15 results on '"Mahesworo B"'
Search Results
2. Identification of rice plants via DNA barcoding for securing future food availability.
- Author
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Trinugroho, J P, Sudigyo, D, Hidayat, A A, Nirwantono, R, Mahesworo, B, and Pardamean, B
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- 2023
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3. Genome-wide interaction analysis of folate for colorectal cancer risk.
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Bouras E, Kim AE, Lin Y, Morrison J, Du M, Albanes D, Barry EL, Baurley JW, Berndt SI, Bien SA, Bishop TD, Brenner H, Budiarto A, Burnett-Hartman A, Campbell PT, Carreras-Torres R, Casey G, Cenggoro TW, Chan AT, Chang-Claude J, Conti DV, Cotterchio M, Devall M, Diez-Obrero V, Dimou N, Drew DA, Figueiredo JC, Giles GG, Gruber SB, Gunter MJ, Harrison TA, Hidaka A, Hoffmeister M, Huyghe JR, Joshi AD, Kawaguchi ES, Keku TO, Kundaje A, Le Marchand L, Lewinger JP, Li L, Lynch BM, Mahesworo B, Männistö S, Moreno V, Murphy N, Newcomb PA, Obón-Santacana M, Ose J, Palmer JR, Papadimitriou N, Pardamean B, Pellatt AJ, Peoples AR, Platz EA, Potter JD, Qi L, Qu C, Rennert G, Ruiz-Narvaez E, Sakoda LC, Schmit SL, Shcherbina A, Stern MC, Su YR, Tangen CM, Thomas DC, Tian Y, Um CY, van Duijnhoven FJ, Van Guelpen B, Visvanathan K, Wang J, White E, Wolk A, Woods MO, Ulrich CM, Hsu L, Gauderman WJ, Peters U, and Tsilidis KK
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- Humans, Risk Factors, Case-Control Studies, Dietary Supplements, Folic Acid metabolism, Colorectal Neoplasms genetics
- Abstract
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., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)- Published
- 2023
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4. Probing the diabetes and colorectal cancer relationship using gene - environment interaction analyses.
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Dimou N, Kim AE, Flanagan O, Murphy N, Diez-Obrero V, Shcherbina A, Aglago EK, Bouras E, Campbell PT, Casey G, Gallinger S, Gruber SB, Jenkins MA, Lin Y, Moreno V, Ruiz-Narvaez E, Stern MC, Tian Y, Tsilidis KK, Arndt V, Barry EL, Baurley JW, Berndt SI, Bézieau S, Bien SA, Bishop DT, Brenner H, Budiarto A, Carreras-Torres R, Cenggoro TW, Chan AT, Chang-Claude J, Chanock SJ, Chen X, Conti DV, Dampier CH, Devall M, Drew DA, Figueiredo JC, Giles GG, Gsur A, Harrison TA, Hidaka A, Hoffmeister M, Huyghe JR, Jordahl K, Kawaguchi E, Keku TO, Larsson SC, Le Marchand L, Lewinger JP, Li L, Mahesworo B, Morrison J, Newcomb PA, Newton CC, Obon-Santacana M, Ose J, Pai RK, Palmer JR, Papadimitriou N, Pardamean B, Peoples AR, Pharoah PDP, Platz EA, Potter JD, Rennert G, Scacheri PC, Schoen RE, Su YR, Tangen CM, Thibodeau SN, Thomas DC, Ulrich CM, Um CY, van Duijnhoven FJB, Visvanathan K, Vodicka P, Vodickova L, White E, Wolk A, Woods MO, Qu C, Kundaje A, Hsu L, Gauderman WJ, Gunter MJ, and Peters U
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- Humans, Gene-Environment Interaction, Genetic Predisposition to Disease, Risk Factors, Polymorphism, Single Nucleotide, Genome-Wide Association Study methods, Microfilament Proteins genetics, Diabetes Mellitus genetics, Colorectal Neoplasms genetics
- Abstract
Background: Diabetes is an established risk factor for colorectal cancer. However, the mechanisms underlying this relationship still require investigation and it is not known if the association is modified by genetic variants. To address these questions, we undertook a genome-wide gene-environment interaction analysis., Methods: We used data from 3 genetic consortia (CCFR, CORECT, GECCO; 31,318 colorectal cancer cases/41,499 controls) and undertook genome-wide gene-environment interaction analyses with colorectal cancer risk, including interaction tests of genetics(G)xdiabetes (1-degree of freedom; d.f.) and joint testing of Gxdiabetes, G-colorectal cancer association (2-d.f. joint test) and G-diabetes correlation (3-d.f. joint test)., Results: Based on the joint tests, we found that the association of diabetes with colorectal cancer risk is modified by loci on chromosomes 8q24.11 (rs3802177, SLC30A8 - OR
AA : 1.62, 95% CI: 1.34-1.96; ORAG : 1.41, 95% CI: 1.30-1.54; ORGG : 1.22, 95% CI: 1.13-1.31; p-value3-d.f. : 5.46 × 10-11 ) and 13q14.13 (rs9526201, LRCH1 - ORGG : 2.11, 95% CI: 1.56-2.83; ORGA : 1.52, 95% CI: 1.38-1.68; ORAA : 1.13, 95% CI: 1.06-1.21; p-value2-d.f. : 7.84 × 10-09 )., Discussion: These results suggest that variation in genes related to insulin signaling (SLC30A8) and immune function (LRCH1) may modify the association of diabetes with colorectal cancer risk and provide novel insights into the biology underlying the diabetes and colorectal cancer relationship., (© 2023. The Author(s).)- Published
- 2023
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5. A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk.
