TNFSF15 polymorphisms and genetic susceptibility to lung cancer.Tumor necrosis factor superfamily member 15 (TNFSF15) is closely related to tumorigenesis and development. This study aimed to investigate the correlations between TNFSF15–638 A > G and − 358 T > C polymorphisms were genotyped by polymerase chain reaction-restrictive fragment length polymorphism (PCR-RFLP) analysis. Odds ratio (OR) and 95% confidence interval (95% CI) were estimated by unconditional logistic regression.This case-control study included 209 small cell lung cancer patients (SCLC), 340 non- small cell lung cancer patients (NSCLC) and 460 health controls. TNFSF15–638GG genotype or -358CC genotype were more likely to develop SCLC , but not NSCLC (P > 0.05). In stratified analysis, −638GG genotype was related to SCLC among males  and older patients . However, -358CC genotype was associated with SCLC among females  and older subjects with OR (95%CI) of 11.04 (3.57–34.15) (P < 0.001). Moreover, TNFSF15 -358CC was linked with a higher risk of SCLC among non-smokers  but not among smokers .Our results showed that subjects carrying the TNFSF15 polymorphisms in the development of SCLC.These findings highlight the importance of  Lung cancer is one of the most common malignant tumors worldwide and the first leading cause of cancer-related mortality in China , 2. AccoTNFSF15), also known as vascular endothelial growth inhibitor (VEGI), belongs to the TNF ligand family, which negatively regulates angiogenesis [The initiation and progression of cancer are closely linked to inflammation and angiogenesis , 6. As oogenesis . By stimogenesis , 10. Stuogenesis –15.TNFSF15 promoter by direct sequencing, and found that -358 T > C variant changed the transcriptional activity of TNFSF15 and was significantly associated with the susceptibility to gastric adenocarcinoma [TNFSF15 promoter region contributed to the risk of developing lung cancer by performing a case-control study in a Chinese population.Single nucleotide polymorphisms (SNPs) in regulatory region of a gene can influence the gene expression and further contribute to the development of various cancers –19. In oarcinoma . In the This case-control study consisted of 209 SCLC patients, 340 NSCLC patients and 460 healthy controls Table . The 549TNFSF15 genotyping. The PCR primer pairs for −638A > G (rs7848647) were 5′- AGT CAC CTC GAT CTG TGG CCTC-3′ and 5′-AAT CAC GGC TTG GAG TTG TAA CCTC-3′. The target DNA fragment containing − 358 T > C (rs6478109) was amplified with primer pairs, − 358 -PF (5′-AAA TGT GAT TTC CGT TTC CCCA-3′) and − 358 -PR (5′- AAT ATA CCT GTT CCC TGC ACTG -3′). Briefly, PCR was performed using 6 μL reaction mixture containing 10 ng DNA, 0.1 μM each primer, and 1 × Taq PCR StarMix with loading dye .The PCR thermal cycling condition consists of an initial denaturation step at 94 °C for 3 min, followed by 30 cycles of 94 °C for 40 s, 58 °C for 30 s and 72 °C for 15 s, and then a final extension step at 72 °C for 3 min. PCR products for TNFSF15–638A > G (114 bp) and -358 T > C (123 bp) were digested by Rsa I and Bcc I  and separated on 3% agarose gel. The genotypes revealed by PCR-RFLP were further confirmed by DNA sequencing , according to the manufacturer’s instructions. PCR-restriction fragment length polymorphism (PCR-RFLP) analysis were applied for 2 test. Pearson goodness-of-fit χ2 test was performed to test whether the distribution of genotypes in the control group was in accordance with Hardy-Weinberg Equilibrium (HWE). Odd ratios (ORs) and 95% Confidence interval (CI) were calculated by unconditional logistic regression model to evaluate the association of TNFSF15 genetic variations with the susceptibility to lung cancer. The smoking status of pack-years was determined as an indicator of the cumulative cigarette dose level (pack-years cigarettes per day/20 × years smoked). Light and heavy smokers were categorized by using 30 as the cut-off point [https://www.who.int). All statistical calculations were performed using SPSS version 23.0 .Quanto program was used to calculate the power of the sample size for this case-control study. The power estimation was performed, which indicated that our sample size is sufficient for the case-control study. Differences of basic characteristics in cases and control subjects were compared using the χff point . Older aP > 0.05). In terms of the amount of smoking, the significant difference was showed between lung cancer group and control group (P < 0.001 for NSCLC and P < 0.001 for SCLC). The proportion of heavy smokers in SCLC and NSCLC patients (66.4 and 61.4%) was significantly higher than that in healthy controls (32.6%).Demographic and clinical characteristics of lung cancer cases and controls are shown in Table TNFSF15–638A > G and -358 T > C variants in lung cancer patients and controls. Genotype distributions of TNFSF15–638A > G and -358 T > C in controls were conformed to be in the Hardy-Weinberg equilibrium (HWE) . We used unconditional logistic regression to assess the association of TNFSF15 SNPs with the risk of lung cancer. For the TNFSF15–638A > G polymorphism, we found that GG genotype carriers had a significantly elevated risk for developing SCLC , but not for developing NSCLC , in comparison to those with AA genotype. For the TNFSF15 -358 T > C variant, our data showed that CC genotype and CT genotype were associated with a higher risk of SCLC  as compared to TT genotype. However, we did not find that the TNFSF15 -358 T > C polymorphism was associated with the susceptibility to NSCLC with an OR(95% CI) of 1.45 (0.96–2.11) in CT carriers and an OR (95% CI) of 1.24 (0.86–1.76) in CC carriers, respectively.Tables TNFSF15–638A > G with the risk of SCLC, we performed stratification analysis , but not among females. Our data also showed that the risk of SCLC was associated with the −638GG genotype among older subjects with an OR (95% CI) of 2.93 (1.44–8.68), but not among younger subjects with an OR (95% CI) of 1.28 (0.71–2.34). However, no effect of the TNFSF15–638A > G variation on the risk of SCLC was found in stratified analysis based on smoking status.To evaluate the effect of smoking status and non-modifiable risk factors (age and gender) on the association of is Table . When stTNFSF15 -358 T > C genotypes with SCLC , but not among males. Age stratification analysis showed that there was a correlation between the CC genotype and the risk of SCLC  among elders when compared to TT carriers, but not among youngers. In addition, the CC genotype increased the risk of lung cancer among non-smokers  compared with the TT genotype.We then performed stratification analysis to evaluate the association of Small-cell lung cancer (SCLC) is a deadly tumor with poor prognosis, which originates from high-grade malignant neuroendocrine cells . AlthougTNF superfamily, is likely to inhibit the growth of tumors by suppressing neovascularization. TNFSF15 inhibits the proliferation of vascular endothelial cells in the G0 and G1 phases of cell cycle, and ultimately inhibits angiogenesis. TNFSF15 gene encodes three splice variants, namely VEGI-174, VEGI-251 and VEGI-192 depending on the number of amino acids included [VEGI-251, also known as TL1A (TNF-like molecule 1A), is the longest one of the splice variants. The combination of TL1A and DR3 (Death Receptor 3) activates different signal transduction pathways by inducing NF-kB to activate initial T cell [TNF superfamily members play an important role in cell proliferation, differentiation and apoptosis and are used for clinical treatment, or in clinical trials , 25. TNFincluded . VEGI-25l T cell  and actil T cell . These pTNFSF15 polymorphisms with the susceptibility to cancer. In our previous study, we found that TNFSF15–638A > G polymorphism was associated with the development of gastric adenocarcinoma [TNFSF15 rs6478106 is related to the risk of breast cancer in Chinese Han population [TNFSF15 variants with the susceptibility to lung cancer and found that -638A > G and -358 T > C variants elevated the risk of SCLC, but not of NSCLC. These findings suggested that the TNFSF15 polymorphisms were involved in the development of various cancer types; however, the specific mechanism is not fully clear. We speculate that the TNFSF15 genetic variation affects the expression of TNFSF15 protein and then controls the downstream signal transduction molecules. These changes affect inflammatory and immune response, and further contribute to the development of cancers. Matijja and Clara found that an intron polymorphism of TNFSF15 (rs6478108) affected the expression level of TNFSF15 and increased NOD2-induced signaling and cytokines through caspase-8–induced IL-1 [Till now, a few studies have been carried out to demonstrate the association of arcinoma . In anotpulation . In thisced IL-1 . In our ced IL-1 .TNFSF15 variants on SCLC by smoking status. Studies have shown a strong association between tobacco exposure and the development of SCLC [TNFSF15 -358 T > C polymorphism was related to SCLC among non-smokers instead of smokers, which needs more studies to explain. After stratified by smoking status, the sample size is not enough to evaluate the risk of this genetic variant with the risk of SCLC.Tobacco smoking is recognized as one of the most important risk factors contributing to lung cancer . Thus, w of SCLC , 32. Cig of SCLC , 34. TNF of SCLC . Long-te of SCLC . Our preTNFSF15–638GG genotype elevated the risk of SCLC among males and individuals aged 60 years and older. Whether gender is related to the risk of lung cancer is controversial after taking into account smoking [Age and gender are considered to be risk factors for tumor development and progression . Our stu smoking . Due to In the future, it is necessary to evaluate the usability of these polymorphisms as a low-cost NSCLC screening tool for predicting individual lung cancer risk.TNFSF15 promoter polymorphisms might be involved in the development of SCLC.Taken together, our results indicated that


