Literature DB >> 28053552

Diet and lifestyle factors associated with miRNA expression in colorectal tissue.

Martha L Slattery1, Jennifer S Herrick1, Lila E Mullany1, John R Stevens2, Roger K Wolff1.   

Abstract

MicroRNAs (miRNAs) are small non-protein-coding RNA molecules that regulate gene expression. Diet and lifestyle factors have been hypothesized to be involved in the regulation of miRNA expression. In this study it was hypothesized that diet and lifestyle factors are associated with miRNA expression. Data from 1,447 cases of colorectal cancer to evaluate 34 diet and lifestyle variables using miRNA expression in normal colorectal mucosa as well as for differential expression between paired carcinoma and normal tissue were used. miRNA data were obtained using an Agilent platform. Multiple comparisons were adjusted for using the false discovery rate q-value. There were 250 miRNAs differentially expressed between carcinoma and normal colonic tissue by level of carbohydrate intake and 198 miRNAs differentially expressed by the level of sucrose intake. Of these miRNAs, 166 miRNAs were differentially expressed for both carbohydrate intake and sucrose intake. Ninety-nine miRNAs were differentially expressed by the level of whole grain intake in normal colonic mucosa. Level of oxidative balance score was associated with 137 differentially expressed miRNAs between carcinoma and paired normal rectal mucosa. Additionally, 135 miRNAs were differentially expressed in colon tissue based on recent NSAID use. Other dietary factors, body mass index, waist and hip circumference, and long-term physical activity levels did not alter miRNA expression after adjustment for multiple comparisons. These results suggest that diet and lifestyle factors regulate miRNA level. They provide additional support for the influence of carbohydrate, sucrose, whole grains, NSAIDs, and oxidative balance score on colorectal cancer risk.

Entities:  

Keywords:  NSAIDs; carbohydrate; colorectal cancer; miRNA; oxidative balance; sucrose

Year:  2016        PMID: 28053552      PMCID: PMC5189704          DOI: 10.2147/PGPM.S117796

Source DB:  PubMed          Journal:  Pharmgenomics Pers Med        ISSN: 1178-7066


Introduction

MicroRNAs (miRNAs) are small non-protein-coding RNA molecules that regulate gene expression either by posttranscriptionally suppressing messenger RNA (mRNA) translation or by causing mRNA degradation.1–6 We know that miRNAs play a critical role in regulation of proliferation, differentiation, apoptosis, and stress response and are involved in the majority of physiological processes.7,8 While we are beginning to understand the role of miRNAs in various physiological functions, our understanding of what regulates miRNA expression is minimal. However, some studies have shown that some diet and other lifestyle factors such as specific dietary components, oxidative stress, and aspirin and nonsteroidal anti-inflammatory drugs (NSAIDs) alter miRNA expression.9–13 One of the factors most consistently inversely associated with colorectal cancer (CRC) risk is use of aspirin/NSAIDs. Likewise, dietary factors such as antioxidants have been associated with CRC risk.14–17 We and others have shown that the oxidative balance score (OBS) is associated with CRC,18–20 with CRC risk lowest among those with a score that is higher in antioxidants and lower in prooxidant factors. The role that these diet and lifestyle factors have on miRNA expression is limited, especially as it applies to colorectal tissue. In this study, we examine the linear association between diet and lifestyle factors and miRNA expression in colon and rectal tissues. Our hypothesis is that lifestyle factors commonly associated with CRC risk alter miRNA expression profiles. We test associations for colon and rectal cancers separately, since risk factors often differ by tumor location. We evaluate associations of diet and lifestyle factors with miRNA expression for normal colon and rectal mucosa as well as for the difference of miRNA expression between paired carcinoma and normal colorectal tissue to help determine if associations influence the disease process. If miRNA expression profiles are altered by diet and lifestyle factors, it would strengthen the biological support for these associations and provide avenues for cancer prevention.

Methods

Study participants

Study participants came from two population-based case–control studies that included all incident colon and rectal cancers between 30 and 79 years of age who resided along the Wasatch Front in Utah or were members of the Kaiser Permanente Medical Care Program (KPMCP) in Northern California. Participants were White, Hispanic, or Black for the colon cancer study; the rectal cancer study also included Asians and American Indians not living on reservations.21,22 Cases had to have tumor registry verification of a first primary adenocarcinoma of the colon or rectum and were diagnosed between October 1991 and September 1994 for the colon cancer study and between June 1997 and May 2001 for the rectal cancer study. Detail study methods have been described earlier.23 The study was approved by the Institutional Review Board of the University of Utah and at KPMCP and all participants provided written informed consent.

miRNA processing

RNA was extracted from formalin-fixed paraffin-embedded tissue. Both normal mucosa adjacent to the carcinoma tissue and matched carcinoma tissue were used. Normal mucosa tissue served as a control. The Agilent Human miRNA Microarray V19.0 (Agilent Technologies, Santa Clara, CA, USA) was used given the number of miRNAs, its high level of reliability (repeatability coefficient was 0.98 in our data), and the amount of RNA needed to run the platform. The microarray contains probes for 2,006 unique human miRNAs. About 100 ng total RNA was labeled with Cy3 and hybridized to the Agilent Microarray and were scanned on an Agilent SureScan microarray scanner model G2600D. Data were extracted from the scanned image using Agilent Feature Extract software v. 11.5.1.1 (Agilent Technologies). Data were required to pass stringent quality control (QC) parameters established by Agilent that included tests for excessive background fluorescence, excessive variation among probe sequence replicates on the array, and measures of the total gene signal on the array to assess low signal. If samples failed to meet quality standards for any of these parameters, the sample was relabeled, hybridized to arrays, and scanned. If a sample failed QC assessment a second time, the sample was deemed to be of poor quality and was excluded from down-stream analysis.

Diet and lifestyle data

Data were collected by trained and certified interviewers using laptops. All interviews were audiotaped as previously described and reviewed for QC purposes.24 The referent period for the study was 2 years prior to diagnosis. As part of the study questionnaire, information was collected on regular use and current use of aspirin and NSAIDs and on physical activity during the referent period and for 10 and 20 years prior to diagnosis. Physical activity was obtained for the physical intensity of activity performed as well as the frequency and duration of activity. Body size information, including height (measured at the time of interview), weight (recalled for referent period), and waist and hip circumference measurements, were also collected. Dietary information was obtained for the referent period using an extensive diet history questionnaire adapted from the validated CARDIA diet history.25 Foods were converted to nutrients using the Nutrition Coding Center Nutrient Data System Version 19 (Nutrition Coordinating Center, University of Minnesota, Minneapolis, MN, USA) as well as being grouped into categories of similar foods. Foods units were standard servings per day, which was half cup of fruit, vegetable, or dairy product; meat servings were 2–3 oz of meat; grain products were half cup of rice-type grains or one slice of bread. Prudent and western dietary patterns were developed based on the principal component analysis.26 Our prudent dietary pattern was heavily loaded toward diets high in fruits, vegetables, whole grains, fish, and chicken, whereas the western dietary pattern was highly loaded toward red meat, processed meats, and refined grains and high-sugar-high-fat foods. Additional questions were asked about meat consumption, doneness, and preparation methods that were combined and used to create a mutagen index score.27

