Associations Between Genetic Ancestries and Nicotine Metabolism Biomarkers in the Multiethnic Cohort Study.
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ABSTRACT:
SUBMITTER: Wang H
PROVIDER: S-EPMC4805060 | biostudies-literature | 2015 Dec
REPOSITORIES: biostudies-literature
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Associations Between Genetic Ancestries and Nicotine Metabolism Biomarkers in the Multiethnic Cohort Study.
Wang Hansong H Park Sungshim L SL Stram Daniel O DO Haiman Christopher A CA Wilkens Lynne R LR Hecht Stephen S SS Kolonel Laurence N LN Murphy Sharon E SE Le Marchand Loïc L
American journal of epidemiology 20151114 11
Differences in internal dose of nicotine and tobacco-derived carcinogens among ethnic/racial groups have been observed. In this study, we explicitly examined the relationships between genetic ancestries (genome-wide average) and 19 tobacco-derived biomarkers in smokers from 3 admixed groups in the Multiethnic Cohort Study (1993-present), namely, African ancestry in African Americans (n = 362), Amerindian ancestry in Latinos (n = 437), and Asian and Native Hawaiian ancestries in Native Hawaiians ...[more]
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Project description:BackgroundThere is a need to match characteristics of tobacco users with cessation treatments and risks of tobacco attributable diseases such as lung cancer. The rate in which the body metabolizes nicotine has proven an important predictor of these outcomes. Nicotine metabolism is primarily catalyzed by the enzyme cytochrone P450 (CYP2A6) and CYP2A6 activity can be measured as the ratio of two nicotine metabolites: trans-3'-hydroxycotinine to cotinine (NMR). Measurements of these metabolites are only possible in current tobacco users and vary by biofluid source, timing of collection, and protocols; unfortunately, this has limited their use in clinical practice. The NMR depends highly on genetic variation near CYP2A6 on chromosome 19 as well as ancestry, environmental, and other genetic factors. Thus, we aimed to develop prediction models of nicotine metabolism using genotypes and basic individual characteristics (age, gender, height, and weight).ResultsWe identified four multiethnic studies with nicotine metabolites and DNA samples. We constructed a 263 marker panel from filtering genome-wide association scans of the NMR in each study. We then applied seven machine learning techniques to train models of nicotine metabolism on the largest and most ancestrally diverse dataset (N=2239). The models were then validated using the other three studies (total N=1415). Using cross-validation, we found the correlations between the observed and predicted NMR ranged from 0.69 to 0.97 depending on the model. When predictions were averaged in an ensemble model, the correlation was 0.81. The ensemble model generalizes well in the validation studies across ancestries, despite differences in the measurements of NMR between studies, with correlations of: 0.52 for African ancestry, 0.61 for Asian ancestry, and 0.46 for European ancestry. The most influential predictors of NMR identified in more than two models were rs56113850, rs11878604, and 21 other genetic variants near CYP2A6 as well as age and ancestry.ConclusionsWe have developed an ensemble of seven models for predicting the NMR across ancestries from genotypes and age, gender and BMI. These models were validated using three datasets and associate with nicotine dosages. The knowledge of how an individual metabolizes nicotine could be used to help select the optimal path to reducing or quitting tobacco use, as well as, evaluating risks of tobacco use.
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Project description:IntroductionThe nicotine metabolite ratio and nicotine equivalents are measures of metabolism rate and intake. Genome-wide prediction of these nicotine biomarkers in multiethnic samples will enable tobacco-related biomarker, behavioral, and exposure research in studies without measured biomarkers.Aims and methodsWe screened genetic variants genome-wide using marginal scans and applied statistical learning algorithms on top-ranked genetic variants, age, ethnicity and sex, and, in additional modeling, cigarettes per day (CPD), (in additional modeling) to build prediction models for the urinary nicotine metabolite ratio (uNMR) and creatinine-standardized total nicotine equivalents (TNE) in 2239 current cigarette smokers in five ethnic groups. We predicted these nicotine biomarkers using model ensembles and evaluated external validity using dependence measures in 1864 treatment-seeking smokers in two ethnic groups.ResultsThe genomic regions with the most selected and included variants for measured biomarkers were chr19q13.2 (uNMR, without and with CPD) and chr15q25.1 and chr10q25.3 (TNE, without and with CPD). We observed ensemble correlations between measured and predicted biomarker values for the uNMR and TNE without (with CPD) of 0.67 (0.68) and 0.65 (0.72) in the training sample. We observed inconsistency in penalized regression models of TNE (with CPD) with fewer variants at chr15q25.1 selected and included. In treatment-seeking smokers, predicted uNMR (without CPD) was significantly associated with CPD and predicted TNE (without CPD) with CPD, time-to-first-cigarette, and Fagerström total score.ConclusionsNicotine metabolites, genome-wide data, and statistical learning approaches developed novel robust predictive models for urinary nicotine biomarkers in multiple ethnic groups. Predicted biomarker associations helped define genetically influenced components of nicotine dependence.ImplicationsWe demonstrate development of robust models and multiethnic prediction of the uNMR and TNE using statistical and machine learning approaches. Variants included in trained models for nicotine biomarkers include top-ranked variants in multiethnic genome-wide studies of smoking behavior, nicotine metabolites, and related disease. Association of the two predicted nicotine biomarkers with Fagerström Test for Nicotine Dependence items supports models of nicotine biomarkers as predictors of physical dependence and nicotine exposure. Predicted nicotine biomarkers may facilitate tobacco-related disease and treatment research in samples with genomic data and limited nicotine metabolite or tobacco exposure data.
