Introduction

Liver cancer is the seventh most commonly diagnosed cancer and the second leading cause of cancer death worldwide in 2020.[1] The number of new cases and deaths in China were 431,383 and 412,216, respectively.[2] China accounts for about half of the total number of new cases and deaths of liver cancer in the world alone.[3,4] Hepatocellular carcinoma (HCC), the most predominant type of primary liver cancer, is insidious and highly malignant with a 5-year survival rate ranging between 5% and 30%.[5] To prevent the occurrence of HCC, the most effective initiative is to reduce its burden.[6] Accumulating evidence has suggested that dietary risks, which are important modifiable lifestyle factors for deaths,[7] play an important role in the development of HCC.[8]

Copper (Cu) and zinc (Zn) are essential micronutrients derived from a wide variety of animal foods, legumes, grain germ, etc.[9] They are important components of metalloenzymes involved in tissue respiration, energy metabolism, and antioxidant processes, such as Cu/Zn-superoxide dismutase (Cu/Zn-SOD).[10,11] Cu/Zn-SOD is a powerful intracellular antioxidant enzyme that is essential for scavenging reactive oxygen species, but the homeostatic imbalance of copper and zinc will affect Cu/Zn-SOD activity, causing oxidative damage to biomolecules such as DNA, proteins, and lipids, thus promoting the development of cancer.[12,13] In addition, copper and zinc have their own physiological effects in carcinogenesis. Copper is a limiting factor in cancer progression such as tumor growth, angiogenesis, and metastasis.[14] Zinc has important functions such as maintaining immune function and cell structural stability and regulating cell differentiation and proliferation, DNA/RNA synthesis, and repair.[15]

A case-control study also found that serum copper levels were significantly higher and serum zinc levels were significantly lower in HCC patients than in healthy subjects.[16] And there was significant copper accumulation in surgically resected HCC tissue compared with para-cancerous tissue in HCC patients.[17] These findings suggest that imbalance in copper–zinc homeostasis may be closely related to the incidence of HCC. Nevertheless, there are few epidemiological studies regarding copper and zinc and the risk of HCC. A nested case-control study from the European Prospective Investigation into Cancer and Nutrition (EPIC), including 106 pairs of HCC patients and healthy controls, found that higher serum zinc levels and lower copper-to-zinc ratio are associated with a lower risk of HCC.[18] However, two prospective cohort studies from China reported null association between dietary copper and zinc intakes and the risk of liver cancer.[19] To our knowledge, limited studies have examined the role of copper and zinc, measured both in diets and blood samples, in the development of HCC.

Against this background, this study was designed to investigate the association between dietary intake, serum levels of copper and zinc with the risk of HCC in a 1:1 case-control study.

Methods Study population

This 1:1 matched case–control study was conducted in Guangdong, China. HCC cases were from the Guangdong Liver Cancer Cohort (GLCC). A prospective cohort study of patients aged 18–80 years with incident liver cancer, was established in September 2013 at Sun Yat-sen University Cancer Center (SYSUCC). In this study, we limited our analyses to cases with newly diagnosed HCC (C22.0 as per the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision [ICD-10], codes), who had not received anti-tumor therapy at recruitment and who had data on both dietary intake and serum levels of copper and zinc. Cases were excluded if they had the following conditions: (1) other serious chronic diseases (including heart failure, liver failure, renal failure, physical or mental disability); (2) significant changes in dietary habits or lifestyles within the previous 5 years (i.e., changing from omnivorous diets to vegetarian diets, abstaining recruited from smoking and alcohol drinking). Healthy controls were recruited from the Guangzhou Nutrition and Health Study (GNHS). The GNHS, established in 2008, is a community-based prospective cohort study. The inclusion and exclusion criteria for cases and controls were the same (except for the diagnosis of HCC). The recruitment and enrollment procedures of the cohorts have been previously described in detail.[20,21]

Ethical approval

The GLCC and GNHS were approved by the Ethics Committee of the School of Public Health at Sun Yat-sen University (Nos.013[2017] and 048[2018]). Written informed consent was obtained from all participants.

Cases and controls were matched 1:1 according to sex and age (±1 year), and a total of 434 case-control pairs were included in the present analysis. The study protocol was approved by the institutional review board of the School of Public Health at Sun Yat-sen University. Written informed consent was provided by each participant.

