Ben Zhang

Prof. Ben Zhang


Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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15 March 2024 in PLOS Medicine
Verified
Journal Article
Open access
PDF file
HCHuijie Cui
Huijie Cui
WZWenqiang Zhang
Wenqiang Zhang
LZLi Zhang
Li Zhang
YQYang Qu
Yang Qu
ZXZhengxing Xu
Zhengxing Xu
BZBen Zhang
Ben Zhang
Background: The incidence of prostate cancer is increasing in older males globally. Age, ethnicity, and family history are identified as the well-known risk factors for prostate cancer, but few modifiable factors have been firmly established. The objective of this study was to identify and evaluate various factors modifying the risk of prostate cancer reported in meta-analyses of prospective observational studies and mendelian randomization (MR) analyses. Methods and findings: We searched PubMed, Embase, and Web of Science from the inception to January 10, 2022, updated on September 9, 2023, to identify meta-analyses and MR studies on prostate cancer. Eligibility criteria for meta-analyses were (1) meta-analyses including prospective observational studies or studies that declared outcome-free at baseline; (2) evaluating the factors of any category associated with prostate cancer incidence; and (3) providing effect estimates for further data synthesis. Similar criteria were applied to MR studies. Meta-analysis was repeated using the random-effects inverse-variance model with DerSimonian—Laird method. Quality assessment was then conducted for included meta-analyses using AMSTAR-2 tool and for MR studies using STROBE-MR and assumption evaluation. Subsequent evidence grading criteria for significant associations in meta-analyses contained sample size, P values and 95% confidence intervals, 95% prediction intervals, heterogeneity, and publication bias, assigning 4 evidence grades (convincing, highly suggestive, suggestive, or weak). Significant associations in MR studies were graded as robust, probable, suggestive, or insufficient considering P values and concordance of effect directions. Finally, 92 selected from 411 meta-analyses and 64 selected from 118 MR studies were included after excluding the overlapping and outdated studies which were published earlier and contained fewer participants or fewer instrument variables for the same exposure. In total, 123 observational associations (45 significant and 78 null) and 145 causal associations (55 significant and 90 null) were categorized into lifestyle; diet and nutrition; anthropometric indices; biomarkers; clinical variables, diseases, and treatments; and environmental factors. Concerning evidence grading on significant associations, there were 5 highly suggestive, 36 suggestive, and 4 weak associations in meta-analyses, and 10 robust, 24 probable, 4 suggestive, and 17 insufficient causal associations in MR studies. Twenty-six overlapping factors between meta-analyses and MR studies were identified, with consistent significant effects found for physical activity (PA) (occupational PA in meta: OR = 0.87, 95% CI: 0.80, 0.94; accelerator-measured PA in MR: OR = 0.49, 95% CI: 0.33, 0.72), height (meta: OR = 1.09, 95% CI: 1.06, 1.12; MR: OR = 1.07, 95% CI: 1.01, 1.15, for aggressive prostate cancer), and smoking (current smoking in meta: OR = 0.74, 95% CI: 0.68, 0.80; smoking initiation in MR: OR = 0.91, 95% CI: 0.86, 0.97). Methodological limitation is that the evidence grading criteria could be expanded by considering more indices. Conclusions: In this large-scale study, we summarized the associations of various factors with prostate cancer risk and provided comparisons between observational associations by meta-analysis and genetically estimated causality by MR analyses. In the absence of convincing overlapping evidence based on the existing literature, no robust associations were identified, but some effects were observed for height, physical activity, and smoking.

31 May 2024 in Sleep Medicine Reviews
Verified
Journal Article
Closed access
CYChao Yang
Chao Yang
PYPeijing Yan
Peijing Yan
XWXueyao Wu
Xueyao Wu
WZWenqiang Zhang
Wenqiang Zhang
HCHuijie Cui
Huijie Cui
BZBen Zhang
Ben Zhang

9 December 2023 in Journal of Hazardous Materials
Verified
Journal Article
Closed access
MZManyu Zhao
Manyu Zhao
MWMengzhu Wang
Mengzhu Wang
XCXuxi Chen
Xuxi Chen
YGYing Gao
Ying Gao
QCQing Chen
Qing Chen
YYYuqin Yao
Yuqin Yao

