The association between diabetes and APs has been noted previously and detected by meta-analysis in both non-advanced and advanced adenomas; however, the sample size was too limited to assess risk by sex via meta-analysis (14). In contrast, other data in women did find an association with adenomas and diabetes (21). Other studies have associated diabetes with having multiple polyps (22) or have found an association with adenomas and diabetes in diabetic subgroups such as in younger populations (23) or in those with other comorbidities such as chronic kidney disease (24). However, not all studies have detected an association between diabetes and APs and differences in underlying population characteristics and/or study design (retrospective vs prospective) may be responsible (14). Potentially consistent with an association of diabetes and polyp risk, metformin, a medication commonly used to treat type 2 diabetes, has been investigated as a treatment for colorectal adenomas; two meta-analyses revealed that metformin use was associated with reduced risk of colorectal adenoma (25,26). Metformin’s protective effects may vary by population subtypes; it may potentially be more protective in populations with higher DM prevalence (26). Thus, as yet, ill-defined differences amongst study populations likely contribute to adenoma risk in diabetes.
Mechanisms behind these associations are not fully understood, but several have been proposed (11). For example, by meta-analysis, levels of adiponectin, an adipokine protein hormone important in limiting glucose levels, were decreased in individuals with adenomas and CRC (27); this suggests greater exposure of the colon epithelium to glucose excess. Elevated insulin levels, commonly resulting from obesity or other similar morbidities, and the insulin to insulin-like growth factor axis may create a favorable environment for formation of CRC tumors (28,29). Further, the inflammatory state found in obesity may contribute by increasing tumorigenic cytokines like Interleukin-6 (IL-6) (28). Kim et. al considered the neutrophil-to-lymphocyte ratio (NLR) in association with colorectal adenomas as an inflammation marker revealing a strong independent association between higher NLR and colorectal adenomas after controlling for age, gender, BMI, smoking, alcohol, and exercise (30). Similarly, elevated C-reactive protein (CRP), a marker of inflammation, has been associated with adenomas (31). Understanding mechanisms contributing to polyp development is key to providing insight into approaches for modifying lifestyle factors to lower polyp risk and identify risk factors for SSPs.
Unexpectedly, herein, hypertension associated with advanced, but not non-advanced, APs. Hypertension more than doubled the odds of advanced APs. In limited data, other researchers have also found this association albeit in small studies or in association with AP recurrence (32,33). Of interest, Huang et al. also found that hypertension was significantly associated with advanced, but not non-advanced, APs (34). A few studies suggest that antihypertensive medications modify the relationship between polyps and hypertension; however, outcomes are variable, such as increased risk associated with anti-hypertensive medications (35); beta-blockers associated with decreased risk of colon cancer (36,37); or no impact of calcium channel blockers on colon cancer risk (38). Collectively, our study adds to the plausibility of the association of hypertension and AP risk, especially in advanced APs. However, further study, including mechanisms, is warranted.
Our data display a distinct difference in metabolic risk factor associations between APs and SSPs, where no associations with SSPs were identified. Information on risk factors for SSPs are limited because risk factors for serrated polyps overall, which include the more common HPs, were typically studied as a whole before the serrated pathway to CRC was better understood (3). Studies have been hampered by small populations of SSPs (32). Because HPs are benign, the challenges with elucidating an understanding of SSP risk factors in studies that combine HPs and SSPs has been noted (16). A meta-analysis evaluating risk factors for serrated polyps overall found BMI among other non-metabolic risk factors to be associated, but in a sub-study investigating risk factors specifically for SSPs this association was not seen (39). Consistent with our analyses, even when metabolic risk factors were included in analyses, to date, only non-metabolic risk factors for SSPs were reported (18,40–42). Whether sample sizes have been too limited, or there is just a weaker effect of metabolic risk factors on SSPs, needs further study.
Herein obesity or hypertension was associated with increased risk of synch polyps, mirroring associations we observed for APs, although with stronger point estimates. Few studies have examined individuals with synch polyps. Limited observations suggest that synch polyps associate with increased risk of advanced polyps (6) and potentially associate with smoking and increased BMI, although the study finding this association grouped traditional serrated adenomas (TSAs) with SSPs as a proxy for SSPs (17). Our study adds to a framework associating increased BMI with synch polyps, yet further study is needed to understand risk factors for synch polyps.
