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

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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.

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References

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

    Article  Google Scholar 

  2. 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.42480

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. 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.21660

    Article  PubMed  Google Scholar 

  4. 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-2022-327736

    Article  PubMed  Google Scholar 

  5. 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/c9fo00288j

    Article  CAS  PubMed  Google Scholar 

  6. 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-15-0924

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. 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):17–48

    Article  CAS  PubMed  Google Scholar 

  8. 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.28655

    Article  CAS  PubMed  Google Scholar 

  9. 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.0000000000000680

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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/nu13113927

    Article  PubMed  PubMed Central  Google Scholar 

  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.2022.03.002

    Article  CAS  PubMed  Google Scholar 

  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/10.1080/01635581.2013.741762

    Article  PubMed  PubMed Central  Google Scholar 

  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.28789

    Article  CAS  PubMed  Google Scholar 

  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/mdx171

    Article  CAS  PubMed  Google Scholar 

  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.0000000000010514

    Article  PubMed  PubMed Central  Google Scholar 

  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/S1368980012002601

    Article  CAS  PubMed  Google Scholar 

  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.2014.09.005

    Article  CAS  PubMed  Google Scholar 

  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/10.1186/1471-2407-11-96

    Article  PubMed  PubMed Central  Google Scholar 

  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.0000000000000476

    Article  CAS  PubMed  Google Scholar 

  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):2026–2033

    Article  CAS  PubMed  Google Scholar 

  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.30013

    Article  CAS  PubMed  Google Scholar 

  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/s41416-020-01143-6

    Article  CAS  PubMed  Google Scholar 

  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.S156690

    Article  PubMed  PubMed Central  Google Scholar 

  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.2020.599

    Article  CAS  PubMed  Google Scholar 

  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):1637–1646

    Article  CAS  PubMed  Google Scholar 

  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-09-0496

    Article  CAS  PubMed  Google Scholar 

  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):2600–2608

    Article  CAS  PubMed  Google Scholar 

  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/10.1111/1753-0407.12904

    Article  CAS  PubMed  Google Scholar 

  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-2015-0305

    Article  CAS  PubMed  Google Scholar 

  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.2020.12.042

    Article  CAS  PubMed  Google Scholar 

  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):1407–1411

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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):257–261

    Article  CAS  PubMed  Google Scholar 

  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):599–605

    Article  CAS  PubMed  Google Scholar 

  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.2021.08.041

    Article  PubMed  PubMed Central  Google Scholar 

  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/cac2.12220

    Article  PubMed  Google Scholar 

  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/ddu328

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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.k601

    Article  PubMed  PubMed Central  Google Scholar 

  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-x

    Article  PubMed  PubMed Central  Google Scholar 

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

    Article  PubMed  Google Scholar 

  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):1133–1163

    Article  MathSciNet  PubMed  Google Scholar 

  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/dyv071

    Article  PubMed  Google Scholar 

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

    Article  MathSciNet  PubMed  Google Scholar 

  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.1003062

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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/s12885-022-09457-9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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/btz469

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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-2021-325021

    Article  CAS  PubMed  Google Scholar 

  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.2014.579

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  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-2020-321661

    Article  CAS  PubMed  Google Scholar 

  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/10.1177/0962280210394459

    Article  MathSciNet  PubMed  PubMed Central  Google Scholar 

  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/s41467-020-14389-8

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  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/dyr036

    Article  PubMed  Google Scholar 

  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.9133

    Article  MathSciNet  PubMed  PubMed Central  Google Scholar 

  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-x

    Article  PubMed  PubMed Central  Google Scholar 

  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/dyv080

    Article  PubMed  PubMed Central  Google Scholar 

  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.21965

    Article  PubMed  PubMed Central  Google Scholar 

  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.7492

    Article  MathSciNet  PubMed  PubMed Central  Google Scholar 

  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.2014.09.005

    Article  PubMed  Google Scholar 

  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/ddy163

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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/dyt179

    Article  PubMed  Google Scholar 

  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.34408

    Article  PubMed  PubMed Central  Google Scholar 

  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/dyx034

    Article  PubMed  PubMed Central  Google Scholar 

  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.1007081

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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/dyz149

    Article  PubMed  Google Scholar 

  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/s12967-022-03691-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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/NEJMsr1606602

