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European Journal of Nutrition

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01.12.2023 | Original Contribution

Causal relationships between coffee intake, apolipoprotein B and gastric, colorectal, and esophageal cancers: univariable and multivariable Mendelian randomization

verfasst von: Xingwu Liu, Han Yu, Guanyu Yan, Boyang Xu, Mingjun Sun, Mingliang Feng

Erschienen in: European Journal of Nutrition | Ausgabe 2/2024

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Abstract

Purpose

Coffee intake and apolipoprotein B levels have been linked to gastric, colorectal, and esophageal cancers in numerous recent studies. However, whether these associations are all causal remains unestablished. This study aimed to assess the potential causal associations of apolipoprotein B and coffee intake with the risk of gastric, colorectal, and esophageal cancers using Mendelian randomization analysis.

Methods

In this study, we utilized a two-sample Mendelian randomization analysis to access the causal effects of coffee intake and apolipoprotein B on gastric, colorectal, and esophageal cancers. The summary statistics of coffee intake (n = 428,860) and apolipoprotein B (n = 439,214) were obtained from the UK Biobank. In addition, the summary statistics of gastric cancer, colorectal cancer, and esophageal cancer were obtained from the FinnGen biobank (n = 218,792). Inverse variance weighted, MR–Egger, weighted median, and weighted mode were applied to examine the causal relationship between coffee intake, apolipoprotein B and gastric, colorectal, and esophageal cancers. MR–Egger intercept test, Cochran’s Q test, and leave-one-out analysis were performed to evaluate possible heterogeneity and pleiotropy. Steiger filtering and bidirectional mendelian randomization analysis were performed to evaluate the possible reverse causality.

Results

The result of the inverse variance weighted method indicated that apolipoprotein B levels were significantly associated with a higher risk of gastric cancer (OR = 1.392, 95% CI 1.027–1.889, P = 0.0333) and colorectal cancer (OR = 1.188, 95% CI 1.001–1.411, P = 0.0491). Furthermore, multivariable Mendelian randomization analysis also revealed a positive association between apolipoprotein B levels and colorectal cancer risk, but the effect of apolipoprotein B on gastric cancer risk disappeared after adjustment of coffee intake, body mass index or lipid-related traits. However, we did not discover any conclusive evidence linking coffee intake to gastric, colorectal, or esophageal cancers.

Conclusions

This study suggested a causal association between genetically increased apolipoprotein B levels and higher risk of colorectal cancer. No causal relationship was observed between coffee intake and gastric, colorectal, or esophageal cancers.

Nur mit Berechtigung zugänglich

Siegel RL, Miller KD, Jemal A (2020) Cancer statistics, 2020. CA J Clinic. https://doi.org/10.3322/caac.21590CrossRef

Fernandes E, Sores J, Cotton S et al (2020) Esophageal, gastric and colorectal cancers: looking beyond classical serological biomarkers towards glycoproteomics-assisted precision oncology. Theranostics 10(11):4903–4928. https://doi.org/10.7150/thno.42480CrossRefPubMedPubMedCentral

Sung H, Ferlay J, Siegel RL et al (2021) Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 71(3):209–249. https://doi.org/10.3322/caac.21660CrossRefPubMed

Morgan E, Arnold M, Gini A et al (2023) Global burden of colorectal cancer in 2020 and 2040: incidence and mortality estimates from GLOBOCAN. Gut 72(2):338–344. https://doi.org/10.1136/gutjnl-2022-327736CrossRefPubMed

Hu GL, Wang X, Zhang L, Qiu MH (2019) The sources and mechanisms of bioactive ingredients in coffee. Food Funct 10(6):3113–3126. https://doi.org/10.1039/c9fo00288jCrossRefPubMed

Schmit SL, Rennert HS, Rennert G, Gruber SB (2016) Coffee consumption and the risk of colorectal cancer. Cancer Epidemiol Biomarkers Prev 25(4):634–639. https://doi.org/10.1158/1055-9965.EPI-15-0924CrossRefPubMedPubMedCentral

