Dietary Intake as Determinant Nongenetic Factors to Colorectal Cancer Incidence and Staging Progression: A Study in South Sulawesi Population, Indonesia.

Reports from various population-based studies indicate that the incidence of colorectal cancer may be strongly affected by dietary patterns of the respective populations. The nature of dietary patterns of specific Indonesia population on the risk of colorectal cancer might differ from previously published data with the global population. Therefore, we conducted a study where the dietary pattern in colorectal cancer patient cohorts was compared to age- and population-matched control. We documented 89 colorectal cancer cases and among 173 individuals from the South Sulawesi population. A series of logistic regression and Fisher's exact tests were utilized to test associations of dietary intakes and colorectal cancer risk as well as colorectal cancer staging. Our data demonstrate that vegetable (p-value = 8.70 × 10-26, OR = 0.49) and fruit (p-value = 7.59x10-5, OR = 0.70) intakes are associated with the reduced risk of colorectal cancer incidence. Conversely, acidic food, reheated food, meat, spicy food, and alcohol are associated with the increment case of cancer. Moreover, meat intake (p-value < 0.01) shows a significant association with cancer staging progression. Common dietary pattern is a determinant aspect to the colorectal cancer incidence as well as its staging progression.

Changing Colorectal Cancer Trends in Asians: Epidemiology and Risk Factors.

Once an infrequent disease in parts of Asia, the rate of colorectal cancer in recent decades appears to be steadily increasing. Colorectal cancer represents one of the most important causes of cancer mortality worldwide, including in many regions in Asia. Rapid changes in socioeconomic and lifestyle habits have been attributed to the notable increase in the incidence of colorectal cancers in many Asian countries. Through published data from the International Agency for Cancer Research (IARC), we utilized available continuous data to determine which Asian nations had a rise in colorectal cancer rates. We found that East and South East Asian countries had a significant rise in colorectal cancer rates. Subsequently, we summarized here the known genetics and environmental risk factors for colorectal cancer among populations in this region as well as approaches to screening and early detection that have been considered across various countries in the region.

Genome-wide interaction analysis of folate for colorectal cancer risk.

BACKGROUND: Epidemiological and experimental evidence suggests that higher folate intake is associated with decreased colorectal cancer (CRC) risk; however, the mechanisms underlying this relationship are not fully understood. Genetic variation that may have a direct or indirect impact on folate metabolism can provide insights into folate's role in CRC. OBJECTIVES: Our aim was to perform a genome-wide interaction analysis to identify genetic variants that may modify the association of folate on CRC risk. METHODS: We applied traditional case-control logistic regression, joint 3-degree of freedom, and a 2-step weighted hypothesis approach to test the interactions of common variants (allele frequency >1%) across the genome and dietary folate, folic acid supplement use, and total folate in relation to risk of CRC in 30,550 cases and 42,336 controls from 51 studies from 3 genetic consortia (CCFR, CORECT, GECCO). RESULTS: Inverse associations of dietary, total folate, and folic acid supplement with CRC were found (odds ratio [OR]: 0.93; 95% confidence interval [CI]: 0.90, 0.96; and 0.91; 95% CI: 0.89, 0.94 per quartile higher intake, and 0.82 (95% CI: 0.78, 0.88) for users compared with nonusers, respectively). Interactions (P-interaction < 5×10-8) of folic acid supplement and variants in the 3p25.2 locus (in the region of Synapsin II [SYN2]/tissue inhibitor of metalloproteinase 4 [TIMP4]) were found using traditional interaction analysis, with variant rs150924902 (located upstream to SYN2) showing the strongest interaction. In stratified analyses by rs150924902 genotypes, folate supplementation was associated with decreased CRC risk among those carrying the TT genotype (OR: 0.82; 95% CI: 0.79, 0.86) but increased CRC risk among those carrying the TA genotype (OR: 1.63; 95% CI: 1.29, 2.05), suggesting a qualitative interaction (P-interaction = 1.4×10-8). No interactions were observed for dietary and total folate. CONCLUSIONS: Variation in 3p25.2 locus may modify the association of folate supplement with CRC risk. Experimental studies and studies incorporating other relevant omics data are warranted to validate this finding.

Genome-wide Interaction Study with Smoking for Colorectal Cancer Risk Identifies Novel Genetic Loci Related to Tumor Suppression, Inflammation, and Immune Response.

