The association of dietary pattern and breast cancer in Jiangsu, China: A population-based case-control study

Dietary patterns in relation to glioma: a case-control study

Although the association of individual foods and nutrients with glioma have been investigated, studies on the association of major dietary patterns and glioma are scarce. The aim of this study was to examine the association between major dietary patterns and risk of glioma in a group of Iranian adults. In this hospital-based case-control design, we recruited 128 newly diagnosed glioma cases and 256 controls in Tehran from 2009 to 2011. A Willett-format-validated 126-item semi-quantitative Food Frequency Questionnaire (FFQ) was used to assess participants' dietary intake. Factor analysis was used to identify major dietary patterns. We identified 3 major dietary patterns using factor analysis: high protein, vegetarian and western dietary pattern. After several adjustments for potential confounders, adherence to the high protein dietary pattern was inversely associated with risk of glioma (OR: 0.47; 95% CI: 0.23, 0.95). Consumption of vegetarian dietary pattern was also associated with a reduced risk of glioma (OR: 0.16; 95% CI: 0.07, 0.34). Greater adherence to the western dietary pattern was associated with a greater chance of glioma (OR: 3.30; 95% CI: 1.52, 7.17). We found that high protein, vegetarian and western dietary pattern were significantly associated with glioma risk. Further prospective studies are needed to confirm these findings.

Dietary patterns and breast cancer risk, prognosis, and quality of life: A systematic review

Background

Statistics indicate that the morbidity of breast cancer is increasing globally, and its (overall figures) incidence has now surpassed that of lung cancer for the first time. The relation between a whole dietary pattern, rather than of a single food or nutrient, and breast cancer (BC) should be examined for findings to capture the complexities of diet and the potential for synergism between dietary components. Hence, the effects of dietary patterns on breast cancer have recently attracted increasing attention.

Objective

To systematically review the effects of dietary patterns on breast cancer risk, prognosis, and quality of life in survivors.

Methods

This systematic review was conducted following PRISMA guidelines and was registered in PROSPERO. Data from Ovid, China Biomedical Literature Database, Wanfang Data Knowledge Service Platform, CNKI, PubMed, Weipu, The Cochrane Library, Duxiu Data, ProQuest, Embase, Web of Science, and Scopus Database were retrieved and evaluated.

Results

A total of 47 studies that investigated the association between eating patterns and breast cancer were identified. Ten studies evaluated the effect of the model on treatment outcome and prognosis of breast cancer and two cross-sectional studies examined the influence of dietary patterns on quality of life. The resulting favorable dietary patterns were shown to regulate metabolic biomarkers, antioxidants, anti-inflammatory agents, and protective genes, and inhibit cell proliferation and invasion.

Conclusion

Numerous studies have examined the effects of healthy eating, plant-based, anti-inflammation, low-fat, and other favorable dietary patterns in relation to breast cancer. However, few studies reported significant associations and the studies had limitations, suggesting that the current findings should be interpreted with caution.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, CRD4202 2350171.

Nutritional, functional, and bioactive properties of african underutilized legumes

Globally, legumes are vital constituents of diet and perform critical roles in maintaining well-being owing to the dense nutritional contents and functional properties of their seeds. While much emphasis has been placed on the major grain legumes over the years, the neglected and underutilized legumes (NULs) are gaining significant recognition as probable crops to alleviate malnutrition and give a boost to food security in Africa. Consumption of these underutilized legumes has been associated with several health-promoting benefits and can be utilized as functional foods due to their rich dietary fibers, vitamins, polyunsaturated fatty acids (PUFAs), proteins/essential amino acids, micro-nutrients, and bioactive compounds. Despite the plethora of nutritional benefits, the underutilized legumes have not received much research attention compared to common mainstream grain legumes, thus hindering their adoption and utilization. Consequently, research efforts geared toward improvement, utilization, and incorporation into mainstream agriculture in Africa are more convincing than ever. This work reviews some selected NULs of Africa (Adzuki beans (Vigna angularis), African yam bean (Sphenostylis stenocarpa), Bambara groundnut (Vigna subterranea), Jack bean (Canavalia ensiformis), Kidney bean (Phaseolus vulgaris), Lima bean (Phaseolus lunatus), Marama bean (Tylosema esculentum), Mung bean, (Vigna radiata), Rice bean (Vigna Umbellata), and Winged bean (Psophocarpus tetragonolobus)), and their nutritional, and functional properties. Furthermore, we highlight the prospects and current challenges associated with the utilization of the NULs and discusses the strategies to facilitate their exploitation as not only sources of vital nutrients, but also their integration for the development of cheap and accessible functional foods.