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Aglago EK, Kim A, Lin Y, Qu C, Evangelou M, Ren Y, Morrison J, Albanes D, Arndt V, Barry EL, Baurley JW, Berndt SI, Bien SA, Bishop DT, Bouras E, Brenner H, Buchanan DD, Budiarto A, Carreras-Torres R, Casey G, Cenggoro TW, Chan AT, Chang-Claude J, Chen X, Conti DV, Devall M, Diez-Obrero V, Dimou N, Drew D, Figueiredo JC, Gallinger S, Giles GG, Gruber SB, Gsur A, Gunter MJ, Hampel H, Harlid S, Hidaka A, Harrison TA, Hoffmeister M, Huyghe JR, Jenkins MA, Jordahl K, Joshi AD, Kawaguchi ES, Keku TO, Kundaje A, Larsson SC, Marchand LL, Lewinger JP, Li L, Lynch BM, Mahesworo B, Mandic M, Obón-Santacana M, Moreno V, Murphy N, Nan H, Nassir R, Newcomb PA, Ogino S, Ose J, Pai RK, Palmer JR, Papadimitriou N, Pardamean B, Peoples AR, Platz EA, Potter JD, Prentice RL, Rennert G, Ruiz-Narvaez E, Sakoda LC, Scacheri PC, Schmit SL, Schoen RE, Shcherbina A, Slattery ML, Stern MC, Su YR, Tangen CM, Thibodeau SN, Thomas DC, Tian Y, Ulrich CM, van Duijnhoven FJ, Van Guelpen B, Visvanathan K, Vodicka P, Wang J, White E, Wolk A, Woods MO, Wu AH, Zemlianskaia N, Hsu L, Gauderman WJ, Peters U, Tsilidis KK, and Campbell PT
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- Humans, Body Mass Index, Risk Factors, Genetic Loci, Polymorphism, Single Nucleotide, Genetic Predisposition to Disease, Genome-Wide Association Study, Intercellular Signaling Peptides and Proteins genetics, Obesity complications, Obesity genetics, Colorectal Neoplasms genetics
- Abstract
Colorectal cancer risk can be impacted by genetic, environmental, and lifestyle factors, including diet and obesity. Gene-environment interactions (G × E) can provide biological insights into the effects of obesity on colorectal cancer risk. Here, we assessed potential genome-wide G × E interactions between body mass index (BMI) and common SNPs for colorectal cancer risk using data from 36,415 colorectal cancer cases and 48,451 controls from three international colorectal cancer consortia (CCFR, CORECT, and GECCO). The G × E tests included the conventional logistic regression using multiplicative terms (one degree of freedom, 1DF test), the two-step EDGE method, and the joint 3DF test, each of which is powerful for detecting G × E interactions under specific conditions. BMI was associated with higher colorectal cancer risk. The two-step approach revealed a statistically significant G×BMI interaction located within the Formin 1/Gremlin 1 (FMN1/GREM1) gene region (rs58349661). This SNP was also identified by the 3DF test, with a suggestive statistical significance in the 1DF test. Among participants with the CC genotype of rs58349661, overweight and obesity categories were associated with higher colorectal cancer risk, whereas null associations were observed across BMI categories in those with the TT genotype. Using data from three large international consortia, this study discovered a locus in the FMN1/GREM1 gene region that interacts with BMI on the association with colorectal cancer risk. Further studies should examine the potential mechanisms through which this locus modifies the etiologic link between obesity and colorectal cancer., Significance: This gene-environment interaction analysis revealed a genetic locus in FMN1/GREM1 that interacts with body mass index in colorectal cancer risk, suggesting potential implications for precision prevention strategies., (©2023 The Authors; Published by the American Association for Cancer Research.)