Mirvish SS (1995) Role of N-nitroso compounds (NOC) and N-nitrosation in etiology of gastric, esophageal, nasopharyngeal and bladder cancer and contribution to cancer of known exposures to NOC. Cancer Lett 93(1):17–48CrossRefPubMed

Dik VK, Bueno-de-Mesquita HBA, Van Oijen MGH et al (2014) Coffee and tea consumption, genotype-based CYP1A2 and NAT2 activity and colorectal cancer risk-results from the EPIC cohort study. Int J Cancer 135(2):401–412. https://doi.org/10.1002/ijc.28655CrossRefPubMed

Martimianaki G, Bertuccio P, Alicandro G et al (2022) Coffee consumption and gastric cancer: a pooled analysis from the Stomach cancer Pooling Project consortium. Eur J Cancer Prev 31(2):117–127. https://doi.org/10.1097/CEJ.0000000000000680CrossRefPubMedPubMedCentral

10.

Kim SY, Yoo DM, Min C, Choi HG (2021) Association between coffee consumption/physical exercise and gastric, hepatic, colon, breast, uterine cervix, lung, thyroid, prostate, and bladder cancer. Nutrients. https://doi.org/10.3390/nu13113927CrossRefPubMedPubMedCentral

11.

Song H, Shen X, Chu Q, Zheng X (2022) Coffee consumption is not associated with the risk of gastric cancer: an updated systematic review and meta-analysis of prospective cohort studies. Nutr Res 102:35–44. https://doi.org/10.1016/j.nutres.2022.03.002CrossRefPubMed

12.

Zheng J-S, Yang J, Fu Y-Q, Huang T, Huang Y-J, Li D (2013) Effects of green tea, black tea, and coffee consumption on the risk of esophageal cancer: a systematic review and meta-analysis of observational studies. Nutr Cancer. https://doi.org/10.1080/01635581.2013.741762CrossRefPubMedPubMedCentral

13.

Zamora-Ros R, Luján-Barroso L, Bueno-de-Mesquita HB et al (2014) Tea and coffee consumption and risk of esophageal cancer: the European prospective investigation into cancer and nutrition study. Int J Cancer 135(6):1470–1479. https://doi.org/10.1002/ijc.28789CrossRefPubMed

14.

Vieira AR, Abar L, Chan DSM et al (2017) 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 28(8):1788–1802. https://doi.org/10.1093/annonc/mdx171CrossRefPubMed

15.

Zhang J, Zhou B, Hao C (2018) Coffee consumption and risk of esophageal cancer incidence: a meta-analysis of epidemiologic studies. Medicine 97(17):e0514. https://doi.org/10.1097/MD.0000000000010514CrossRefPubMedPubMedCentral

16.

Li G, Ma D, Zhang Y, Zheng W, Wang P (2013) Coffee consumption and risk of colorectal cancer: a meta-analysis of observational studies. Public Health Nutr 16(2):346–357. https://doi.org/10.1017/S1368980012002601CrossRefPubMed

17.

Shen Z, Liu H, Cao H (2015) Coffee consumption and risk of gastric cancer: an updated meta-analysis. Clin Res Hepatol Gastroenterol 39(2):245–253. https://doi.org/10.1016/j.clinre.2014.09.005CrossRefPubMed

18.

Yu X, Bao Z, Zou J, Dong J (2011) Coffee consumption and risk of cancers: a meta-analysis of cohort studies. BMC Cancer 11:96. https://doi.org/10.1186/1471-2407-11-96CrossRefPubMedPubMedCentral

19.

Trompet S, Packard CJ, Jukema JW (2018) Plasma apolipoprotein-B is an important risk factor for cardiovascular disease, and its assessment should be routine clinical practice. Curr Opin Lipidol 29(1):51–52. https://doi.org/10.1097/MOL.0000000000000476CrossRefPubMed

20.