ACYP2, which plays a role in calcium homeostasis, increases the risk of ototoxicity by 4.61  as well as LRP2 rs4668123 shows a cumulated Odds Ratio of 3.53 , which could not be evidenced in individual studies. Despite the evidence of heterogeneity across studies, these meta-analytic results from 30 studies are consistent with a view of a genetic predisposition to platinum-based chemotherapy mediated ototoxicity. These new findings are informative and encourage the genetic screening of cancer patients in order to identify patients with greater vulnerability of developing hearing loss, a condition having a potentially large impact on quality of life. More studies are needed, with larger sample size, in order to identify additional markers of ototoxic risk associated with platinum-based chemotherapy and investigate polygenic risks, where multiple markers may exacerbate the side-effects.Ototoxicity is one of the major side-effects of platinum-based chemotherapy, in particular cisplatin (cis-diammine dichloroplatinum II). To our knowledge, no systematic review has previously provided a quantitative summary estimate of the impact of genetics upon the risk of developing hearing loss. We searched Embase, Medline, ASSIA, Pubmed, Scopus, and Web of Science, for studies documenting the genetic risk of ototoxicity in patients with cancer treated with cisplatin. Titles/abstracts and full texts were reviewed for inclusion. Meta-analytic estimates of risk (Odds Ratio) from the pooled data were calculated for studies that have been repeated twice or more. The search identified 3891 papers, of which 30 were included. The majority were retrospective (44%), ranging from n = 39 to n = 317, some including only patients younger than 25 years of age (33%), and some on both genders (80%). The most common cancers involved were osteosarcoma (53%), neuroblastoma (37%), prostate (17%) and reproductive (10%). Most studies performed genotyping, though only 5 studies performed genome-wide association studies. Nineteen single-nucleotide polymorphisms (SNPs) from 15 genes were repeated more than twice. Meta-analysis of group data indicated that rs1872328 on  As the number of cancer survivors increases, so does the need to understand and moderate the factors that may adversely impact quality of life in survivorhood. One such factor is that of hearing loss, which has been shown in general populations to have adverse consequences for cognition2, and mental health3, if untreated. Specifically, hearing loss is a significant risk factor for dementia4. Given the vulnerability of many cancer survivors, the understanding of ototoxicity arising from cancer therapies is of high importance.Early detection and modern treatments for cancer have contributed to improved survival rates for many types and sites of disease, such that there are presently 14.5 million cancer survivors in the United States alone5, although this is still not clearly communicated to the cancer patient in the current medical practice4. The prevalence of hearing loss following cisplatin treatment is dependent upon cumulative dose6, and has been reported as being up to 90%7. Given the recent classification of hearing problems as the 4th leading cause in years lived with disability by the WHO8, interventions that cause hearing problems as a side-effect can have significant adverse consequences for quality of life. Whilst cisplatin administration leads to changes in auditory function that are detectable during and immediately after treatment, specifically bilateral progressive and irreversible high frequency hearing loss, the long-term persistent presence of the platinum compounds in the cochlea10 can increase the vulnerability to subsequent insults  and cumulate towards greater social communication impediments and burden.Treatment with cisplatin (cis-diamminedichloroplatinum II or CDDP) chemotherapy continues to be a mainstay of curative therapy for many common cancers including breast, testis, and ovarian cancer in adults, and paediatric neuroblastoma. The propensity for cisplatin to instigate cochlear dysfunction, and hence deficits in auditory sensitivity and discrimination abilities has long been known11. Through its binding to nuclear DNA, cisplatin blocks transcription and causes double-strand breaks leading to cell cycle arrest13. However, since cells from the cochlea do not proliferate, it is thought that platination of mitochondrial DNA is a more likely cause of hearing loss than nuclear DNA damage15. It is generally known that cisplatin ototoxicity has 3 major targets, hair cells, spiral ganglion neurons and the stria vascularis (the metabolic hub of the cochlea)17. Several molecular mechanisms have been described as mediators of cisplatin-induced ototoxicity. Cisplatin has been shown to target the NOX3 anti-oxidant system by causing the formation of reactive oxidative species (ROS), which in turn triggers inflammatory pathways in the cochlea and promotes apoptotic and necrotic cell death18. Downstream of ROS generation is the JNK pathway, which activates STAT-1 mediated inflammatory pathways, leading to the induction of apoptotic cascades involving caspase 3 and 919. Elegant in vitro and in vivo animal experiments have recently evidenced the involvement of the ATM-Chk2-p53 signaling pathway in cisplatin-mediated hair cell damage20. Interestingly, the stria vascularis retains platinum-based compounds for a long period of time, leading to subsequent alterations in potassium homeostasis and in the generation of the endocochlear potential, both being essential for normal hearing function21. Consequently, strial pathology could potentially contribute in disruptions in cochlear metabolic balance, production of ROS, and subsequent apoptosis of cochlear hair cells.The anti-cancer actions of cisplatin are mainly due to its interference with tumour cell proliferation22. A genetic predisposition has also been proposed based upon observations of substantial inter-individual variability in the prevalence and severity of ototoxicity23. Whilst there are multiple potential pathways for ototoxic hearing loss associated with cisplatin, the possibility of genetic susceptibility to ototoxic side effects is of interest from a number of perspectives24. The identification of polymorphisms that render individuals vulnerable to chemotherapy induced hearing loss is an important precursive step to precision individualized medicine approach that might titrate a chemotherapy regimen such that hearing loss was less likely or severe. Further, such knowledge would support translational genomic approaches in this area25. Additionally, it has been suggested that ototoxicity may act as a valid surrogate marker for other, less well defined health tissue damage associated with platinum-based chemotherapy26.Several risk factors for ototoxicity related to cisplatin chemotherapy have been identified, including poor renal function, very young or old age, gender, nutritional status, melanin content, and pre-existing cochlear hearing lossThe aim of the present study was to perform a systematic review and meta-analysis of the literature pertaining to potential genetic predisposition to ototoxicity associated with cisplatin chemotherapy in humans.).A systematic search of the literature was conducted by two of the authors (E. T. & T. N.) from 6 different databases: Embase, Medline, ASSIA, Pubmed, Scopus and Web of Science. For each database, the search was performed using the key terms: (Gene* OR genotype OR genetic) AND (tinnitus OR ototoxic* OR hearing loss OR hearing impairment OR hearing disorder OR cochleotoxicity OR deaf*) AND . Literature searches were conducted in October 2017 and updated in September 2018  on those study records included in the meta-analysis. Risk of bias criteria that were taken into consideration in this review were the study population , type of cancer , type of intervention  and measurement of hearing outcome. All these criteria were taken into account in the interpretation of the results.Forest plots were created using the Forest Plot add-in (version 8.0) for JMP 13.2.1 data analysis software to visually summarize the results from each study included in this review. The forest plots display the odds ratios (OR) and 95% confidence intervals that demonstrate the association between ototoxicity and the various genes and single-nucleotide polymorphisms (SNPs) reported in the literature. One forest plot was created to demonstrate the results for the genes tested in a single study. A second forest plot was created to compare the findings of different studies examining the same genes and SNPs and provide an estimate of the combined result of these studies. This is a meta-analysis of the data. The combined odds ratios and 95% confidence intervals were calculated using the values for the number of variant SNPs and controls in the patient groups with normal hearing and with ototoxicity after chemotherapy.2) test to ensure comparability with the literature.The number of cases from the included publications were extracted to four groups: Ototoxicity with SNP variant (OtSNP), Ototoxicity no SNP variant (Ot), Normal hearing with SNP variant (NhSNP), Normal hearing no SNP variant (Nh), and arranged the groups in a contingency table. Since the number of observations in all contingency tables considered is not too large, Fisher’s exact test serves for hypothesis testing. Although Fisher’s exact test is preferable whenever the computational power allows to carry it out, we also report results from the commonly used chi-squared  for quantifying the risk of ototoxicity. The OR for being affected by ototoxicity if also having the SNP variant was then calculated as:35, the 95% confidence interval (CI) of the odds ratio is given by:Employing the Woolf method37, that is we added 0.5 to all cells in the table for that publication. The statistical procedures were carried out using JMP 13.2.1. Values of p < 0.05 were considered significant.For tables containing empty cells (i.e. if no research subjects populated a group), we applied the Haldane-Anscombe correction47 and 80% on both genders. The ethnicity was rather broad with Northern America and Norwegians representing together the majority of the articles (14%)50. However, 12 of the papers did not specify the ethnicity of the patients55 and 4 papers did not include age56, which is a known risk factor for ototoxicity22.From the 30 included papers, 44% were retrospective with a sample size ranging from 39 to 317 59, and reporting mean values (from 328.2 to 425.5 mg/m2)45. Seven studies only reported the range60, and 3 the dose per cycle61. Only 9 studies reported the number of cycles/courses61. Regarding auditory measures, there was also a large heterogeneity. Information on the tests and metrics used was missing in 9 studies61. Sixty-three percent of the studies used pure-tone audiometry (PTA), of which 5 included auditory brainstem responses (ABR)54 and 4 included distortion products of otoacoustic emissions (DPOAE)40. However, 33% did not measure hearing at baseline, which makes the changes in hearing difficult to assess58. The average percent of patients with ototoxicity (>grade 2) was 41.8%, ranging from 8 to 75%. There were 6 different grading systems of ototoxicity used across the literature: Brock classification, CTCAE, Boston classification, Chang classification, ASHA, Muenster classification and the Standard National Cancer Institute classification. Nevertheless, in 10 papers there was no clarification of the ototoxicity grading system used55.Supplementary Table 52. Radiation to the head and neck causes ototoxic effects and is a confounding factor when investigating the ototoxic effect of chemotherapy29. Only 8 studies adjusted the statistical analysis to relevant clinical variables, such as age at diagnosis, gender, ethnic group, cumulative cisplatin dose, vincristine treatment and craniospinal irradiation doses60.Radiotherapy or other ototoxic drugs (such as aminoglycosides and vincristine) were used as part of the treatment of patients in 24 of the included studies. Six papers did not specify whether other ototoxic drugs or radiotherapy were used60. Epoxides are among the many targets of GSTs. Converging this pathway, the Epoxide Hydrolase 1 (EPXH1) rs2234922 was related to otoprotection 36. Spracklen et al. identified two SNPs predictors of cisplatin otoprotection60; rs6721961 of NFE2L2 gene, involved in the protection of cells against oxidative stress  and rs10950831 of ABCB5 gene, which contributes on the cellular efflux of cisplatin .Twenty SNPs of 9 genes were investigated once without having been