There were several limitations in the current study. The study data are cross-sectional and therefore information on temporality could not be ascertained. Metabolic risk factor assignments were based on self-reported medical histories, were not verified by prior medical records, and lacked quantitative precision (e.g., current HbA1C levels) as well as information on length and severity of these conditions. While these self-reported medical histories leave open the possibility of misclassification, we do not believe that there is differential misclassification among those with versus those without polyps and misclassifications would most likely have weakened (e.g., under-reporting of prior conditions and/or excess weight) rather than strengthened the estimates presented in this study. Although a strength of our study was a larger population sample size of individuals with SSPs and synch polyps than in other studies, the sample size of these populations combined with metabolic risk factors remained small. For example, there were only 6 participants that had both diabetes and SSPs. Lastly, the study participants were majority white, limiting generalizability.
Strengths of this study include information on prior polyp history which allowed exclusion of participants with a previous history of polyps from the control group. This exclusion of individuals with a history of polyps has been done in the literature, though not consistently (32,43–46). This allowed for sharpening of the categories of those with and without polyps, since a previous history of polyps is associated with an increased risk for polyp recurrence (47,48). Further, our populations of SSPs and synch polyps is larger than a number of previous studies and, importantly, our inclusion of SSPs was limited to histopathologically confirmed SSPs and did not include benign HPs or rare TSAs.
In conclusion, our findings suggest that histopathologically distinct colon polyp precursors to CRC differ in metabolic risk factors associations, which we postulate, reflect promotion of different pathways leading to CRC. Key is a distinction between APs and SSPs, with the former, but not the latter, associated with metabolic risk factors that may differ by sex. Obesity appears to be the strongest factor for both non-advanced and advanced APs, while being overweight or having diabetes are also notable risk factors for non-advanced APs. Hypertension may be a specific risk factor for advanced APs. However, larger studies are needed to assess these associations and, in particular, associations with SSPs and synch polyps. Our results suggest that self-reported medical history provides valuable insight to polyp risk, potentially enabling the use of larger retrospective studies of colonoscopy populations to assess knowledge gaps. As data accrue, more aggressive colonoscopy screening, critical to CRC prevention (49,50), may be considered in populations of individuals with metabolic risk factors and modifiable lifestyle risk factors.
Prevention Relevance.
Self-reported medical history provides valuable insight into polyp risk, potentially enabling the use of larger retrospective studies of colonoscopy populations to assess knowledge gaps. More aggressive colonoscopy screening, critical to CRC prevention, may be considered in populations of individuals with metabolic risk factors and modifiable lifestyle risk factors.
Acknowledgements
This study was supported by grants R01CA196845 (CLS, FG, CNS, JD, GM, ES, DK, DC, LLL), Bloomberg Philanthropies (CLS, JJG), T32DK007632 (SR), intramural funds (LH) and the Johns Hopkins Cancer Center Support Grant, NCI P30CA006973 (CLS, FG). All data from R01CA196845 (Johns Hopkins) were stored in Research Electronic Data Capture (REDCap). The content of this paper is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the National Institutes of Health. The authors thank all members of the Sears laboratory for assistance with the Biofilm Colonoscopy Study.
Abbreviations
- CRC
Colorectal cancer
- HP
Hyperplastic polyp
- AP
Adenomatous polyp (also known as conventional adenomas)
- SSP
Sessile serrated polyp (also known as sessile serrated adenomas)
- Synch polyps
Synchronous presence of SSPs and APs
- COR
conditional odds ratio
- aCOR
adjusted conditional odds ratio
- aOR
adjusted odds ratio
- 95% CI
95% confidence interval
- SD
standard deviation
- IQR
interquartile range
- Ref
baseline reference group to which other categories are compared
Footnotes
Conflict of interest disclosure. CLS receives grant support from Bristol Myers Squibb and Janssen.
Institutional review board statement. The Biofilm study was approved by the Johns Hopkins Hospital (JHH) institutional review board: IRB00094020 (Principal investigators: CL Sears, FM Giardiello).
Informed consent statement. All participants provided written informed consent.