Walldius G, Jungner I, Holme I, Aastveit AH, Kolar W, Steiner E (2001) High apolipoprotein B, low apolipoprotein A-I, and improvement in the prediction of fatal myocardial infarction (AMORIS study): a prospective study. Lancet (London, England) 358(9298):2026–2033CrossRefPubMed

21.

Borgquist S, Butt T, Almgren P et al (2016) Apolipoproteins, lipids and risk of cancer. Int J Cancer 138(11):2648–2656. https://doi.org/10.1002/ijc.30013CrossRefPubMed

22.

Fang Z, He M, Song M (2021) Serum lipid profiles and risk of colorectal cancer: a prospective cohort study in the UK Biobank. Br J Cancer 124(3):663–670. https://doi.org/10.1038/s41416-020-01143-6CrossRefPubMed

23.

Ma M-Z, Yuan S-Q, Chen Y-M, Zhou Z-W (2018) Preoperative apolipoprotein B/apolipoprotein A1 ratio: a novel prognostic factor for gastric cancer. Onco Targets Ther 11:2169–2176. https://doi.org/10.2147/OTT.S156690CrossRefPubMedPubMedCentral

24.

Pih GY, Gong EJ, Choi JY et al (2021) Associations of serum lipid level with gastric cancer risk, pathology, and prognosis. Cancer Res Treat 53(2):445–456. https://doi.org/10.4143/crt.2020.599CrossRefPubMed

25.

Faraj M, Messier L, Bastard JP et al (2006) Apolipoprotein B: a predictor of inflammatory status in postmenopausal overweight and obese women. Diabetologia 49(7):1637–1646CrossRefPubMed

26.

Foran E, Garrity-Park MM, Mureau C et al (2010) Upregulation of DNA methyltransferase-mediated gene silencing, anchorage-independent growth, and migration of colon cancer cells by interleukin-6. Mol Cancer Res 8(4):471–481. https://doi.org/10.1158/1541-7786.MCR-09-0496CrossRefPubMed

27.

Lin M-T, Lin B-R, Chang C-C et al (2007) IL-6 induces AGS gastric cancer cell invasion via activation of the c-Src/RhoA/ROCK signaling pathway. Int J Cancer 120(12):2600–2608CrossRefPubMed

28.

Du R, Wu X, Peng K et al (2019) Serum apolipoprotein B is associated with increased risk of metabolic syndrome among middle-aged and elderly Chinese: a cross-sectional and prospective cohort study. J Diabetes 11(9):752–760. https://doi.org/10.1111/1753-0407.12904CrossRefPubMed

29.

Castro JP, Grune T, Speckmann B (2016) The two faces of reactive oxygen species (ROS) in adipocyte function and dysfunction. Biol Chem 397(8):709–724. https://doi.org/10.1515/hsz-2015-0305CrossRefPubMed

30.

Zhou A, Hyppönen E (2021) Habitual coffee intake and plasma lipid profile: evidence from UK Biobank. Clin Nutr 40(6):4404–4413. https://doi.org/10.1016/j.clnu.2020.12.042CrossRefPubMed

31.

Williams PT, Wood PD, Vranizan KM, Albers JJ, Garay SC, Taylor CB (1985) Coffee intake and elevated cholesterol and apolipoprotein B levels in men. JAMA 253(10):1407–1411CrossRefPubMedPubMedCentral

32.

Aro A, Teirilä J, Gref CG (1990) Dose-dependent effect on serum cholesterol and apoprotein B concentrations by consumption of boiled, non-filtered coffee. Atherosclerosis 83(2–3):257–261CrossRefPubMed

33.

Superko HR, Bortz W, Williams PT, Albers JJ, Wood PD (1991) Caffeinated and decaffeinated coffee effects on plasma lipoprotein cholesterol, apolipoproteins, and lipase activity: a controlled, randomized trial. Am J Clin Nutr 54(3):599–605CrossRefPubMed

34.

Yang J, Wei H, Zhou Y et al (2022) High-fat diet promotes colorectal tumorigenesis through modulating gut microbiota and metabolites. Gastroenterology. https://doi.org/10.1053/j.gastro.2021.08.041CrossRefPubMedPubMedCentral

35.