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- 2023
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6. Changing Colorectal Cancer Trends in Asians: Epidemiology and Risk Factors.
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Pardamean CI, Sudigyo D, Budiarto A, Mahesworo B, Hidayat AA, Baurley JW, and Pardamean B
- Abstract
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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Pardamean, Sudigyo, Budiarto, Mahesworo, Hidayat, Baurley and Pardamean.)
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- 2023
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7. Genome-wide Interaction Study with Smoking for Colorectal Cancer Risk Identifies Novel Genetic Loci Related to Tumor Suppression, Inflammation, and Immune Response.
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Carreras-Torres R, Kim AE, Lin Y, Díez-Obrero V, Bien SA, Qu C, Wang J, Dimou N, Aglago EK, Albanes D, Arndt V, Baurley JW, Berndt SI, Bézieau S, Bishop DT, Bouras E, Brenner H, Budiarto A, Campbell PT, Casey G, Chan AT, Chang-Claude J, Chen X, Conti DV, Dampier CH, Devall MAM, Drew DA, Figueiredo JC, Gallinger S, Giles GG, Gruber SB, Gsur A, Gunter MJ, Harrison TA, Hidaka A, Hoffmeister M, Huyghe JR, Jenkins MA, Jordahl KM, Kawaguchi E, Keku TO, Kundaje A, Le Marchand L, Lewinger JP, Li L, Mahesworo B, Morrison JL, Murphy N, Nan H, Nassir R, Newcomb PA, Obón-Santacana M, Ogino S, Ose J, Pai RK, Palmer JR, Papadimitriou N, Pardamean B, Peoples AR, Pharoah PDP, Platz EA, Rennert G, Ruiz-Narvaez E, Sakoda LC, Scacheri PC, Schmit SL, Schoen RE, Shcherbina A, Slattery ML, Stern MC, Su YR, Tangen CM, Thomas DC, Tian Y, Tsilidis KK, Ulrich CM, van Duijnhoven FJB, Van Guelpen B, Visvanathan K, Vodicka P, Cenggoro TW, Weinstein SJ, White E, Wolk A, Woods MO, Hsu L, Peters U, Moreno V, and Gauderman WJ
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- Humans, Smoking genetics, Risk Factors, Genotype, Inflammation, Tobacco Smoking, Genetic Loci, Polymorphism, Single Nucleotide, Case-Control Studies, Genetic Predisposition to Disease, Colorectal Neoplasms epidemiology
- Abstract
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., (©2022 American Association for Cancer Research.)
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- 2023
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8. A genetic association study of tobacco withdrawal endophenotypes in African Americans.
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Leventhal AM, Conti DV, Ray LA, Baurley JW, Bello MS, Cho J, Zhang Y, Pester MS, Lebovitz L, Budiarto A, Mahesworo B, and Pardamean B
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- Endophenotypes, Female, Genome-Wide Association Study, Humans, Male, Nicotiana, Black or African American genetics, Smoking Cessation methods
- Abstract
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).
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- 2022
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9. Cancer Risk Score Prediction Based on a Single-Nucleotide Polymorphism Network.
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Mahesworo B, Budiarto A, Hidayat AA, and Pardamean B
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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.
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- 2022
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10. Beyond GWAS of Colorectal Cancer: Evidence of Interaction with Alcohol Consumption and Putative Causal Variant for the 10q24.2 Region.