repeated Fig. . Three oCTR1 rs10981694, GSTM1 and T1 deletions, GSTP1 rs1695, SLC16A5 rs4788863, XPC rs2228001 [a component of nucleotide excision repair (NER)] and XPD rs1799793. Albeit, XPD rs1799793 did not present an overall effect, was significantly ototoxic in one study 47. The low-density lipoprotein-related protein 2 (LRP2) encoding the protein megalin was shown positively associated with ototoxicity on 2 SNPs , likely due to an increase in the statistical power. Three SNPs  on the thiopurine S-methyltransferase gene (TPMT) were found significant in 2 studies43 and not in 3 others57. However, the overall pattern of the 5 studies merged together displayed significant associations with increased ototoxic risk from OR 2.47 to 2.82, with a total sample size of 786 (p < 0.0001). Another variant in COMT rs9332377 showed mixed results with 2 studies showing positive associations53, and 4 others not57, while Hagleitner et al. presented an otoprotective effect of this SNP 57. The meta-analysis showed an overall positive association but with the smallest risk of all genes . The acylphosphatase-2 ACYP2 variant rs1872328, showed in Vos et al.58 and in Xu et al.54 reports a significant association , in spite of an extremely large confidence interval . Another gene playing an important role in oxidative stress, superoxide dismutase 2, mitochondrial (SOD2), with the rs4880 showing a positive association with cisplatin ototoxicity in one of the two studies45, but also in the overall meta-analysis with an OR of 1.917  was associated with increased otoprotection , a drug clearing transporter, namely the solute carrier SLC22A2 rs316019  and rs1051640 of ABCC3 gene . Although the COMT rs4646316 variant appeared ototoxic in one study42, no significant associations were found in the other studies57 and the overall meta-analysis instead presented otoprotective associations with an OR of 0.620 (p = 0.0008).In contrast, some genes presented overall otoprotective associations in this meta-analysis such as the antioxidant polymorphism th in the leading causes of years lived with disability8. It is thus an important factor to consider when performing cisplatin interventions in patients, not only to inform patients of the risks, but also to determine whether a given individual has a greater risk and for whom the regimen of administration may be adjusted or alternatives to cisplatin being given. The confirmation that there is a non-negligible risk for ototoxicity when treating patients with cisplatin, and that this risk is influenced by genetics, is in support for greater cautiousness in considering auditory impairments that cancer patients may develop.One of the most prevalent adverse effects of cisplatin treatment is ototoxicity, in which the consequent hearing loss - although is not lethal - has a non-negligible impact on life quality. Hearing deficits are now 4LRP2 rs4668123, which emphasizes the need of considering larger sample sizes when performing such studies in order to provide more statistically solid evidence. Although our meta-analysis did not use individual data nor included adjustments , the summarized analysis emphasizes the need of large sample sizes to reveal biologically relevant associations that would otherwise been underestimated or missed.A striking finding from this systematic review is that studies with non-significant findings in isolation reached sufficient power when combined to show increased risk of developing cisplatin-induced ototoxicity. This is the case for LRP2) from repeated studies showing significant associations with cisplatin ototoxicity , which suggests its major involvement in cisplatin ototoxicity and opens the possibility for more investigations addressing the contribution of this polymorphism in cisplatin-mediated ototoxicity.We identified 8 different SNPs from 5 different genes  and gallstone disease63.With an OR ranging from 2.8 to 3.53, the TPMT gene in chromosome 664. A decreased enzymatic activity leads to myelosuppression, gastrointestinal intolerance, pancreatitis and hypersensitivity64. Here, 3 polymorphisms were found with significant OR . Mutations in COMT genes are implicated in sensorineural deafness. Hearing loss is less severe in subjects with COMT Met allele, possible due to the protective effect of dopamine on the hearing system69. While COMT has not been described in the cochlea, a homolog sharing 30% sequence identity, Comt2 was found expressed in hair cells and mice homozygous for a missense mutation in Comt2 showed sensorineural deafness due to degeneration of hair cells70. Overall, there are strong indications that catecholamines play a potential role in the auditory function. Thus, a greater vulnerability to cisplatin ototoxicity may arise when the function of the auditory system is already weakened.Of the two polymorphisms tested for SOD2 rs4880 presented an overall OR of 1.917. SOD2 catalyses the metabolism of the highly toxic superoxide anion to less but still toxic hydrogen peroxide. The SNP rs4880, which results in an exchange of valine against alanine, increases the catalytic activity of SOD2, leading to the accumulation of hydrogen peroxide and secondary ROS generation45. It is thus possible that altered mitochondrial function in the cochlea may increase the vulnerability to cisplatin ototoxicity. Notably, SOD2 polymorphisms  have also been implicated in noise induced hearing loss (NIHL)72.Another important polymorphism related with increased risk of cisplatin ototoxicity is ABCC3 rs1051640, GSTM3 rs1799735 and SLC22A2 rs316019. ABCC3 is an ATP-binding cassette member of the MRP subfamily which is involved in multi-drug resistance. This transporter regulates the efflux of organic anions, glutathione S‐conjugates and xenobiotics74. MRP expression in cancer cells correlates with resistance to cisplatin75. The mechanisms by which ABCC3 regulates cisplatin-induced hearing loss are unclear, but some studies suggest it may act upstream of GST73. Indeed, consistent with the otoprotective effects of the ABCC3 variant, GSTM3 rs1799735 shown to be otoprotective by Peters et al.40 but also in the overall analysis. GSTM3 variations are indeed thought to alter the susceptibility to potential carcinogens and toxins76. SLC22A2 is a solute carrier that encodes CTR1, which is a plasma-membrane transport-protein that has an essential role in cisplatin uptake into cochlea hair cells. Since cisplatin accumulates in the stria vascularis from the cochlea9, polymorphism that positively affects monocarboxylate transporter function may improve the strial function affected by cisplatin.Three polymorphisms, which have been evaluated twice, were found with a significant oto-protective effect, namely et al. evaluated the cumulated risks of combinations in variants of GSTT1, GSTM1 and GSTP148. Such an approach makes sense when considering that the overall results for GSTM1 and T1 appeared inconclusive 79. The incapacity of these individuals to conjugate certain metabolites may ultimately cause oxidative stress and damage to the cochlea, which would be exacerbated in presence of cisplatin. Pussegoda et al. also performed plurigenic analyses but included more complex models incorporating clinical and genetic variables43. Here the combination of TPMT rs12201199, ABCC3 rs1051640, and COMT rs4646316 in a high risk group could reach an OR of 11 (95% CI: 3.2–37.6). Such studies highlight the need of considering multigenic screens when assessing the risk for ototoxicity which may be underestimated when considering a single marker.Only two studies have evaluated polygenic effects on the vulnerability to cisplatin ototoxicity. Oldenburg ive Fig. . However10, the possibility of longer-term cochlear vulnerability (and hence progressive hearing loss) cannot be discounted. Third, ototoxic effects do not only lead to hearing loss, but also tinnitus, and vestibular toxicity80, which were not assessed in the present review, may help determining additional impacts on the auditory system that cannot be revealed with traditional audiometry. There are numerous ototoxicity grading scales used across the different studies. In the clinical trial setting, standardization is vital and the variability between different studies makes analysis more challenging81. Currently, there are 2 main categories of ototoxicity assessment criteria: (1) those measuring a change of hearing from baseline, such as the National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE), and (2) those measuring absolute hearing levels, such as the Brock or Chang classifications81. Interestingly, Spracklen et al. used the CTCAE and Chang grading scales, but also the American Speech-Language-Hearing Association criteria (ASHA), and the resulting associations differed depending on which scale is used60. As a matter of fact NFE2L2 polymorphisms presented as significantly ototoxic in ASHA and CTCAE scales (the latter of which was included in Fig. 60. As a consequence, the selection of the grading scale can have a dramatic impact on the outcome of the study. These findings highlight the needs of determining the most sensitive measures in order to standardise the methodologies into the context of genetic testing in ototoxic vulnerability.There are a number of limitations to be noted in the present study. First, our meta-analysis was performed using group data and not individual data, which pre-empted the possibility of adjusting for e.g. age at diagnosis, gender, ethnic group, cumulative cisplatin dose. Second, in all studies reviewed, hearing loss associated with cisplatin chemotherapy was assessed immediately or soon after treatment. Given that cisplatin persists indefinitely in the human cochlea after such treatment20. Knowing the genetic predisposition to cisplatin is an important advancement for improving clinical treatment but now new therapies that target specific pathways are being developed to protect against cisplatin-induced ototoxicity.Finally, whilst a genetic predisposition to cisplatin mediated sensorineural hearing loss has been identified and may help identifying cancer patients with greater ototoxic risk, the specific mechanisms remain elusive. This would be an essential precursive step to the development of oto-protective therapy together with cisplatin interventions. It has recently been demonstrated that specifically targeting the p53 pathway protects from cisplatin ototoxicity while still maintaining cancer treatment efficacySupplementary Table S1