Lu L, Mullins CS, Schafmayer C, Zeißig S, Linnebacher M (2021) A global assessment of recent trends in gastrointestinal cancer and lifestyle-associated risk factors. Cancer Commun (Lond) 41(11):1137–1151. https://doi.org/10.1002/cac2.12220CrossRefPubMed

36.

Davey Smith G, Hemani G (2014) Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Hum Mol Genet 23(R1):R89–R98. https://doi.org/10.1093/hmg/ddu328CrossRefPubMedPubMedCentral

37.

Davies NM, Holmes MV, Davey SG (2018) Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians. BMJ 362:k601. https://doi.org/10.1136/bmj.k601CrossRefPubMedPubMedCentral

38.

Li P, Wang H, Guo L et al (2022) Association between gut microbiota and preeclampsia-eclampsia: a two-sample Mendelian randomization study. BMC Med 20(1):443. https://doi.org/10.1186/s12916-022-02657-xCrossRefPubMedPubMedCentral

39.

Emdin CA, Khera AV, Kathiresan S (2017) Mendelian randomization. JAMA 318(19):1925–1926. https://doi.org/10.1001/jama.2017.17219CrossRefPubMed

40.

Lawlor DA, Harbord RM, Sterne JAC, Timpson N, Davey SG (2008) Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Stat Med 27(8):1133–1163MathSciNetCrossRefPubMed

41.

Boef AGC, Dekkers OM, le Cessie S (2015) Mendelian randomization studies: a review of the approaches used and the quality of reporting. Int J Epidemiol 44(2):496–511. https://doi.org/10.1093/ije/dyv071CrossRefPubMed

42.

Didelez V, Sheehan N (2007) Mendelian randomization as an instrumental variable approach to causal inference. Stat Methods Med Res 16(4):309–330MathSciNetCrossRefPubMed

43.

Richardson TG, Sanderson E, Palmer TM et al (2020) Evaluating the relationship between circulating lipoprotein lipids and apolipoproteins with risk of coronary heart disease: a multivariable Mendelian randomisation analysis. PLoS Med 17(3):e1003062. https://doi.org/10.1371/journal.pmed.1003062CrossRefPubMedPubMedCentral

44.

Zhu G-L, Xu C, Yang K-B et al (2022) Causal relationship between genetically predicted depression and cancer risk: a two-sample bi-directional Mendelian randomization. BMC Cancer 22(1):353. https://doi.org/10.1186/s12885-022-09457-9CrossRefPubMedPubMedCentral

45.

Kamat MA, Blackshaw JA, Young R et al (2019) PhenoScanner V2: an expanded tool for searching human genotype-phenotype associations. Bioinformatics 35(22):4851–4853. https://doi.org/10.1093/bioinformatics/btz469CrossRefPubMedPubMedCentral

46.

Bai X, Wei H, Liu W et al (2022) Cigarette smoke promotes colorectal cancer through modulation of gut microbiota and related metabolites. Gut 71(12):2439–2450. https://doi.org/10.1136/gutjnl-2021-325021CrossRefPubMed

47.

Bagnardi V, Rota M, Botteri E et al (2015) Alcohol consumption and site-specific cancer risk: a comprehensive dose-response meta-analysis. Br J Cancer 112(3):580–593. https://doi.org/10.1038/bjc.2014.579CrossRefPubMed

48.

Bardou M, Barkun AN, Martel M (2013) Obesity and colorectal cancer. Gut 62(6):933–947. https://doi.org/10.1136/gutjnl-2013-304701CrossRefPubMed

49.

Chen H, Zheng X, Zong X et al (2021) Metabolic syndrome, metabolic comorbid conditions and risk of early-onset colorectal cancer. Gut 70(6):1147–1154. https://doi.org/10.1136/gutjnl-2020-321661CrossRefPubMed

50.

Palmer TM, Lawlor DA, Harbord RM et al (2012) Using multiple genetic variants as instrumental variables for modifiable risk factors. Stat Methods Med Res 21(3):223–242. https://doi.org/10.1177/0962280210394459MathSciNetCrossRefPubMedPubMedCentral

51.

