A Dietary Intervention High in Green Leafy Vegetables Reduces Oxidative DNA Damage in Adults at Increased Risk of Colorectal Cancer: Biological Outcomes of the Randomized Controlled Meat and Three Greens (M3G) Feasibility Trial
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design and Aims
2.2. Participant Recruitment and Informed Consent
2.3. Randomization and Interventions
2.4. Data Collection
2.5. Statistical Analysis
3. Results
3.1. Study Participant Characteristics
3.2. Circulating Biomarkers
3.3. Microbial Diversity and Taxa
4. Discussion
Limitations
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Bray, F.; Ferlay, J.; Soerjomataram, I.; Siegel, R.L.; Torre, L.A.; Jemal, A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 2018, 68, 394–424. [Google Scholar] [CrossRef] [Green Version]
- Vieira, A.R.; Abar, L.; Chan, D.S.M.; Vingeliene, S.; Polemiti, E.; Stevens, C.; Greenwood, D.; Norat, T. Foods and beverages and colorectal cancer risk: A systematic review and meta-analysis of cohort studies, an update of the evidence of the WCRF-AICR Continuous Update Project. Ann. Oncol. Off. J. Eur. Soc. Med. Oncol. 2017, 28, 1788–1802. [Google Scholar] [CrossRef]
- Zhang, F.F.; Cudhea, F.; Shan, Z.; Michaud, D.S.; Imamura, F.; Eom, H.; Ruan, M.; Rehm, C.D.; Liu, J.; Du, M.; et al. Preventable Cancer Burden Associated With Poor Diet in the United States. JNCI Cancer Spectr. 2019, 3. [Google Scholar] [CrossRef] [Green Version]
- Alsheridah, N.; Akhtar, S. Diet, obesity and colorectal carcinoma risk: Results from a national cancer registry-based middle-eastern study. BMC Cancer 2018, 18, 1227. [Google Scholar] [CrossRef] [Green Version]
- Garcia-Larsen, V.; Morton, V.; Norat, T.; Moreira, A.; Potts, J.F.; Reeves, T.; Bakolis, I. Dietary patterns derived from principal component analysis (PCA) and risk of colorectal cancer: A systematic review and meta-analysis. Eur. J. Clin. Nutr. 2019, 73, 366–386. [Google Scholar] [CrossRef]
- Giovannucci, E.; Ascherio, A.; Rimm, E.B.; Colditz, G.A.; Stampfer, M.J.; Willett, W.C. Physical Activity, Obesity, and Risk for Colon Cancer and Adenoma in Men. Ann. Intern. Med. 1995, 122, 327–334. [Google Scholar] [CrossRef]
- Abar, L.; Vieira, A.R.; Aune, D.; Sobiecki, J.G.; Vingeliene, S.; Polemiti, E.; Stevens, C.; Greenwood, D.C.; Chan, D.S.M.; Schlesinger, S.; et al. Height and body fatness and colorectal cancer risk: An update of the WCRF-AICR systematic review of published prospective studies. Eur. J. Nutr. 2018, 57, 1701–1720. [Google Scholar] [CrossRef] [Green Version]
- Mozaffarian, D.; Hao, T.; Rimm, E.B.; Willett, W.C.; Hu, F.B. Changes in diet and lifestyle and long-term weight gain in women and men. N. Engl. J. Med. 2011, 364, 2392–2404. [Google Scholar] [CrossRef] [Green Version]
- Smith, K.S.; Raney, S.V.; Greene, M.W.; Frugé, A.D. Development and Validation of the Dietary Habits and Colon Cancer Beliefs Survey (DHCCBS): An Instrument Assessing Health Beliefs Related to Red Meat and Green Leafy Vegetable Consumption. J. Oncol. 2019, 2019, 2326808. [Google Scholar] [CrossRef]
- De Vogel, J.; Jonker-Termont, D.S.; van Lieshout, E.M.; Katan, M.B.; van der Meer, R. Green vegetables, red meat and colon cancer: Chlorophyll prevents the cytotoxic and hyperproliferative effects of haem in rat colon. Carcinogenesis 2005, 26, 387–393. [Google Scholar] [CrossRef] [Green Version]