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Project description:BACKGROUND:The mitochondrial genome encodes for thirty-seven proteins, among them thirteen are essential for the oxidative phosphorylation (OXPHOS) system. Inherited variation in mitochondrial genes may influence cancer development through changes in mitochondrial proteins, altering the OXPHOS process and promoting the production of reactive oxidative species. METHODS:To investigate the association between mitochondrial genetic variation and breast cancer risk, we tested 314 mitochondrial SNPs (mtSNPs), capturing four complexes of the mitochondrial OXPHOS pathway and mtSNP groupings for rRNA and tRNA, in 2,723 breast cancer cases and 3,260 controls from the Multiethnic Cohort Study. RESULTS:We examined the collective set of 314 mtSNPs as well as subsets of mtSNPs grouped by mitochondrial OXPHOS pathway, complexes, and genes, using the sequence kernel association test and adjusting for age, sex, and principal components of global ancestry. We also tested haplogroup associations using unconditional logistic regression and adjusting for the same covariates. Stratified analyses were conducted by self-reported maternal race/ethnicity. No significant mitochondrial OXPHOS pathway, gene, and haplogroup associations were observed in African Americans, Asian Americans, Latinos, and Native Hawaiians. In European Americans, a global test of all genetic variants of the mitochondrial genome identified an association with breast cancer risk (P = 0.017, q = 0.102). In mtSNP-subset analysis, the gene MT-CO2 (P = 0.001, q = 0.09) in Complex IV (cytochrome c oxidase) and MT-ND2 (P = 0.004, q = 0.19) in Complex I (NADH dehydrogenase (ubiquinone)) were significantly associated with breast cancer risk. CONCLUSIONS:In summary, our findings suggest that collective mitochondrial genetic variation and particularly in the MT-CO2 and MT-ND2 may play a role in breast cancer risk among European Americans. Further replication is warranted in larger populations and future studies should evaluate the contribution of mitochondrial proteins encoded by both the nuclear and mitochondrial genomes to breast cancer risk.
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Project description:BackgroundGenetic variation in one-carbon metabolism may affect nutrient concentrations and biological functions. However, data on genetic variants associated with blood biomarkers of one-carbon metabolism in US postmenopausal women are limited, and whether these associations were affected by the nationwide folic acid (FA) fortification program is unclear.ObjectivesWe investigated associations between genetic variants and biomarkers of one-carbon metabolism using data from the Women's Health Initiative Observational Study.MethodsIn 1573 non-Hispanic White (NHW) and 282 Black/African American, American Indian/Alaska Native, Asian/Pacific Islander, and Hispanic/Latino women aged 50-79 y, 288 nonsynonymous and tagging single-nucleotide variants (SNVs) were genotyped. RBC folate, plasma folate, pyridoxal-5'-phosphate (PLP), vitamin B-12, homocysteine, and cysteine concentrations were determined in 12-h fasting blood. Multivariable linear regression tested associations per variant allele and for an aggregated genetic risk score. Effect modifications before, during, and after nationwide FA fortification were examined.ResultsAfter correction for multiple comparisons, among NHW women, 5,10-methylenetetrahydrofolate reductase (MTHFR) rs1801133 (677C→T) variant T was associated with lower plasma folate (-13.0%; 95% CI: -17.3%, -8.6%) and higher plasma homocysteine (3.5%; 95% CI: 1.7%, 5.3%) concentrations. Other associations for nonsynonymous SNVs included DNMT3A rs11695471 (T→A) with plasma PLP; EHMT2 rs535586 (G→A), TCN2 rs1131603 (L349S A→G), and TCN2 rs35838082 (R188W G→A) with plasma vitamin B-12; CBS rs2851391 (G→A) with plasma homocysteine; and MTHFD1 rs2236224 (G→A) and rs2236225 (R653Q G→A) with plasma cysteine. The influence of FA fortification on the associations was limited. Highest compared with lowest quartiles of aggregated genetic risk scores from SNVs in MTHFR and MTRR were associated with 14.8% to 18.9% lower RBC folate concentrations. Gene-biomarker associations were similar in women of other races/ethnicities.ConclusionsOur findings on genetic variants associated with several one-carbon metabolism biomarkers may help elucidate mechanisms of maintaining B vitamin status in postmenopausal women.