Papadimitriou N, Dimou N, Tsilidis KK et al (2020) Physical activity and risks of breast and colorectal cancer: a Mendelian randomisation analysis. Nat Commun 11(1):597. https://doi.org/10.1038/s41467-020-14389-8ADSCrossRefPubMedPubMedCentral

52.

Burgess S, Thompson SG (2011) Avoiding bias from weak instruments in Mendelian randomization studies. Int J Epidemiol 40(3):755–764. https://doi.org/10.1093/ije/dyr036CrossRefPubMed

53.

Sanderson E, Spiller W, Bowden J (2021) Testing and correcting for weak and pleiotropic instruments in two-sample multivariable Mendelian randomization. Stat Med 40(25):5434–5452. https://doi.org/10.1002/sim.9133MathSciNetCrossRefPubMedPubMedCentral

54.

Burgess S, Thompson SG (2017) Interpreting findings from Mendelian randomization using the MR-Egger method. Eur J Epidemiol 32(5):377–389. https://doi.org/10.1007/s10654-017-0255-xCrossRefPubMedPubMedCentral

55.

Bowden J, Davey Smith G, Burgess S (2015) Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol 44(2):512–525. https://doi.org/10.1093/ije/dyv080CrossRefPubMedPubMedCentral

56.

Bowden J, Davey Smith G, Haycock PC, Burgess S (2016) Consistent estimation in Mendelian randomization with some invalid instruments using a weighted median estimator. Genet Epidemiol 40(4):304–314. https://doi.org/10.1002/gepi.21965CrossRefPubMedPubMedCentral

57.

Rees JMB, Wood AM, Burgess S (2017) Extending the MR-Egger method for multivariable Mendelian randomization to correct for both measured and unmeasured pleiotropy. Stat Med 36(29):4705–4718. https://doi.org/10.1002/sim.7492MathSciNetCrossRefPubMedPubMedCentral

58.

Cohen JF, Chalumeau M, Cohen R, Korevaar DA, Khoshnood B, Bossuyt PMM (2015) Cochran’s Q test was useful to assess heterogeneity in likelihood ratios in studies of diagnostic accuracy. J Clin Epidemiol 68(3):299–306. https://doi.org/10.1016/j.jclinepi.2014.09.005CrossRefPubMed

59.

Hemani G, Bowden J, Davey SG (2018) Evaluating the potential role of pleiotropy in Mendelian randomization studies. Hum Mol Genet 27(R2):R195–R208. https://doi.org/10.1093/hmg/ddy163CrossRefPubMedPubMedCentral

60.

Brion M-JA, Shakhbazov K, Visscher PM (2013) Calculating statistical power in Mendelian randomization studies. Int J Epidemiol 42(5):1497–1501. https://doi.org/10.1093/ije/dyt179CrossRefPubMed

61.

Hemani G, Zheng J, Elsworth B et al (2018) The MR-Base platform supports systematic causal inference across the human phenome. Elife. https://doi.org/10.7554/eLife.34408CrossRefPubMedPubMedCentral

62.

Yavorska OO, Burgess S (2017) Mendelian randomization: an R package for performing Mendelian randomization analyses using summarized data. Int J Epidemiol 46(6):1734–1739. https://doi.org/10.1093/ije/dyx034CrossRefPubMedPubMedCentral

63.

Hemani G, Tilling K, Davey SG (2017) Orienting the causal relationship between imprecisely measured traits using GWAS summary data. PLoS Genet 13(11):e1007081. https://doi.org/10.1371/journal.pgen.1007081CrossRefPubMedPubMedCentral

64.

Richmond RC, Davey SG (2019) Commentary: Orienting causal relationships between two phenotypes using bidirectional Mendelian randomization. Int J Epidemiol 48(3):907–911. https://doi.org/10.1093/ije/dyz149CrossRefPubMed

65.