- De Vogel, J.; Jonker-Termont, D.S.M.L.; Katan, M.B.; van der Meer, R. Natural Chlorophyll but Not Chlorophyllin Prevents Heme-Induced Cytotoxic and Hyperproliferative Effects in Rat Colon. J. Nutr. 2005, 135, 1995–2000. [Google Scholar] [CrossRef] [Green Version]
- De Vogel, J.; van-Eck, W.B.; Sesink, A.L.; Jonker-Termont, D.S.; Kleibeuker, J.; van der Meer, R. Dietary heme injures surface epithelium resulting in hyperproliferation, inhibition of apoptosis and crypt hyperplasia in rat colon. Carcinogenesis 2008, 29, 398–403. [Google Scholar] [CrossRef] [PubMed]
- Jssennagger, N.J.; Derrien, M.; van Doorn, G.M.; Rijnierse, A.; van den Bogert, B.; Muller, M.; Dekker, J.; Kleerebezem, M.; van der Meer, R. Dietary heme alters microbiota and mucosa of mouse colon without functional changes in host-microbe cross-talk. PLoS ONE 2012, 7, e49868. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Martin, O.C.; Lin, C.; Naud, N.; Tache, S.; Raymond-Letron, I.; Corpet, D.E.; Pierre, F.H. Antibiotic suppression of intestinal microbiota reduces heme-induced lipoperoxidation associated with colon carcinogenesis in rats. Nutr. Cancer 2015, 67, 119–125. [Google Scholar] [CrossRef] [PubMed]
- Ijssennagger, N.; Belzer, C.; Hooiveld, G.J.; Dekker, J.; van Mil, S.W.; Muller, M.; Kleerebezem, M.; van der Meer, R. Gut microbiota facilitates dietary heme-induced epithelial hyperproliferation by opening the mucus barrier in colon. Proc. Natl. Acad. Sci. USA 2015, 112, 10038–10043. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sato, T.; Takeda, H.; Otake, S.; Yokozawa, J.; Nishise, S.; Fujishima, S.; Orii, T.; Fukui, T.; Takano, J.; Sasaki, Y.; et al. Increased Plasma Levels of 8-Hydroxydeoxyguanosine Are Associated with Development of Colorectal Tumors. J. Clin. Biochem. Nutr. 2010, 47, 59–63. [Google Scholar] [CrossRef] [Green Version]
- Verdam, F.J.; Fuentes, S.; de Jonge, C.; Zoetendal, E.G.; Erbil, R.; Greve, J.W.; Buurman, W.A.; de Vos, W.M.; Rensen, S.S. Human intestinal microbiota composition is associated with local and systemic inflammation in obesity. Obesity 2013, 21, E607–E615. [Google Scholar] [CrossRef] [PubMed]
- Xiao, S.; Fei, N.; Pang, X.; Shen, J.; Wang, L.; Zhang, B.; Zhang, M.; Zhang, X.; Zhang, C.; Li, M.; et al. A gut microbiota-targeted dietary intervention for amelioration of chronic inflammation underlying metabolic syndrome. FEMS Microbiol. Ecol. 2014, 87, 357–367. [Google Scholar] [CrossRef]
- Zhou, B.; Shu, B.; Yang, J.; Liu, J.; Xi, T.; Xing, Y. C-reactive protein, interleukin-6 and the risk of colorectal cancer: A meta-analysis. Cancer Causes Control CCC 2014, 25, 1397–1405. [Google Scholar] [CrossRef] [PubMed]
- Allin, K.H.; Nordestgaard, B.G. Elevated C-reactive protein in the diagnosis, prognosis, and cause of cancer. Crit. Rev. Clin. Lab. Sci. 2011, 48, 155–170. [Google Scholar] [CrossRef] [PubMed]
- Goyal, A.; Terry, M.B.; Jin, Z.; Siegel, A.B. C-reactive protein and colorectal cancer mortality in U.S. adults. Cancer Epidemiol. Biomark. 2014, 23, 1609–1618. [Google Scholar] [CrossRef] [Green Version]
- Shiga, K.; Hara, M.; Nagasaki, T.; Sato, T.; Takahashi, H.; Sato, M.; Takeyama, H. Preoperative Serum Interleukin-6 Is a Potential Prognostic Factor for Colorectal Cancer, including Stage II Patients. Gastroenterol. Res. Pract. 2016, 2016, 8. [Google Scholar] [CrossRef]