Statistical methods

Of the 2,006 unique human miRNAs assessed, 1,278 were expressed in colorectal carcinoma tissue. To minimize differences in miRNA expression that could be attributed to the array, amount of RNA, location on array, or other factors that could erroneously influence expression, total gene signal was normalized by multiplying each sample by a scaling factor28 (http://genespring-support.com/files/gs_12_6/GeneSpring-manual.pdf), which was the median of the 75th percentiles of all the samples divided by the individual 75th percentile of each sample. We limited our analysis to miRNAs that were expressed in at least 20% of the samples in the tissue(s) of interest. Data were assessed for colon and rectal cancer separately, and the number of miRNAs analyzed varied from 766 to 817 depending on tumor site and tissue type (ie, carcinoma or normal mucosa). Our sample consisted of 1,447 subjects with both miRNA expression data for carcinoma and paired normal mucosa as well as diet and lifestyle variables. We assessed long-term vigorous physical activity, body mass index (kilogram per square meter) during referent year, waist circumference, and hip circumference. Assessment of aspirin/NSAID use included recent use (ie, using NSAIDs during the referent period or not) and ever regular use. We assessed 28 dietary variables including energy intake, western dietary pattern, prudent dietary pattern, mutagen index, total fat, total trans-fatty acid, total carbohydrates, sucrose, animal protein, vegetable protein, vitamins B12, C, D, and E, calcium, folic acid, dietary fiber, carotenoids, β-carotene, lutein + zeaxanthin, lycopene, and servings per day of dairy, fruit, vegetables, meat, processed meat, whole grains, and refined grains. All variables were analyzed as continuous variables unless they were collected as categorical (ie, NSAIDs variables). To summarize risk associated with multiple exposures, we developed an OBS that consisted of 13 diet and lifestyle factors that were prooxidants (dietary iron and polyunsaturated fat and cigarette smoking) and antioxidants (vitamin C, vitamin E, selenium, β-carotene, lycopene, lutein + zeaxanthin, vitamin D, calcium, and folic acid and NSAID use).18 To create the OBS, these diet and lifestyle factors were assigned values of 2 for low levels of exposure for each prooxidants or high exposure to antioxidants (low risk), 1 for intermediate levels of exposure, and 0 for high levels of exposure to prooxidants and low exposure to antioxidants (high risk). The individual scores for the 13 variables were then combined to obtain the OBS. Higher summary score corresponded to greater oxidative balance. We examined lifestyle variables to determine if there was an association between each lifestyle variable and miRNA expression by fitting a linear model to the log2-transformed expression levels and adjusting for age at diagnosis, study center, and sex. We examined miRNA expression in both normal mucosa and the difference between miRNA expressions in carcinoma and in the normal colonic mucosa. p-values were generated using the bootstrap method by creating a distribution of 10,000 F statistics derived by resampling the residuals from the null hypothesis model of no association between the lifestyle variables and the miRNAs using the boot package in R. Associations were considered important if the false discovery rate (FDR) q-value was <0.11.29 We standardized the β coefficient presented in order to compare the results across the miRNA and lifestyle factors by subtracting the mean of the mRNA and dividing the result by the standard deviation of the mRNA before calculating the slope. If the lifestyle variable in the regression model was continuous, then we applied the same technique to it as well.

Results

The study population consisted of 892 cases of colon cancer and 555 cases of rectal cancer (Table 1). The mean age for colon cancer cases was 64.7 years and for rectal cancer cases was 61.8 years. The majority of study participants were males and most reported never having used aspirin/NSAIDs (subsequently referred to as NSAIDs) on a regular basis.
Table 1

Description of study population

Lifestyle factorColonRectal
Sexa
 Male485 (54.4)316 (56.9)
 Female407 (45.6)239 (43.1)
Centera
 Kaiser626 (70.2)340 (61.3)
 Utah266 (29.8)215 (38.7)
OBSa
 Low321 (36.0)191 (34.4)
 2187 (21.0)120 (21.6)
 3242 (27.1)160 (28.8)
 High142 (15.9)84 (15.1)
Ever used NSAIDs regularlya
 No531 (59.5)318 (57.3)
 Yes361 (40.5)237 (42.7)
Recent NSAID usea
 No583 (65.6)350 (63.6)
 Yes306 (34.4)200 (36.4)
Age at diagnosisb64.7 (9.5)61.8 (10.8)
Calories (Kcal)b2,479 (1,223)2,660 (1,261)
Total carbohydrates(gram per 1,000 Kcal)b127.9 (22.6)123.8 (21.8)
Sucrose (gram per 1,000 Kcal)b20.6 (8.48)21.8 (9.80)

Notes:

Values are given as N (%);

Values are given as mean (SD).

Abbreviations: NSAIDs, nonsteroidal anti-inflammatory drugs; OBS, oxidative balance score; SD, standard deviation.

There were few diet and lifestyle factors associated with miRNA expression in either normal colonic mucosa or with differential miRNA expression between carcinoma and normal mucosa when applying an FDR q-value of <0.1. Body mass index, waist and hip circumference, and physical activity showed no associations with miRNA expression with the FDR q-value at <0.1 as did most dietary factors analyzed. Only three dietary factors, carbohydrate intake, servings per day of whole grains, and sucrose intake, were associated with miRNA expression. For carbohydrate intake and sucrose intake, there were 250 and 198 miRNAs significantly differentially expressed between colon carcinoma and normal mucosa tissue by level of dietary intake. Of these miRNAs, 166 were significantly differentially expressed for both carbohydrate intake and sucrose intake (Table 2 shows the top 85 miRNAs based on q-value and Table S1 shows all miRNAs significantly differentially expressed for both carbohydrate and sucrose intake). Although the adjusted q-values indicated more significant associations with carbohydrate intake, the β coefficients for the two variables were very similar. There were 32 miRNAs uniquely associated with sucrose intake (Table 3). The top 53 miRNAs associated uniquely with carbohydrate intake (Table 3) all had a q-value of <0.05. Evaluation of miRNA expression in whole grains showed 99 miRNAs differentially expressed by level of intake in normal colonic mucosa with an FDR of <0.1 (Table 4).
Table 2

Colon cancer differential miRNA expression (top 85) associated with both sucrose and carbohydrate intake