Xiao G, He Q, Liu L et al (2022) Causality of genetically determined metabolites on anxiety disorders: a two-sample Mendelian randomization study. J Transl Med 20(1):475. https://doi.org/10.1186/s12967-022-03691-2CrossRefPubMedPubMedCentral

66.

Lauby-Secretan B, Scoccianti C, Loomis D, Grosse Y, Bianchini F, Straif K (2016) Body fatness and cancer-viewpoint of the IARC working group. N Engl J Med 375(8):794–798. https://doi.org/10.1056/NEJMsr1606602CrossRefPubMedPubMedCentral

67.

Renehan AG, Tyson M, Egger M, Heller RF, Zwahlen M (2008) Body-mass index and incidence of cancer: a systematic review and meta-analysis of prospective observational studies. Lancet (London, England) 371(9612):569–578. https://doi.org/10.1016/S0140-6736(08)60269-XCrossRefPubMed

68.

Avgerinos KI, Spyrou N, Mantzoros CS, Dalamaga M (2019) Obesity and cancer risk: emerging biological mechanisms and perspectives. Metabolism 92:121–135. https://doi.org/10.1016/j.metabol.2018.11.001CrossRefPubMed

69.

Blücher C, Stadler SC (2017) Obesity and breast cancer: current insights on the role of fatty acids and lipid metabolism in promoting breast cancer growth and progression. Front Endocrinol 8:293. https://doi.org/10.3389/fendo.2017.00293CrossRef

70.

Sierra-Johnson J, Fisher RM, Romero-Corral A et al (2009) Concentration of apolipoprotein B is comparable with the apolipoprotein B/apolipoprotein A-I ratio and better than routine clinical lipid measurements in predicting coronary heart disease mortality: findings from a multi-ethnic US population. Eur Heart J 30(6):710–717. https://doi.org/10.1093/eurheartj/ehn347CrossRefPubMed

71.

Fernández-Friera L, Fuster V, López-Melgar B et al (2017) Normal LDL-cholesterol levels are associated with subclinical atherosclerosis in the absence of risk factors. J Am Coll Cardiol 70(24):2979–2991. https://doi.org/10.1016/j.jacc.2017.10.024CrossRefPubMed

72.

Mach F, Baigent C, Catapano AL et al (2020) 2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk. Eur Heart J 41(1):111–188. https://doi.org/10.1093/eurheartj/ehz455CrossRefPubMed

73.

Kimak E, Nurczyk K, Skoczylas T, Duma D, Gieroba R, Solski J (2019) Fibroblast growth factor 21, epidermal growth factor receptor, interleukin 6, myeloperoxidase, lipid hydroperoxide, apolipoproteins A-I and B, as well as lipid and lipoprotein ratios as diagnostic serum biomarkers for gastric cancer. Pol Arch Intern Med 129(7–8):559–562. https://doi.org/10.20452/pamw.14836CrossRefPubMed

74.

Zhang X, Zhao X-W, Liu D-B et al (2014) Lipid levels in serum and cancerous tissues of colorectal cancer patients. World J Gastroenterol 20(26):8646–8652. https://doi.org/10.3748/wjg.v20.i26.8646CrossRefPubMedPubMedCentral

75.

Ren L, Yi J, Li W et al (2019) Apolipoproteins and cancer. Cancer Med 8(16):7032–7043. https://doi.org/10.1002/cam4.2587CrossRefPubMedPubMedCentral

76.

Yan X, Yao M, Wen X et al (2019) Elevated apolipoprotein B predicts poor postsurgery prognosis in patients with hepatocellular carcinoma. Onco Targets Ther 12:1957–1964. https://doi.org/10.2147/OTT.S192631CrossRefPubMedPubMedCentral

77.

Nakajima K, Nagamine T, Fujita MQ, Ai M, Tanaka A, Schaefer E (2014) Apolipoprotein B-48: a unique marker of chylomicron metabolism. Adv Clin Chem 64:117–177CrossRefPubMed

78.