BACKGROUND: Tobacco smoking is an established risk factor for colorectal cancer. However, genetically defined population subgroups may have increased susceptibility to smoking-related effects on colorectal cancer. METHODS: A genome-wide interaction scan was performed including 33,756 colorectal cancer cases and 44,346 controls from three genetic consortia. RESULTS: Evidence of an interaction was observed between smoking status (ever vs. never smokers) and a locus on 3p12.1 (rs9880919, P = 4.58 × 10-8), with higher associated risk in subjects carrying the GG genotype [OR, 1.25; 95% confidence interval (CI), 1.20-1.30] compared with the other genotypes (OR <1.17 for GA and AA). Among ever smokers, we observed interactions between smoking intensity (increase in 10 cigarettes smoked per day) and two loci on 6p21.33 (rs4151657, P = 1.72 × 10-8) and 8q24.23 (rs7005722, P = 2.88 × 10-8). Subjects carrying the rs4151657 TT genotype showed higher risk (OR, 1.12; 95% CI, 1.09-1.16) compared with the other genotypes (OR <1.06 for TC and CC). Similarly, higher risk was observed among subjects carrying the rs7005722 AA genotype (OR, 1.17; 95% CI, 1.07-1.28) compared with the other genotypes (OR <1.13 for AC and CC). Functional annotation revealed that SNPs in 3p12.1 and 6p21.33 loci were located in regulatory regions, and were associated with expression levels of nearby genes. Genetic models predicting gene expression revealed that smoking parameters were associated with lower colorectal cancer risk with higher expression levels of CADM2 (3p12.1) and ATF6B (6p21.33). CONCLUSIONS: Our study identified novel genetic loci that may modulate the risk for colorectal cancer of smoking status and intensity, linked to tumor suppression and immune response. IMPACT: These findings can guide potential prevention treatments.

Cancer Risk Score Prediction Based on a Single-Nucleotide Polymorphism Network.

OBJECTIVES: Genome-wide association studies (GWAS) are performed to study the associations between genetic variants with respect to certain phenotypic traits such as cancer. However, the method that is commonly used in GWAS assumes that certain traits are solely affected by a single mutation. We propose a network analysis method, in which we generate association networks of single-nucleotide polymorphisms (SNPs) that can differentiate case and control groups. We hypothesize that certain phenotypic traits are attributable to mutations in groups of associated SNPs. METHODS: We propose a method based on a network analysis framework to study SNP-SNP interactions related to cancer incidence. We employed logistic regression to measure the significance of all SNP pairs from GWAS for the incidence of colorectal cancer and computed a cancer risk score based on the generated SNP networks. RESULTS: We demonstrated our method in a dataset from a case-control study of colorectal cancer in the South Sulawesi population. From the GWAS results, 20,094 pairs of 200 SNPs were created. We obtained one cluster containing four pairs of five SNPs that passed the filtering threshold based on their p-values. A locus on chromosome 12 (12:54410007) was found to be strongly connected to the four variants on chromosome 1. A polygenic risk score was computed from the five SNPs, and a significant difference in colorectal cancer risk was obtained between the case and control groups. CONCLUSIONS: Our results demonstrate the applicability of our method to understand SNP-SNP interactions and compute risk scores for various types of cancer.

A genetic association study of tobacco withdrawal endophenotypes in African Americans.

Genome-wide association (GWA) genetic epidemiology research has identified several variants modestly associated with brief self-report smoking measures, predominately in European Americans. GWA research has not applied intensive laboratory-based measures of smoking endophenotypes in African Americans-a population with disproportionately low quit smoking rates and high tobacco-related disease risk. This genetic epidemiology study of non-Hispanic African Americans tested associations of 89 genetic variants identified in previous GWA research and exploratory GWAs with 24 laboratory-derived tobacco withdrawal endophenotypes. African American cigarette smokers (N = 528; ≥10 cig/day; 36.2% female) completed two counterbalanced visits following either 16-hr of tobacco deprivation or ad libitum smoking. At both visits, self-report and behavioral measures across six unique "sub-phenotype" domains within the tobacco withdrawal syndrome were assessed (Urge/Craving, Negative Affect, Low Positive Affect, Cognition, Hunger, and Motivation to Resume Smoking). Results of the candidate variant analysis found two significant small-magnitude associations. The rs11915747 alternate allele in the CAD2M gene region was associated with .09 larger deprivation-induced changes in reported impulsivity (0-4 scale). The rs2471711alternate allele in the AC097480.1/AC097480.2 gene region was associated with 0.26 lower deprivation-induced changes in confusion (0-4 scale). For both variants, associations were opposite in direction to previous research. Individual genetic variants may exert only weak influences on tobacco withdrawal in African Americans. Larger sample sizes of non-European ancestry individuals might be needed to investigate both known and novel loci that may be ancestry-specific. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Beyond GWAS of Colorectal Cancer: Evidence of Interaction with Alcohol Consumption and Putative Causal Variant for the 10q24.2 Region.