    Article  PubMed  PubMed Central  Google Scholar 

  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-X

    Article  PubMed  Google Scholar 

  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.2018.11.001

    Article  CAS  PubMed  Google Scholar 

  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.2017.00293

    Article  Google Scholar 

  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/ehn347

    Article  CAS  PubMed  Google Scholar 

  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.2017.10.024

    Article  CAS  PubMed  Google Scholar 

  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/ehz455

    Article  PubMed  Google Scholar 

  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.14836

    Article  PubMed  Google Scholar 

  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.i26.8646

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  PubMed  PubMed Central  Google Scholar 

  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.S192631

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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 64:117–177

    Article  CAS  PubMed  Google Scholar 

  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):862–871

    Article  CAS  PubMed  Google Scholar 

  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):1062–1070

    Article  CAS  PubMed  Google Scholar 

  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):194–200

    Article  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  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.2022.09.023

    Article  CAS  PubMed  Google Scholar 

  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-20-1255

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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-2021-325851

    Article  CAS  PubMed  Google Scholar 

  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.2020.09.009

    Article  PubMed  PubMed Central  Google Scholar 

  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.0000000000000341

    Article  CAS  PubMed  Google Scholar 

  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/dyz064

    Article  PubMed  Google Scholar 

  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):2118–2125

    Article  CAS  PubMed  Google Scholar 

  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/10.1080/01635581.2014.932398

    Article  CAS  PubMed  Google Scholar 

  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/nu9030211

    Article  PubMed  PubMed Central  Google Scholar 

  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.2021.12.004

    Article  CAS  PubMed  Google Scholar 

  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/ehx741

    Article  PubMed  Google Scholar 

  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.2020.09.006

    Article  PubMed  Google Scholar 

  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-13-0042

    Article  PubMed  Google Scholar 

  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.2009.04.019

    Article  PubMed  Google Scholar 

  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.2010.04.005

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

All authors are grateful of investigators and participants of the UK Biobank and FinnGen biobank. We also sincerely thank the developers of Phenoscanner V2, R package “TwoSampleMR”, R package “MendelianRandomization”, and R package “MVMR”.

Funding

This research was funded by the Major Science and Technology Project of Liaoning Province, grant number 2022JH1/10400002.

Author information

Author notes

  1. Xingwu Liu and Han Yu contributed equally to this work and should be considered co-first author.

Authors and Affiliations

  1. Department of Gastroenterology, The First Hospital of China Medical University, Shenyang, China

    Xingwu Liu, Guanyu Yan, Boyang Xu & Mingjun Sun

  2. School of Health Management, China Medical University, Shenyang, China

    Han Yu

  3. Department of Endoscopy, The First Hospital of China Medical University, Shenyang, China

    Mingliang Feng

Authors
  1. Xingwu Liu
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  2. Han Yu
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  3. Guanyu Yan
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  4. Boyang Xu
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Contributions

XL wrote the original draft; HY visualized the result; GY collected the data; BX edited the figures and tables; MS and MF revised the manuscript. All authors contributed to the article and approved the submitted version.

Corresponding author

Correspondence to Mingliang Feng.

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The authors declare no conflict of interest.

Ethics statement

We used publicly available summary data where no ethical approval is required.

Supplementary Information

Below is the link to the electronic supplementary material.

394_2023_3281_MOESM1_ESM.pdf

Supplementary file1 (PDF 21 KB) Supplementary Fig. 1 Forest plot of the casual effect of apolipoprotein B on gastric cancer

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Supplementary file2 (PDF 20 KB) Supplementary Fig. 2 Forest plot of the casual effect of apolipoprotein B on colorectal cancer

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Supplementary file3 (PDF 21 KB) Supplementary Fig. 3 Forest plot of the casual effect of apolipoprotein B on esophageal cancer

Supplementary file4 (PDF 8 KB) Supplementary Fig. 4 Forest plot of the casual effect of coffee intake on gastric cancer

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Supplementary file5 (PDF 8 KB) Supplementary Fig. 5 Forest plot of the casual effect of coffee intake on colorectal cancer

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Supplementary file6 (PDF 8 KB) Supplementary Fig. 6 Forest plot of the casual effect of coffee intake on esophageal cancer

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Supplementary file7 (PDF 5 KB) Supplementary Fig. 7 Scatter plot of the causal effect of gastric cancer on apolipoprotein B

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Supplementary file8 (PDF 5 KB) Supplementary Fig. 8 Scatter plot of the causal effect of gastric cancer on coffee intake

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Supplementary file9 (PDF 5 KB) Supplementary Fig. 9 Scatter plot of the causal effect of colorectal cancer on apolipoprotein B

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Supplementary file10 (PDF 5 KB) Supplementary Fig. 10 Scatter plot of the causal effect of colorectal cancer on coffee intake