SucroseTumorNormalSucroseCarbohydrate



miRNA expressionMeanMeanβp-valueq-valueβp-valueq-value
hsa_miR_10b_3p47.0653.71−0.08380.01280.0641−0.09110.00740.0350
hsa_miR_1224_5p910.911,009.30−0.08910.00930.0641−0.09880.00600.0350
hsa_miR_1225_5p2,775.373,033.07−0.09220.00840.0641−0.10300.00370.0350
hsa_miR_1227_5p966.191,082.86−0.09910.00330.0641−0.10710.00270.0350
hsa_miR_1307_3p11.0712.84−0.09010.01000.0641−0.10700.00280.0350
hsa_miR_135a_3p146.18161.98−0.07700.02700.0743−0.09250.00780.0350
hsa_miR_1471237.51257.92−0.08010.02040.0680−0.10970.00160.0350
hsa_miR_15871,337.631,396.92−0.10670.00220.0641−0.11080.00200.0350
hsa_miR_181b_5p23.2218.61−0.09170.00670.0641−0.09030.00790.0350
hsa_miR_188_5p406.17458.31−0.08100.01860.0651−0.10330.00360.0350
hsa_miR_1914_3p120.96130.99−0.08210.01730.0641−0.10310.00370.0350
hsa_miR_1915_3p2,946.523,444.83−0.08960.01010.0641−0.09460.00680.0350
hsa_miR_195_3p1.121.030.08380.01610.06410.09490.00610.0350
hsa_miR_197_5p3,010.833,334.22−0.11040.00100.0641−0.10870.00180.0350
hsa_miR_28615,575.326,458.02−0.09260.00730.0641−0.09540.00540.0350
hsa_miR_3124_5p1.672.220.11800.00090.06410.11030.00100.0350
hsa_miR_3137235.66244.41−0.07760.02300.0714−0.10620.00280.0350
hsa_miR_313878.4380.84−0.07300.03240.0826−0.10200.00450.0350
hsa_miR_3156_5p87.6493.95−0.07530.03130.0818−0.10240.00260.0350
hsa_miR_3158_5p29.9832.45−0.08230.01680.0641−0.10530.00230.0350
hsa_miR_3162_5p2,715.582,982.07−0.10110.00400.0641−0.11410.00160.0350
hsa_miR_3188218.59247.20−0.08750.01120.0641−0.09690.00560.0350
hsa_miR_3194_5p153.17167.90−0.06930.04550.0976−0.09650.00530.0350
hsa_miR_31961,228.771,388.20−0.07860.02240.0712−0.09330.00730.0350
hsa_miR_319729.5031.14−0.08010.02020.0678−0.10000.00420.0350
hsa_miR_345_5p58.9865.81−0.07530.02610.0728−0.10940.00090.0350
hsa_miR_3610109.25128.54−0.08700.01290.0641−0.10800.00310.0350
hsa_miR_362136.2238.31−0.07870.02320.0715−0.10100.00480.0350
hsa_miR_37044.9541.52−0.10750.00170.0641−0.13230.00040.0350
hsa_miR_378e2.052.150.08110.01970.06670.09410.00600.0350
hsa_miR_3940_5p754.26842.23−0.10240.00330.0641−0.10720.00180.0350
hsa_miR_4257332.86361.83−0.07650.02670.0740−0.09890.00600.0350
hsa_miR_4270482.93483.89−0.09250.00970.0641−0.09100.00770.0350
hsa_miR_4271277.51288.76−0.09760.00430.0641−0.10200.00450.0350
hsa_miR_42961.911.370.08600.01370.06410.09640.00550.0350
hsa_miR_44281,303.071,361.56−0.07300.03540.0873−0.11050.00250.0350
hsa_miR_4442288.05293.52−0.08220.01760.0641−0.09590.00650.0350
hsa_miR_4478292.78326.72−0.09290.00700.0641−0.11510.00120.0350
hsa_miR_448179.7385.64−0.10770.00200.0641−0.11870.00080.0350
hsa_miR_4486178.26186.85−0.09620.00610.0641−0.09260.00800.0350
hsa_miR_448792.03100.77−0.07550.03010.0797−0.09320.00670.0350
hsa_miR_45071,821.932,056.47−0.09260.00480.0641−0.09330.00840.0350
hsa_miR_4515305.06344.83−0.07460.02890.0780−0.09260.00830.0350
hsa_miR_451615,260.0317,545.65−0.08500.01360.0641−0.10050.00390.0350
hsa_miR_4651216.67229.48−0.09850.00480.0641−0.09700.00530.0350
hsa_miR_4695_5p356.79385.84−0.09130.00790.0641−0.10460.00240.0350
hsa_miR_4707_5p95.2998.20−0.08800.01020.0641−0.09470.00710.0350
hsa_miR_47211,590.351,739.00−0.09510.00580.0641−0.09930.00390.0350
hsa_miR_4725_3p15.1316.09−0.09520.00700.0641−0.10450.00340.0350
hsa_miR_4734189.46206.40−0.08720.00970.0641−0.09380.00730.0350
hsa_miR_4758_5p139.37134.74−0.08710.01120.0641−0.09740.00630.0350
hsa_miR_4763_3p1,338.051,402.42−0.11380.00130.0641−0.10650.00230.0350
hsa_miR_4776_5p36.7537.60−0.06790.04760.0993−0.09290.00730.0350
hsa_miR_4788327.29342.72−0.09620.00510.0641−0.09880.00560.0350
hsa_miR_5006_5p653.96737.60−0.07290.03300.0836−0.10110.00440.0350
hsa_miR_5196_5p76.1666.21−0.10400.00320.0641−0.09990.00390.0350
hsa_miR_520b16.2120.36−0.08250.01770.0641−0.09900.00400.0350
hsa_miR_525_5p1.952.410.08330.01490.06410.09590.00480.0350
hsa_miR_548q71.5291.25−0.09520.00660.0641−0.10370.00210.0350
hsa_miR_55775.7375.51−0.11290.00160.0641−0.10680.00260.0350
hsa_miR_572441.84510.90−0.08980.00920.0641−0.09400.00730.0350
hsa_miR_60682,305.932,676.49−0.09630.00550.0641−0.10010.00460.0350
hsa_miR_61271,378.021,494.38−0.08940.00970.0641−0.10360.00350.0350
hsa_miR_62345.7948.87−0.08150.02200.0710−0.10150.00350.0350
hsa_miR_6383,686.154,168.08−0.10140.00310.0641−0.10640.00170.0350
hsa_miR_642a_3p3,880.944,192.71−0.08020.01910.0657−0.10020.00390.0350
hsa_miR_642b_3p659.58707.40−0.08960.00960.0641−0.10170.00330.0350
hsa_miR_6511b_5p70.1367.42−0.09660.00510.0641−0.10160.00310.0350
hsa_miR_6722_3p98.64103.55−0.08670.01280.0641−0.09120.00840.0350
hsa_miR_6724_5p842.08891.10−0.09580.00510.0641−0.09950.00440.0350
hsa_miR_718103.79115.55−0.08970.00910.0641−0.09600.00600.0350
hsa_miR_877_5p39.2639.14−0.08390.01560.0641−0.09730.00510.0350
hsa_miR_937_5p658.60673.28−0.11390.00110.0641−0.10610.00170.0350
hsa_miR_124934.3634.94−0.09150.01000.0641−0.09120.00940.0357
hsa_miR_4632_5p212.75224.93−0.07750.02540.0728−0.09120.00950.0357
hsa_miR_4787_5p1,109.551,394.63−0.08150.01660.0641−0.09040.00920.0357
hsa_miR_57871,928.962,138.52−0.07090.04010.0919−0.09260.00940.0357
hsa_miR_60142.3846.88−0.08030.01840.0651−0.09030.00910.0357
hsa_miR_1233_1_5p178.73198.48−0.07270.03720.0888−0.09020.01050.0367
hsa_miR_36562,793.882,941.93−0.09910.00420.0641−0.08710.01060.0367
hsa_miR_371b_5p1,139.601,438.06−0.08710.01070.0641−0.09090.01020.0367
hsa_miR_44973,447.193,736.33−0.08240.01790.0643−0.08950.01000.0367
hsa_miR_4633_5p7.367.840.11230.00110.06410.08970.01010.0367
hsa_miR_4687_3p1,902.372,193.37−0.09370.00630.0641−0.09120.01050.0367
hsa_miR_5001_5p968.461,138.75−0.09550.00570.0641−0.08710.01030.0367

Abbreviation: miRNA, micro RNA.

Table 3

Differential miRNA expression between colon carcinoma and normal colonic mucosa uniquely associated with either sucrose or carbohydrate intake