MTNR1B) variants are associated with type 2 diabetes mellitus (T2DM) remains unclear. Therefore, we performed this meta‐analysis to better explore correlations between MTNR1B variants and T2DM.Whether melatonin receptor 1B  and 95% confidence intervals (CIs) were calculated.MTNR1B rs10830963 variant was significantly correlated with the susceptibility to T2DM . Further subgroup analyses by ethnicity of participants revealed that rs10830963 variant was significantly correlated with the susceptibility to T2DM in South Asians, but not in Caucasians or East Asians. No any other positive results were found in overall and subgroup analyses.Totally 21 studies were enrolled to analyses. Pooled overall analyses showed that MTNR1B rs10830963 variant might serve as a genetic biomarker of T2DM, especially in South Asians.Our findings indicated that  Studies were excluded if one of the following criteria was fulfilled: (a) not relevant to MTNR1B genetic variants and T2DM; (b) case reports or case series; (c) abstracts, reviews, comments, letters, and conference presentations. For duplicate publications, we only included the study with the largest sample size for analyses.To test the research hypothesis of this meta‐analysis, included studies must meet all the following criteria: (a) case–control study on correlations between 2.2MTNR1B variants in cases and controls. The probability value  of Hardy‐Weinberg equilibrium (HWE) was also calculated. When necessary, we wrote to the corresponding authors for raw data. We used the Newcastle–Ottawa scale (NOS) to assess the quality of eligible studies  name of the first author; (b) publication time; (c) country and ethnicity; (d) sample size; and (e) genotypic distributions of s Stang, . This sc2.3MTNR1B and T2DM in all possible genetic models, and P‐values ≤0.05 were considered to be statistically significant. Between‐study heterogeneities were evaluated by I2 statistic. If I2 was greater than 50%, random effect models (REMs) would be used to pool the data. Otherwise, fixed effect models (FEMs) would be employed for synthetic analyses. Subgroup analyses by ethnicity of participants were subsequently performed. Sensitivity analyses were conducted to examine the stability of synthetic results. Funnel plots were used to evaluate possible publication biases.All statistical analyses were conducted with Review Manager Version 5.3.3 . Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to estimate strength of associations between 33.1We found 370 potential relevant articles. Among these articles, a total of 21 eligible studies were finally included for synthetic analyses , two studies about rs4753426 variant , two studies about rs10830962 variant (763 cases and 811 controls), and eighteen studies about rs10830963 variant  were enrolled to analyses. A significant association with the susceptibility to T2DM was detected for rs10830963 variant  in overall analyses. Further subgroup analyses according to ethnicity of participants revealed that rs10830963 variant was significantly correlated with the susceptibility to T2DM in South Asians, but not in East Asians or Caucasians. No any other positive results were found in overall and subgroup analyses (see Table To investigate potential correlations between 3.3We performed sensitivity analyses by excluding studies that deviated from HWE. No alterations of results were detected in sensitivity analyses, which suggested that our findings were statistically reliable.3.4Publication biases were evaluated with funnel plots. We did not find obvious asymmetry of funnel plots in any comparisons, which indicated that our findings were unlikely to be impacted by severe publication biases.4MTNR1B genetic variants and T2DM, and our pooled analyses demonstrated that rs10830963 variant may be correlated with susceptibility to T2DM, especially in South Asians.To the best of our knowledge, this is so far the most comprehensive meta‐analysis on correlations between There are several points that need to be addressed about this meta‐analysis. Firstly, previous experimental studies showed that mutant allele of rs10830963 variants was correlated with altered glucose level and B‐cell function, which may partially explain our positive finding (Li et al., MTNR1B genetic variants and T2DM may also be modified by gene–gene and gene–environmental interactions. However, most eligible studies ignore these potential interactions, which impeded us to perform relevant analyses accordingly. To sum up, our findings should be cautiously interpreted on account of above mentioned limitations.Like all meta‐analyses, this study certainly has some limitations. First, our results were derived from unadjusted analyses due to lack of raw data, and lack of further adjusted analyses for potential confounding factors may impact the reliability of our findings (Xie, Shi, & Liu, MTNR1B rs10830963 variant might serve as a genetic biomarker of T2DM, especially in South Asians. However, further well‐designed studies are still warranted to confirm our findings.In conclusion, our meta‐analysis suggested that This article does not contain any studies with human participants or animals performed by any of the authors.The authors declare that they have no conflict of interest.Ling‐long Shen and Yin Jin conceived the study, participated in its design, conducted the systematic literature review, performed data analyses, and drafted the manuscript. All the authors gave final approval and agreed to be accountable for all aspects of work ensuring integrity and accuracy. Click here for additional data file.


Background: Recently, the roles of tumor necrosis factor-α (TNF-α) polymorphisms in colorectal cancer (CRC) were analyzed by some pilot studies, with inconsistent results. Therefore, we performed the present study to better assess the relationship between TNF-α polymorphisms and the risk of CRC.Methods: Eligible studies were searched in PubMed, Medline, Embase and CNKI. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess correlations between TNF-α polymorphisms and CRC.Results: A total of 22 studies were included for analyses. A significant association with the risk of CRC was detected for TNF-α -308 G/A  polymorphism in overall analyses. Further subgroup analyses based on ethnicity of participants revealed that TNF-α -238 G/A was significantly correlated with the risk of CRC in Caucasians , while -308 G/A polymorphism was significantly correlated with the risk of CRC in Asians .Conclusions: Our findings indicated that TNF-α -238 G/A polymorphism may serve as a potential biological marker for CRC in Caucasians, and TNF-α -308 G/A polymorphism may serve as a potential biological marker for CRC in Asians. Colorectal cancer (CRC) refers to malignancy that occurs in the colon and rectum. It is the third most commonly seen cancer in men, and the second commonly seen cancer in women . DespiteTNF-α polymorphisms were thought to be ideal candidate genetic markers of CRC. Recently, some pilot studies were conducted to investigate associations between TNF-α polymorphisms and the risk of CRC. But the results of these studies were conflicting [TNF-α polymorphisms in the development of CRC.Tumor necrosis factor-α (TNF-α) plays a central role in the regulation of anti-tumor immune responses. Previous clinical investigations showed that serum TNF-α levels in CRC patients were significantly elevated , and patflicting . TherefoThis meta-analysis was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guideline . PotentiTNF-α polymorphisms and the risk of CRC; (2) provide adequate data to calculate odds ratios (ORs) and 95% confidence intervals (CIs); (3) full text available. Studies were excluded if one of the following criteria was fulfilled: (1) not relevant to TNF-α polymorphisms and CRC; (2) family-based association studies; (3) case reports or case series; (4) abstracts, reviews, comments, letters and conference presentations. For duplicate reports, only the study with the largest sample size was included. No language restrictions were imposed in this meta-analysis.Included studies should meet all the following criteria: (1) case–control study on correlations between TNF-α polymorphisms in cases and controls. Additionally, the probability value  of Hardy–Weinberg equilibrium (HWE) test was also calculated based on genotypic frequency of TNF-α polymorphisms in the control group.The following data were extracted from included studies: (1) name of the first author; (2) year of publication; (3) country and ethnicity of participants; (4) the number of cases and controls and (5) genotypic distributions of The Newcastle–Ottawa scale (NOS) was employed to assess the quality of eligible studies from three aspects: (1) selection of cases and controls; (2) comparability between cases and controls and (3) exposure in cases and controls . The NOSTwo reviewers (Huang and Qin) conducted data extraction and quality assessment independently. When necessary, the reviewers wrote to the corresponding authors for extra information or raw data. Any disagreement between two reviewers was solved by discussion with the third reviewer (Jiang) until a consensus was reached.TNF-α polymorphisms with the risk of CRC in the dominant, recessive, overdominant and allele models, and a P value of 0.05 or less was considered to be statistically significant. Between-study heterogeneity was evaluated based on Q test and I2 statistic. If P value of Q test was less than 0.1 or I2 was greater than 50%, random-effect models (REMs) would be used for analyses due to the existence of significant heterogeneities. Otherwise, fixed-effect models (FEMs) would be applied for analyses. Subgroup analyses by ethnicity of participants were subsequently conducted to obtain more specific results. Sensitivity analyses were carried out to test the stability of the results. Funnel plots were applied to evaluate possible publication bias.All statistical analyses in the present study were conducted with Review Manager Version 5.3.3 . ORs and 95% CIs were used to assess potential associations of The literature search identified 389 potentially relevant articles. After exclusion of irrelevant and duplicate articles by reading titles and abstracts, 42 articles were retrieved for further evaluation. Another 20 articles were subsequently excluded after reading the full text. Finally, a total of 22 eligible studies were included in this meta-analysis see . CharactTNF-α polymorphisms with the risk of CRC, 7 studies about TNF-α -238 G/A polymorphism (901 cases and 1179 controls), 20 studies about TNF-α -308 G/A polymorphism (4412 cases and 5528 controls), 5 studies about TNF-α -857 C/T polymorphism (1045 cases and 1032 controls), 2 studies about TNF-α -863 C/A polymorphism (464 cases and 464 controls) and 3 studies about TNF-α -1031 T/C polymorphism (664 cases and 664 controls) were enrolled for analyses. A significant association with the risk of CRC was detected for TNF-α -308 G/A  polymorphism in overall analyses.To investigate potential correlations of TNF-α -238 G/A was significantly correlated with the risk of CRC in Caucasians , while -308 G/A polymorphism was significantly correlated with the risk of CRC in Asians . No any other positive results were found for investigated polymorphisms in overall and subgroup analyses . In further stratified analyses, a great reduction in heterogeneity was found in the Asian subgroup. However, the reduction tendency of heterogeneity in Caucasians was not obvious. These findings suggested that differences in ethnic background could partially explain observed heterogeneities between studies.TNF-α polymorphisms and CRC may also be influenced by gene-gene and gene-environmental interactions. However, the majority of studies did not consider these potential interactions, which impeded us to perform relevant analyses accordingly [As with all meta-analysis, the present study certainly has some limitations. First, our results were based on unadjusted estimations due to lack of raw data, and failure to perform further stratified analyses according to age, gender and co-morbidity conditions may affect the reliability of our findings ,35. Secoordingly ,38. TakeTNF-α -238 G/A polymorphism may serve as a potential biological marker for CRC in Caucasians, and TNF-α -308 G/A polymorphism may serve as a potential biological marker for CRC in Asians. However, further well-designed studies are warranted to confirm our findings. Additionally, future investigations are needed to explore potential roles of other TNF-α polymorphisms in the development of CRC.Overall, our meta-analysis suggested that