Dietary assessment

A semi-quantitative 79-item food frequency questionnaire (FFQ) was used to assess dietary intake during the previous year before HCC diagnosis for cases or prior to the interview for controls. Each food item had five predefined qualitative responses, namely "daily," "weekly," "monthly," "annually," and "not eaten." Participants were asked to report the frequency and intake amount of each food consumed. Photographs of common food portion sizes were provided to help participants to quantify their consumption. Individual food intake was translated into grams per day. Daily dietary intakes of total energy, copper, zinc, and other nutrients were then calculated by multiplying the daily consumption of each food item by the nutrient content obtained from the China Food Composition Table 2009.[22] Copper and zinc intakes were adjusted for total energy intake (i.e., 1922 kcal/day for men and 1688 kcal/day for women) by the residual method.[23] The Healthy Eating Index 2015 (HEI-2015)[24] was also calculated to reflect the diet quality of participants, with higher scores indicating better adherence to dietary guidelines. The validity and reproducibility of the FFQ had been confirmed by six non-consecutive, 3-day dietary records at intervals of 2 months within 1 year and two FFQs administered 1 year apart among 61 healthy women recruited from Guangdong.[25]

Laboratory assays

Blood samples were collected on the second day of the hospital admission for HCC cases and at the first follow-up for controls. Serum samples were separated, aliquoted, and stored in –80°C freezers. To minimize technical variability, 100 μL of serum samples was assayed in batches at the KingMed Diagnostics Laboratory (Guangzhou, China) by blinded laboratory personnel between December 2016 and March 2017. Serum copper and zinc concentrations were quantified by using inductively coupled plasma mass spectrometry (Agilent 7700x ICP-MS spectrometer, Agilent Technologies, Germany). Masked, replicate, and quality control samples were interspersed among the samples. The intra-assay coefficients of variance for serum copper and zinc were 7.4% and 6.6%, respectively.

Routine laboratory parameters including seropositivity for hepatitis B surface antigen (HBsAg) were analyzed to a standardized protocol at the Clinical Laboratory of SYSUCC for cases and the KingMed Diagnostics Laboratory for controls.

Covariates

The same structured questionnaire was used to collect the following information from cases and controls through face-to-face interviews: socio-demographic characteristics (i.e., sex, age); lifestyle habits (i.e., diet, smoking status, alcohol drinking status); and relevant diseases (i.e., a history of fatty liver disease, a history of diabetes). Smokers or alcohol drinkers were defined as participants who smoked at least one cigarette per day or drank alcohol at least once a week continuously for at least 6 months. Anthropometric measurements (i.e., height and body weight) were collected by a standard procedure. Body mass index (BMI, kg/m2) was then calculated by dividing weight (kg) by height squared (m2).

Statistical analysis

The Cu/Zn ratio was computed by dividing copper levels by zinc levels. Paired student's t-test, Wilcoxon signed-rank test, or McNemar χ2 test were used to compare differences in baseline characteristics between cases and controls. Spearman's rank correlation coefficients were estimated between dietary intake and serum levels of copper or zinc. Cases and controls were divided into three groups according to the tertiles of copper and zinc levels in the control group. Conditional logistic regression models were used to calculate the odds ratio (OR) and 95% confidence intervals (95% CIs). The trend test was performed by assigning the median value for each group as a continuous variable in the regression models. We also calculated OR and 95% CIs for one standard deviation increase (per-SD increase) in copper and zinc levels. Model 1 was adjusted for age and total energy intake; model 2 was additionally adjusted for BMI, smoking status, alcohol drinking status, and HEI-2015 based on model 1; and model 3 was additionally adjusted for HBsAg, history of fatty liver disease, and history of diabetes based on model 2. The interaction of copper and zinc with other established risk factors for HCC including sex, age, smoking status, alcohol drinking status, HBsAg, history of fatty liver disease, and history of diabetes was explored using the multiplicative scale. Stratified analyses were further performed using a binary logistic regression model for all factors except sex and age.

The statistical analyses were performed in SPSS (IBM, Armonk, NY, USA), version 26.0. All tests were two-sided, and a value of P <0.05 was considered statistically significant.