miRNATumorNormalβp-valueq-value

MeanMean
Sucrose
hsa_miR_1229_3p15.0017.87−0.06800.04540.0976
hsa_miR_1247_3p27.6226.20−0.07380.03000.0797
hsa_miR_1273g_5p9.2110.050.09430.00640.0641
hsa_miR_155_5p44.5146.29−0.06990.04220.0947
hsa_miR_181a_5p34.2124.91−0.07780.02450.0726
hsa_miR_200a_5p6.095.120.07950.02380.0723
hsa_miR_21023.6614.90−0.08150.01650.0641
hsa_miR_2277_3p3.865.010.08570.01250.0641
hsa_miR_302c_5p2.702.400.06880.04730.0993
hsa_miR_31701.862.440.08880.01080.0641
hsa_miR_320b82.2580.23−0.07650.02580.0728
hsa_miR_3614_5p5.136.550.07150.03810.0894
hsa_miR_3648331.00274.75−0.07670.02460.0726
hsa_miR_365b_5p13.3414.460.07040.04240.0947
hsa_miR_373_5p17.5818.43−0.07180.03480.0871
hsa_miR_39762.151.110.08170.01770.0641
hsa_miR_4419a69.6366.94−0.07280.03740.0888
hsa_miR_44489.309.040.08280.01740.0641
hsa_miR_448464.1071.60−0.07540.02610.0728
hsa_miR_4488109.70113.97−0.08460.01100.0641
hsa_miR_4532316.22368.80−0.07760.02560.0728
hsa_miR_4700_5p1.340.960.06930.04590.0977
hsa_miR_4715_5p4.405.060.08020.02080.0682
hsa_miR_4717_3p3.673.390.09120.00820.0641
hsa_miR_4733_5p67.0769.46−0.07530.02870.0780
hsa_miR_4793_3p5.896.420.08150.01950.0666
hsa_miR_5003_3p19.7620.35−0.07040.04080.0921
hsa_miR_60244.2247.11−0.07070.03780.0892
hsa_miR_606918.9519.15−0.06740.04670.0989
hsa_miR_6075209.46246.60−0.07130.03550.0873
hsa_miR_61343.053.180.07520.02930.0786
hsa_miR_659_5p2.283.280.08620.01340.0641
Carbohydrate
hsa_miR_12915.623.310.09660.00530.0350
hsa_miR_129_5p9.269.98−0.09730.00480.0350
hsa_miR_1305112.80129.42−0.09200.00810.0350
hsa_miR_30c_1_3p10.1711.17−0.09110.00820.0350
hsa_miR_3198165.30171.97−0.09270.00760.0350
hsa_miR_394543.3447.78−0.09380.00630.0350
hsa_miR_445920,580.4524,456.49−0.09510.00750.0350
hsa_miR_447034.3840.65−0.11080.00160.0350
hsa_miR_4499376.55430.33−0.10300.00310.0350
hsa_miR_4656182.68185.98−0.09090.00840.0350
hsa_miR_575561.79607.76−0.10920.00140.0350
hsa_miR_6131129.70148.03−0.09250.00710.0350
hsa_miR_1236_5p186.86188.18−0.09080.00920.0357
hsa_miR_221_3p11.212.530.08960.00930.0357
hsa_miR_3652150.82160.30−0.09090.00930.0357
hsa_miR_769_3p21.6024.95−0.09000.00910.0357
hsa_miR_4740_5p31.4433.08−0.08980.01030.0367
hsa_miR_128850.6456.68−0.08960.01110.0374
hsa_miR_47306.405.810.08820.01190.0386
hsa_miR_431460.8963.69−0.08660.01350.0388
hsa_miR_46822.041.820.08730.01330.0388
hsa_miR_196b_5p15.416.060.08330.01560.0410
hsa_miR_4462328.28365.23−0.08290.01570.0410
hsa_miR_4716_3p103.29116.31−0.08480.01530.0410
hsa_miR_39723.952.610.08410.01700.0420
hsa_miR_4739913.211,025.15−0.08580.01710.0420
hsa_miR_3925_5p42.6146.66−0.08250.01840.0435
hsa_miR_4665_5p59.3761.84−0.08360.01850.0435
hsa_miR_1207_5p1,881.802,044.90−0.08250.01910.0438
hsa_miR_378a_3p112.01146.82−0.08060.01960.0438
hsa_miR_4701_3p78.1075.38−0.07980.02010.0438
hsa_miR_4793_5p225.94220.22−0.07870.01920.0438
hsa_miR_497_5p1.215.890.08000.01960.0438
hsa_miR_57002.392.490.08060.02010.0438
hsa_miR_5581_5p106.65121.34−0.08160.02060.0441
hsa_miR_449656.0860.47−0.07930.02130.0448
hsa_miR_3130_5p11.4811.830.08150.02190.0455
hsa_miR_47371.100.940.07970.02200.0455
hsa_miR_519454.5760.38−0.07990.02270.0466
hsa_miR_612978.0786.34−0.07880.02310.0469
hsa_miR_6717_5p118.74134.59−0.07980.02360.0474
hsa_miR_429421.4322.45−0.07840.02390.0475
hsa_miR_4713_3p229.14258.22−0.07850.02380.0475
hsa_miR_1307_5p51.0867.75−0.07720.02410.0476
hsa_miR_318518.3917.80−0.07760.02530.0478
hsa_miR_430416.8018.22−0.07840.02470.0478
hsa_miR_467379.9394.86−0.07830.02520.0478
hsa_miR_49415,260.3215,700.29−0.07710.02470.0478
hsa_miR_508847.4155.74−0.07950.02500.0478
hsa_miR_6515_3p8.548.710.07930.02510.0478
hsa_miR_518c_5p1.842.580.07910.02560.0479
hsa_miR_4646_5p110.21112.97−0.07800.02630.0483
hsa_miR_378i56.6273.03−0.07570.02760.0490
hsa_miR_88753.7863.17−0.07650.02870.0500
hsa_miR_3679_5p672.88742.50−0.07600.02910.0504
hsa_miR_345_3p62.1460.39−0.07490.02950.0509
hsa_miR_312556.4060.80−0.07470.03050.0523
hsa_miR_191_3p8.849.030.07490.03270.0542
hsa_miR_450848.7557.69−0.07520.03240.0542
hsa_miR_62289.8088.61−0.07470.03230.0542
hsa_miR_4690_5p164.97209.18−0.07360.03420.0560
hsa_miR_4419b25.3926.54−0.07350.03540.0568
hsa_miR_4534224.12255.34−0.07350.03550.0568
hsa_miR_4659b_3p4.155.060.07500.03670.0583
hsa_miR_520e11.0114.21−0.07360.03710.0585
hsa_miR_3150b_5p14.0619.14−0.07310.03740.0587
hsa_miR_590_5p1.932.430.07430.03800.0594
hsa_miR_4538140.02191.59−0.07410.03930.0609
hsa_miR_13033.894.350.07080.03950.0610
hsa_miR_513c_5p91.98100.86−0.07260.03980.0612
hsa_miR_339_3p3.813.950.07250.04010.0613
hsa_miR_14704.485.860.07150.04090.0620
hsa_miR_550b_2_5p37.5139.99−0.07120.04090.0620
hsa_miR_3195892.681,067.06−0.06970.04240.0635
hsa_miR_120829.7332.93−0.07040.04300.0639
hsa_miR_2276101.7396.46−0.07150.04290.0639