The effect of nitric oxide (NO) on renal function is controversial in critical illness. We performed a systematic meta-analysis and trial sequential analysis to determine the effect of NO gas on renal function and other clinical outcomes in patients requiring cardiopulmonary bypass (CPB). The primary outcome was the relative risk (RR) of acute kidney injury (AKI), irrespective of the AKI stage. The secondary outcome was the mean difference (MD) in the length of ICU and hospital stay, the RR of postoperative hemorrhage, and the MD in levels of methemoglobin. Trial sequential analysis (TSA) was performed for the primary outcome.I2 = 0%). In the subgroup analysis by NO initiation timing, NO did not decrease the risk of AKI when started at the end of CPB . However, NO did significantly reduce the risk of AKI when started from the beginning of CPB . We conducted TSA based on three trials (400 patients) using KDIGO criteria and with low risk of bias. TSA indicated a CI of 0.50–1.02 and an optimal information size of 589 patients, suggesting a lack of definitive conclusion. Furthermore, NO does not affect the length of ICU and hospital stay or the risk of postoperative hemorrhage. NO slightly increased the level of methemoglobin at the end of CPB , but it was clinically negligible.54 trials were assessed for eligibility and 5 studies (579 patients) were eligible for meta-analysis. NO was associated with reduced risk of AKI (RR 0.76, 95% confidential interval [CI], 0.62 to 0.93, NO appeared to reduce the risk of postoperative AKI in patients undergoing CPB. Additional studies are required to ascertain the finding and further determine the dosage, timing and duration of NO administration. Acute kidney injury (AKI) is a multifactorial and common complication in patients undergoing cardiopulmonary bypass (CPB), as it occurs in 30–70% of patients –4. CPB lNO regulates vascular tone and distal blood perfusion while also acting as an anti-inflammatory and anti-thrombotic mediator . NO gas We hypothesized that the effect of NO on kidney function might be disease specific, as two of the RCTs in the meta-analysis of Ruan et al.  showed tWe performed a meta-analysis aiming to ascertain the effect of NO therapy on renal function in patients undergoing CPB and to further investigate whether the effect of NO varies between different initiation time points of such therapy.This systematic review and meta-analysis was registered on PROSPERO (NO. CRD42019125948) based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines .Two trained investigators (J.H. and J.P.) independently searched pertinent studies in PubMed, Cochrane Central Register of Controlled Trials (CENTRAL), Embase, Web of Science, and Clinicaltrial.gov from inception through December 2018, with the help of a librarian from the Countway Library at Harvard Medical School. Details of our search strategy are described in Additional file Two investigators  independently searched if the eligible studies met the following PICOS criteria: (1) population: patients undergoing CPB; (2) intervention: NO delivery either from the beginning of CPB or at the end of CPB; (3) comparison intervention: placebo or no therapy; (4) outcome: the relative risk of postoperative AKI; and (5) study design: randomized controlled trials (RCTs).There were no restrictions on the dose or time of NO administration. We included unpublished trials only if trial data and methodological descriptions were provided either in written form or could be retrieved from the trial authors. No language restriction was enforced. The exclusion criteria included crossover trials and studies not reporting the renal outcome.Two authors (J.H. and J.P.) independently assessed the selected studies for the final analysis, with disagreements resolved by discussion and, if needed, via a third author (LB), who acted as an adjudicator. A standardized recording form was used for data extraction.The primary outcome was the risk of AKI, irrespective of the AKI stage. The secondary outcome was as follows: the length of ICU and hospital stay, the risk of postoperative hemorrhage , and the levels of methemoglobin (MetHb) at the end of CPB.Quality assessment of the screened studies was performed using the Cochrane Collaboration tool  by two iWe calculated the pooled risk ratios (RR) and 95% confidence intervals (CI) for the binary outcome of AKI, and postoperative hemorrhage using the Mantel–Haenszel method with the random-effects model. We estimated the mean difference (MD) and 95% CI for continuous outcomes of the length of ICU and hospital stay and the levels of MetHb using the inverse variance method with the random-effects model. If continuous variables were expressed as a median and interquartile range, the mean and standard deviation were computed based on the median, interquartile range, and sample size as described elsewhere .I2 statistic [Considering that the inclusion of fewer than ten studies in meta-analysis causes low statistical power for detecting funnel plot asymmetry , we assetatistic .We performed a subgroup analysis to investigate whether the effect of NO on AKI varied based on the timing of NO therapy initiation, i.e., starting from the beginning of CPB or at the end of CPB (immediately before the weaning of CPB).We performed sensitivity analyses to determine the robustness of the effect size using different data analysis methods. First, we used the Peto method, since it may be the least biased in the presence of sparse data and imbalance of sample size within trials . Second,We conducted trial sequential analysis (TSA) to quantify the statistical reliability of data in the cumulative meta-analysis and adjusted significance levels for the risk of random errors due to repetitive testing on accumulating data . For thihttp://www.ctu.dk/tsa) and R v.1.1.456  with the “metafor” and “meta” packages.Statistical analyses were conducted using Review Manager v.5.3 , Trial Sequential Analysis v.0.9.5.10 beta  based on 30% RRR (from a baseline event rate of 50.8%).To decrease the risk of random errors due to sparse data or repetitive testing and calculate the optimal information size for this meta-analysis, we performed TSA based on three trials that used KDIGO criteria and were considered to have a low risk of bias (400 patients). Although the cumulative ize Fig. . Based op = 0.15, I2 = 0%, Additional file p = 0.14, I2 = 27%, Additional file For the secondary outcomes, there appeared to be no benefit of NO on the length of ICU and hospital stay, with MD of − 0.09 day   [In comparison, there is no obvious NO deficiency in ARDS. Instead, intrapulmonary NO generation due to inducible NO synthase was found in an experimental model of endotoxemia-induced ARDS and finally proved to be involved in the development of ARDS . Moreove2) , and cre2) . Based oOur second question is: does the effect of NO on renal function vary by the timing of initiation? To answer to this question, one should consider the differences in renal dysfunction definition adopted in the five studies included in our meta-analysis. The first two studies in which NO was administrated at the end of CPB, renal dysfunction was defined as severe AKI  are damaged when passing through the CPB circuit  and thus2O [Moreover, hemolysis-induced NO consumption increased pulmonary vascular resistance , thereby2O . Further2O –48 or in2O , 50 did 2O . FurtherAlthough NO appears to improve renal function in patients requiring CPB, possible adverse effects need to be monitored during gas delivery. Hemorrhage is one of the common concerns of NO treatment in cardiac surgery patients undergoing CPB. NO ha been shown to inhibit platelet activation in in vitro studies  and pote3+) has a lower capacity to bind oxygen compared to oxy-hemoglobin (Fe2+), which may lead to decreased delivery of oxygen to the peripheral tissues and, consequent, tissue hypoxia. It is generally accepted that blood MetHb levels in healthy individuals is less than 2% of the hemoglobin [The monitoring of MetHb levels in the blood is warranted during NO delivery. MetHb (Femoglobin . Cyanosimoglobin . Our metmoglobin , 19. Meamoglobin  and Kamemoglobin .This study has some limitations. First, the small number of studies included in our meta-analysis may have reduced the statistical power of the analysis. To balance our interpretation, we performed trial sequential analysis, which accounts for the type I, and type II errors, using widely accepted, methods for adjusting thresholds for significance in randomized clinical trials when the required sample size has not been reached .Second, although the level of statistical heterogeneity was very low in our analyses, the heterogeneity in other independent variables including AKI diagnosis criteria, duration and dosage of NO therapy, and time of CPB should not be overlooked. Over the past decades, the diagnostic criteria for AKI and AKI stage definitions have changed, i.e., decades ago common medical terminology referred to acute renal failure to describe kidney injury in acute settings, subsequently, the RIFLE criteria introduced the term AKI , the AKIFinally, some competing endpoints, such as 28- or 90-day mortality, the impact of different dose and duration of NO on renal function, and the right heart function were not reported in the present study.In our meta-analysis, we found that NO appeared to reduce the risk of postoperative AKI in patients undergoing CPB, suggesting that the effect of NO on renal function might be disease specific. Future trials involving NO therapy are required to consolidate our findings and investigate potential mechanisms of renal protection properties.Additional file 1. Search strategy.Additional file 2. Risk of bias graph.Additional file 3. Funnel plot for the primary outcome.Additional file 4. Forest plot for the Peto method. OR, odds ratio. CI, confidential interval; AKI, acute kidney injury; NO, nitric oxide.Additional file 5. Forest plot for sensitivity analysis including studies that had lower risk of bias and reported AKI using KDIGO criteria. RR, risk ratio. CI, confidential interval; AKI, acute kidney injury; NO, nitric oxide.Additional file 6. Forest plot for the length of ICU stay. MD, mean difference. SD, standard deviation; CI, confidential interval; NO, nitric oxide.Additional file 7. Forest plot for the length of hospital stay. MD, mean difference. SD, standard deviation; CI, confidential interval; NO, nitric oxide.Additional file 8. Forest plot for the risk of postoperative hemorrhage, i.e., requiring blood transfusion after the operation or reoperation. RR, risk ratio. CI, confidential interval; NO, nitric oxide.Additional file 9. Forest plot for levels of methemoglobin at the end of CPB, %. MD, mean difference. SD, standard deviation; CI, confidential interval; NO, nitric oxide; CPB, cardiopulmonary bypass.