Results Baseline characteristics

A total of 434 case-control pairs were included in this study. Men accounted for 83.2% (361/434); the mean ± standard deviation (SD) age was 59.8 ± 7.6 years. The baseline characteristics of the case and control groups are shown in Table 1. The case group had a higher proportion of smokers, alcohol drinkers, HBsAg (+), and a history of fatty liver disease but lower HEI-2015 scores than the control group (all P <0.001). No significant differences in BMI, total energy intake, and the proportion with a history of diabetes were found between cases and controls.

Table 1 - Baseline characteristics of HCC cases and matched controls. Characteristics

HCC cases

(n = 434)

Matched controls

(n = 434)

Statistics P values Sex 0† 1.000 Women 73 (16.8) 73 (16.8) Men 361 (83.2) 361 (83.2) Age (years) 59.8 ± 7.6 59.9 ± 7.5 1.98* 0.048 BMI (kg/m2) 22.8 ± 3.2 22.8 ± 2.8 0.35* 0.727 Smoking 117.44† <0.001 No 169 (38.9) 327 (75.3) Yes 265 (61.1) 107 (24.7) Alcohol drinking 73.36† <0.001 No 253 (58.3) 367 (84.6) Yes 181 (41.7) 67 (15.4) BCLC stage – – 0 41 (9.4) – A 165 (38.0) – B 42 (9.7) – C 186 (42.9) – D – – HBsAg (+) 448.00† <0.001 No 66 (15.2) 366 (84.3) Yes 368 (84.8) 51 (11.8) Missing – 17 (3.9) History of fatty liver disease 14.34† <0.001 No 339 (78.1) 375 (86.4) Yes 95 (21.9) 52 (12.0) Missing – 7 (1.6) History of diabetes 1.63† 0.257 No 378 (87.1) 390 (89.9) Yes 56 (12.9) 44 (10.1) HEI-2015 55.5 ± 7.0 65.1 ± 6.3 21.01* <0.001 Total energy intake (kcal/day) 1912 ± 610 1951 ± 585 0.97* 0.334

Values are shown as n (%) or mean ± standard deviation. *t value, †chi-squared value. BCLC stage: Barcelona Clinic Liver Cancer stage; BMI: Body mass index; HBsAg: Hepatitis B surface antigen; HCC: Hepatocellular carcinoma; HEI-2015: Healthy Eating Index 2015. –: Not available.

As shown in Table 2, dietary intakes of copper (median: 1.56 mg/day vs. 2.10 mg/day), zinc (median: 12.3 mg/day vs. 13.0 mg/day), and their ratio (median: 0.13 vs. 0.16) were significantly lower in cases than in controls (all P <0.001). Regarding serum levels, serum copper (median: 982 μg/L vs. 874 μg/L) and Cu/Zn ratio (median: 1.13 vs. 0.79) were higher, while serum zinc was lower (median: 871 μg/L vs. 1098 μg/L) in cases than in controls (all P <0.001). There was significantly inverse correlation between serum copper levels and dietary copper intake (rspearman = -0.101, P = 0.003), whereas serum zinc levels were positively correlated with dietary zinc intake (rspearman = 0.171, P <0.001).

Table 2 - Dietary intakes and serum levels of copper and zinc of HCC cases and matched controls. Characteristics

HCC cases

(n = 434)

Matched controls

(n = 434)

Statistics P values Dietary copper intakes (mg/day)* 1.56 (1.21, 2.04) 2.10 (1.63, 2.89) -8.26 <0.001 Dietary zinc intakes (mg/day)* 12.3 (11.1, 13.6) 13.0 (12.0, 14.0) -5.48 <0.001 Dietary Cu/Zn ratio* 0.13 (0.10, 0.16) 0.16 (0.13, 0.23) -7.15 <0.001 Serum copper (μg/L) 982 (838, 1200) 874 (802, 955) -9.26 <0.001 Serum zinc (μg/L) 871 (773, 980) 1098 (968, 1257) -14.85 <0.001 Serum Cu/Zn ratio 1.13 (0.94, 1.42) 0.79 (0.66, 0.93) -15.67 <0.001

Values are shown as median (IQR). *Intakes of copper and zinc were adjusted for sex-specific mean total energy intake (i.e., 1922 kcal/day for men and 1688 kcal/day for women) using the Residual Method. Cu/Zn: Copper/zinc; HCC: Hepatocellular carcinoma; IQR: Interquartile range.