hsa_miR_3200_5p25.2928.98−0.07020.04410.0648
hsa_miR_471043.1240.75−0.06930.04460.0651
hsa_miR_500a_5p20.6823.85−0.06940.04540.0658
hsa_miR_453567.3772.01−0.06900.04780.0687
hsa_miR_630345.63402.87−0.06780.04860.0695
hsa_miR_425345.5848.10−0.06850.04940.0700
hsa_miR_452_5p8.8110.340.06830.04960.0700
hsa_miR_5101.100.970.06740.04980.0700

Abbreviation: miRNA, micro RNA.

Table 4

miRNA expression in normal colonic mucosa associated with whole grain intake

miRNATumorNormalβp-valueq-value

MeanMean
hsa_let_7b_5p304.74250.810.08440.00800.0722
hsa_miR_103a_3p58.1240.900.07710.01660.0919
hsa_miR_10737.6726.200.07460.02220.0988
hsa_miR_10a_3p3.984.44−0.08600.00960.0753
hsa_miR_1234_3p40.5647.470.07900.01620.0919
hsa_miR_1237_5p6.527.50−0.09050.00910.0742
hsa_miR_125419.2421.91−0.11830.00120.0536
hsa_miR_125a_5p11.669.000.07130.02130.0981
hsa_miR_1260a317.07341.640.09730.00200.0536
hsa_miR_1260b125.8398.870.08580.00890.0742
hsa_miR_12613.204.23−0.10510.00210.0536
hsa_miR_1273d27.6128.000.08470.01080.0790
hsa_miR_1273f261.20268.960.07520.01960.0943
hsa_miR_1273g_3p2,181.392,647.150.10320.00270.0536
hsa_miR_12915.623.31−0.07910.01600.0919
hsa_miR_1295a9.3010.75−0.11460.00180.0536
hsa_miR_13033.894.35−0.09510.00310.0536
hsa_miR_13236.547.09−0.07550.01940.0943
hsa_miR_141_3p38.2728.270.08690.00780.0722
hsa_miR_145_5p116.51184.460.07600.01430.0903
hsa_miR_192_5p81.69123.550.08950.00790.0722
hsa_miR_194_3p5.566.870.12020.00050.0536
hsa_miR_194_5p79.56107.890.09960.00310.0536
hsa_miR_1972113.21113.890.08730.00900.0742
hsa_miR_197_3p13.3914.160.07990.01700.0919
hsa_miR_200b_3p141.48120.080.08190.01420.0903
hsa_miR_200c_3p128.38103.590.09880.00380.0581
hsa_miR_21538.9764.590.07990.01550.0919
hsa_miR_23b_3p59.3657.720.07540.02090.0973
hsa_miR_24_3p89.3252.200.08000.01360.0903
hsa_miR_28_5p1.361.910.07410.01450.0903
hsa_miR_30b_3p5.464.85−0.10610.00230.0536
hsa_miR_30d_5p30.0927.110.08510.00630.0722
hsa_miR_31639.399.74−0.11310.00100.0536
hsa_miR_3173_3p8.768.51−0.10310.00260.0536
hsa_miR_320d42.9139.970.07720.01740.0919
hsa_miR_320e37.8736.130.07650.02090.0973
hsa_miR_339_3p3.813.95−0.08580.00870.0742
hsa_miR_3605_5p14.3614.33−0.09850.00630.0722
hsa_miR_3614_5p5.136.55−0.09180.00690.0722
hsa_miR_3617_5p4.715.20−0.07770.01800.0919
hsa_miR_365150.7621.670.08810.00940.0752
hsa_miR_365912.3712.99−0.09190.00750.0722
hsa_miR_366618.8520.61−0.10400.00310.0536
hsa_miR_3680_3p7.446.56−0.08790.00890.0742
hsa_miR_37136.296.87−0.07870.01720.0919
hsa_miR_37515.7342.480.10020.00290.0536
hsa_miR_378a_3p112.01146.820.08300.01350.0903
hsa_miR_378c6.827.25−0.10000.00330.0536
hsa_miR_378i56.6273.030.07460.02070.0973
hsa_miR_392634.6933.620.07770.02190.0987
hsa_miR_42608.287.84−0.13400.00110.0536
hsa_miR_426117.4216.920.07620.02310.0988
hsa_miR_42841,257.361,195.390.08950.00610.0722
hsa_miR_42861,057.761,096.920.10910.00090.0536
hsa_miR_43165.737.66−0.09210.00540.0717
hsa_miR_44185.375.37−0.09190.00570.0717
hsa_miR_44259.7310.92−0.12170.00060.0536
hsa_miR_4436a4.755.23−0.08060.01450.0903
hsa_miR_4436b_3p7.667.03−0.07940.01710.0919
hsa_miR_4436b_5p19.1623.140.07530.02260.0988
hsa_miR_44449.638.77−0.09690.00430.0626
hsa_miR_4446_3p12.2815.26−0.08300.01440.0903
hsa_miR_445441,752.1743,243.720.10860.00090.0536
hsa_miR_445572.0370.070.07830.01710.0919
hsa_miR_44851,034.221,284.960.09100.00750.0722
hsa_miR_448911.8512.56−0.12490.00060.0536
hsa_miR_450217.4319.16−0.08670.01100.0790
hsa_miR_45106.036.45−0.08320.01130.0798
hsa_miR_45198.598.71−0.10520.00200.0536
hsa_miR_45263.594.36−0.09120.00510.0708
hsa_miR_452_5p8.8110.34−0.09010.00780.0722
hsa_miR_46605.175.04−0.08300.01180.0819
hsa_miR_4684_3p2.883.29−0.07510.02310.0988
hsa_miR_4691_5p11.5612.49−0.10100.00320.0536
hsa_miR_47485.836.27−0.07650.01790.0919
hsa_miR_4750_5p8.696.66−0.07900.01830.0923
hsa_miR_4755_3p6.867.81−0.10980.00110.0536
hsa_miR_47738.169.29−0.07710.02170.0987
hsa_miR_486_5p16.6421.500.07920.01860.0927
hsa_miR_500a_3p2.932.96−0.07970.01620.0919
hsa_miR_50933.643.86−0.07500.02270.0988
hsa_miR_509652.5051.070.10180.00280.0536
hsa_miR_509_5p7.118.08−0.14000.00020.0536
hsa_miR_51003,645.514,386.600.10740.00120.0536
hsa_miR_516a_5p27.0029.72−0.12580.00110.0536
hsa_miR_518a_5p4.605.94−0.07800.01900.0936
hsa_miR_5195_5p8.308.56−0.08420.01100.0790
hsa_miR_550a_5p7.648.54−0.08660.01090.0790
hsa_miR_55727.658.28−0.11170.00110.0536
hsa_miR_56851.932.93−0.07620.01720.0919
hsa_miR_608330.2037.230.08390.01020.0786
hsa_miR_659_3p11.2211.27−0.09690.00570.0717
hsa_miR_6716_5p5.415.25−0.10450.00150.0536
hsa_miR_6718_5p7.767.68−0.09240.00720.0722
hsa_miR_708_5p9.3310.69−0.09540.00670.0722
hsa_miR_71120.3718.07−0.08060.01770.0919
hsa_miR_770_5p5.586.29−0.09100.00790.0722
hsa_miR_92a_3p94.0635.740.07720.01710.0919