Bibliography
- 1.Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin [Internet] Wiley; 2018. [cited 2020 May 7];68:394–424. Available from: 10.3322/caac.21492 [DOI] [PubMed] [Google Scholar]
- 2.Arnold M, Sierra MS, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global patterns and trends in colorectal cancer incidence and mortality. Gut [Internet] BMJ Publishing Group; 2017. [cited 2019 Mar 8];66:683–91. Available from: http://www.ncbi.nlm.nih.gov/pubmed/26818619 [DOI] [PubMed] [Google Scholar]
- 3.Crockett SD, Snover DC, Ahnen DJ, Baron JA. Sessile serrated adenomas: An evidence-based guide to management. Clin Gastroenterol Hepatol W.B. Saunders; 2015;13:11–26.e1. [DOI] [PubMed] [Google Scholar]
- 4.Meester RGS, Ladabaum U. Sessile serrated polyps and colorectal cancer mortality [Internet]. Lancet Gastroenterol. Hepatol Elsevier Ltd; 2020. [cited 2021 Feb 5]. page 516–7. Available from: https://pubmed.ncbi.nlm.nih.gov/32192629/ [DOI] [PubMed] [Google Scholar]
- 5.Vu HT, Lopez R, Bennett A, Burke CA. Individuals With Sessile Serrated Polyps Express an Aggressive Colorectal Phenotype. Dis Colon Rectum [Internet] 2011. [cited 2019 Apr 14];54:1216–23. Available from: http://www.ncbi.nlm.nih.gov/pubmed/21904135 [DOI] [PubMed] [Google Scholar]
- 6.Symonds E, Anwar S, Young G, Meng R, Coats M, Simpson K, et al. Sessile Serrated Polyps with Synchronous Conventional Adenomas Increase Risk of Future Advanced Neoplasia. Dig Dis Sci Springer New York LLC; 2019;64:1680–5. [DOI] [PubMed] [Google Scholar]
- 7.Platz EA, Willett WC, Colditz GA, Rimm EB, Spiegelman D, Giovannucci E. Proportion of colon cancer risk that might be preventable in a cohort of middle-aged US men. Cancer Causes Control [Internet] 2000. [cited 2019 Apr 29];11:579–88. Available from: http://www.ncbi.nlm.nih.gov/pubmed/10977102 [DOI] [PubMed] [Google Scholar]
- 8.Erdrich J, Zhang X, Giovannucci E, Willett W. Proportion of colon cancer attributable to lifestyle in a cohort of US women. Cancer Causes Control Kluwer Academic Publishers; 2015;26:1271–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Edwards BK, Ward E, Kohler BA, Eheman C, Zauber AG, Anderson RN, et al. Annual report to the nation on the status of cancer, 1975–2006, featuring colorectal cancer trends and impact of interventions (risk factors, screening, and treatment) to reduce future rates. Cancer [Internet] 2010. [cited 2019 Mar 8];116:544–73. Available from: http://www.ncbi.nlm.nih.gov/pubmed/19998273 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Saklayen MG. The Global Epidemic of the Metabolic Syndrome. Curr Hypertens Rep [Internet] Springer; 2018. [cited 2019 Apr 29];20:12. Available from: http://www.ncbi.nlm.nih.gov/pubmed/29480368 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.sang Wong MC, hei Chan C, Cheung W, hei Fung D, Liang M, wen Huang JL, et al. Association between investigator-measured body-mass index and colorectal adenoma: a systematic review and meta-analysis of 168,201 subjects. Eur J Epidemiol Springer Netherlands; 2018;33:15–26. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Okabayashi K, Ashrafian H, Hasegawa H, Yoo J-H, Patel VM, Harling L, et al. Body Mass Index Category as a Risk Factor for Colorectal Adenomas: A Systematic Review and Meta-Analysis 2012. [cited 2020 May 21]; Available from: http://www.nature.com/ajg [DOI] [PubMed]
- 13.Ben Q, An W, Jiang Y, Zhan X, Du Y, Cai QC, et al. Body mass index increases risk for colorectal adenomas based on meta-analysis. Gastroenterology W.B. Saunders; 2012;142:762–72. [DOI] [PubMed] [Google Scholar]