Many studies have analyzed the relationship between cereal, whole, or refined grain and the risk of gastric cancer (GC) and have yielded mixed results. Therefore, we performed a meta‐analysis of observational studies to summarize the available evidence on this topic. Databases such as PubMed, EMBASE, Web of Science, MEDLINE, and the Cochrane Library were searched for studies focusing on these associations from inception to October 2017. Summary odd ratios (OR) and 95% confidence intervals (CI) were calculated by using either a random‐ or fixed‐effect model according to the between‐studies heterogeneity. Subgroup analysis was also performed. In total, eleven studies that included 530,176 participants were identified. In a pooled analysis of all studies, cereal exposure was not associated with GC risk . Specific analyses indicated that whole grain consumption was associated with decreased GC risk  and that refined grain consumption was associated with increased GC risk . Higher whole grain and lower refined grain intake but not cereal consumption reduces GC risk. This study has been registered at ClinicalTrials.gov (ID: NCT03419663). The following three themes of medical terms were used in combination:  AND (gastric OR stomach) AND . The reference lists of included articles and published systematic reviews or meta‐analyses were carefully assessed to identify additional studies as well. Moreover, we contacted first authors to ask for additional information when necessary.2.2The criteria for study selection were as follows: (a) a case–control study or cohort study; (b) investigation of the association between cereal or grain intake and GC occurrence; (c) the odds ratio (OR) or relative risk (RR) with confidence intervals (CI) or data necessary to estimate these statistics were provided. We excluded GC mortality‐based cohort studies. If a study was reported multiple publications, we generally selected the most recent one with the largest sample size.Eligible studies were independently evaluated by two authors (Yujie Xu and Yong Zhou), and a third author (Ka Li) resolved any discrepancies. For each study, the following data were extracted into data collection form: abbreviation of the main researcher's name, publication year, study design, participants’ nationalities, follow‐up duration, numbers of cases (patients diagnosed with GC) and participants, categories of cereal consumption, quantities of cereal intake in each category, adjusted OR or RR with corresponding 95%CI for the highest versus the lowest intake as well as across more than two exposure levels in each category, and adjustment factors.2.3The PRISMA checklist was used as a protocol and guideline of this meta‐analysis. We investigated the association between cereal intake and GC risk based on the effect estimates and their 95%CI in each included report. The OR mathematically approximates the RR in case–control studies owing to the low rates of GC; therefore, the measure of effect is OR along with 95%CI in our meta‐analysis. For the pooled analysis, we used either fixed‐effect models when heterogeneity was low or random‐effect models that take heterogeneity within and between studies into account to calculate the summary OR.I2 statistics were used to assess statistical heterogeneity across studies. A p value <0.10 for the Q test or I2 >50% was considered to indicate heterogeneity. Subgroup analysis according to study design and cereal consumption categories was also conducted to evaluate the potential source of heterogeneity.The Cochran's Q test and p < 0.05. We also carried out a traditional sensitivity analysis and excluded a study with extreme data to explore whether the results were stable or driven by a specific study. All quantitative analyses were conducted by using Stata software .The presence of publication bias was investigated by using the Begg's and Egger's tests, and the results were considered to indicate potential bias at 33.1Figure 3.2A summary of study characteristics of individual studies is presented in Table 3.3I2 = 52.4%, p for heterogeneity = 0.12) and refined grain . For intake of other grains, which was not significantly associated with GC risk, the pooled OR was 1.04 , and heterogeneity was significant . The results of main analysis and specific analyses are reported in Table For the analyses of the relation of GC with cereal or grain consumption, we included nine case–control studies and two cohort studies presenting data on the issue. In the pooled analysis of all studies, cereal exposure was not associated with risk of GC . Specific analyses for cereal, whole grains, refined grains, and other grains were also conducted. Among the two case–control studies and one cohort study assessing whole grain or refined grain consumption, higher whole grain intake was related to a statistically significant decrease in GC morbidity risk , while a higher category of refined grain intake increased the incidence of GC . In addition, the meta‐analysis revealed substantial heterogeneity across studies with low intake of whole grains .Sensitivity analyses were further carried out, excluding a study with extreme data, and the results obtained were essentially unchanged compared with those of the main analysis. Begg's and Egger's tests Figures  and 4 we4We meta‐analyzed the evidence regarding the relationship between cereal or grain consumption and the risk of GC. Our meta‐analysis indicated that higher whole grain intake was associated with lower GC risk, higher refined grain intake was associated with higher risk of GC, and no association was found between overall cereal and GC risk.A previous meta‐analysis  whole grain is made up of germ, endosperm, and bran, and the latter two contain a large amount of nutrients. Refined grain includes only the endosperm. Moreover, whole grain is a major source of dietary fiber, vitamins, and several minerals Stephen, . (b) TheInterestingly, studies have confirmed that whole grain intake had an inverse association with other cancers. Levi et al.  conducteTo our knowledge, this was the first meta‐analysis performed to summarize the effect of cereal intake on GC risk. First, the extensive search strategy was conducted to identify all relevant global publications. Second, another strength of this study was the large number of participants from Asia, America, and Europe, allowing further subgroup analyses. Third, although different types of studies, such as case–control and cohort studies, were included, between‐study heterogeneity was small, and publication bias was not found.There are also several limitations in our study. First, we found no data on some tumor types (such as cardia GC or noncardia GC) that deserve attention by clinical researchers. Therefore, we need more investigation into the association of cereals with the risk of different types of GC. Second, most of the studies in this meta‐analysis were case–control studies. Third, the number of studies for the whole grain and refined grain analyses was small. Finally, although all included studies were adjusted for potential confounding factors, we cannot exclude the possibility that some other unmeasured factors might be responsible for the inverse relationship.In conclusion, intake of higher whole grains and lower refined grains but not cereal reduces GC risk. Our findings may provide useful evidence for public health researchers and help provide a proposal for appropriate cereal food consumption among healthy citizens in the near future. However, further well‐designed studies are still needed.The authors declare that they do not have any conflict of interest.The authors’ responsibilities were as follows—YJX, YZ, and KL: designed the study; YZ and YJX: conducted the library search and wrote the manuscript; YZ and JY: extracted and controlled the data; YJX and LD: analyzed the data; YZ and KL: had primary responsibility for the final content; and all authors: read and approved the final manuscript.This study does not involve any human or animal testing, and all analyses are based on previous published studies, thus no ethical review and patient consent are required.


Background: Chitinase 3-like 1 (CHI3L1) is involved in the Th2 cell mediated pathway, tissue remodeling and fibrosis. Correlations of CHI3L1 gene polymorphisms with asthma in previous studies have been inconsistent. The present study was designed to investigate the association between CHI3L1 polymorphisms and asthma in the southwest Chinese Han population. Methods: Two single nucleotide polymorphisms (SNPs), rs4950928 and rs10399931, were genotyped in 410 asthma patients and 418 healthy controls from Southwest China. Dual-luciferase reporter gene analysis was performed to detect allele-dependent promoter activity of CHI3L1 variants in HEK293 cells. Real-time quantitative PCR was applied to detect the relative mRNA expression associated with different genotypes of CHI3L1 rs10399931. A meta-analysis was performed using data collected from previously published reports and the present study. Results: No significant association was found between rs4950928 and asthma. The rs10399931 CT/TT genotype increased the risk of asthma under the dominant model , while the CT genotype showed the same tendency under the heterozygous model . No statistically significant difference was found between alleles T and C of rs10399931in the dual-luciferase reporter gene analysis (P = 0.201). The rs10399931 CT/TT genotypes reduced the relative mRNA expression detected by real-time quantitative PCR (P = 0.002). There was no significant association between the CHI3L1 rs4950928 polymorphism and the risk of asthma in the meta-analysis. Conclusion: In the southwest Chinese Han population, the CHI3L1 rs10399931 CT/TT genotypes may increase the risk of asthma. rs10399931 may be a functional variant of CHI3L1 due to its effect on mRNA expression. Asthma is a complex airway disorder characterized by chronic airway inflammation, bronchial hyper-responsiveness and reversible airway obstruction. Currently, 300 million patients worldwide are suffering from this disease and the number may increase to 400 million by 2025 .HI3L1), localized at chromosome 1q32.1, encodes the YKL-40 protein. CHI3L1 was identified as an asthma susceptibility locus that was also related to airway hyper-responsiveness and decline in lung function in a population of European descent in a genome-wide association study (GWAS) [CHI3L1 and YKL-40 protein are involved in the Th2 cell mediated inflammatory pathway, tissue remodeling and fibrosis [CHI3L1 with adult asthma in a southwest Chinese Han population.Although the exact etiology of asthma is still uncertain, it is considered as a heterogeneous disease caused by the interaction of genetic and environmental factors. The incidence of asthma varies in different countries and ethnicities . Chitinafibrosis . HoweverAll subjects were unrelated Chinese Han individuals recruited from the West China Hospital of Sichuan University from 2014 to 2016. Informed consent was obtained from every participant in this case and control study which was approved by the ethical committee of the West China Hospital of Sichuan University .The 410 asthmatic patients were diagnosed by physicians in the respiratory clinic according to the criteria of the Global Strategy for Asthma Management and Prevention . SubjectA blood sample was drawn from every subject and stored in a −80°C freezer. Clinical information including sex, age, body mass index (BMI), smoking history and the age of asthma onset, was collected from the medical records, questionnaire and