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Supplementary file11 (PDF 5 KB) Supplementary Fig. 11 Scatter plot of the causal effect of esophageal cancer on apolipoprotein B

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Supplementary file12 (PDF 5 KB) Supplementary Fig. 12 Scatter plot of the causal effect of esophageal cancer on coffee intake

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Supplementary file13 (PDF 5 KB) Supplementary Fig. 13 Funnel plot of the casual effect of gastric cancer on apolipoprotein B

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Supplementary file14 (PDF 5 KB) Supplementary Fig. 14 Funnel plot of the casual effect of gastric cancer on coffee intake

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Supplementary file15 (PDF 5 KB) Supplementary Fig. 15 Funnel plot of the casual effect of colorectal cancer on apolipoprotein B

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Supplementary file16 (PDF 5 KB) Supplementary Fig. 16 Funnel plot of the casual effect of colorectal cancer on coffee intake

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Supplementary file17 (PDF 5 KB) Supplementary Fig. 17 Funnel plot of the casual effect of esophageal cancer on apolipoprotein B

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Supplementary file18 (PDF 5 KB) Supplementary Fig. 18 Funnel plot of the casual effect of esophageal cancer on coffee intake

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Supplementary file19 (PDF 5 KB) Supplementary Fig. 19 Forest plot of the casual effect of gastric cancer on apolipoprotein B

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Supplementary file20 (PDF 5 KB) Supplementary Fig. 20 Forest plot of the casual effect of gastric cancer on coffee intake

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Supplementary file21 (PDF 5 KB) Supplementary Fig. 21 Forest plot of the casual effect of colorectal cancer on apolipoprotein B

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Supplementary file22 (PDF 5 KB) Supplementary Fig. 22 Forest plot of the casual effect of colorectal cancer on coffee intake

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Supplementary file23 (PDF 5 KB) Supplementary Fig. 23 Forest plot of the casual effect of esophageal cancer on apolipoprotein B

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Supplementary file24 (PDF 5 KB) Supplementary Fig. 24 Forest plot of the casual effect of esophageal cancer on coffee intake

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Supplementary file25 (PDF 20 KB) Supplementary Fig. 25 Leave-one-out inverse-variance weighted mendelian randomization analysis of apolipoprotein B on gastric cancer

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Supplementary file26 (PDF 20 KB) Supplementary Fig. 26 Leave-one-out inverse-variance weighted mendelian randomization analysis of apolipoprotein B on colorectal cancer

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Supplementary file27 (PDF 20 KB) Supplementary Fig. 27 Leave-one-out inverse-variance weighted mendelian randomization analysis of apolipoprotein B on esophageal cancer

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Supplementary file28 (PDF 8 KB) Supplementary Fig. 28 Leave-one-out inverse-variance weighted mendelian randomization analysis of coffee intake on gastric cancer

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Supplementary file29 (PDF 8 KB) Supplementary Fig. 29 Leave-one-out inverse-variance weighted mendelian randomization analysis of coffee intake on colorectal cancer

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Supplementary file30 (PDF 8 KB) Supplementary Fig. 30 Leave-one-out inverse-variance weighted mendelian randomization analysis of coffee intake on esophageal cancer

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Supplementary file31 (PDF 5 KB) Supplementary Fig. 31 Leave-one-out inverse-variance weighted mendelian randomization analysis of gastric cancer on apolipoprotein B

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Supplementary file32 (PDF 5 KB) Supplementary Fig. 32 Leave-one-out inverse-variance weighted mendelian randomization analysis of gastric cancer on coffee intake

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Supplementary file33 (PDF 5 KB) Supplementary Fig. 33 Leave-one-out inverse-variance weighted mendelian randomization analysis of colorectal cancer on apolipoprotein B

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Supplementary file34 (PDF 5 KB) Supplementary Fig. 34 Leave-one-out inverse-variance weighted mendelian randomization analysis of colorectal cancer on coffee intake

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Supplementary file35 (PDF 5 KB) Supplementary Fig. 35 Leave-one-out inverse-variance weighted mendelian randomization analysis of esophageal cancer on apolipoprotein B

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Supplementary file36 (PDF 5 KB) Supplementary Fig. 36 Leave-one-out inverse-variance weighted mendelian randomization analysis of esophageal cancer on coffee intake

Supplementary file37 (XLSX 115 KB)

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Liu, X., Yu, H., Yan, G. et al. Causal relationships between coffee intake, apolipoprotein B and gastric, colorectal, and esophageal cancers: univariable and multivariable Mendelian randomization. Eur J Nutr 63, 469–483 (2024). https://doi.org/10.1007/s00394-023-03281-y

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