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Additive Interaction

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Xilin Yang – 1st expert on this subject based on the ideXlab platform

  • Interactive effect of serum uric acid and total bilirubin for cardiovascular disease in Chinese patients with type 2 diabetes
    Scientific Reports, 2016
    Co-Authors: Yanfeng Ren, Xilin Yang, Nan Jin, Tianpei Hong, Yiming Mu, Lixin Guo, Qiuhe Ji, Qiang Li, Linong Ji

    Abstract:

    Serum uric acid (SUA) at high levels and bilirubin at low levels were potent antioxidant but it was uncertain that whether SUA and total bilirubin (TBIL) had Additive Interaction for the risk of CVD in type 2 diabetes mellitus (T2DM). We conducted a cross-sectional survey of 6713 inpatients with T2DM and admitted to 81 tertiary care hospitals. CVD was defined as having either prior coronary heart disease or stroke or peripheral arterial disease. Binary logistic regression was used to estimate odds ratios of SUA and TBIL for CVD. The effect size of Additive Interaction was estimated by three measures, i.e., relative excess risk due to Interaction, attributable proportion due to Interaction and synergy index. Among 6713 patients with T2DM, 561 (8.36%) suffered from CVD. Using ≥283 umol/L (median) to define high SUA and

  • Renin angiotensin system inhibitors may attenuate low LDL cholesterol-related cancer risk in type 2 diabetes
    Diabetes/Metabolism Research and Reviews, 2014
    Co-Authors: Xilin Yang, Ronald C W Ma, Wing-yee So, Ying Wang, Alice P.s. Kong, Risa Ozaki, Gang Xu, Juliana C N Chan

    Abstract:

    BACKGROUND: In type 2 diabetes (T2D), copresence of low-density lipoprotein cholesterol (LDL-C) < 2.8 mmol/L with triglyceride < 1.7 mmol/L or with albuminuria synergistically increased cancer risk. We tested whether use of renin angiotensin system inhibitors attenuated the increased cancer risk associated with these two risk subphenotypes. METHODS: A prospective cohort of 4307 patients with T2D enrolled from December 1996 to January 2005 was analysed using a new user cohort design. Cox model analysis was used to obtain hazard ratios and 95% confidence intervals. The study measured Additive Interactions between nonuse of renin angiotensin system inhibitors and low LDL-C plus low triglyceride or albuminuria for the risk of cancer. A positive Interaction suggests a specific drug effect on the low LDL-C-related cancer risk. RESULTS: During 18 769 person years of follow-up (median follow-up years: 4.44), 4.48% (n = 193) of patients developed cancer. Use of renin angiotensin system inhibitors was associated with reduced cancer risk among patients with copresence of low LDL-C plus low triglyceride or low LDL-C plus albuminuria but not in patients without these subphenotypes. In multivariable analysis, renin angiotensin system inhibitor usage attenuated the hazard ratio of copresence of low LDL-C plus low triglyceride versus lack of this subphenotype for cancer from 2.08 (95% CI: 1.25-3.47) to 1.13 (0.61-2.11) with significant Additive Interaction (p = 0.0225). Similarly, RAS inhibitor usage attenuated the hazard ratio of copresence of low LDL-C plus albuminuria versus lack of this subphenotype for cancer from 1.99 (95% CI: 1.12-3.56) to 0.82 (0.43-1.54) with significant Additive Interaction (p = 0.0009). CONCLUSION: In T2D, renin angiotensin system inhibitor usage may specifically attenuate the low LDL-C-related cancer risk.