Association Between Dietary Patterns and Plasma Lipid Biomarker and Female Breast Cancer Risk: Comparison of Latent Class Analysis (LCA) and Factor Analysis (FA)

Background: Diet research focuses on the characteristics of "dietary patterns" regardless of the statistical methods used to derive them. However, the solutions to these methods are both conceptually and statistically different. Methods: We compared factor analysis (FA) and latent class analysis (LCA) methods to identify the dietary patterns of participants in the Chinese Wuxi Exposure and Breast Cancer Study, a population-based case-control study that included 818 patients and 935 healthy controls. We examined the association between dietary patterns and plasma lipid markers and the breast cancer risk. Results: Factor analysis grouped correlated food items into five factors, while LCA classified the subjects into four mutually exclusive classes. For FA, we found that the Prudent-factor was associated with a lower risk of breast cancer [4th vs. 1st quartile: odds ratio (OR) for 0.70, 95% CI = 0.52, 0.95], whereas the Picky-factor was associated with a higher risk (4th vs. 1st quartile: OR for 1.35, 95% CI = 1.00, 1.81). For LCA, using the Prudent-class as the reference, the Picky-class has a positive association with the risk of breast cancer (OR for 1.42, 95% CI = 1.06, 1.90). The multivariate-adjusted model containing all of the factors was better than that containing all of the classes in predicting HDL cholesterol (p = 0.04), triacylglycerols (p = 0.03), blood glucose (p = 0.04), apolipoprotein A1 (p = 0.02), and high-sensitivity C-reactive protein (p = 0.02), but was weaker than that in predicting the breast cancer risk (p = 0.03). Conclusion: Factor analysis is useful for understanding which foods are consumed in combination and for studying the associations with biomarkers, while LCA is useful for classifying individuals into mutually exclusive subgroups and compares the disease risk between the groups.

Dietary Intake of Polyphenols and the Risk of Breast Cancer: a Case-Control Study

Despite mounting evidence that dietary polyphenols might have a protective role against the risk of breast cancer (BC), few studies have assessed the relationship between intake of polyphenol classes and subclasses with BC. Thus, we examined the relationship between dietary polyphenol classes and individual polyphenol subclasses and the risk of BC. Overall, 134 newly diagnosed BC patients and 267 healthy hospitalized controls were studied. Dietary intake was assessed using a validated 168-item food frequency questionnaire (FFQ). To estimate dietary intake of polyphenols, polyphenol content (flavonoids, lignans, stilbenes and phenolic acids) of 80 food items were derived from an updated version of the phenol explorer database containing information on the effects of food processing on polyphenol content. The dietary polyphenol intake was calculated by matching the subjects' food consumption data with our polyphenol content database. Multivariate logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Controls had higher intake of total polyphenol (marginally significant; p = 0.07), hydroxycinnamic acid (marginally significant; p = 0.05) and lignan (p = 0.01). After adjusting for potential confounders, high consumption of lignans (highest vs. lowest tertile: OR, 0.51; 95% CI, 0.26–0.97; p for trend = 0.04) associated with decreased risk of BC. There was no significant relationship between intake of other polyphenols and risk of BC. Our findings suggest that high lignan intake is associated with a reduced risk of BC.

Prediction of Metastasis in the Axillary Lymph Nodes of Patients With Breast Cancer: A Radiomics Method Based on Contrast-Enhanced Computed Tomography

Background

The use of traditional techniques to evaluate breast cancer is restricted by the subjective nature of assessment, variation across radiologists, and limited data. Radiomics may predict axillary lymph node metastasis (ALNM) of breast cancer more accurately.

Purpose

The aim was to evaluate the diagnostic performance of a radiomics model based on ALNs themselves that used contrast-enhanced computed tomography (CECT) to detect ALNM of breast cancer.

Methods

We retrospectively enrolled 402 patients with breast cancer confirmed by pathology from January 2016 to October 2019. Three hundred and ninety-six features were extracted for all patients from axial CECT images of 825 ALNs using Artificial Intelligent Kit software (GE Medical Systems, Version V3.1.0.R). Next, the radiomics model was trained, validated, and tested for predicting ALNM in breast cancer by using a support vector machine algorithm. Finally, the performance of the radiomics model was evaluated in terms of its classification accuracy and the value of the area under the curve (AUC).