Abbreviation: miRNA, micro RNA.

Associations with miRNAs were similar for all indicators of NSAIDs use and for both normal colonic mucosa and differential miRNA expression between carcinoma and normal colonic mucosa. Table 5 shows the top 85 of the 135 miRNAs differentially expressed in normal colonic mucosa by recent NSAID use versus no recent NSAID use. OBS was only associated with miRNA expression for rectal tissue (Table 6 for top dysregulated miRNAs); 137 miRNAs were differentially expressed between rectal carcinoma and paired normal rectal mucosa based on OBS level.
Table 5

miRNA expression in normal colonic mucosa associated with recent NSAIDs use

miRNANo recent use
Recent use
βp-valueq-value
TumorNormalTumorNormal


MeanMeanMeanMean
hsa_miR_1185_1_3p396.08442.93414.35413.20−0.160.01140.0845
hsa_miR_1185_2_3p136.55150.38147.62139.56−0.150.01820.0845
hsa_miR_1225_3p17.0119.0316.8417.73−0.170.01120.0845
hsa_miR_1227_5p976.851,110.48949.541,030.83−0.160.01210.0845
hsa_miR_1228_3p34.1235.6233.5533.29−0.160.01630.0845
hsa_miR_1229_5p659.51722.70692.39665.34−0.150.01790.0845
hsa_miR_1233_1_5p180.18202.49176.16190.91−0.180.00810.0845
hsa_miR_1268b1,303.231,289.541,295.271,189.93−0.170.00770.0845
hsa_miR_129_5p9.3210.239.189.50−0.180.00650.0845
hsa_miR_150_3p256.88283.63266.29266.67−0.160.01400.0845
hsa_miR_15871,352.231,428.351,312.101,337.13−0.160.01400.0845
hsa_miR_195_3p1.050.971.231.120.170.01060.0845
hsa_miR_196a_5p6.013.566.233.860.170.01150.0845
hsa_miR_197_5p3,005.553,430.323,033.623,151.71−0.170.00970.0845
hsa_miR_2392228.38235.42229.30214.90−0.160.01700.0845
hsa_miR_28615,626.176,628.805,494.236,135.84−0.170.00960.0845
hsa_miR_28_3p1.361.471.361.630.160.01780.0845
hsa_miR_3141217.64209.30230.06194.84−0.180.00890.0845
hsa_miR_314736.5035.5437.0333.73−0.170.01260.0845
hsa_miR_318518.4618.1218.2817.20−0.160.01690.0845
hsa_miR_3188217.86253.49220.57235.46−0.160.01670.0845
hsa_miR_319729.3731.6629.8230.16−0.170.01550.0845
hsa_miR_3591_3p1.341.291.401.400.180.00800.0845
hsa_miR_3648326.34281.62339.96261.57−0.180.00800.0845
hsa_miR_36562,807.673,026.732,776.462,782.58−0.160.01330.0845
hsa_miR_36653,199.263,688.473,103.183,381.05−0.180.00530.0845
hsa_miR_3679_5p673.97761.63671.02706.29−0.170.01010.0845
hsa_miR_371b_5p1,170.131,490.031,085.201,339.67−0.220.00100.0845
hsa_miR_391196.5189.0599.1284.30−0.180.00750.0845
hsa_miR_391797.6099.9197.4094.78−0.170.00870.0845
hsa_miR_39230.581.320.801.650.180.00720.0845
hsa_miR_3940_5p760.89864.96743.30799.19−0.170.01060.0845
hsa_miR_423_5p53.1658.4854.2254.85−0.220.00120.0845
hsa_miR_4257337.07372.94325.74340.76−0.190.00560.0845
hsa_miR_4271276.36295.46280.32276.17−0.160.01400.0845
hsa_miR_42813,828.074,117.963,928.633,793.36−0.160.01720.0845
hsa_miR_4298183.19168.33191.21157.16−0.190.00520.0845
hsa_miR_430624.8323.1225.5422.04−0.180.01030.0845
hsa_miR_4322108.18102.21108.1095.91−0.180.00880.0845
hsa_miR_4327248.12251.53256.93233.14−0.180.00610.0845
hsa_miR_4417211.11191.02221.11179.36−0.150.01820.0845
hsa_miR_4419a68.3968.5272.0163.97−0.170.00910.0845
hsa_miR_4433_3p294.45316.29302.33289.43−0.160.01030.0845
hsa_miR_4433_5p19.6820.3519.0918.90−0.170.01620.0845
hsa_miR_444714.1115.7914.6914.63−0.180.00570.0845
hsa_miR_44661,784.941,996.871,780.901,849.17−0.160.01820.0845
hsa_miR_44791.922.272.192.540.170.01670.0845
hsa_miR_4486180.46191.15174.64178.73−0.180.00730.0845
hsa_miR_4488111.67117.23106.27107.89−0.170.00950.0845
hsa_miR_45053,082.723,378.632,949.313,173.69−0.170.01430.0845
hsa_miR_45071,847.972,105.801,776.121,963.15−0.170.01180.0845
hsa_miR_4532319.46378.39310.60350.83−0.160.01670.0845
hsa_miR_4669349.43374.17355.47348.03−0.170.01550.0845
hsa_miR_4690_5p166.05213.24163.22201.57−0.160.01650.0845
hsa_miR_4695_5p359.45392.74352.89372.91−0.170.01120.0845
hsa_miR_4700_3p1.291.532.242.850.25<0.00010.0845
hsa_miR_4734192.44211.44184.33196.97−0.170.01200.0845
hsa_miR_4763_3p1,335.391,438.921,346.771,333.66−0.160.01650.0845
hsa_miR_4787_5p1,138.111,440.101,058.081,308.81−0.210.00180.0845
hsa_miR_4800_5p186.25167.82201.33158.36−0.170.01310.0845
hsa_miR_49825.4128.6125.9726.90−0.170.01310.0845
hsa_miR_5001_5p990.751,177.94928.901,065.39−0.220.00130.0845
hsa_miR_514b_5p32.5132.2433.7530.55−0.170.01020.0845
hsa_miR_518933.4434.6433.1833.00−0.160.01440.0845
hsa_miR_5196_5p75.4767.4677.7463.88−0.170.01070.0845
hsa_miR_572448.42524.02430.84486.13−0.160.01760.0845
hsa_miR_590_5p1.892.251.922.740.200.00430.0845
hsa_miR_60682,337.202,750.482,254.492,536.41−0.180.00640.0845
hsa_miR_60752,14.34254.50200.64231.62−0.230.00070.0845
hsa_miR_6086346.89377.05359.93345.16−0.190.00610.0845
hsa_miR_60883,169.093,495.653,177.393,219.68−0.170.01050.0845
hsa_miR_608928,714.2633,589.7928,275.3831,010.21−0.160.01570.0845
hsa_miR_61259,092.9911,058.098,810.3310,118.16−0.200.00240.0845
hsa_miR_6126603.41713.44599.82671.34−0.160.01700.0845
hsa_miR_61271,375.551,531.091,385.681,425.00−0.180.00620.0845
hsa_miR_6165359.86332.79380.59311.21−0.170.01310.0845
hsa_miR_62345.9949.9945.5046.77−0.180.00720.0845
hsa_miR_6511a_5p47.5944.9046.8242.60−0.160.01710.0845
hsa_miR_6701.221.531.761.770.160.01750.0845
hsa_miR_671_5p259.87299.18266.28278.64−0.160.01500.0845
hsa_miR_6724_5p843.41914.95839.90845.93−0.180.00830.0845
hsa_miR_76542.1241.4543.6839.09−0.180.00600.0845
hsa_miR_874204.36226.29202.36212.98−0.190.00430.0845
hsa_miR_937_5p660.48689.07657.22643.64−0.160.01160.0845
hsa_miR_939_5p642.45703.34628.40648.33−0.180.00460.0845
hsa_miR_320a99.91102.52101.4397.48−0.160.01890.0867
hsa_miR_118363.5365.2863.1162.42−0.160.02010.0872
hsa_miR_1207_5p1,878.632,100.911,890.051,940.24−0.150.02090.0872
hsa_miR_1226_5p52.3056.0853.7352.71−0.150.02100.0872
hsa_miR_1915_3p2,957.003,531.482,930.603,282.81−0.150.02100.0872
hsa_miR_362136.3539.0236.0936.99−0.160.02100.0872
hsa_miR_431460.7064.7761.4261.71−0.150.01980.0872
hsa_miR_4707_5p95.66100.5194.8493.87−0.150.01990.0872
hsa_miR_606918.9219.5819.0118.32−0.160.02020.0872
hsa_miR_6511b_5p70.4468.6069.7865.25−0.150.02020.0872
hsa_miR_1181218.07244.37226.56231.00−0.160.02210.0888
hsa_miR_1234_5p4,635.895,342.624,700.324,968.38−0.150.02320.0888
hsa_miR_31701.812.401.942.510.160.02420.0888
hsa_miR_365a_5p25.4226.0625.1924.84−0.150.02390.0888
hsa_miR_43150.072.100.252.420.160.02430.0888
hsa_miR_4442283.26299.26297.28282.82−0.150.02200.0888
hsa_miR_4672827.58883.29794.89831.14−0.150.02380.0888
hsa_miR_470617.8917.9517.8317.30−0.150.02290.0888
hsa_miR_4745_5p260.36297.48264.24279.82−0.150.02410.0888
hsa_miR_476726.0128.9926.5227.00−0.150.02210.0888
hsa_miR_6076249.40277.34250.34261.52−0.160.02240.0888
hsa_miR_663a409.92278.30433.93261.51−0.150.02400.0888
hsa_miR_6722_3p98.16106.1699.8198.69−0.150.02280.0888
hsa_miR_120829.6833.3929.8732.06−0.150.02500.0897
hsa_miR_6383,709.774,267.163,653.323,982.11−0.150.02500.0897