Association of dietary copper and zinc intake with HCC risk

The associations of dietary intake of copper and zinc and their ratios with HCC risk are shown in Table 3. Higher dietary zinc intake was associated with a lower risk of HCC after adjustment for age and total energy intake (model 1: OR [95% CI] Tertile 3vs.Tertile 1 = 0.39 [0.27, 0.56], Ptrend <0.001). The inverse association remained significant after further adjustment for BMI, smoking, alcohol drinking, HEI-2015 (model 2: OR [95% CI] Tertile 3vs.Tertile 1 = 0.33 [0.17, 0.63], Ptrend = 0.001), as well as HBsAg, history of fatty liver disease, and history of diabetes (model 3: OR [95% CI] Tertile 3vs.Tertile 1 = 0.26 [0.08, 0.81], Ptrend = 0.029). Per-SD increase in dietary zinc intake was associated with a 35% decrease in the risk of HCC (OR [95% CI]per-SD increase = 0.65 [0.44, 0.96]). An inverse association with HCC risk was also observed for dietary copper intake and dietary Cu/Zn ratio in model 1, however, the association became non-significant after additional adjustment for other risk factors.

Table 3 - OR (95% CI) of the risk of HCC by tertiles of dietary copper and zinc intakes. Characteristics OR (95% CI) P trend values OR (95% CI) Tertile 1 Tertile 2 Tertile 3 per-SD increase Dietary copper intake* ≤1.76 mg/day >1.76–2.52 mg/day >2.52 mg/day per 2.02 mg/day Cases/control 273/144 93/145 68/145 434/434 Model 1† 1.00 (ref||) 0.31 (0.21, 0.45) 0.25 (0.17, 0.37) <0.001 0.60 (0.49, 0.74) Model 2‡ 1.00 (ref||) 1.08 (0.58, 2.00) 0.66 (0.36, 1.22) 0.140 0.87 (0.67, 1.12) Model 3§ 1.00 (ref||) 1.15 (0.40, 3.29) 0.94 (0.37, 2.38) 0.834 0.86 (0.59, 1.26) Dietary zinc intake* ≤12.35 mg/day >12.35–13.68 mg/day >13.68 mg/day per 1.81 mg/day Cases/controls 229/144 102/145 103/145 434/434 Model 1† 1.00 (ref||) 0.38 (0.27, 0.55) 0.39 (0.27, 0.56) <0.001 0.70 (0.61, 0.81) Model 2‡ 1.00 (ref||) 0.23 (0.11, 0.46) 0.33 (0.17, 0.63) 0.001 0.68 (0.54, 0.86) Model 3§ 1.00 (ref||) 0.19 (0.06, 0.63) 0.26 (0.08, 0.81) 0.029 0.65 (0.44, 0.96) Dietary Cu/Zn ratio* ≤0.14 >0.14–0.20 >0.20 per 0.19 Cases/controls 267/145 99/144 68/145 434/434 Model 1† 1.00 (ref||) 0.32 (0.22, 0.47) 0.25 (0.17, 0.37) <0.001 0.70 (0.57, 0.86) Model 2‡ 1.00 (ref||) 1.09 (0.59, 2.05) 0.65 (0.35, 1.23) 0.110 0.95 (0.74, 1.23) Model 3§ 1.00 (ref||) 0.86 (0.30, 2.47) 0.88 (0.36, 2.16) 0.799 0.97 (0.68, 1.39)

*Intakes of copper and zinc were adjusted for total energy intake (i.e., 1922 kcal/day for men and 1688 kcal/day for women) using the residual method. †Model 1: Adjusted for age and total energy intake. ‡Model 2: Adjusted for covariates in model 1 + BMI, smoking status, alcohol drinking status, and HEI-2015. §Model 3: Adjusted for covariates in model 2 + HBsAg, history of fatty liver disease, and history of diabetes. ||"ref" refers to the inclusion of copper and zinc indicators as categorical variables in the model, using Tertile 1 as a reference to calculate the OR (95% CI) for Tertile 2 and Tertile 3, respectively. BMI: Body mass index; CI: Confidence interval; Cu/Zn: Copper/zinc; HBsAg: Hepatitis B surface antigen; HCC: Hepatocellular carcinoma; HEI-2015: Healthy Eating Index 2015; OR: Odds ratio; SD: Standard deviation.