  • Additive Interaction between the renin angiotensin system and lipid metabolism for cancer in type 2 diabetes
    Diabetes, 2009
    Co-Authors: Xilin Yang, Wing-yee So, Alice P.s. Kong, Risa Ozaki, Gang Xu, Hai-lu Zhao, Ronald C W, Gary T C Ko, Chun Yip Yeung, Peter C Y Tong

    Abstract:

    OBJECTIVE Clinical and experimental studies suggest cross-talk between lipid metabolism and the renin-angiotensin system (RAS) in atherogenesis. The aim of this study was to explore Interactions between these two systems in mediating cancer risk in type 2 diabetes. RESEARCH DESIGN AND METHODS A prospective cohort of 4,160 Chinese patients with type 2 diabetes, free of cancer at enrollment, were analyzed using Cox models. Interaction of RAS inhibitors (angiotensin I–converting enzyme inhibitors or angiotensin II receptor blockers) and statins was estimated using relative excess risk due to Interaction (RERI), attributable proportion due to Interaction (AP), and synergy index (S). RERI > 0, AP > 0, or S > 1 indicates Additive Interaction between the two classes of drugs. Molecular mechanisms underlying these Interactions were explored using a uninephrectomy (UNX) rat model with renal carcinogenesis. RESULTS During 21,992 person-years of follow-up, 190 patients developed cancer. Use of RAS inhibitors and statins in isolation or combination during follow-up was associated with reduced risk of cancer after adjustment for covariates. The multivariable RERI and AP for the Additive Interaction between these drug classes for cancer were significant (0.53 [95% CI 0.20–0.87] and 2.65 [0.38–4.91], respectively). In the UNX rat model, inhibition of the RAS prevented renal cell carcinoma by normalizing hydroxymethylglutaryl-CoA reductase (HMGCR) expression and the insulin-like growth factor-1 (IGF-1) signaling pathway. CONCLUSIONS Combined use of RAS inhibitors and statins may act synergistically to reduce cancer risk, possibly via HMGCR and IGF-1 signaling pathways in high-risk conditions such as type 2 diabetes.

Wing-yee So – 2nd expert on this subject based on the ideXlab platform

  • Additive Interaction Between the Renin-Angiotensin System and Lipid Metabolism for Cancer in Type 2
    , 2020
    Co-Authors: Diabetes Yang, Hai-lu Zhao, Wing-yee So

    Abstract:

    OBJECTIVE—Clinical and experimental studies suggest crosstalk between lipid metabolism and the renin-angiotensin system (RAS) in atherogenesis. The aim of this study was to explore Interactions between these two systems in mediating cancer risk in type 2 diabetes. RESEARCH DESIGN AND METHODS—A prospective cohort of 4,160 Chinese patients with type 2 diabetes, free of cancer at enrollment, were analyzed using Cox models. Interaction of RAS inhibitors (angiotensin I– converting enzyme inhibitors or angiotensin II receptor blockers) and statins was estimated using relative excess risk due to Interaction (RERI), attributable proportion due to Interaction (AP), and synergy index (S). RERI 0, AP 0, or S 1 indicates Additive Interaction between the two classes of drugs. Molecular mechanisms underlying these Interactions were explored using a uninephrectomy (UNX) rat model with renal carcinogenesis. RESULTS—During 21,992 person-years of follow-up, 190 patients developed cancer. Use of RAS inhibitors and statins in isolation or combination during follow-up was associated with reduced risk of cancer after adjustment for covariates. The multivariable RERI and AP for the Additive Interaction between these drug classes for cancer were significant (0.53 [95% CI 0.20 – 0.87] and 2.65 [0.38 – 4.91], respectively). In the UNX rat model, inhibition of the RAS prevented renal cell carcinoma by normalizing hydroxymethylglutaryl-CoA reductase (HMGCR) expression and the insulin-like growth factor-1 (IGF-1) signaling pathway. CONCLUSIONS—Combined use of RAS inhibitors and statins may act synergistically to reduce cancer risk, possibly via HMGCR and IGF-1 signaling pathways in high-risk conditions such as type 2 diabetes. Diabetes 58:1518–1525, 2009 T

  • Renin angiotensin system inhibitors may attenuate low LDL cholesterol-related cancer risk in type 2 diabetes
    Diabetes/Metabolism Research and Reviews, 2014
    Co-Authors: Xilin Yang, Ronald C W Ma, Wing-yee So, Ying Wang, Alice P.s. Kong, Risa Ozaki, Gang Xu, Juliana C N Chan

    Abstract:

    BACKGROUND: In type 2 diabetes (T2D), copresence of low-density lipoprotein cholesterol (LDL-C) < 2.8 mmol/L with triglyceride < 1.7 mmol/L or with albuminuria synergistically increased cancer risk. We tested whether use of renin angiotensin system inhibitors attenuated the increased cancer risk associated with these two risk subphenotypes. METHODS: A prospective cohort of 4307 patients with T2D enrolled from December 1996 to January 2005 was analysed using a new user cohort design. Cox model analysis was used to obtain hazard ratios and 95% confidence intervals. The study measured Additive Interactions between nonuse of renin angiotensin system inhibitors and low LDL-C plus low triglyceride or albuminuria for the risk of cancer. A positive Interaction suggests a specific drug effect on the low LDL-C-related cancer risk. RESULTS: During 18 769 person years of follow-up (median follow-up years: 4.44), 4.48% (n = 193) of patients developed cancer. Use of renin angiotensin system inhibitors was associated with reduced cancer risk among patients with copresence of low LDL-C plus low triglyceride or low LDL-C plus albuminuria but not in patients without these subphenotypes. In multivariable analysis, renin angiotensin system inhibitor usage attenuated the hazard ratio of copresence of low LDL-C plus low triglyceride versus lack of this subphenotype for cancer from 2.08 (95% CI: 1.25-3.47) to 1.13 (0.61-2.11) with significant Additive Interaction (p = 0.0225). Similarly, RAS inhibitor usage attenuated the hazard ratio of copresence of low LDL-C plus albuminuria versus lack of this subphenotype for cancer from 1.99 (95% CI: 1.12-3.56) to 0.82 (0.43-1.54) with significant Additive Interaction (p = 0.0009). CONCLUSION: In T2D, renin angiotensin system inhibitor usage may specifically attenuate the low LDL-C-related cancer risk.

  • Additive Interaction between the renin angiotensin system and lipid metabolism for cancer in type 2 diabetes
    Diabetes, 2009
    Co-Authors: Xilin Yang, Wing-yee So, Alice P.s. Kong, Risa Ozaki, Gang Xu, Hai-lu Zhao, Ronald C W, Gary T C Ko, Chun Yip Yeung, Peter C Y Tong

    Abstract:

    OBJECTIVE Clinical and experimental studies suggest cross-talk between lipid metabolism and the renin-angiotensin system (RAS) in atherogenesis. The aim of this study was to explore Interactions between these two systems in mediating cancer risk in type 2 diabetes. RESEARCH DESIGN AND METHODS A prospective cohort of 4,160 Chinese patients with type 2 diabetes, free of cancer at enrollment, were analyzed using Cox models. Interaction of RAS inhibitors (angiotensin I–converting enzyme inhibitors or angiotensin II receptor blockers) and statins was estimated using relative excess risk due to Interaction (RERI), attributable proportion due to Interaction (AP), and synergy index (S). RERI > 0, AP > 0, or S > 1 indicates Additive Interaction between the two classes of drugs. Molecular mechanisms underlying these Interactions were explored using a uninephrectomy (UNX) rat model with renal carcinogenesis. RESULTS During 21,992 person-years of follow-up, 190 patients developed cancer. Use of RAS inhibitors and statins in isolation or combination during follow-up was associated with reduced risk of cancer after adjustment for covariates. The multivariable RERI and AP for the Additive Interaction between these drug classes for cancer were significant (0.53 [95% CI 0.20–0.87] and 2.65 [0.38–4.91], respectively). In the UNX rat model, inhibition of the RAS prevented renal cell carcinoma by normalizing hydroxymethylglutaryl-CoA reductase (HMGCR) expression and the insulin-like growth factor-1 (IGF-1) signaling pathway. CONCLUSIONS Combined use of RAS inhibitors and statins may act synergistically to reduce cancer risk, possibly via HMGCR and IGF-1 signaling pathways in high-risk conditions such as type 2 diabetes.