Abbreviations: miRNA, micro RNA; NSAIDs, nonsteroidal anti-inflammatory drugs.

Table 6

Rectal cancer differential miRNA expression between carcinoma and normal rectal mucosa associated with OBS

miRNALow
Q2
Q3
High
βp-valueq-value
TumorNormalTumorNormalTumorNormalTumorNormal

MeanMeanMeanMeanMeanMeanMeanMean
hsa_miR_106b_5p12.713.4311.093.0013.243.1313.873.240.100.0150.0748
hsa_miR_118357.9356.9055.8259.1855.2957.2455.2658.99−0.090.01240.0748
hsa_miR_12021,148.161,137.831,094.671,255.861,059.691,180.331,101.841,276.40−0.110.00490.0748
hsa_miR_1207_5p1,539.781,681.811,473.821,870.361,399.161,714.491,455.641,792.49−0.090.02130.0748
hsa_miR_1234_5p3,735.984,230.543,564.894,536.043,362.814,236.963,549.804,499.46−0.090.02030.0748
hsa_miR_126_3p13.8213.4614.1913.4315.9713.1817.3813.390.110.0040.0748
hsa_miR_1275586.07640.38561.24722.57526.32673.33539.49711.07−0.100.00840.0748
hsa_miR_134216.89238.07209.35259.08200.11240.91206.40251.41−0.090.02250.0748
hsa_miR_135a_3p135.39147.31126.90149.81124.85150.89125.52153.09−0.100.01250.0748
hsa_miR_138_2_3p5.246.195.635.525.715.826.185.950.110.00530.0748
hsa_miR_1471165.81183.08159.25195.46150.04182.99161.60219.81−0.100.00860.0748
hsa_miR_200a_5p6.044.906.454.316.384.456.814.380.110.00560.0748
hsa_miR_21543.0962.3838.5755.6144.9258.6746.4055.970.100.00990.0748
hsa_miR_227693.3284.5388.9486.7688.2685.5390.5189.73−0.090.01560.0748
hsa_miR_3135b430.17460.54417.24483.00408.83467.76404.70472.46−0.090.02120.0748
hsa_miR_313862.9466.4861.3569.5758.3966.7561.5072.66−0.100.01060.0748
hsa_miR_3141193.39169.59183.86180.15177.63172.04185.06178.89−0.090.01960.0748
hsa_miR_3150b_3p1.771.722.501.582.381.492.631.090.120.00270.0748
hsa_miR_3195759.99899.09722.37914.86681.46900.11708.87942.07−0.100.00880.0748
hsa_miR_320c151.24155.10139.99183.66134.47173.06142.97203.22−0.120.00260.0748
hsa_miR_345_3p51.0647.4848.7451.4246.2347.2749.6351.55−0.090.01750.0748
hsa_miR_3622b_3p2.071.151.600.892.520.711.920.460.110.00570.0748
hsa_miR_36603.653.853.923.643.883.453.903.420.100.01110.0748
hsa_miR_3663_3p127.73136.18122.73144.56118.88142.37120.45149.26−0.110.00380.0748
hsa_miR_3667_5p20.3820.8119.6323.3418.5922.9119.5825.88−0.120.00230.0748
hsa_miR_3676_5p3,259.893,130.992,810.342,948.812,963.053,084.492,760.102,921.68−0.090.0240.0748
hsa_miR_394537.9542.5937.4845.9335.9644.6137.2248.01−0.100.01170.0748
hsa_miR_39608,167.428,562.897,843.769,715.457,369.858,884.257,907.719,999.93−0.090.01850.0748
hsa_miR_4270394.51389.95378.71417.22361.86397.35377.73425.26−0.110.00570.0748
hsa_miR_43171.801.052.070.762.210.622.000.840.100.0160.0748
hsa_miR_442510.3211.7010.9211.7010.7711.8211.0611.430.090.01830.0748
hsa_miR_442923.1822.0021.5623.2020.2822.0522.2323.42−0.100.00990.0748
hsa_miR_445918,407.6721,996.8517,732.0823,874.4516,907.9723,689.1317,443.9124,811.06−0.100.01150.0748
hsa_miR_447661.7564.7259.3667.1357.5466.4360.0569.97−0.100.01020.0748
hsa_miR_448460.8763.1856.1664.1055.7963.1157.1766.04−0.090.02350.0748
hsa_miR_450845.2754.1842.9054.9840.9353.0442.3355.39−0.090.02350.0748
hsa_miR_451612,859.3914,765.5712,208.1716,233.8411,758.2115,345.8812,308.1416,542.65−0.110.00440.0748
hsa_miR_4534186.77207.00179.24219.34169.13209.22182.00231.13−0.090.02130.0748
hsa_miR_4634261.48284.84251.85313.20239.29300.46247.34336.48−0.120.00290.0748
hsa_miR_4655_5p28.9828.1327.7930.2826.7328.3628.7430.61−0.090.02210.0748
hsa_miR_4689109.63101.83104.67110.46100.56103.75106.31112.06−0.100.01070.0748
hsa_miR_4709_3p1.121.281.571.011.401.101.501.050.090.02420.0748
hsa_miR_4739756.23852.13735.58934.44703.38876.68725.94916.12−0.090.0240.0748
hsa_miR_476725.3627.2424.3327.6723.6627.1523.1427.98−0.090.01970.0748
hsa_miR_4768_3p2.873.643.253.373.433.313.473.560.100.0140.0748
hsa_miR_4783_3p11.6913.1411.5613.9310.8713.2711.4414.63−0.090.02460.0748
hsa_miR_4787_3p87.24100.6384.74101.8777.1096.9881.83105.01−0.100.01580.0748
hsa_miR_479221.9322.9921.3822.5620.2522.6121.2723.81−0.090.01930.0748
hsa_miR_4800_5p189.78151.55177.22156.88177.34154.11177.96158.70−0.100.01250.0748
hsa_miR_483_5p106.8089.0899.1494.3498.4491.77102.2296.52−0.090.02260.0748
hsa_miR_512_3p9.9911.509.5910.689.6710.8910.1510.600.100.00790.0748
hsa_miR_518c_5p1.362.041.731.871.781.552.101.990.090.01770.0748
hsa_miR_5195_3p138.45142.76131.18149.95125.68143.20131.49150.95−0.090.01780.0748
hsa_miR_525_5p1.381.411.941.801.651.362.361.490.100.01020.0748
hsa_miR_5580_3p10.6111.2810.8010.8410.7911.0810.8410.850.110.00430.0748
hsa_miR_5585_3p315.49306.63310.14309.20305.59305.96294.30311.32−0.090.02210.0748
hsa_miR_5703207.72265.79207.86312.71185.76305.53200.05363.43−0.090.02430.0748
hsa_miR_57871,616.141,778.111,552.861,982.271,448.391,915.681,489.322,116.47−0.120.00180.0748
hsa_miR_60137.1039.1334.7041.0934.1840.1235.6441.07−0.090.02320.0748
hsa_miR_6085580.90584.83559.94631.04546.52603.35563.01638.08−0.100.00880.0748
hsa_miR_608713,089.8514,902.6312,300.3115,684.3511,770.3215,080.6912,590.5215,866.09−0.090.01880.0748
hsa_miR_60882,478.372,649.042,371.032,878.272,188.642,626.392,373.452,823.12−0.090.02440.0748
hsa_miR_60904,618.185,049.314,401.445,582.734,096.365,193.184,462.145,805.83−0.110.00460.0748
hsa_miR_6124448.21420.35424.87454.58406.85435.30438.91474.68−0.100.01380.0748
hsa_miR_630291.06381.14289.74458.60261.19438.12275.15510.63−0.090.01750.0748
hsa_miR_642a_3p3,285.093,486.193,239.543,762.133,040.613,625.403,190.243,892.74−0.090.0210.0748
hsa_miR_6500_5p15.4617.2814.6116.8914.2817.3414.6017.85−0.100.00970.0748
hsa_miR_652_3p1.450.781.450.882.240.671.720.620.090.02040.0748
hsa_miR_671_3p0.711.070.770.860.920.980.990.990.090.01970.0748
hsa_miR_6722_3p82.0285.6478.4692.2473.7885.0879.5691.22−0.090.02390.0748
hsa_miR_6723_5p108.28110.46104.38117.18102.39113.55105.10120.56−0.110.00320.0748
hsa_miR_71887.8397.0184.47101.6280.6199.4384.62106.95−0.110.00530.0748
hsa_miR_769_3p15.9118.8015.6619.7814.7718.8415.6420.19−0.110.00640.0748
hsa_miR_940611.90774.01603.08766.65592.77773.30559.65809.99−0.090.02040.0748

Abbreviations: miRNA, micro RNA; OBS, oxidative balance score; Q, quartile.

Discussion

We assessed 34 diet and lifestyle variables with miRNA expression levels in colorectal tissue and observed that only five of these factors altered miRNA expression level after adjusting for multiple comparisons (FDR q-value <0.1). These variables fell into two categories: 1) dietary carbohydrate, sucrose, and whole grains that could be operating through an insulin-related pathway and 2) NSAIDs and OBS that could be influencing miRNA expression level because of their role in inflammation and oxidative stress. Although others have suggested that diet and lifestyle factors could alter disease risk through their impact on miRNA expression,13,30 we have been able to test this hypothesis broadly within a large population-based study with detailed diet and lifestyle data along with miRNA expression data. In evaluating these results, there are several considerations, such as miRNA expression in this study is from colorectal carcinoma and normal colorectal mucosa, and miRNA expression could be different in other tissue types. Perhaps the largest limitation of the study relates to the interpretation of results. While we can show that factors such as carbohydrate intake are associated with miRNA expression after adjustment for multiple comparisons, it is much more difficult to determine the specific biological mechanism associated with alteration in miRNA expression. For instance, the 250 miRNAs differentially expressed by level of carbohydrate intake are associated with 7,152 unique validated target genes. It is difficult to determine the relative importance of the multitude of pathways associated with these genes that relate specifically with carbohydrate intake. However, we can say that some lifestyle factors do influence miRNA expression levels, giving credence to reports of these factors in disease processes. We have also compared our current findings to our previous findings from these data for miRNAs that were differentially expressed between carcinoma and normal colorectal mucosa.23,31 We observed that 223 of the 250 miRNAs associated with carbohydrate intake, 175 of the 198 miRNAs associated with sucrose intake, 75 of the 99 miRNAs associated with whole grain intake, 121 of the 135 miRNAs associated with recent NSAID use, and 116 of the 137 miRNAs associated with OBS were also differentially expressed between carcinoma and normal colorectal mucosa, suggesting a role in tumor development. Dietary factors have been cited as being important regulators of miRNAs.9,30 Studies have primarily been done in mice and have focused on targeted miRNAs. Reported associations have been found between dietary folate and let-7a, miR-21, miR-23, miR-130, miR-190, miR-17-92, and miR-122 in liver samples and between retinoic acid and let-7a, miR-15a/miR-16-1, and miR-23 in acute promyelocytic leukemia.9 Others have reported associations between miRNAs and polyphenols such as the antioxidant resveratrol with miR-663, miR-155, miR-21, miR-181b, and miR-30c2 in breast tissue cells.32 We did not replicate these findings. In a review by Garcia-Segura et al,30 carbohydrates were cited as being associated with miR-29c and miR-21. In our study, miR-21-3p was associated with carbohydrates. One controlled study using colorectal cells showed that starch consumption upregulated expression of the miR-17-92 cluster.33 We did not see associations within this miR cluster. Sucrose was associated with dysregulated miRNAs in a similar manner that carbohydrate intake was associated with miRNA expression. It has been proposed that sucrose metabolism downregulates expression of miR-15634 and that miR-398 and miR-408 are responsive to sucrose levels.35 Again, we did not see associations between these miRNAs and dietary sucrose level in our data. Although there was overlap of nine miRNAs that differentially expressed by level of carbohydrate intake and by level of whole grain intake, the direction of the associations was different. NSAIDs have been examined with miRNAs in a few studies. Celecoxib has been associated with miR-222 levels in breast tissue in mice,36 and miR-271 has been associated with an NSAID and reactive oxygen species pathway.11 Other studies have focused on COX-2 expression and miRNAs and have shown that miR-101a and miR-199a are associated with higher COX-2 expression and that miR-10b and miR-21 had a high influence on Cox-2 expression. None of these miRNAs were associated with recent NSAID use in our study population, although miR-199a was associated with ever using NSAIDs. Inflammation and oxidative stress are key elements in the CRC carcinogenic process. We developed an OBS to account for dietary and lifestyle factors that could act together to influence CRC risk.18 Oxidative stress also has been examined with miRNA expression in a limited number of studies.10 miR-200a has been associated with oxidative stress in breast cells; miR-155 has been linked to inflammatory and oxidative stress pathways; miR-21, miR-125b, miR-196, and miR-210 have been linked to inflammatory cytokines and signaling pathways.10 Others have cited miR-181a, miR-205, miR-1, miR-21, miR-24, miR-25, miR-185, miR-214, miR-133, miR-145, and miR-495 as being modulated by reactive oxygen species.37 Of these, only miR-200a-5p was associated with OBS in our data. While we have found associations between a limited number of diet and lifestyle factors and miRNA expression levels, we have failed to replicate other findings that have been cited in the literature. These differences could stem from several sources, the primary reason being our study is the only study conducted in humans, while others have relied on mouse models and cell lines and were usually conducted in noncolorectal tissue. Additionally, while others have targeted a few miRNAs, we have incorporated a platform of over 2,000 miRNAs. This methodological difference has resulted in our level of adjustment being considerable, while other studies have no or minimal adjustment for multiple comparisons. Our data are based on recall of diet and lifestyle factors from cases, mainly for a referent period of 2 years to diagnosis. While other referent periods may be important, more distant referent periods would represent a time less temporal to the time of the miRNA expression. We do however believe that our data are excellent, in that results obtained from this study in terms of risk are similar to several other large cohort studies. However, if there is bias toward the null in our recalled data, it could influence our ability to detect associations. Other factors such as potentially different effects by age of participant are possible. Although we adjusted for age to control for confounding, we did not conduct separate age-stratified analysis. Our sample size, although large, would be too small for detailed subgroup analysis. Likewise, we have used an Agilent platform and have previously compared platform results to those obtained from quantitative polymerase chain reaction. Our results were in 100% agreement in direction of association and fold changes calculated from data on the Agilent platform and that obtained from quantitative polymerase chain reaction.31