Yuasa-Kawase M, Masuda D, Kitazume-Taneike R et al (2012) Apolipoprotein B-48 to triglyceride ratio is a novel and useful marker for detection of type III hyperlipidemia after antihyperlipidemic intervention. J Atheroscler Thromb 19(9):862–871CrossRefPubMed

79.

Masuda D, Sakai N, Sugimoto T et al (2011) Fasting serum apolipoprotein B-48 can be a marker of postprandial hyperlipidemia. J Atheroscler Thromb 18(12):1062–1070CrossRefPubMed

80.

Pei W-d, Sun Y-h, Lu B et al (2007) Apolipoprotein B is associated with metabolic syndrome in Chinese families with familial combined hyperlipidemia, familial hypertriglyceridemia and familial hypercholesterolemia. Int J Cardiol 116(2):194–200CrossRefPubMed

81.

Ramasamy I (2014) Recent advances in physiological lipoprotein metabolism. Clin Chem Lab Med 52(12):1695–1727. https://doi.org/10.1515/cclm-2013-0358CrossRefPubMed

82.

Martin-Perez M, Urdiroz-Urricelqui U, Bigas C, Benitah SA (2022) The role of lipids in cancer progression and metastasis. Cell Metab 34(11):1675–1699. https://doi.org/10.1016/j.cmet.2022.09.023CrossRefPubMed

83.

Rozeveld CN, Johnson KM, Zhang L, Razidlo GL (2020) KRAS controls pancreatic cancer cell lipid metabolism and invasive potential through the lipase HSL. Cancer Res 80(22):4932–4945. https://doi.org/10.1158/0008-5472.CAN-20-1255CrossRefPubMedPubMedCentral

84.

Li C, Wang Y, Liu D et al (2022) Squalene epoxidase drives cancer cell proliferation and promotes gut dysbiosis to accelerate colorectal carcinogenesis. Gut 71(11):2253–2265. https://doi.org/10.1136/gutjnl-2021-325851CrossRefPubMed

85.

Jun SY, Brown AJ, Chua NK et al (2021) Reduction of squalene epoxidase by cholesterol accumulation accelerates colorectal cancer progression and metastasis. Gastroenterology. https://doi.org/10.1053/j.gastro.2020.09.009CrossRefPubMedPubMedCentral

86.

Alicandro G, Tavani A, La Vecchia C (2017) Coffee and cancer risk: a summary overview. Eur J Cancer Prev 26(5):424–432. https://doi.org/10.1097/CEJ.0000000000000341CrossRefPubMed

87.

Bradbury KE, Murphy N, Key TJ (2020) Diet and colorectal cancer in UK Biobank: a prospective study. Int J Epidemiol 49(1):246–258. https://doi.org/10.1093/ije/dyz064CrossRefPubMed

88.

Lee KJ, Choi JH, Jeong HG (2007) Hepatoprotective and antioxidant effects of the coffee diterpenes kahweol and cafestol on carbon tetrachloride-induced liver damage in mice. Food Chem Toxicol 45(11):2118–2125CrossRefPubMed

89.

Hori A, Kasai H, Kawai K et al (2014) Coffee intake is associated with lower levels of oxidative DNA damage and decreasing body iron storage in healthy women. Nutr Cancer 66(6):964–969. https://doi.org/10.1080/01635581.2014.932398CrossRefPubMed

90.

(2002) Risk factors for atrophic chronic gastritis in a European population: results of the Eurohepygast study. Gut 50(6):779–785

91.

Frondelius K, Borg M, Ericson U, Borné Y, Melander O, Sonestedt E (2017) Lifestyle and dietary determinants of serum apolipoprotein A1 and apolipoprotein B concentrations: cross-sectional analyses within a Swedish cohort of 24,984 individuals. Nutrients. https://doi.org/10.3390/nu9030211CrossRefPubMedPubMedCentral

92.

Webb RJ, Mazidi M, Lip GYH, Kengne AP, Banach M, Davies IG (2022) The role of adiposity, diet and inflammation on the discordance between LDL-C and apolipoprotein B. Nutr Metab Cardiovasc Dis 32(3):605–615. https://doi.org/10.1016/j.numecd.2021.12.004CrossRefPubMed

93.