Juliana C N Chan – 3rd expert on this subject based on the ideXlab platform

  • Renin angiotensin system inhibitors may attenuate low LDL cholesterol-related cancer risk in type 2 diabetes
    Diabetes/Metabolism Research and Reviews, 2014
    Co-Authors: Xilin Yang, Ronald C W Ma, Wing-yee So, Ying Wang, Alice P.s. Kong, Risa Ozaki, Gang Xu, Juliana C N Chan

    Abstract:

    BACKGROUND: In type 2 diabetes (T2D), copresence of low-density lipoprotein cholesterol (LDL-C) < 2.8 mmol/L with triglyceride < 1.7 mmol/L or with albuminuria synergistically increased cancer risk. We tested whether use of renin angiotensin system inhibitors attenuated the increased cancer risk associated with these two risk subphenotypes. METHODS: A prospective cohort of 4307 patients with T2D enrolled from December 1996 to January 2005 was analysed using a new user cohort design. Cox model analysis was used to obtain hazard ratios and 95% confidence intervals. The study measured Additive Interactions between nonuse of renin angiotensin system inhibitors and low LDL-C plus low triglyceride or albuminuria for the risk of cancer. A positive Interaction suggests a specific drug effect on the low LDL-C-related cancer risk. RESULTS: During 18 769 person years of follow-up (median follow-up years: 4.44), 4.48% (n = 193) of patients developed cancer. Use of renin angiotensin system inhibitors was associated with reduced cancer risk among patients with copresence of low LDL-C plus low triglyceride or low LDL-C plus albuminuria but not in patients without these subphenotypes. In multivariable analysis, renin angiotensin system inhibitor usage attenuated the hazard ratio of copresence of low LDL-C plus low triglyceride versus lack of this subphenotype for cancer from 2.08 (95% CI: 1.25-3.47) to 1.13 (0.61-2.11) with significant Additive Interaction (p = 0.0225). Similarly, RAS inhibitor usage attenuated the hazard ratio of copresence of low LDL-C plus albuminuria versus lack of this subphenotype for cancer from 1.99 (95% CI: 1.12-3.56) to 0.82 (0.43-1.54) with significant Additive Interaction (p = 0.0009). CONCLUSION: In T2D, renin angiotensin system inhibitor usage may specifically attenuate the low LDL-C-related cancer risk.

  • Additive Interaction of hyperglycemia and albuminuria on risk of ischemic stroke in type 2 diabetes hong kong diabetes registry
    Diabetes Care, 2008
    Co-Authors: Xilin Yang, Wing-yee So, Alice P.s. Kong, Peter C Y Tong, Ronald C W, Gary T C Ko, Chung Shun Ho, Chunchung Chow, Juliana C N Chan

    Abstract:

    OBJECTIVE—The study aims to test whether biological Interaction between hyperglycemia and albuminuria can explain the inconsistent findings from epidemiological studies and clinical trials about effects of hyperglycemia on stroke in type 2 diabetes.

    RESEARCH DESIGN AND METHODS—A total of 6,445 Hong Kong Chinese patients with type 2 diabetes and free of stroke at enrollment were followed up for a median of 5.37 years. Spline Cox proportional hazard regression was used to obtain hazard ratio curves, which were used to identify cutoff points of A1C and spot urinary albumin–to–creatinine ratio for increased ischemic stroke risk. The identified cutoff point of A1C was used to check biological Interaction between A1C and albuminuria (micro- and macroalbuminuria). The biological Interaction was estimated using relative excess risk due to Interaction (RERI), attributable proportion due to Interaction (AP), and synergy index.

    RESULTS—During the follow-up period, 4.45% (n = 287) of patients developed ischemic stroke. A1C was associated with increased hazard ratios of ischemic stroke in a near-linear manner except for two points—6.2 and 8.0%—where the slope between these two points accelerated. For A1C values <6.2%, the presence of micro/macroalbuminuria did not confer additional risk, while significant biological Interaction between A1C and micro/macroalbuminuria for values ≥6.2% was observed (RERI 0.92, 95% CI 0.16–1.68, and AP 0.40, 0.01–0.78).

    CONCLUSIONS—A1C ≥6.2% and micro/macroalbuminuria interact to markedly increase the ischemic stroke risk, which explains a large proportion of risk in patients with type 2 diabetes harboring both risk factors.