- 14.Yu F, Guo Y, Wang H, Feng J, Jin Z, Chen Q, et al. Type 2 diabetes mellitus and risk of colorectal adenoma: A meta-analysis of observational studies. BMC Cancer BioMed Central Ltd.; 2016;16. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Lee G-E, Park HS, Yun KE, Jun SH, Kim HK, Cho S, et al. Association Between BMI and Metabolic Syndrome and Adenomatous Colonic Polyps in Korean Men. Obesity [Internet] 2008. [cited 2019 Mar 9];16:1434–9. Available from: http://www.ncbi.nlm.nih.gov/pubmed/18388894 [DOI] [PubMed] [Google Scholar]
- 16.Crockett SD, Nagtegaal ID. Terminology, Molecular Features, Epidemiology, and Management of Serrated Colorectal Neoplasia. Gastroenterology W.B. Saunders; 2019. page 949–966.e4. [DOI] [PubMed] [Google Scholar]
- 17.Anderson JC, Calderwood AH, Christensen BC, Robinson CM, Amos CI, Butterly L. Smoking and Other Risk Factors in Individuals With Synchronous Conventional High-Risk Adenomas and Clinically Significant Serrated Polyps. Am J Gastroenterol Nature Publishing Group; 2018;113:1828. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Davenport JR, Su T, Zhao Z, Coleman HG, Smalley WE, Ness RM, et al. Modifiable lifestyle factors associated with risk of sessile serrated polyps, conventional adenomas and hyperplastic polyps. Gut BMJ Publishing Group; 2018;67:456–65. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Rifkin SB, Giardiello FM, Zhu X, Hylind LM, Ness RM, Drewes JL, et al. Yogurt consumption and colorectal polyps. Br J Nutr Cambridge University Press; 2020; [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Bozdogan H Model selection and Akaike’s Information Criterion (AIC): The general theory and its analytical extensions. Psychometrika [Internet] Springer-Verlag; 1987. [cited 2020 Aug 21];52:345–70. Available from: 10.1007/BF02294361 [DOI] [Google Scholar]
- 21.Elwing JE, Gao F, Davidson NO, Early DS. Type 2 Diabetes Mellitus: The Impact on Colorectal Adenoma Risk in Women. Am J Gastroenterol 2006;101:1866–71. [DOI] [PubMed] [Google Scholar]
- 22.Suh S, Kang M, Kim MY, Chung HS, Kim SK, Hur KY, et al. Korean type 2 diabetes patients have multiple adenomatous polyps compared to non-diabetic controls. J Korean Med Sci Korean Academy of Medical Sciences; 2011;26:1196–200. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Vu HT, Ufere N, Yan Y, Wang JS, Early DS, Elwing JE. Diabetes mellitus increases risk for colorectal adenomas in younger patients. World J Gastroenterol WJG Press; 2014;20:6946–52. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Chowdhury DN, Botros Y, DeBari VA, Baddoura W, Chandran CB. Adenomatous Colon Polyps in Diabetes: Increased Prevalence in Patients with Chronic Kidney Disease and Its Association with Parathyroid Hormone. Ann Clin Lab Sci [Internet] Association of Clinical Scientists; 2016. [cited 2020 May 26];46:608–15. Available from: http://www.ncbi.nlm.nih.gov/pubmed/27993873 [PubMed] [Google Scholar]
- 25.Jung YS, Park CH, Eun CS, Park D Il, Han DS. Metformin use and the risk of colorectal adenoma: A systematic review and meta-analysis. J Gastroenterol Hepatol [Internet] Blackwell Publishing; 2017. [cited 2020 May 26];32:957–65. Available from: 10.1111/jgh.13639 [DOI] [PubMed] [Google Scholar]