- Tawara, K.; Oxford, J.T.; Jorcyk, C.L. Clinical significance of interleukin (IL)-6 in cancer metastasis to bone: Potential of anti-IL-6 therapies. Cancer Manag. Res. 2011, 3, 177–189. [Google Scholar] [CrossRef] [Green Version]
- Waldner, M.J.; Foersch, S.; Neurath, M.F. Interleukin-6—A Key Regulator of Colorectal Cancer Development. Int. J. Biol. Sci. 2012, 8, 1248–1253. [Google Scholar] [CrossRef] [PubMed]
- Cani, P.D.; Amar, J.; Iglesias, M.A.; Poggi, M.; Knauf, C.; Bastelica, D.; Neyrinck, A.M.; Fava, F.; Tuohy, K.M.; Chabo, C.; et al. Metabolic Endotoxemia Initiates Obesity and Insulin Resistance. Diabetes 2007, 56, 1761–1772. [Google Scholar] [CrossRef] [Green Version]
- Li, Y.; Zhang, T.; Chen, G.Y. Flavonoids and Colorectal Cancer Prevention. Antioxidants 2018, 7, 187. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Frugé, A.D.; Smith, K.S.; Riviere, A.J.; Demark-Wahnefried, W.; Arthur, A.E.; Murrah, W.M.; Morrow, C.D.; Arnold, R.D.; Braxton-Lloyd, K. Primary Outcomes of a Randomized Controlled Crossover Trial to Explore the Effects of a High Chlorophyll Dietary Intervention to Reduce Colon Cancer Risk in Adults: The Meat and Three Greens (M3G) Feasibility Trial. Nutrients 2019, 11, 2349. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Barnard, N.D.; Gloede, L.; Cohen, J.; Jenkins, D.J.A.; Turner-McGrievy, G.; Green, A.A.; Ferdowsian, H. A Low-Fat Vegan Diet Elicits Greater Macronutrient Changes, but Is Comparable in Adherence and Acceptability, Compared with a More Conventional Diabetes Diet among Individuals with Type 2 Diabetes. J. Am. Diet. Assoc. 2009, 109, 263–272. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Moore, W.J.; McGrievy, M.E.; Turner-McGrievy, G.M. Dietary adherence and acceptability of five different diets, including vegan and vegetarian diets, for weight loss: The New DIETs study. Eat. Behav. 2015, 19, 33–38. [Google Scholar] [CrossRef] [PubMed]
- Barnard, N.; Scialli, A.R.; Bertron, P.; Hurlock, D.; Edmunds, K. Acceptability of a therapeutic low-fat, vegan diet in premenopausal women. J. Nutr. Educ. Behav. 2000, 32, 314–319. [Google Scholar] [CrossRef]
- Craig, C.L.; Marshall, A.L.; Sjostrom, M.; Bauman, A.E.; Booth, M.L.; Ainsworth, B.E.; Pratt, M.; Ekelund, U.; Yngve, A.; Sallis, J.F.; et al. International physical activity questionnaire: 12-country reliability and validity. Med. Sci. Sports Exerc. 2003, 35, 1381–1395. [Google Scholar] [CrossRef] [Green Version]
- Subar, A.F.; Kirkpatrick, S.I.; Mittl, B.; Zimmerman, T.P.; Thompson, F.E.; Bingley, C.; Willis, G.; Islam, N.G.; Baranowski, T.; McNutt, S.; et al. The Automated Self-Administered 24-Hour Dietary Recall (ASA24): A Resource for Researchers, Clinicians, and Educators from the National Cancer Institute. J. Acad. Nutr. Diet. 2012, 112, 1134–1137. [Google Scholar] [CrossRef] [Green Version]
- Lohman, T.G.; Roche, A.F.; Martorell, R. Anthropometric Standardization Reference Manual; Human Kinetics Books: Champaign, IL, USA, 1988; Volume 177. [Google Scholar]
- O’Donnell, L.J.; Virjee, J.; Heaton, K.W. Detection of pseudodiarrhoea by simple clinical assessment of intestinal transit rate. BMJ 1990, 300, 439–440. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Caporaso, J.G.; Kuczynski, J.; Stombaugh, J.; Bittinger, K.; Bushman, F.D.; Costello, E.K.; Fierer, N.; Pena, A.G.; Goodrich, J.K.; Gordon, J.I.; et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Meth. 2010, 7, 335–336. [Google Scholar] [CrossRef] [Green Version]