Results

The radiomics model yielded the best classification accuracy of 89.1% and the highest AUC of 0.92 (95% CI: 0.91-0.93, p=0.002) for discriminating ALNM in breast cancer in the validation cohorts. In the testing cohorts, the model also demonstrated better performance, with an accuracy of 88.5% and an AUC of 0.94 (95% CI: 0.93-0.95, p=0.005) for predicting ALNM in breast cancer.

Conclusion

The radiomics model based on CECT images can be used to predict ALNM in breast cancer and has significant potential in clinical noninvasive diagnosis and in the prediction of breast cancer metastasis.

Association between dietary patterns and risk of breast cancer in Chinese female population: a latent class analysis

OBJECTIVE

To determine if specific dietary patterns are associated with breast cancer (BC) risk in Chinese women.

DESIGN

Latent class analysis (LCA) was performed to identify generic dietary patterns based on daily food-frequency data.

SETTING

The Chinese Wuxi Exposure and Breast Cancer Study (2013-2014).

PARTICIPANTS

A population-based case-control study (695 cases, 804 controls).

RESULTS

Four dietary patterns were identified, Prudent, Chinese traditional, Western and Picky; the proportion in the controls and cases was 0·30/0·32/0·16/0·23 and 0·29/0·26/0·11/0·33, respectively. Women in Picky class were characterised by higher extreme probabilities of non-consumption of specific foods, the highest probabilities of consumption of pickled foods and the lowest probabilities of consumption of cereals, soya foods and nuts. Compared with Prudent class, Picky class was associated with a higher risk (OR = 1·42, 95 % CI 1·06, 1·90), while the relevant association was only in post- (OR = 1·44, 95 % CI 1·01, 2·05) but not in premenopausal women. The Western class characterised by high-protein, high-fat and high-sugar foods, and the Chinese traditional class characterised by typical consumption of soya foods and white meat over red meat, both of them showed no difference in BC risk compared with Prudent class did.

CONCLUSIONS

LCA captures the heterogeneity of individuals embedded in the population and could be a useful approach in the study of dietary pattern and disease. Our results indicated that the Picky class might have a positive association with the risk of BC.

The relationship between dietary patterns, dietary quality index, and dietary inflammatory index with the risk of all types of cancer: Golestan cohort study

Background: Dietary patterns and diet quality index (DQI) are widely discussed in relation with different health conditions and have recently been taken into consideration for all cancer types. Since chronic inflammation has been recognized as an important biologic risk factor for cancer occurrence, especially in epithelial tissues, proinflammatory or anti-inflammatory characteristics of diet has become the center of attention. In the present study, we aimed to identify whether a specific dietary pattern, Mediterranean dietary score (MDs), and dietary inflammatory index (DII) were associated with overall cancer risk in Iranian population.

Methods: This study was performed in the context of the Golestan cohort study. Participants with extreme daily energy intake or those who did not answer more than 30 question of the Food Frequency questionnaire (FFQ) were excluded. Dietary patterns, MDs, and DII were measured from FFQ. Age, sex, total energy, place of residence, smoking, wealth score, ethnicity, opiate use, BMI, education, marital status, and physical activity score were considered as confounding variables. Using Cox proportional hazards regression models, hazard ratios (HRs) and 95% confidence interval of cancer were estimated.

Results: HRs (95% CIs) of all cancers by quartiles of Western dietary pattern, DII, and MDs showed that the forth quartile of the Western dietary pattern is attributed to 23% higher cancer risk (HRs: 1.23, CI: 1.09-1.40, P< 0.001, adjusted for age and sex) compared to the first quartile. It also remained significant after further adjustments (HRs = 1.20, CI: 1.06-1.36, P< 0.001). There was a higher cancer risk in the fourth quartile of DII in comparison with the first quartile (HRs = 1.16, CI: 1.01-1.32, P trend < 0.001, adjusted for age and sex). The lower adherence to the Mediterranean dietary pattern also largely contributes to 27% higher cancer risk (HRs: 1.27, CI: 1.12-1.44), P trend < 0.001, adjusted for age and sex), which also remained remarkable after further adjustments ((HRs =1.19, CI: 1.05-1.35, P trend < 0.001).

Conclusion: Cancer is highly correlated to dietary intake and dietary patterns, such as the Western dietary pattern, while the Mediterranean diet score was inversely associated with cancer risk. Further investigations are required to get a broader insight into cancer determinants in population.