- 26.Hou Y-C, Hu Q, Huang J, Fang J-Y, Xiong H. Metformin therapy and the risk of colorectal adenoma in patients with type 2 diabetes: A meta-analysis. Oncotarget Impact Journals, LLC; 2017;8:8843. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.An W, Bai Y, Deng SX, Gao J, Ben QW, Cai QC, et al. Adiponectin levels in patients with colorectal cancer and adenoma: A meta-analysis. Eur J Cancer Prev 2012;21:126–33. [DOI] [PubMed] [Google Scholar]
- 28.Renehan AG, Frystyk J, Flyvbjerg A. Obesity and cancer risk: the role of the insulin-IGF axis. Trends Endocrinol. Metab Elsevier Current Trends; 2006. page 328–36. [DOI] [PubMed] [Google Scholar]
- 29.Clayton PE, Banerjee I, Murray PG, Renehan AG. Growth hormone, the insulin-like growth factor axis, insulin and cancer risk. Nat. Rev. Endocrinol Nature Publishing Group; 2011. page 11–24. [DOI] [PubMed] [Google Scholar]
- 30.Kim JH, Cho KI, Kim YA, Park SJ. Elevated Neutrophil-to-Lymphocyte Ratio in Metabolic Syndrome Is Associated with Increased Risk of Colorectal Adenoma. Metab Syndr Relat Disord [Internet] 2017. [cited 2019 Mar 20];15:393–9. Available from: 10.1089/met.2017.0041 [DOI] [PubMed] [Google Scholar]
- 31.Lee HM, Cha JM, Lee JL, Jeon JW, Shin HP, Joo KR, et al. High C-reactive protein level is associated with high-risk adenoma. Intest Res [Internet] Korean Association for the Study of Intestinal Diseases; 2017. [cited 2020 Aug 21];15:511–7. Available from: /pmc/articles/PMC5683982/?report=abstract [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Fliss-Isakov N, Zelber-Sagi S, Webb M, Halpern Z, Shibolet O, Kariv R. Distinct Metabolic Profiles are Associated with Colorectal Adenomas and Serrated Polyps. Obesity [Internet] 2017. [cited 2019 Mar 9];25:S72–80. Available from: http://www.ncbi.nlm.nih.gov/pubmed/29086511 [DOI] [PubMed] [Google Scholar]
- 33.Lin CC, Huang KW, Luo JC, Wang YW, Hou MC, Lin HC, et al. Hypertension is an important predictor of recurrent colorectal adenoma after screening colonoscopy with adenoma polypectomy. J Chinese Med Assoc Elsevier Ltd; 2014;77:508–12. [DOI] [PubMed] [Google Scholar]
- 34.Huang H-E, Yang Y-C, Wu J-S, Wang R-H, Lu F-H, Chang C-J. The relationship between different glycemic statuses and colon polyps in a Taiwanese population. J Gastroenterol [Internet] 2014. [cited 2019 Apr 20];49:1145–51. Available from: 10.1007/s00535-013-0863-5 [DOI] [PubMed] [Google Scholar]
- 35.Watanabe Y, Yamaji Y, Kobayashi Y, Yoshida S, Sugimoto T, Yamada A, et al. Association between colorectal polyps and hypertension treatment. J Dig Dis [Internet] Blackwell Publishing; 2015. [cited 2021 Feb 6];16:649–55. Available from: https://pubmed.ncbi.nlm.nih.gov/26356801/ [DOI] [PubMed] [Google Scholar]
- 36.Chang PY, Huang WY, Lin CL, Huang TC, Wu YY, Chen JH, et al. Propranolol reduces cancer risk. Med (United States) [Internet] Lippincott Williams and Wilkins; 2015. [cited 2021 Feb 5];94:e1097. Available from: https://pubmed.ncbi.nlm.nih.gov/26166098/ [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Coelho M, Moz M, Correia G, Teixeira A, Medeiros R, Ribeiro L. Antiproliferative effects of β-blockers on human colorectal cancer cells. Oncol Rep [Internet] Spandidos Publications; 2015. [cited 2021 Feb 6];33:2513–20. Available from: https://pubmed.ncbi.nlm.nih.gov/25812650/ [DOI] [PubMed] [Google Scholar]
- 38.Grimaldi-Bensouda L, Klungel O, Kurz X, De Groot MCH, Afonso ASM, De Bruin ML, et al. Calcium channel blockers and cancer: A risk analysis using the UK Clinical Practice Research Datalink (CPRD). BMJ Open [Internet] BMJ Publishing Group; 2016. [cited 2021 Feb 6];6. Available from: https://pubmed.ncbi.nlm.nih.gov/26747033/ [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Bailie L, Loughrey MB, Coleman HG. Lifestyle Risk Factors for Serrated Colorectal Polyps: A Systematic Review and Meta-analysis. Gastroenterology [Internet] 2017. [cited 2019 Mar 9];152:92–104. Available from: http://www.ncbi.nlm.nih.gov/pubmed/27639804 [DOI] [PubMed] [Google Scholar]