telephone follow-up. Spirometry was performed in the pulmonary function test department of the West China Hospital. The forced expiratory volume in the first second (FEV1) and forced vital capacity (FVC) were measured and expressed as percent of predicted (FEV1PP and FVCPP).r2 <0.8 in Han Chinese in Beijing, China (CHB) in 1000 genomes (http://grch37.ensembl.org/Homo_sapiens/Info/Index). Genomic DNA was isolated from the peripheral blood using a genomic DNA purification kit . SNPs were genotyped by Genesky Bio-Tech Co., Ltd (http://geneskybiotech.com/index.html) using the SNPscan™ multiplex SNP genotyping technique. The probes and primers were designed by the SpectroDESIGNER software . In addition, 5% of random samples were repeatedly genotyped with a concordance rate of 100%. The JASPAR database (http://jaspar.genereg.net/) and F-SNP database (http://compbio.cs.queensu.ca/F-SNP/) were used to predict the function of asthma susceptibility SNPs.rs4950928 and rs10399931 were selected after literature review. The minor allele frequency (MAF) of the two single nucleotide polymorphisms (SNPs) were 0.146 and 0.359, respectively, with CHI3L1 was detected by the dual-luciferase reporter gene system. HEK293 cells were transfected with the Firefly luciferase reporter plasmid pGL3-basic  under the control of the CHI3L1 promoter region containing each allele of rs10399931. The pRL-CMV renilla luciferase reporter plasmid  was cotransfected for normalization of transfection efficiency, and Dual-Luciferase reporter assays were read 24 h later with a GloMax 96 Microplate Luminometer. RNAs of 52 subjects were extracted from the whole blood stored in Tempus™ Blood RNA Tubes by Terpus™ Spin RNA Isolation Reagent Kit , then reverse transcribed to cDNA by PrimeScript™ RT reagent Kit with gDNA Eraser  . Real-time quantitative PCR was applied to detect the relative mRNA expression with different genotypes of CHI3L1 rs10399931 with QuantiNova™ SYBR Green PCR Kit .The allele-dependent promoter activity of www.cnki.net) and Wanfang database (www.wanfangdata.com.cn) for all the eligible literature published up to February 2019 using the key search terms: (‘CHI3L1’ or ‘chitinase 3–like 1’), (‘single nucleotide polymorphism’ or ‘SNP’ or ‘polymorphism’ or ‘variation’ or ‘mutation’) and (‘asthma’ or ‘asthmatic’). The language was restricted to English or Chinese but there was no other limitation of any type in the literature searches. In addition, we manually searched the references of relevant publications. All analyses in the current meta-analysis were based on previously published studies and our present study. The inclusion criteria were: (1) studies with a case-control design and the diagnosis criteria of asthma according to international criteria [CHI3L1 polymorphism and risk of asthma; (3) studies that provided sufficient data on the genotypic and allelic distributions of CHI3L1polymorphisms. Exclusion criteria were as follows: (1) studies without control groups; (2) studies with no available data reported and extracted; (3) reviews, letters, abstracts, animal experiments, GWAS studies, epigenetic studies, or overlapping and irrelevant studies. Two independent authors (Guo Chen and Miao-Miao Zhang) extracted the detailed information and data from each primary study. The correspondent author (Jian-Qing He) reviewed these articles, if there was any doubt.We searched the electronic databases of PubMed, Embase, China National Knowledge Infrastructure  with 95% confidence intervals (95% CI). Linkage disequilibrium (LD) was calculated using the SHEsis online software .All analyses were performed using the Statistical Package for the Social Sciences , version 17.0. All data were expressed as the mean ± standard deviation. Comparisons of the cases and controls were conducted using Pearson’s Chi-squared test. Continuous variables were analyzed using the Mann–Whitney Q-test and I-squared (I2) test were used to assess the between-study heterogeneity. A P-value of <0.10 or an I2-value of >50% suggested a statistically significant heterogeneity. A fixed-effect model was used for non-heterogeneous studies (Mantel–Haenszel method) and a random-effect model was used for heterogeneous studies (M–H heterogeneity method). Publication bias was evaluated by Begg’s funnel plot and Egger’s regression test. Hardy–Weinberg equilibrium (HWE) was tested in the control group for each study by the Chi-squared test. Statistical significance was defined as P<0.05 except the between-study heterogeneity analysis.The meta-analyses were performed with STATA version 12.0 . The chi-squared-based Baseline characteristics of the 410 cases and 418 controls are presented in P = 0.031, OR = 1.428, 95% CI, 1.033–1.974) and genotype CT was associated with increased risk of asthma under the heterozygous model . No significant association was found between the rs4950928 and asthma under different genetic models. The LD between rs4950928 and rs10399931 was 0.27 (P>0.05) (All subjects were successfully genotyped and no deviation from Hardy–Weinberg equilibrium was observed. The association results are presented in was 0.27 . There w(P>0.05) .CHI3L1, was predicted to be a possible functional SNP with regulatory effects on gene transcription. The luciferase activity of rs10399931 allele C was higher than allele T in the dual-luciferase reporter gene analysis. However, there was no statistically significant difference between the two alleles (P = 0.201) (P = 0.002)  . Compare= 0.002) .CHI3L1 with asthma. A total of 95 articles were identified in the initial searches of the above databases. Finally, 10 case–control studies from 9 published articles [We only successfully performed a meta-analysis of the relationship between rs4950928 and asthma due to the lack of association studies of other variants, including rs10399931, in articles  and our CHI3L1 rs4950928 polymorphism and the risk of asthma for all genetic models. Furthermore, subgroup analyses based on ethnicity and age were performed. Although the P value of the association between rs4950928 polymorphism and asthma was 0.046 among Asians under the allele model, it was close to 0.05 and I2 was >50% indicating a large heterogeneity detected in the result. Therefore, the result was not convincing and we did not consider that the rs4950928 variant contributed to the risk of asthma among Asians. Moreover, there was no significant association in the other subgroups (P > 0.05)  of n genome  and is an genome .CHI3L1, rs4950928 and rs10399931 were frequently reported in many association studies of CHI3L1 genetic polymorphisms and asthma. However, the results in different populations were inconsistent and controversial. Ober et al. [CHI3L1 expression in Caucasian and Yoruban African asthmatic individuals. James et al. [CHI3L1 rs4950928 CC genotype was associated with higher YKL-40 levels than the GG genotype in preschool children with wheeze. Interestingly, Rathcke et al. [As promoter SNPs of r et al.  revealeds et al.  found the et al.  reportede et al. , which we et al.  in Europe et al.  did not As for rs10399931, there were also inconsistent results in a variety of studies. Verlaan et al.  confirmeIn our study, we did not find an association between rs4950928 and asthma. The rs10399931 genotypes CT/TT were associated with increased risk of asthma under the dominant model and there was a similar association with genotype CT under the heterozygous model. Although the rs10399931 T and C alleles increased the luciferase activity, there was no significant difference between the two alleles. The relative mRNA expression of the rs10399931CC genotype was higher than CT/TT genotypes. Parts of the above results were consistent with some previous studies. We speculate the reasons for this discrepancy as follows: Firstly, the allele and genotype frequency, as well as LD between rs4950928 and rs10399931 differ in different ethnic populations. This provides a potential reason that results may not always replicate in other populations. Asthma is caused by the interaction of environmental and genetic factors and there are several asthma phenotypes. Therefore, even though the subjects were from the same ethnic group, different environmental exposures, geographical distributions and habits may lead to diversity in the pathogenesis and regulation of disease. In the study by Tsai et al. , the ethCHI3L1 polymorphisms and asthma, a meta-analysis was performed using data collected from previously published reports and the present study. Unfortunately, only the rs4950928 meta-analysis was successfully conducted. Analysis of the other variants was not performed, as the number of the published articles was too small. We failed to find any association between rs4950928 and asthma in the overall analysis as well as in the stratification analysis, which was consistent with the current study. Due to the high heterogeneity of the relation between rs4950928 and asthma in the Asians under the allele model, the result was unreliable. Therefore, further meta-analysis is needed to include more eligible articles published in the future. This was an updated meta-analysis drawing the same conclusion as the report by Xu et al. [In addition, due to the ambiguous results of different studies on the relationship between u et al. , one of u et al. . The othu et al.  but onlyCHI3L1 and asthma in the southwest Chinese Han population and there are some limitations. As the effect of each single polymorphism on asthma susceptibility was weak, we did not correct the results for multiple testing to due to its conservative nature. Furthermore, it would have been better to include more SNPs of CHI3L1 to be tested in this association study, including rs12141494 [This was the first association study between 12141494  and rs1012141494 . FurtherCHI3L1 was a susceptibility locus for asthma in the southwest Chinese Han population and rs10399931 may be a functional variant of CHI3L1. The rs10399931 CT/TT genotypes may increase the risk of asthma and reduce the relative mRNA expression. There was no significant difference between allele C and T in the transcriptional regulation activity.In conclusion,