- Kumar, R.; Eipers, P.; Little, R.B.; Crowley, M.; Crossman, D.K.; Lefkowitz, E.J.; Morrow, C.D. Getting started with microbiome analysis: Sample acquisition to bioinformatics. Curr. Protoc. Hum. Genet. 2014, 82, 18.18.11–18.18.29. [Google Scholar] [CrossRef] [Green Version]
- Longstreth, G.F.; Thompson, W.G.; Chey, W.D.; Houghton, L.A.; Mearin, F.; Spiller, R.C. Functional Bowel Disorders. Gastroenterology 2006, 130, 1480–1491. [Google Scholar] [CrossRef] [PubMed]
- Blake, M.R.; Raker, J.M.; Whelan, K. Validity and reliability of the Bristol Stool Form Scale in healthy adults and patients with diarrhoea-predominant irritable bowel syndrome. Aliment. Pharmacol. Ther. 2016, 44, 693–703. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Rosenthal, R.; Rubin, D.B. r equivalent: A simple effect size indicator. Psychol. Methods 2003, 8, 492–496. [Google Scholar] [CrossRef] [Green Version]
- Fruge, A.D.; Ptacek, T.; Tsuruta, Y.; Morrow, C.D.; Azrad, M.; Desmond, R.A.; Hunter, G.R.; Rais-Bahrami, S.; Demark-Wahnefried, W. Dietary Changes Impact the Gut Microbe Composition in Overweight and Obese Men with Prostate Cancer Undergoing Radical Prostatectomy. J. Acad. Nutr. Diet 2016. [Google Scholar] [CrossRef] [PubMed]
- O’Sullivan, S.M.; Galvin, K.; Heneghan, C.; Davidson, R.; Clark, I.; Lucey, A.J. Does daily consumption of vitamin K1 from cruciferous vegetables reach the circulation and the knee joint? Proc. Nutr. Soc. 2018, 77, E68. [Google Scholar] [CrossRef] [Green Version]
- Westerman, K.; Kelly, J.M.; Ordovás, J.M.; Booth, S.L.; DeMeo, D.L. Epigenome-wide association study reveals a molecular signature of response to phylloquinone (vitamin K1) supplementation. Epigenetics 2020, 1–12. [Google Scholar] [CrossRef] [PubMed]
- Sanchez, M.; Roussel, R.; Hadjadj, S.; Moutairou, A.; Marre, M.; Velho, G.; Mohammedi, K. Plasma concentrations of 8-hydroxy-2′-deoxyguanosine and risk of kidney disease and death in individuals with type 1 diabetes. Diabetologia 2018, 61, 977–984. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Valavanidis, A.; Vlachogianni, T.; Fiotakis, C. 8-hydroxy-2′-deoxyguanosine (8-OHdG): A critical biomarker of oxidative stress and carcinogenesis. J. Environ. Sci. Health. Part C 2009, 27, 120–139. [Google Scholar] [CrossRef] [Green Version]
- Kasai, H. Analysis of a form of oxidative DNA damage, 8-hydroxy-2’-deoxyguanosine, as a marker of cellular oxidative stress during carcinogenesis. Mutat. Res. 1997, 387, 147–163. [Google Scholar] [CrossRef]
- Espinosa-Moncada, J.; Marín-Echeverri, C.; Galvis-Pérez, Y.; Ciro-Gómez, G.; Aristizábal, J.C.; Blesso, C.N.; Fernandez, M.L.; Barona-Acevedo, J. Evaluation of Agraz Consumption on Adipocytokines, Inflammation, and Oxidative Stress Markers in Women with Metabolic Syndrome. Nutrients 2018, 10, 1639. [Google Scholar] [CrossRef] [Green Version]
- López-Uriarte, P.; Nogués, R.; Saez, G.; Bulló, M.; Romeu, M.; Masana, L.; Tormos, C.; Casas-Agustench, P.; Salas-Salvadó, J. Effect of nut consumption on oxidative stress and the endothelial function in metabolic syndrome. Clin. Nutr. 2010, 29, 373–380. [Google Scholar] [CrossRef]
- Müllner, E.; Brath, H.; Pleifer, S.; Schiermayr, C.; Baierl, A.; Wallner, M.; Fastian, T.; Millner, Y.; Paller, K.; Henriksen, T.; et al. Vegetables and PUFA-rich plant oil reduce DNA strand breaks in individuals with type 2 diabetes. Mol. Nutr. Food Res. 2013, 57, 328–338. [Google Scholar] [CrossRef]