Association of serum levels of copper and zinc with HCC risk

The associations of serum levels of copper and zinc and their ratio with HCC risk are shown in Table 4. After adjusting for potential confounders, higher serum zinc levels were associated with a lower risk of HCC (model 3: OR [95% CI] Tertile 3vs.Tertile 1 = 0.02 [0.002, 0.13], Ptrend <0.001). For each SD increase in serum zinc levels, the risk of HCC was decreased by 89% (model 3: OR [95% CI]per-SD increase = 0.11 [0.04, 0.30]). However, serum copper levels (model 3: OR [95% CI]per-SD increase = 2.05 [1.39, 3.03]) and serum Cu/Zn ratio (model 3: OR [95% CI]per-SD increase = 6.53 [2.52, 16.92]) were positively associated with HCC risk.

Table 4 - OR (95% CI) of the risk of HCC by tertiles of serum copper and zinc levels. Characteristics OR (95% CI) P trend values OR (95% CI) Tertile 1 Tertile 2 Tertile 3 per-SD increase Serum copper levels ≤825 μg/L >825–921 μg/L >921 μg/L per 122 μg/L Cases/controls 100/144 74/146 260/144 434/434 Model 1* 1.00 (ref§) 0.76 (0.51, 1.14) 2.51 (1.78, 3.55) <0.001 1.56 (1.40, 1.73) Model 2† 1.00 (ref§) 0.75 (0.38, 1.47) 1.48 (0.82, 2.68) 0.100 1.33 (1.14, 1.55) Model 3‡ 1.00 (ref§) 0.68 (0.19, 2.38) 2.57 (0.90, 7.32) 0.020 2.05 (1.39, 3.03) Serum zinc levels ≤1020 μg/L >1020–1186 μg/L >1186 μg/L per 404 μg/L Cases/controls 361/144 57/146 16/144 434/434 Model 1* 1.00 (ref§) 0.10 (0.06, 0.17) 0.03 (0.01, 0.06) <0.001 0.05 (0.03, 0.58) Model 2† 1.00 (ref§) 0.16 (0.07, 0.37) 0.03 (0.01, 0.09) <0.001 0.09 (0.04, 0.20) Model 3‡ 1.00 (ref§) 0.43 (0.13, 1.44) 0.02 (0.002, 0.13) <0.001 0.11 (0.04, 0.30) Serum Cu/Zn ratio ≤0.71 >0.71–0.87 >0.87 per 0.21 Cases/controls 17/144 56/145 361/145 434/434 Model 1* 1.00 (ref§) 3.04 (1.50, 6.14) 24.86 (12.34, 50.07) <0.001 4.05 (3.03, 5.40) Model 2† 1.00 (ref§) 7.27 (2.43, 21.80) 26.06 (9.16, 74.12) <0.001 3.97 (2.56, 6.16) Model 3‡ 1.00 (ref§) 9.17 (1.41, 59.65) 65.42 (8.90, 480.83) <0.001 6.53 (2.52, 16.92)

*Model 1: Adjusted for age and total energy intake. †Model 2: Adjusted for covariates in model 1 + BMI, smoking status, alcohol drinking status, and HEI-2015. ‡Model 3: Adjusted for covariates in model 2 + HBsAg, history of fatty liver disease, and history of diabetes. §"ref" refers to the inclusion of copper and zinc indicators as categorical covariates in the model, using Tertile 1 as a reference to calculate the OR (95% CI) for Tertile 2 and Tertile 3, respectively. BMI: Body mass index; CI: Confidence interval; Cu/Zn: Copper/zinc; HBsAg: Hepatitis B surface antigen; HEI-2015: Healthy Eating Index 2015; HCC: Hepatocellular carcinoma; OR: Odds ratio; SD: Standard deviation.

Stratified analyses

Supplementary Tables 1 and 2, https://links.lww.com/CM9/B614 show a significant interaction of dietary zinc intake and serum zinc levels with sex, respectively (Pinteraction = 0.041; 0.010). Higher zinc intake (ORTertile 3