BACKGROUND: Currently known associations between common genetic variants and colorectal cancer explain less than half of its heritability of 25%. As alcohol consumption has a J-shape association with colorectal cancer risk, nondrinking and heavy drinking are both risk factors for colorectal cancer. METHODS: Individual-level data was pooled from the Colon Cancer Family Registry, Colorectal Transdisciplinary Study, and Genetics and Epidemiology of Colorectal Cancer Consortium to compare nondrinkers (≤1 g/day) and heavy drinkers (>28 g/day) with light-to-moderate drinkers (1-28 g/day) in GxE analyses. To improve power, we implemented joint 2df and 3df tests and a novel two-step method that modifies the weighted hypothesis testing framework. We prioritized putative causal variants by predicting allelic effects using support vector machine models. RESULTS: For nondrinking as compared with light-to-moderate drinking, the hybrid two-step approach identified 13 significant SNPs with pairwise r2 > 0.9 in the 10q24.2/COX15 region. When stratified by alcohol intake, the A allele of lead SNP rs2300985 has a dose-response increase in risk of colorectal cancer as compared with the G allele in light-to-moderate drinkers [OR for GA genotype = 1.11; 95% confidence interval (CI), 1.06-1.17; OR for AA genotype = 1.22; 95% CI, 1.14-1.31], but not in nondrinkers or heavy drinkers. Among the correlated candidate SNPs in the 10q24.2/COX15 region, rs1318920 was predicted to disrupt an HNF4 transcription factor binding motif. CONCLUSIONS: Our study suggests that the association with colorectal cancer in 10q24.2/COX15 observed in genome-wide association study is strongest in nondrinkers. We also identified rs1318920 as the putative causal regulatory variant for the region. IMPACT: The study identifies multifaceted evidence of a possible functional effect for rs1318920.

SSMFN: a fused spatial and sequential deep learning model for methylation site prediction.

BACKGROUND: Conventional in vivo methods for post-translational modification site prediction such as spectrophotometry, Western blotting, and chromatin immune precipitation can be very expensive and time-consuming. Neural networks (NN) are one of the computational approaches that can predict effectively the post-translational modification site. We developed a neural network model, namely the Sequential and Spatial Methylation Fusion Network (SSMFN), to predict possible methylation sites on protein sequences. METHOD: We designed our model to be able to extract spatial and sequential information from amino acid sequences. Convolutional neural networks (CNN) is applied to harness spatial information, while long short-term memory (LSTM) is applied for sequential data. The latent representation of the CNN and LSTM branch are then fused. Afterwards, we compared the performance of our proposed model to the state-of-the-art methylation site prediction models on the balanced and imbalanced dataset. RESULTS: Our model appeared to be better in almost all measurement when trained on the balanced training dataset. On the imbalanced training dataset, all of the models gave better performance since they are trained on more data. In several metrics, our model also surpasses the PRMePred model, which requires a laborious effort for feature extraction and selection. CONCLUSION: Our models achieved the best performance across different environments in almost all measurements. Also, our result suggests that the NN model trained on a balanced training dataset and tested on an imbalanced dataset will offer high specificity and low sensitivity. Thus, the NN model for methylation site prediction should be trained on an imbalanced dataset. Since in the actual application, there are far more negative samples than positive samples.

Comparative study of predicted miRNA between Indonesia and China (Wuhan) SARS-CoV-2: a bioinformatics analysis.