- 40.Anderson JC, Rangasamy P, Rustagi T, Myers M, Sanders M, Vaziri H, et al. Risk Factors for Sessile Serrated Adenomas. J Clin Gastroenterol [Internet] 2011. [cited 2019 Mar 20];45:694–9. Available from: http://www.ncbi.nlm.nih.gov/pubmed/21325950 [DOI] [PubMed] [Google Scholar]
- 41.Michalopoulos G, Vrakas S, Ntouli V, Lamprinakos S, Makris K, Tzathas C. Sessile serrated adenomas versus conventional adenomas. Different polyps in different populations? Indian J Gastroenterol [Internet] 2015. [cited 2019 Apr 14];34:245–51. Available from: 10.1007/s12664-015-0562-7 [DOI] [PubMed] [Google Scholar]
- 42.Pyo JH, Ha SY, Hong SN, Chang DK, Son HJ, Kim K-M, et al. Identification of risk factors for sessile and traditional serrated adenomas of the colon by using big data analysis. J Gastroenterol Hepatol [Internet] Blackwell Publishing; 2018. [cited 2020 May 27];33:1039–46. Available from: 10.1111/jgh.14035 [DOI] [PubMed] [Google Scholar]
- 43.Kim BC, Shin A, Hong CW, Sohn DK, Han KS, Ryu KH, et al. Association of colorectal adenoma with components of metabolic syndrome. Cancer Causes Control [Internet] 2012. [cited 2019 Mar 9];23:727–35. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22450737 [DOI] [PubMed] [Google Scholar]
- 44.Brauer PM, McKeown-Eyssen GE, Jazmaji V, Logan AG, Andrews DF, Jenkins D, et al. Familial aggregation of diabetes and hypertension in a case-control study of colorectal neoplasia. Am J Epidemiol [Internet] 2002. [cited 2019 Apr 20];156:702–13. Available from: http://www.ncbi.nlm.nih.gov/pubmed/12370158 [DOI] [PubMed] [Google Scholar]
- 45.Eddi R, Karki A, Shah A, DeBari VA, DePasquale JR. Association of Type 2 Diabetes and Colon Adenomas. J Gastrointest Cancer [Internet] 2012. [cited 2019 Mar 20];43:87–92. Available from: http://www.ncbi.nlm.nih.gov/pubmed/21894459 [DOI] [PubMed] [Google Scholar]
- 46.Trabulo D Metabolic syndrome and colorectal neoplasms: An ominous association. World J Gastroenterol [Internet] 2015. [cited 2019 Apr 20];21:5320. Available from: http://www.wjgnet.com/1007-9327/full/v21/i17/5320.htm [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Ashktorab H, Paydar M, Yazdi S, Namin HH, Sanderson A, Begum R, et al. BMI and the risk of colorectal adenoma in African-Americans. Obesity [Internet] 2014. [cited 2019 Mar 20];22:1387–91. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24519988 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Sass DA, Schoen RE, Weissfeld JL, Weissfeld L, Thaete FL, Kuller LH, et al. Relationship of visceral adipose tissue to recurrence of adenomatous polyps. Am J Gastroenterol [Internet] 2004. [cited 2019 Apr 20];99:687–93. Available from: 10.1111/j.1572-0241.2004.04136.x [DOI] [PubMed] [Google Scholar]
- 49.Loffeld RJLF, Liberov B, Dekkers PEP. The incidence of colorectal cancer in patients with previously removed polyp(s)-a cross-sectional study. J Gastrointest Oncol AME Publishing Company; 2018;9:674–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Niikura R, Hirata Y, Suzuki N, Yamada A, Hayakawa Y, Suzuki H, et al. Colonoscopy reduces colorectal cancer mortality: A multicenter, long-term, colonoscopy-based cohort study. PLoS One Public Library of Science; 2017;12. [DOI] [PMC free article] [PubMed] [Google Scholar]