- Johnson, S.A.; Feresin, R.G.; Navaei, N.; Figueroa, A.; Elam, M.L.; Akhavan, N.S.; Hooshmand, S.; Pourafshar, S.; Payton, M.E.; Arjmandi, B.H. Effects of daily blueberry consumption on circulating biomarkers of oxidative stress, inflammation, and antioxidant defense in postmenopausal women with pre- and stage 1-hypertension: A randomized controlled trial. Food Funct. 2017, 8, 372–380. [Google Scholar] [CrossRef]
- Manchali, S.; Chidambara Murthy, K.N.; Patil, B.S. Crucial facts about health benefits of popular cruciferous vegetables. J. Funct. Foods 2012, 4, 94–106. [Google Scholar] [CrossRef]
- Kamada, N.; Núñez, G. Regulation of the immune system by the resident intestinal bacteria. Gastroenterology 2014, 146, 1477–1488. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Chow, J.C.; Young, D.W.; Golenbock, D.T.; Christ, W.J.; Gusovsky, F. Toll-like receptor-4 mediates lipopolysaccharide-induced signal transduction. J. Biol. Chem. 1999, 274, 10689–10692. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Rabiei, S.; Hedayati, M.; Rashidkhani, B.; Saadat, N.; Shakerhossini, R. The Effects of Synbiotic Supplementation on Body Mass Index, Metabolic and Inflammatory Biomarkers, and Appetite in Patients with Metabolic Syndrome: A Triple-Blind Randomized Controlled Trial. J. Diet. Suppl. 2019, 16, 294–306. [Google Scholar] [CrossRef]
- Park, E.; Edirisinghe, I.; Burton-Freeman, B. Avocado Fruit on Postprandial Markers of Cardio-Metabolic Risk: A Randomized Controlled Dose Response Trial in Overweight and Obese Men and Women. Nutrients 2018, 10, 1287. [Google Scholar] [CrossRef] [Green Version]
- Mayr, H.L.; Itsiopoulos, C.; Tierney, A.C.; Ruiz-Canela, M.; Hebert, J.R.; Shivappa, N.; Thomas, C.J. Improvement in dietary inflammatory index score after 6-month dietary intervention is associated with reduction in interleukin-6 in patients with coronary heart disease: The AUSMED heart trial. Nutr. Res. 2018, 55, 108–121. [Google Scholar] [CrossRef] [Green Version]
- Martin, K.R.; Burrell, L.; Bopp, J. Authentic tart cherry juice reduces markers of inflammation in overweight and obese subjects: A randomized, crossover pilot study. Food Funct. 2018, 9, 5290–5300. [Google Scholar] [CrossRef] [PubMed]
- López-Chillón, M.T.; Carazo-Díaz, C.; Prieto-Merino, D.; Zafrilla, P.; Moreno, D.A.; Villaño, D. Effects of long-term consumption of broccoli sprouts on inflammatory markers in overweight subjects. Clin. Nutr. 2019, 38, 745–752. [Google Scholar] [CrossRef]
- Kopf, J.C.; Suhr, M.J.; Clarke, J.; Eyun, S.I.; Riethoven, J.M.; Ramer-Tait, A.E.; Rose, D.J. Role of whole grains versus fruits and vegetables in reducing subclinical inflammation and promoting gastrointestinal health in individuals affected by overweight and obesity: A randomized controlled trial. Nutr. J. 2018, 17, 72. [Google Scholar] [CrossRef] [Green Version]
- Hou, Y.Y.; Ojo, O.; Wang, L.L.; Wang, Q.; Jiang, Q.; Shao, X.Y.; Wang, X.H. A Randomized Controlled Trial to Compare the Effect of Peanuts and Almonds on the Cardio-Metabolic and Inflammatory Parameters in Patients with Type 2 Diabetes Mellitus. Nutrients 2018, 10, 1565. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Estévez-Santiago, R.; Silván, J.M.; Can-Cauich, C.A.; Veses, A.M.; Alvarez-Acero, I.; Martinez-Bartolome, M.A.; San-Román, R.; Cámara, M.; Olmedilla-Alonso, B.; de Pascual-Teresa, S. Lack of a Synergistic Effect on Cardiometabolic and Redox Markers in a Dietary Supplementation with Anthocyanins and Xanthophylls in Postmenopausal Women. Nutrients 2019, 11, 1533. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Esgalhado, M.; Kemp, J.A.; Azevedo, R.; Paiva, B.R.; Stockler-Pinto, M.B.; Dolenga, C.J.; Borges, N.A.; Nakao, L.S.; Mafra, D. Could resistant starch supplementation improve inflammatory and oxidative stress biomarkers and uremic toxins levels in hemodialysis patients? A pilot randomized controlled trial. Food Funct. 2018, 9, 6508–6516. [Google Scholar] [CrossRef]
- Bardagjy, A.S.; Hu, Q.; Giebler, K.A.; Ford, A.; Steinberg, F.M. Effects of grape consumption on biomarkers of inflammation, endothelial function, and PBMC gene expression in obese subjects. Arch. Biochem. Biophys. 2018, 646, 145–152. [Google Scholar] [CrossRef] [PubMed]
- Chang, P.H.; Pan, Y.P.; Fan, C.W.; Tseng, W.K.; Huang, J.S.; Wu, T.H.; Chou, W.C.; Wang, C.H.; Yeh, K.Y. Pretreatment serum interleukin-1β, interleukin-6, and tumor necrosis factor-α levels predict the progression of colorectal cancer. Cancer Med. 2016, 5, 426–433. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Erlinger, T.P.; Platz, E.A.; Rifai, N.; Helzlsouer, K.J. C-Reactive Protein and the Risk of Incident Colorectal Cancer. JAMA 2004, 291, 585–590. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Frugé, A.D.; Van der Pol, W.; Rogers, L.Q.; Morrow, C.D.; Tsuruta, Y.; Demark-Wahnefried, W. Fecal Akkermansia muciniphila Is Associated with Body Composition and Microbiota Diversity in Overweight and Obese Women with Breast Cancer Participating in a Presurgical Weight Loss Trial. J. Acad. Nutr. Diet 2020, 120, 650–659. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- De Angelis, M.; Ferrocino, I.; Calabrese, F.M.; De Filippis, F.; Cavallo, N.; Siragusa, S.; Rampelli, S.; Di Cagno, R.; Rantsiou, K.; Vannini, L.; et al. Diet influences the functions of the human intestinal microbiome. Sci. Rep. 2020, 10, 4247. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Louis, P.; Flint, H.J. Diversity, metabolism and microbial ecology of butyrate-producing bacteria from the human large intestine. FEMS Microbiol. Lett. 2009, 294, 1–8. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Davis, C.D. The Gut Microbiome and Its Role in Obesity. Nutr. Today 2016, 51, 167–174. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Chakraborti, C.K. New-found link between microbiota and obesity. World J. Gastrointest. Pathophysiol. 2015, 6, 110–119. [Google Scholar] [CrossRef] [PubMed]
- Lu, Y.; Fan, C.; Li, P.; Lu, Y.; Chang, X.; Qi, K. Short Chain Fatty Acids Prevent High-fat-diet-induced Obesity in Mice by Regulating G Protein-coupled Receptors and Gut Microbiota. Sci. Rep. 2016, 6, 37589. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ozato, N.; Saito, S.; Yamaguchi, T.; Katashima, M.; Tokuda, I.; Sawada, K.; Katsuragi, Y.; Kakuta, M.; Imoto, S.; Ihara, K.; et al. Blautia genus associated with visceral fat accumulation in adults 20–76 years of age. NPJ Biofilms Microbiomes 2019, 5, 28. [Google Scholar] [CrossRef] [Green Version]
- United States Census Bureau. Quickfacts United States. 2020. Available online: https://www.census.gov/quickfacts/fact/table/US/PST045218 (accessed on 1 December 2020).
- United States Census Bureau. QuickFacts Alabama. 2020. Available online: https://www.census.gov/quickfacts/AL (accessed on 1 December 2020).