BACKGROUND: Several reports on the discovery of SARS-CoV-2 mutations and variations in Indonesia COVID-19 cases led to genomic dysregulation with the first pandemic cases in Wuhan, China. MicroRNA (miRNA) plays an important role in this genetic regulation and contributes to the enhancement of viral RNA binding through the host mRNA. OBJECTIVE: This research is aimed to detect miRNA targets of SARS-CoV-2 and examines their role in Indonesia cases against Wuhan cases. METHODS: SARS-CoV-2 sequences were obtained from GISAID ( https://www.gisaid.org/ ), NCBI ( https://ncbi.nlm.nih.gov ), and National Genomics Data Center ( https://bigd.big.ac.cn/gwh/ ) databases. MiRDB ( https://github.com/gbnegrini/mirdb-custom-target-search ) was used to annotate and predict target human mature miRNAs. For statistical analysis, we utilized a series chi-square test to obtain significant miRNA. DIANA-miRPath v3.0 ( http://www.microrna.gr/miRPathv3 ) analyzed the Gene Ontology of mature miRNAs. RESULT: The statistical results detected five significant miRNAs. Two miRNAs: hsa-miR-4778-5p and hsa-miR-4531 were consistently found in the majority of Wuhan samples, while they were only found in less than half of the Indonesia samples. The other three miRNA, hsa-miR-6844, hsa-miR-627-5p, and hsa-miR-3674, were discovered in most samples in both groups but with a significant difference ratio. Among these five significant miRNA targets, hsa-miR-6844 is the only miRNA that has an association with the ORF1ab gene of SARS-CoV-2. CONCLUSION: The Gene Ontology analysis of five significant miRNA targets indicates a significant role in inflammation and the immune system. The specific detection of host miRNAs in this study shows that there are differences in the characteristics of SARS-CoV-2 between Indonesia and Wuhan.

Intronic Variant of MUTYH Gene Exhibits A Strong Association with Early Onset of Breast Cancer Susceptibility in Indonesian Women Population.

OBJECTIVE: Several studies have recently indicated a huge shifting pattern toward early age onset cases in breast cancer (BC) patients. However, the studies exerted relatively limited to the Caucasian population. This preliminary study is aimed to investigate the genetic risk factors for young BC patients specifically in Indonesia population. METHODS: DNA samples were extracted from 79 BC patients aged younger than 40 years old and 90 healthy samples. These DNA samples were sequenced using Illumina NextSeq 500 platform and preprocessed to extract the single-nucleotide polymorphisms (SNPs) data. Firstly, multiple univariate logistic regressions were performed to test the association between each SNP and BC incidence in young patients. Furthermore, to analyze the polygenic effects derived from multiple SNPs, we employed a multivariate logistics regression. RESULTS: There were only 15 SNPs passed our 95% call rate threshold thus subsequently were used in the association test. One of these variants, rs3219493, emerged to be significantly associated with early-onset BC (p-value = 0.025, OR = 3.750, 95% CI = 1.178-11.938). This result is consistent with the multivariate logistic regression model, where the pertinent variant was found statistically significant (p-value = 0.008, OR = 8.398, 95% CI = 1.720-40.920). This variant was identified as an intronic variant within MUTYH gene which has been reported in several published studies to exhibit an association with the incidence of breast cancer in China, Italy and Sephardi Jews population. However, there is no evident this gene impacting the risk of developing early onset of BC in Indonesia population. CONCLUSION: Despite our limitation in terms of sample size analyzed in this preliminary study, our finding on significant association of intronic MUTHY with the early onset of BC in Indonesia led to a broadened insight of population-based unique aspect to being taken into an in-depth account for and advancement of chemotherapy.

Quantified Self-Using Consumer Wearable Device: Predicting Physical and Mental Health.

OBJECTIVES: Recently, wearable device technology has gained more popularity in supporting a healthy lifestyle. Hence, researchers have begun to put significant efforts into studying the direct and indirect benefits of wearable devices for health and wellbeing. This paper summarizes recent studies on the use of consumer wearable devices to improve physical activity, mental health, and health consciousness. METHODS: A thorough literature search was performed from several reputable databases, such as PubMed, Scopus, ScienceDirect, arXiv, and bioRxiv mainly using "wearable device research" as a keyword, no earlier than 2018. As a result, 25 of the most recent and relevant papers included in this review cover several topics, such as previous literature reviews (9 papers), wearable device accuracy (3 papers), self-reported data collection tools (3 papers), and wearable device intervention (10 papers). RESULTS: All the chosen studies are discussed based on the wearable device used, complementary data, study design, and data processing method. All these previous studies indicate that wearable devices are used either to validate their benefits for general wellbeing or for more serious medical contexts, such as cardiovascular disorders and post-stroke treatment. CONCLUSIONS: Despite their huge potential for adoption in clinical settings, wearable device accuracy and validity remain the key challenge to be met. Some lessons learned and future projections, such as combining traditional study design with statistical and machine learning methods, are highlighted in this paper to provide a useful overview for other researchers carrying out similar research.