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Project description:ImportanceSocioeconomic status may help delineate racial and ethnic inequities in mortality.ObjectiveTo investigate the joint associations of race, ethnicity, and neighborhood and individual socioeconomic status with mortality.Design, setting, and participantsThis prospective analysis used data from the Multiethnic Cohort Study. A population-based sample of participants recruited from California (mainly Los Angeles County) and Hawaii from 1993 to 1996 was followed up until 2013. African American, European American, Japanese American, Latino American, and Native Hawaiian men and women were included. Participants with baseline residential addresses that could not be geocoded or who were missing information on education or adjustment variables were excluded. Data analyses were conducted from January 2018 to December 2020.ExposuresNeighborhood socioeconomic status (nSES) was derived using US Census block group data on education, occupation, unemployment, household income, poverty, rent, and house values. Participants self-reported their highest education attainment. Five racial and ethnic groups, 2 states of residence, 2 nSES, and 2 education categories were combined to create a joint exposure variable. Low and high nSES were defined as quintiles 1 to 3 and 4 to 5, respectively. Low and high education levels were defined as high school or less and greater than high school graduate, respectively.Main outcomes and measuresAll-cause, cardiovascular disease (CVD), cancer, and non-CVD and noncancer deaths were ascertained through 2013 via linkage to death certificates and the US National Death Index. Multivariable Cox proportional hazards regression analyses were conducted.ResultsAmong 182 912 participants (100 785 [55.1%] women and 82 127 [44.9%] men; mean [SD] age, 60.0 [8.9] years; 31 138 African American, 45 796 European American, 52 993 Japanese American, 39 844 Latino American, and 13 141 Native Hawaiian participants) with a mean (SD) follow-up of 17 (5) years, there were 63 799 total deaths, including 23 191 CVD deaths, 19 008 cancer deaths, and 21 235 non-CVD and noncancer deaths. The lowest all-cause mortality was found among 15 104 Japanese American participants in Hawaii with high nSES and high education (eg, 2870 all-cause deaths [19.0%]), and this population served as the reference group for all regression analyses. Native Hawaiian participants in Hawaii with low nSES and low education had the highest all-cause mortality HR (2.38; 95% CI, 2.21-2.57). African American and European American participants in California with low nSES and low education had the next highest all-cause mortality HRs (2.01; 95% CI, 1.91-2.11 and 1.98; 95% CI, 1.85-2.12, respectively). Latino American participants in California with low nSES had equivalent all-cause mortality HRs regardless of education level (high education: 1.57; 95% CI, 1.48-1.66; low education: 1.57; 95% CI, 1.50-1.65). Patterns for cause-specific mortality were similar to those for all-cause mortality. For example, Native Hawaiian participants in Hawaii with low nSES and low education had highest CVD mortality HR (2.92; 95% CI, 2.60-3.27) and cancer mortality HR (2.01; 95% CI, 1.77-2.29).Conclusions and relevanceThese results suggest that joint associations of nSES and education may further delineate racial and ethnic inequities in mortality and that future investigations of racial and ethnic inequities in mortality should consider differences by measures of socioeconomic status, especially for underserved populations.
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Project description:This case-control study explored the relationship between SNPs in miR-221 and self-reported essential hypertension, as well as interactions between genetic and environmental factors, in a multiethnic Chinese cohort. A MassArray analysis was performed to genotype 462 patients with essential hypertension and 442 healthy participants. The association between four SNPs in miR-221 and essential hypertension risk was determined by investigating the differences in allelic and genotypic frequencies between case and control groups using PLINK version 1.07 software. A 4 × 2 table approach was conducted to explore the synergistic effect of SNPs and environmental factors on the risk of essential hypertension. Subjects with the C allele of rs2858060 in miR-221 had a lower risk of essential hypertension than those with the G allele (OR = 0.692; 95% CI = 0.521-0.920; P = 0.011). Logistic regression analysis showed that carriers of the CC genotype had a significantly lower risk of essential hypertension than those with the homozygous GG genotype (OR = 0.679; 95% CI = 0.498-0.925; P = 0.014). Using crossover analyses, we identified significant interactions between rs2858060 and the effect of age, triglycerides, HDL-C, ApoB, and fasting blood glucose on essential hypertension risk. We conclude that rs2858060 in miR-221 is associated with essential hypertension risk in the Chinese population, with a clear interaction between rs2858060 and classical risk factors in predicting the condition. Therefore, rs2858060 in miR-221 could play an important role as a genetic risk factor for the development of essential hypertension in the Chinese population.
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