Total | Immediate | Delayed | ||
---|---|---|---|---|
(n = 50) | (n = 26) | (n = 24) | ||
-------- Mean (SD) -------- | P | |||
Age (years) | 48 (13.1) | 47 (13) | 49 (13) | 0.649 |
Body Mass Index (kg/m2) | 36.2 (4.7) | 35.2 (4.6) | 37.3 (4.8) | 0.123 |
RM servings per week | 10.3 (5.0) | 10.5 (4.8) | 10.2 (5.4) | 0.846 |
GLV servings per week | 0.21 (0.25) | 0.20 (0.26) | 0.22 (0.23) | 0.852 |
-------- N (%) -------- | P | |||
Gender | 1.000 | |||
Male | 19 (38) | 10 (39) | 9 (38) | |
Female | 31 (62) | 16 (61) | 15 (62) | |
Race | 0.035 | |||
African American | 10 (20) | 2 (8) | 8 (33) | |
White | 40 (80) | 24 (92) | 16 (67) | |
Education | 0.050 | |||
Associate degree or less | 8 (16) | 1 (4) | 7 (29) | |
Bachelor’s degree | 19 (38) | 11 (42) | 8 (33) | |
Advanced degree(s) | 23 (46) | 14 (54) | 9 (38) | |
Marital Status | 0.775 | |||
Married | 29 (58) | 16 (62) | 13 (54) | |
Not currently Married | 21 (42) | 10 (38) | 11 (46) |
Baseline | Intervention Change | Control Change | ||||
---|---|---|---|---|---|---|
All participants (n = 40) | Mean (SD) | Mean (SD) | p-value ¹ | Mean (SD) | p-value ¹ | p-value 2 |
Vitamin K1 (ng/mL) | 0.1 (0.27) | 0.48 (0.8) | 0.0005 | 0.04 (0.72) | 0.757 | <0.001 |
8OHdG (ng/mL) | 41.81 (18.18) | −8.05 (14.11) | 0.001 | 1.25 (11.5) | 0.507 | <0.001 |
Fecal 8OHdG (µg/mL) | 24.31 (54.52) | −12.06 (39.66) | 0.040 | −5.29 (29.41) | 0.219 | <0.001 |
TNFa (pg/mL) | 156.15 (43.5) | −22.49 (47.41) | 0.005 | −5.21 (35.31) | 0.369 | <0.001 |
IL6 (pg/mL) | 5.07 (3.17) | 0.97 (3.46) | 0.083 | 0.9 (5.13) | 0.285 | <0.001 |
CRP (pg/mL) | 3251 (3965) | 870 (3884) | 0.926 | −601 (3679) | 0.321 | 0.945 |
Immediate Group (n = 21) | ||||||
Vitamin K1 (ng/mL) | 0.06 (0.18) | 0.79 (0.97) | 0.001 | −0.10 (0.75) | 0.550 | 0.004 |
8OHdG (ng/mL) | 45.56 (22.02) | −11.23 (16.25) | 0.005 | 4.74 (12.18) | 0.090 | 0.003 |
Fecal 8OHdG (µg/mL) | 38.33 (73.85) | −24.92 (53.23) | 0.031 | −6.41 (39.24) | 0.432 | <0.001 |
TNFa (pg/mL) | 166.48 (56.68) | −22.54 (57.58) | 0.088 | −14.85 (41.51) | 0.117 | 0.203 |
IL6 (pg/mL) | 4.56 (2.09) | 0.7 (3.67) | 0.395 | 1.42 (3.06) | 0.046 | 0.242 |
CRP (pg/mL) | 3543 (4657) | −204 (4981) | 0.853 | −1249 (4516) | 0.220 | 0.922 |
Delayed Group (n = 19) | ||||||
Vitamin K1 (ng/mL) | 0.15 (0.34) | 0.14 (0.33) | 0.072 | 0.20 (0.67) | 0.231 | <0.001 |
8OHdG (ng/mL) | 36.95 (10.2) | −4.54 (10.64) | 0.079 | -3.06 (9.2) | 0.189 | <0.001 |
Fecal 8OHdG (µg/mL) | 10.29 (14.51) | 0.8 (5.92) | 0.514 | -4.16 (14.99) | 0.187 | <0.001 |
TNFa (pg/mL) | 143.53 (8.1) | −22.42 (34.42) | 0.011 | 6.69 (21.36) | 0.215 | <0.001 |
IL6 (pg/mL) | 5.68 (4.11) | 1.28 (3.27) | 0.106 | 0.26 (6.95) | 0.877 | <0.001 |
CRP (pg/mL) | 2893 (3005) | 101 (2599) | 0.867 | 200 (2136) | 0.704 | 0.902 |