Blood metabolites including homocysteine (7 µmol/L), methyl-folate (40 nmol/L) with total gene mutations (≥4); age (51 years) and vegetable intake (2 cups), and interactions of gene mutations and methylmalonic acid (MMA) (400 nmol/L) were significant predictors  using the AICc. The results were validated by a 3% misclassification rate, AICc of 26, and >99% area under the receiver operating characteristic curve. These results point to the important roles of blood metabolites as potential markers in the prevention of CRC. Future intervention studies can be designed to target the ways to mitigate the enzyme-metabolite deficiencies in the OCM pathway to prevent cancer.For personalized healthcare, the purpose of this study was to examine the key genes and metabolites in the one-carbon metabolism (OCM) pathway and their interactions as predictors of colorectal cancer (CRC) in multi-ethnic families. In this proof-of-concept study, we included a total of 30 participants, 15 CRC cases and 15 matched family/friends representing major ethnic groups in southern California. Analytics based on supervised machine learning were applied, with the target variable being specified as cancer, including the ensemble method and generalized regression (GR) prediction. Elastic Net with Akaike’s Information Criterion with correction (AICc) and Leave-One-Out cross validation GR methods were used to validate the results for enhanced optimality, prediction, and reproducibility. The results revealed that despite some family members sharing genetic heritage, the CRC group had greater combined gene polymorphism-mutations than the family controls ( We also investigated three additional genes in the pathway: Dihydrofolate reductase (DHFR) 19 base pair (19bp) (rs70991108) which converts folic acid into methylenetetrahydrofolate (MTHF) or methyl-folate as usable folate form [methionine synthase  in the methylation cycle, and methionine synthase reductase  which converts/recycles homocysteine back to usable methionine for the methylation cycle [We examined five genes in the OCM pathway, including two loci of T rs18011 and A129trations . MTHFR pate form ,38, methon cycle ,41,42. TMTHFR and related gene mutations in the OCM methylation pathways [Key methyl-donors related to these genes include folate (vitamin B9) and vitamin B12, that play an integral role in the phenotypic expression of pathways ,34,35,36pathways , was to pathways ,45,46,47pathways ,49,50,51The study methods were reported before ,52 and aDemographic data included lifestyle and dietary status ,52,53, fS-adenosylmethionine (SAM), S-adenosylhomocysteine (SAH), betaine, choline, methionine, cystathionine were quantified by LC-ESI/MS/MS methods described previously [Gene polymorphism and metabolite analysis were performed at the Center of Metabolomics, Baylor Scott & White Research Institute, Dallas, TX, USA. Data sent to the laboratory were de-identified for subjects. Laboratory staff members were blinded to the case control and other status of the samples to enhance the objectivity of laboratory analyses. The specimens were stored on ice and sent in containers with dry ice via express mail to the laboratory following data collection. Once arrived at the laboratory, specimens were kept frozen in deep freezer at −80 °C freezer until analysis. Plasma total homocysteine was determined by liquid chromatography–electrospray ionization tandem mass spectrometry (LC–ESI/MS-MS) as previously described . Plasma eviously ,58, and eviously . Plasma eviously . The intMTHFR C677T and A1298C, MTR A2756G, and MTR A66G) that were presented for the CRC cases [DHFR 19 bp deletion as an additional gene in the folate-metabolism pathway. DHFR 19 bp in the folate methylation pathway has not been presented for the CRC cases in various ethnic groups before. The total gene mutations from 5 genes were computed together, with possible ranges of 0–10, with scores of ‘1’ for heterozygous and ‘2’ for homozygous polymorphism per each gene. The total gene polymorphism rates of the 5 chosen genes in the folate methylation pathways could range from 0 to a possible maximum score of 10 if each of the 5 genes had homozygous polymorphisms. MTHFR enzyme deficiency was calculated by combining the loss of enzyme functions from MTHFR C677T  and MTHFR A1298C , a composite score of both MTHFR C677T and MTHFR A1298C polymorphisms [Genotyping procedures were described elsewhere earlier ,62. BrieRC cases ,42, and RC cases ,14,15,16orphisms ,63.G2 statistics, which is derived from the conventional likelihood ratio X2 statistic, as X2 is a test of goodness-of-fit between the expected count and the actual account. Individual predictors were selected by using the decision tree methods to build models and then from the rank order of column contributions selecting the most influential variables using the bootstrap forest method [Machine learning based analytics were employed in JMP Pro 13  ,65. Unlit method ,47.The most significant variables and potential interactions were visualized using the interaction profilers for bi-variate interactions of the three categories of variables, and the final set of significant variables were selected for the tested models. The prediction profiler and interactive profiler can be used to visualize the direction of association between two parameters (a predictor or factor with the outcome variable of status in profiler) or among three parameters . The visualization of the profiler and interactive profiler will enable the analyst to visualize and account for the interactions of various factors.R2 and adjusted R2, which always go up as additional variables enter in the model, favoring complexity. However, AIC does not necessarily change by adding variables. Rather it varies based upon the composition of the predictors and thus it is a better indicator of the model quality [We used GR to obtain a smaller prediction error . General quality . AICc cox-axis). In this case, the p value at most could only be 0.9999, but not exactly one. However, when all permutations are exhausted, such as what was done in an exact test, the probability could be exactly one. In a similar vein, GR exhausts different paths to find the best model. When the full model has a mixture of important and unused predictors, the p value cannot be one. However, when the data could be perfectly described by the restricted model resulting from path searching, the probability of observing the data could be one.When developing a GR model for a predictive model, the first type of model presented in JMP Pro 13 is a logistic regression (LR) model because the default estimation method is an LR. After this default method, other model launches can be pursued by choosing a variety of estimation methods (Least absolute shrinkage and selection operator (Lasso), Elastic Net and others) and associated validation methods  validation and others, ). Both Ap < 0.05). The family control group had a younger age because many of the available family members were the offspring of the cancer patients. As seen in p < 0.05 for two of the post-hoc group comparisons, CRC with advanced inflammatory health issues being oldest). For dietary healthy eating, the advanced cancer group ate the least portion servings of vegetables and fruits . As this was a proof-of-concept study, additional adjustment of p-values for multiple testing was not used for the exploratory analyses of related factors.We attempted to match the CRC and family groups on various demographic factors for this family-based study. During data visualization within each of the CRC and family control groups, we identified clinical factors that may affect the outcomes. That is, additional chronic health conditions such as diabetes and chronic inflammatory diseases or advanced cancer stage were recognized within the two groups, hence, we explored the potential differences among the four groups with two groups within each group. p < 0.05). We present the distributions of the genotype alleles for five genes in the OCM pathway for the four groups (MTRR A66G had significant (p < 0.05) HWE with disequilibrium for the Hispanic subgroup. We further checked the distribution of alleles for population-based allele frequencies across the ethnic groups to provide the reference distribution to our findings (p < 0.1)  .p < 0.05), with homocysteine increasing incrementally along the disease groups. MMA levels were highest in the early cancer group than the two control groups (both post-hoc p < 0.05). Cystathionine (a converted metabolite from homocysteine through metabolism) was higher in two of the early-stage disease groups for both control and cancer groups  with early cancer stage group presenting the highest value.p < 0.05).For various metabolites including methionine, methyl-folate, and betaine, there were downward trends for these metabolites along the disease groups from most healthy to most advanced disease groups. The difference on the metabolites among four racial groups are presented in p-values for the baseline LR results with validation are shown in the left panels of Using the most influential variables identified in earlier section, two GR models were developed using the Elastic Net GR models of AICc and LOO validation methods to predict the probability of cancer. In each case, the models were first compared to a LR model with validation for a baseline. The parameter estimates along with the associated p < 0.0001 for AICc validation model, and p < 0.0001 for the interaction term and homocysteine and other parameter p < 0.05 for LOO cross validation model). MMA as an individual parameter must remain in the model because of its interaction with another parameter, total gene mutation. However, none of these parameters were significant with the LR model. Misclassification rates for these three methods were at 20% for LR, 3% for AICc and 4% for LOO GR models. AICc was 27 for LR and 26 for GR AICc model. And AUC was close to 100% for all three models , methyl-folate (40 nmol/L); total gene mutations (≥4); age (51 years) and vegetable intake (2 cups) for demographic/diet parameters ; and intdels see . Therefop (GroupCa = 1): Probability of predicting cancer status, 1 being yes). Visually, the more non-parallel the two levels, the more likely there is a significant interaction between the two parameters. For example, we see non-parallel lines for the total gene mutations with MMA, but also with MTHF and vegetable intake. In DHFR 19 bp deletion. However, further GR tested models did not present significant findings.The prediction profiler shown in As appeared in We presented the genes and metabolites in the OCM pathway and their interactions on the prediction of CRC with dietary lifestyle factors by using various machine-learning based analytics to validate the findings across the methods. As a proof-of-concept study to examine genes and metabolites in the OCM pathway for cancer prevention, we used the ensemble method, as it is a well-known remedy for small-sample studies to validate the analyses by the random subsets of samples . We furtWe presented the very first study cross-validating the effects of metabolites and genes along with healthy intakes of vegetables using both conventional LR inferential statistics and new methods including the ensemble method to handle multi-dimensional factors to predict the risk of CRC. While there are limitations to family-based, case-control designs because of genetic associations among the family members, we used the family-based analysis technique to explore and control for the family associations. Despite these limitations, methodological advantages for family-based studies by including family members can enforce the active participation of the family as an ecological unit, and more reliable reporting of lifestyle parameters ,84, withMTHFR gene is known to be associated with many chronic diseases, including CRC [MTHFR and other genes in the OCM pathway play important roles in DNA methylation, a key mechanism in epigenetics, and more specifically nutrigenomics within the OCM pathway. Studies have emerged to document the effects of low folate levels and increased CRC risk [MTHFR 677 TT genotype [MTHFR 677 TT genotype and increased homocysteine levels can lead to methyl donor deficiency that can increase MSI, particularly for aging populations [To add to the genetic factors, our results point to healthy dietary intakes as modifiable lifestyle factors ,41,53 inding CRC ,13,14. ACRC risk ,16. The CRC risk ,14,15,16CRC risk ,32. WhilCRC risk . In addiCRC risk , and MSIgenotype . Both MTulations . Additioulations , concludulations .MTHFR C677T polymorphisms and genes in the methylation pathways [Recent studies including meta-prediction studies that examined gene–environment interactions consistently presented that environmental factors such as air pollution being associated with increased gene polymorphism and trends to increased disease risks across various disease conditions, especially for pathways ,93,94,95pathways ,91,92. T