Davidson MH (2018) Triglyceride-rich lipoprotein cholesterol (TRL-C): the ugly stepsister of LDL-C. Eur Heart J 39(7):620–622. https://doi.org/10.1093/eurheartj/ehx741CrossRefPubMed

94.

Sun CJ, Brisson D, Gaudet D, Ooi TC (2020) Relative effect of hypertriglyceridemia on non-HDLC and apolipoprotein B as cardiovascular disease risk markers. J Clin Lipidol 14(6):825–836. https://doi.org/10.1016/j.jacl.2020.09.006CrossRefPubMed

95.

Chen Y, Liu L, Wang X et al (2013) Body mass index and risk of gastric cancer: a meta-analysis of a population with more than ten million from 24 prospective studies. Cancer Epidemiol Biomarkers Prev 22(8):1395–1408. https://doi.org/10.1158/1055-9965.EPI-13-0042CrossRefPubMed

96.

Yang P, Zhou Y, Chen B et al (2009) Overweight, obesity and gastric cancer risk: results from a meta-analysis of cohort studies. Eur J Cancer 45(16):2867–2873. https://doi.org/10.1016/j.ejca.2009.04.019CrossRefPubMed

97.

Chong P-K, Lee H, Zhou J et al (2010) Reduced plasma APOA1 level is associated with gastric tumor growth in MKN45 mouse xenograft model. J Proteomics 73(8):1632–1640. https://doi.org/10.1016/j.jprot.2010.04.005CrossRefPubMed

Titel: Causal relationships between coffee intake, apolipoprotein B and gastric, colorectal, and esophageal cancers: univariable and multivariable Mendelian randomization
verfasst von: Xingwu Liu
Han Yu
Guanyu Yan
Boyang Xu
Mingjun Sun
Mingliang Feng
Publikationsdatum: 01.12.2023
Verlag: Springer Berlin Heidelberg
Erschienen in: European Journal of Nutrition / Ausgabe 2/2024
Print ISSN: 1436-6207
Elektronische ISSN: 1436-6215
DOI: https://doi.org/10.1007/s00394-023-03281-y

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Schadet Ärger den Gefäßen?

14.05.2024 Arteriosklerose Nachrichten

In einer Studie aus New York wirkte sich Ärger kurzfristig deutlich negativ auf die Endothelfunktion gesunder Probanden aus. Möglicherweise hat dies Einfluss auf die kardiovaskuläre Gesundheit.

Intervallfasten zur Regeneration des Herzmuskels?

14.05.2024 Herzinfarkt Nachrichten

Die Nahrungsaufnahme auf wenige Stunden am Tag zu beschränken, hat möglicherweise einen günstigen Einfluss auf die Prognose nach akutem ST-Hebungsinfarkt. Darauf deutet eine Studie an der Uniklinik in Halle an der Saale hin.

Klimaschutz beginnt bei der Wahl des Inhalators

14.05.2024 Klimawandel Podcast

Auch kleine Entscheidungen im Alltag einer Praxis können einen großen Beitrag zum Klimaschutz leisten. Die neue Leitlinie zur "klimabewussten Verordnung von Inhalativa" geht mit gutem Beispiel voran, denn der Wechsel vom klimaschädlichen Dosieraerosol zum Pulverinhalator spart viele Tonnen CO₂. Leitlinienautor PD Dr. Guido Schmiemann erklärt, warum nicht nur die Umwelt, sondern auch Patientinnen und Patienten davon profitieren.

Typ-2-Diabetes und Depression folgen oft aufeinander

14.05.2024 Typ-2-Diabetes Nachrichten

Menschen mit Typ-2-Diabetes sind überdurchschnittlich gefährdet, in den nächsten Jahren auch noch eine Depression zu entwickeln – und umgekehrt. Besonders ausgeprägt ist die Wechselbeziehung laut GKV-Daten bei jüngeren Erwachsenen.

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