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Jordahl KM, Shcherbina A, Kim AE, Su YR, Lin Y, Wang J, Qu C, Albanes D, Arndt V, Baurley JW, Berndt SI, Bien SA, Bishop DT, Bouras E, Brenner H, Buchanan DD, Budiarto A, Campbell PT, Carreras-Torres R, Casey G, Cenggoro TW, Chan AT, Conti DV, Dampier CH, Devall MA, Díez-Obrero V, Dimou N, Drew DA, Figueiredo JC, Gallinger S, Giles GG, Gruber SB, Gsur A, Gunter MJ, Hampel H, Harlid S, Harrison TA, Hidaka A, Hoffmeister M, Huyghe JR, Jenkins MA, Joshi AD, Keku TO, Larsson SC, Le Marchand L, Lewinger JP, Li L, Mahesworo B, Moreno V, Morrison JL, Murphy N, Nan H, Nassir R, Newcomb PA, Obón-Santacana M, Ogino S, Ose J, Pai RK, Palmer JR, Papadimitriou N, Pardamean B, Peoples AR, Pharoah PDP, Platz EA, Potter JD, Prentice RL, Rennert G, Ruiz-Narvaez E, Sakoda LC, Scacheri PC, Schmit SL, Schoen RE, Slattery ML, Stern MC, Tangen CM, Thibodeau SN, Thomas DC, Tian Y, Tsilidis KK, Ulrich CM, van Duijnhoven FJB, Van Guelpen B, Visvanathan K, Vodicka P, White E, Wolk A, Woods MO, Wu AH, Zemlianskaia N, Chang-Claude J, Gauderman WJ, Hsu L, Kundaje A, and Peters U
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- Alcohol Drinking adverse effects, Alcohol Drinking epidemiology, Alcohol Drinking genetics, Electron Transport Complex IV genetics, Humans, Polymorphism, Single Nucleotide, Risk Factors, Colorectal Neoplasms etiology, Colorectal Neoplasms genetics, Genome-Wide Association Study
- Abstract
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., (©2022 American Association for Cancer Research.)
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- 2022
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11. Intronic Variant of MUTYH Gene Exhibits A Strong Association with Early Onset of Breast Cancer Susceptibility in Indonesian Women Population.
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Panigoro SS, Listiyaningsih E, Nurlaila I, Mahesworo B, Hidayat AA, Budiarto A, Sudigyo D, Amirullah D, Simon S, Baurley J, and Pardamean B
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- Adult, Breast Neoplasms epidemiology, Breast Neoplasms ethnology, Case-Control Studies, Female, Genetic Predisposition to Disease epidemiology, Genetic Predisposition to Disease ethnology, Humans, Incidence, Indonesia epidemiology, Logistic Models, Polymorphism, Single Nucleotide, Asian People genetics, Breast Neoplasms genetics, DNA Glycosylases genetics, Genetic Predisposition to Disease genetics
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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.
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- 2021
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12. Comparative study of predicted miRNA between Indonesia and China (Wuhan) SARS-CoV-2: a bioinformatics analysis.
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Rahmadi A, Fasyah I, Sudigyo D, Budiarto A, Mahesworo B, Hidayat AA, and Pardamean B
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- COVID-19 epidemiology, COVID-19 virology, China, Humans, Indonesia, SARS-CoV-2 pathogenicity, Sequence Homology, Nucleic Acid, COVID-19 genetics, MicroRNAs genetics, SARS-CoV-2 genetics
- Abstract
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., (© 2021. The Genetics Society of Korea.)
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- 2021
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13. SSMFN: a fused spatial and sequential deep learning model for methylation site prediction.
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Lumbanraja FR, Mahesworo B, Cenggoro TW, Sudigyo D, and Pardamean B
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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., Competing Interests: The authors declare there are no competing interests., (©2021 Lumbanraja et al.)
- Published
- 2021
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14. Dietary Intake as Determinant Nongenetic Factors to Colorectal Cancer Incidence and Staging Progression: A Study in South Sulawesi Population, Indonesia.
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Nurlaila I, Hidayat AA, Budiarto A, Mahesworo B, Purwandari K, and Pardamean B
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- Case-Control Studies, Diet, Eating, Humans, Incidence, Indonesia epidemiology, Risk Factors, Colorectal Neoplasms epidemiology, Colorectal Neoplasms etiology
- Abstract
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.- Published
- 2021
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15. Quantified Self-Using Consumer Wearable Device: Predicting Physical and Mental Health.
- Author
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Pardamean B, Soeparno H, Budiarto A, Mahesworo B, and Baurley J
- Abstract
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., Competing Interests: Conflict of Interest No potential conflict of interest relevant to this article was reported., (© 2020 The Korean Society of Medical Informatics.)
- Published
- 2020
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