Variables# | F | p-Value | ηp2 |
---|---|---|---|
Vitamin K1 | |||
Treatment | 70.408 | <0.001 | 0.681 |
Treatment*Gender | 1.239 | 0.274 | 0.036 |
Treatment*Pre-Intervention Vitamin K1 | 0.468 | 0.499 | 0.014 |
Treatment*Arm | 9.055 | 0.005 | 0.215 |
8OHdG | |||
Treatment | 11.020 | 0.002 | 0.250 |
Treatment*Gender | 1.462 | 0.235 | 0.042 |
Treatment*Pre-Intervention 8OHdG | 8.077 | 0.008 | 0.197 |
Treatment*Arm | 4.482 | 0.042 | 0.120 |
Fecal 8OHdG | |||
Treatment | 2.256 | 0.142 | 0.061 |
Treatment*Gender | 1.894 | 0.177 | 0.051 |
Treatment*Pre-Intervention Fecal 8OHdG | 0.780 | 0.383 | 0.022 |
Treatment*Arm | 2.550 | 0.119 | 0.068 |
TNFa | |||
Treatment | 13.713 | 0.001 | 0.294 |
Treatment*Gender | 0.000 | 0.985 | 0.000 |
Treatment*Pre-Intervention TNFa | 12.281 | 0.001 | 0.271 |
Treatment*Arm | 6.629 | 0.015 | 0.167 |
IL6 | |||
Treatment | 8.897 | 0.005 | 0.212 |
Treatment*Gender | 0.185 | 0.670 | 0.006 |
Treatment*Pre-Intervention IL6 | 0.191 | 0.665 | 0.006 |
Treatment*Arm | 4.299 | 0.046 | 0.115 |
CRP | |||
Treatment | 1.513 | 0.227 | 0.044 |
Treatment*Gender | 1.119 | 0.298 | 0.033 |
Treatment*Pre-Intervention CRP | 1.625 | 0.211 | 0.047 |
Treatment*Arm | 0.036 | 0.850 | 0.001 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Frugé, A.D.; Smith, K.S.; Riviere, A.J.; Tenpenny-Chigas, R.; Demark-Wahnefried, W.; Arthur, A.E.; Murrah, W.M.; van der Pol, W.J.; Jasper, S.L.; Morrow, C.D.; et al. A Dietary Intervention High in Green Leafy Vegetables Reduces Oxidative DNA Damage in Adults at Increased Risk of Colorectal Cancer: Biological Outcomes of the Randomized Controlled Meat and Three Greens (M3G) Feasibility Trial. Nutrients 2021, 13, 1220. https://doi.org/10.3390/nu13041220
Frugé AD, Smith KS, Riviere AJ, Tenpenny-Chigas R, Demark-Wahnefried W, Arthur AE, Murrah WM, van der Pol WJ, Jasper SL, Morrow CD, et al. A Dietary Intervention High in Green Leafy Vegetables Reduces Oxidative DNA Damage in Adults at Increased Risk of Colorectal Cancer: Biological Outcomes of the Randomized Controlled Meat and Three Greens (M3G) Feasibility Trial. Nutrients. 2021; 13(4):1220. https://doi.org/10.3390/nu13041220
Chicago/Turabian StyleFrugé, Andrew D., Kristen S. Smith, Aaron J. Riviere, Rachel Tenpenny-Chigas, Wendy Demark-Wahnefried, Anna E. Arthur, William M. Murrah, William J. van der Pol, Shanese L. Jasper, Casey D. Morrow, and et al. 2021. "A Dietary Intervention High in Green Leafy Vegetables Reduces Oxidative DNA Damage in Adults at Increased Risk of Colorectal Cancer: Biological Outcomes of the Randomized Controlled Meat and Three Greens (M3G) Feasibility Trial" Nutrients 13, no. 4: 1220. https://doi.org/10.3390/nu13041220