Conclusion

In summary, we have shown that carbohydrate intake, sucrose intake, NSAID use, and OBS are associated with miRNA expression level. Additionally, most of these miRNAs were differentially expressed between colorectal carcinoma and normal mucosa, suggesting a role in CRC. We believe that these findings lend support to the hypothesis that miRNAs are regulated by diet and lifestyle factors. It is possible that other diet and lifestyle factors could be important in control settings, which we were unable to detect at the population level. We urge other researchers to replicate these findings utilizing laboratory-based studies to better understand the functional significance of these findings. These findings, if replicated, could provide further support for these diet and lifestyle factors in cancer prevention.
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2.  Meat consumption, genetic susceptibility, and colon cancer risk: a United States multicenter case-control study.

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Journal:  Cancer Epidemiol Biomarkers Prev       Date:  1999-01       Impact factor: 4.254

3.  Carotenoids and colon cancer.

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Journal:  Am J Clin Nutr       Date:  2000-02       Impact factor: 7.045

4.  Energy balance and colon cancer--beyond physical activity.

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Journal:  Cancer Res       Date:  1997-01-01       Impact factor: 12.701

Review 5.  Evidence for dietary regulation of microRNA expression in cancer cells.

Authors:  Cindy D Davis; Sharon A Ross
Journal:  Nutr Rev       Date:  2008-08       Impact factor: 7.110

6.  MicroRNAs: New players in cancer prevention targeting Nrf2, oxidative stress and inflammatory pathways.

Authors:  Chengyue Zhang; Limin Shu; Ah-Ng Tony Kong
Journal:  Curr Pharmacol Rep       Date:  2015-01-11

Review 7.  Effects of dietary phytophenols on the expression of microRNAs involved in mammalian cell homeostasis.

Authors:  Allan Lançon; Jean-Jacques Michaille; Norbert Latruffe
Journal:  J Sci Food Agric       Date:  2013-07-11       Impact factor: 3.638

8.  Energy balance and rectal cancer: an evaluation of energy intake, energy expenditure, and body mass index.

Authors:  Martha L Slattery; Bette J Caan; Joan Benson; Maureen Murtaugh
Journal:  Nutr Cancer       Date:  2003       Impact factor: 2.900

9.  A study of the reliability and comparative validity of the cardia dietary history.

Authors:  K Liu; M Slattery; D Jacobs; G Cutter; A McDonald; L Van Horn; J E Hilner; B Caan; C Bragg; A Dyer
Journal:  Ethn Dis       Date:  1994       Impact factor: 1.847

10.  Expression Profiles of miRNA Subsets Distinguish Human Colorectal Carcinoma and Normal Colonic Mucosa.

Authors:  Daniel F Pellatt; John R Stevens; Roger K Wolff; Lila E Mullany; Jennifer S Herrick; Wade Samowitz; Martha L Slattery
Journal:  Clin Transl Gastroenterol       Date:  2016-03-10       Impact factor: 4.488

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1.  Upregulation of polycistronic microRNA-143 and microRNA-145 in colonocytes suppresses colitis and inflammation-associated colon cancer.

Authors:  Urszula Dougherty; Reba Mustafi; Hongyan Zhu; Xiaorong Zhu; Dilip Deb; Stephen C Meredith; Fatma Ayaloglu-Butun; Michelle Fletcher; Arantxa Sanchez; Joel Pekow; Zifeng Deng; Nader Amini; Vani J Konda; Vijaya L Rao; Atsushi Sakuraba; Akushika Kwesi; Sonia S Kupfer; Alessandro Fichera; Loren Joseph; John Hart; Fang He; Tong-Chuan He; Diana West-Szymanski; Yan Chun Li; Marc Bissonnette
Journal:  Epigenetics       Date:  2020-12-28       Impact factor: 4.528

2.  Non-digestible carbohydrates supplementation increases miR-32 expression in the healthy human colorectal epithelium: A randomized controlled trial.

Authors:  Fiona C Malcomson; Naomi D Willis; Iain McCallum; Long Xie; Bart Lagerwaard; Seamus Kelly; D Michael Bradburn; Nigel J Belshaw; Ian T Johnson; John C Mathers
Journal:  Mol Carcinog       Date:  2017-05-09       Impact factor: 4.784

Review 3.  Epidemiology and biology of physical activity and cancer recurrence.

Authors:  Christine M Friedenreich; Eileen Shaw; Heather K Neilson; Darren R Brenner
Journal:  J Mol Med (Berl)       Date:  2017-06-15       Impact factor: 4.599

4.  Identifying factors associated with the direction and significance of microRNA tumor-normal expression differences in colorectal cancer.

Authors:  John R Stevens; Jennifer S Herrick; Roger K Wolff; Martha L Slattery
Journal:  BMC Cancer       Date:  2017-10-30       Impact factor: 4.430

Review 5.  Role of microRNAs in obesity and obesity-related diseases.

Authors:  Giuseppe Iacomino; Alfonso Siani
Journal:  Genes Nutr       Date:  2017-09-25       Impact factor: 5.523

6.  Circulating microRNAs are associated with early childhood obesity: results of the I.Family Study.

Authors:  Giuseppe Iacomino; Paola Russo; Pasquale Marena; Fabio Lauria; Antonella Venezia; Wolfgang Ahrens; Stefaan De Henauw; Pasquale De Luca; Ronja Foraita; Kathrin Günther; Lauren Lissner; Dénes Molnár; Luis A Moreno; Michael Tornaritis; Toomas Veidebaum; Alfonso Siani
Journal:  Genes Nutr       Date:  2019-01-09       Impact factor: 5.523

Review 7.  MicroRNAs in Obesity and Related Metabolic Disorders.

Authors:  Jean-François Landrier; Adel Derghal; Lourdes Mounien
Journal:  Cells       Date:  2019-08-09       Impact factor: 6.600

8.  MiR-3150b inhibits hepatocellular carcinoma cell proliferation, migration and invasion by targeting GOLPH3.

Authors:  Yi Zhang; Jianjun Wang; Hongling Su
Journal:  J Investig Med       Date:  2019-12-05       Impact factor: 2.895

Review 9.  An Assessment on Ethanol-Blended Gasoline/Diesel Fuels on Cancer Risk and Mortality.

Authors:  Steffen Mueller; Gail Dennison; Shujun Liu
Journal:  Int J Environ Res Public Health       Date:  2021-06-28       Impact factor: 3.390

10.  The co-regulatory networks of tumor suppressor genes, oncogenes, and miRNAs in colorectal cancer.

Authors:  Martha L Slattery; Jennifer S Herrick; Lila E Mullany; Wade S Samowitz; John R Sevens; Lori Sakoda; Roger K Wolff
Journal:  Genes Chromosomes Cancer       Date:  2017-07-30       Impact factor: 5.006

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