Gaussian Graphical Models Identified Food Intake Networks among Iranian Women with and without Breast Cancer: A Case-Control Study

BACKGROUND

Dietary patterns may be an important predictor of breast cancer risk. However, they cannot completely explain the pairwise correlations among foods. The purpose of this study is to compare food intake networks derived by Gaussian Graphical Models (GGMs) for women with and without breast cancer to better understand how foods are consumed in relation to each other according to disease status.

METHODS

A total of 134 women with breast cancer and 267 hospital controls were selected from referral hospitals of Tehran, Iran. Dietary intakes were evaluated by using a validated 168 food-items semi-quantitative food frequency questionnaire. GGMs were applied to log-transformed intakes of 28 food groups to construct outcome-specific food networks.

RESULTS

Among cases, a main network containing intakes of 12 central food groups (vegetables, fruits, nuts and seeds, olive oil and olive, processed meat, sweets, salt, soft drinks, fried potatoes, pickles, low-fat dairy, pizza) was detected. In controls, a main network including six central food groups (liquid oils, vegetables, fruits, sweets, fried potatoes and soft drinks) was identified.

CONCLUSIONS

The findings of this study revealed a difference in GGM-identified networks graphs between cases and controls. Overall, GGM may provide additional understanding of relationships between diet and health.

Adult weight change and the risk of pre- and postmenopausal breast cancer in the Chinese Wuxi Exposure and Breast Cancer Study

PURPOSE

The accumulating evidence indicates that weight gain in adulthood is more predictive of breast cancer risk than absolute body weight. However, the relative impact of timing of weight gain in adulthood on breast cancer as well as other characteristics of the association between weight and breast cancer has not been well documented.

METHODS

This population-based case-control study of breast cancer included 818 patients with newly diagnosed primary breast cancer and 935 residence and age-matched healthy controls. The body weight values at 18 years old, 1 year before diagnosis, and at menopause were obtained during in-person interviews. Unconditional logistic regression was used to estimate the effects of the weight change over adulthood on breast cancer risk. Linear mixed-effects regression was also applied as a secondary analysis.

RESULTS

We found that the increased risk of breast cancer was associated with the weight gain in adulthood among postmenopausal women (OR 1.23; 95% CI 1.10-1.37 per 5 kg increase) but not in the premenopausal women. The risk associated with weight gain since menopause (OR 1.65; 95% CI 1.28-2.14 a 5-kg increase) was higher than that from age 18 to menopause (OR 1.14; 95% CI 1.02, 1.28 a 5-kg increase). The association tended to be stronger in those with higher waist circumference and who had never used hormone replacement therapy (HRT). Women who had never used HRT, the increased risk of breast cancer associated with weight gain was more consistent in leaner women at age 18 (BMI < 18.5) or at menopause (BMI < 24).

CONCLUSIONS

Our findings indicated that weight gain has significant impact on postmenopausal breast cancer risk. The time periods of weight gain, central body fat, and HRT may affect the observed association, which should be further studied.

Bioinformatic analysis of differential expression and core GENEs in breast cancer

Breast cancer (BRCA) is one of the most common malignancies in women. The gene expression profile of GSE103512 from the GEO database was downloaded in order to find key genes involved in the occurrence and development of BRCA. 75 samples, including 65 cancer and 10 normal samples, were included in this analysis. Differentially expressed genes (DEGs) between BRCA patients and health people were chosen using R tool. We next performed gene ontology (GO) analysis and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Moreover, Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING) was utilized to visualize protein-protein interaction (PPI) of these DEGs. The related genes and medicines specific to hub genes were predicted by CBioportal. We screened a total of 357 DEGs including 77 up-regulated and 280 down-regulated. A series of BRCA related GO terms and pathways were identified by analysis of these DEGs. Insulin-like growth factor 1 (IGF1); epidermal growth factor receptor (EGFR); v-jun avian sarcoma virus 17 oncogene homolog (JUN) and Estrogen Receptor 1 (ESR1) of the DEGs were screened by construction of the PPI network and the degree of connectivity. IGF1 and ESR1 were finally selected as potential hub genes and treatment targets of BRCA. In conclusion, this bioinformatics analysis demonstrated that DEGs and hub genes, such as IGF1, might regulate the development of gastric cancer. These DEGs could be used as new biomarkers for diagnosis and to guide the combination medicine of BRCA.