16 June 2022 in European Journal of Epidemiology
Verified
Journal Article
Open access
PDF file
XZXuan Zhou
Xuan Zhou
LYLili Yu
Lili Yu
LWLijuan Wang
Lijuan Wang
JXJiarui Xiao
Jiarui Xiao
Jing SunJing Sun
Jing Sun
XLXue Li
Xue Li
Alcohol intake is thought to be a risk factor for breast cancer, but the causal relationship and carcinogenic mechanisms are not clear. We performed an up-to-date meta-analysis of prospective studies to assess observational association, and then conducted MR analysis to make causal inference based on the genetic predisposition to alcohol consumption (“drinks per week”) and pathological drinking behaviours (“alcohol use disorder” and “problematic alcohol use”), as well as genetically predicted DNA methylation at by alcohol-related CpG sites in blood. We found an observational dose–response association between alcohol intake and breast cancer incidence with an additional risk of 4% for per 10 g/day increase in alcohol consumption. Genetic predisposition to alcohol consumption (“drinks per week”) was not causally associated with breast cancer incidence at the OR of 1.01 (95% CI 0.84, 1.23), but problematic alcohol use (PAU) was linked to a higher breast cancer risk at the OR of 1.76 (95% CI 1.04, 2.99) when conditioning on alcohol consumption. Epigenetic MR analysis identified four CpG sites, cg03260624 near CDC7 gene, cg10816169 near ZNF318 gene, cg03345232 near RIN3 gene, and cg26312998 near RP11-867G23.13 gene, where genetically predicted epigenetic modifications were associated with an increased breast cancer incidence risk. Our findings re-affirmed that alcohol consumption is of high risk for breast cancer incidence even at a very low dose, and the pathogenic effect of alcohol on breast cancer could be due to pathological drinking behaviour and epigenetic modification at several CpG sites, which could be potential intervention targets for breast cancer prevention.

18 December 2023 in Journal of Affective Disorders
Verified
Journal Article
Closed access
ZXZhengxing Xu
Zhengxing Xu
XWXueyao Wu
Xueyao Wu
CXChangfeng Xiao
Changfeng Xiao
WZWenqiang Zhang
Wenqiang Zhang
PYPeijing Yan
Peijing Yan
XJXia Jiang
Xia Jiang

1 July 2012 in Cancer Epidemiology, Biomarkers & Prevention
Verified
Journal Article
Open access
PDF file
XMXiangyu Ma
Xiangyu Ma
ABAlicia Beeghly-Fadiel
Alicia Beeghly-Fadiel
WLWei Lu
Wei Lu
JSJIAJUN SHI
JIAJUN SHI
YXYong-Bing Xiang
Yong-Bing Xiang
WZWei Zheng
Wei Zheng
Background: The TGF-β signaling pathway plays a significant role in the carcinogenic process of breast cancer. Methods: We systematically evaluated associations of common variants in TGF-β signaling pathway genes with breast cancer risk using a multistage, case–control study among Asian women. Results: In the first stage, 341 single-nucleotide polymorphisms with minor allele frequencies ≥ 0.05 across 11 genes were evaluated among 2,926 cases and 2,380 controls recruited as a part of the Shanghai Breast Cancer Genetics Study (SBCGS). In the second stage, 20 SNPs with promising associations were evaluated among an additional 1,890 cases and 2,000 controls from the SBCGS. One variant, TGFBR2 rs1078985, had highly consistent and significant associations with breast cancer risk among participants in both study stages, as well as promising results from in silico analysis. Additional genotyping was carried out among 2,475 cases and 2,343 controls from the SBCGS, as well as among 5,077 cases and 5,384 controls from six studies in the Asian Breast Cancer Consortium (stage III). Pooled analysis of all data indicated that minor allele homozygotes (GG) of TGFBR2 rs1078985 had a 24% reduced risk of breast cancer compared with major allele carriers (AG or AA; OR, 0.76; 95% CI, 0.65–0.89; P = 8.42 × 10−4). Conclusion: These findings support a role for common genetic variation in TGF-β signaling pathway genes, specifically in TGFBR2, in breast cancer susceptibility. Impact: These findings may provide new insights into the etiology of breast cancer as well as future potential therapeutic targets. Cancer Epidemiol Biomarkers Prev; 21(7); 1176–84. ©2012 AACR.