In experimental animals, maternal diet during the periconceptional period influences the establishment of DNA methylation at metastable epialleles in the offspring, with permanent phenotypic ...consequences. Pronounced naturally occurring seasonal differences in the diet of rural Gambian women allowed us to test this in humans. We show that significant seasonal variations in methyl-donor nutrient intake of mothers around the time of conception influence 13 relevant plasma biomarkers. The level of several of these maternal biomarkers predicts increased/decreased methylation at metastable epialleles in DNA extracted from lymphocytes and hair follicles in infants postnatally. Our results demonstrate that maternal nutritional status during early pregnancy causes persistent and systemic epigenetic changes at human metastable epialleles.
Tobacco smoking is responsible for over 90% of lung cancer cases, and yet the precise molecular alterations induced by smoking in lung that develop into cancer and impact survival have remained ...obscure.
We performed gene expression analysis using HG-U133A Affymetrix chips on 135 fresh frozen tissue samples of adenocarcinoma and paired noninvolved lung tissue from current, former and never smokers, with biochemically validated smoking information. ANOVA analysis adjusted for potential confounders, multiple testing procedure, Gene Set Enrichment Analysis, and GO-functional classification were conducted for gene selection. Results were confirmed in independent adenocarcinoma and non-tumor tissues from two studies. We identified a gene expression signature characteristic of smoking that includes cell cycle genes, particularly those involved in the mitotic spindle formation (e.g., NEK2, TTK, PRC1). Expression of these genes strongly differentiated both smokers from non-smokers in lung tumors and early stage tumor tissue from non-tumor tissue (p<0.001 and fold-change >1.5, for each comparison), consistent with an important role for this pathway in lung carcinogenesis induced by smoking. These changes persisted many years after smoking cessation. NEK2 (p<0.001) and TTK (p = 0.002) expression in the noninvolved lung tissue was also associated with a 3-fold increased risk of mortality from lung adenocarcinoma in smokers.
Our work provides insight into the smoking-related mechanisms of lung neoplasia, and shows that the very mitotic genes known to be involved in cancer development are induced by smoking and affect survival. These genes are candidate targets for chemoprevention and treatment of lung cancer in smokers.
OBJECTIVES
We aimed to estimate incident frailty risks of prescription drugs for pain and for sleep in older US adults.
DESIGN
Longitudinal cohort.
SETTING
Health and Retirement Study.
PARTICIPANTS
...Community‐living respondents aged 65 years and older, excluding individuals who received recent treatment for cancer (N = 14 208). Our longitudinal analysis sample included respondents who were not frail at baseline and had at least one follow‐up wave with complete information on both prescription drug use and frailty, or date of death (N = 7201).
MEASUREMENTS
Prescription drug use for pain and sleep, sociodemographics, other drug and substance use, and Burden frailty model components. Multivariable drug use stratified hazard models with death as a competing risk evaluated frailty risks associated with co‐use and single use of prescription drugs for pain and for sleep.
RESULTS
Proportions endorsing prescription drug use were 22.1% for pain only, 6.8% for sleep only, and 7.7% for both indications. Burden frailty model prevalence was 41.0% and varied significantly by drug use. Among non‐frail individuals at baseline, proportions endorsing prescription drug use were 14.9%, 5.6%, and 2.2% for the three indications. Prescription drug use was associated with increased risk of frailty (co‐use adjusted subhazard ratio sHR = 1.95; 95% confidence interval CI = 1.6‐2.4; pain only adjusted sHR = 1.58; CI = 1.4‐1.8; sleep‐only adjusted sHR = 1.35; CI = 1.1‐1.6; no use = reference group). Cumulative incidence of frailty over 8 years for the four groups was 60.6%, 50.9%, 45.8%, and 34.1%. Sensitivity analyses controlling for chronic diseases associated with persistent pain resulted in minor risk reductions.
CONCLUSION
Prescription pain and sleep drug use is significantly associated with increased incidence of frailty. Research to estimate effects of pain and sleep indications and of drug class–specific dosage and duration on incident frailty is indicated before advocating deprescribing based on these findings. J Am Geriatr Soc 67:2474–2481, 2019
See related editorial by Paula Rochon and related article by Shahar Shmuel
The molecular drivers that determine histology in lung cancer are largely unknown. We investigated whether microRNA (miR) expression profiles can differentiate histologic subtypes and predict ...survival for non-small cell lung cancer.
We analyzed miR expression in 165 adenocarcinoma and 125 squamous cell carcinoma (SQ) tissue samples from the Environment And Genetics in Lung cancer Etiology (EAGLE) study using a custom oligo array with 440 human mature antisense miRs. We compared miR expression profiles using t tests and F tests and accounted for multiple testing using global permutation tests. We assessed the association of miR expression with tobacco smoking using Spearman correlation coefficients and linear regression models, and with clinical outcome using log-rank tests, Cox proportional hazards, and survival risk prediction models, accounting for demographic and tumor characteristics.
MiR expression profiles strongly differed between adenocarcinoma and SQ (P(global) < 0.0001), particularly in the early stages, and included miRs located on chromosome loci most often altered in lung cancer (e.g., 3p21-22). Most miRs, including all members of the let-7 family, were downregulated in SQ. Major findings were confirmed by quantitative real time-polymerase chain reaction (qRT-PCR) in EAGLE samples and in an independent set of lung cancer cases. In SQ, the low expression of miRs that are downregulated in the histology comparison was associated with 1.2- to 3.6-fold increased mortality risk. A five-miR signature significantly predicted survival for SQ.
We identified a miR expression profile that strongly differentiated adenocarcinoma from SQ and had prognostic implications. These findings may lead to histology-based therapeutic approaches.
The contribution of common genetic variation to one or more established smoking behaviors was investigated in a joint analysis of two genome wide association studies (GWAS) performed as part of the ...Cancer Genetic Markers of Susceptibility (CGEMS) project in 2,329 men from the Prostate, Lung, Colon and Ovarian (PLCO) Trial, and 2,282 women from the Nurses' Health Study (NHS). We analyzed seven measures of smoking behavior, four continuous (cigarettes per day CPD, age at initiation of smoking, duration of smoking, and pack years), and three binary (ever versus never smoking, < or = 10 versus > 10 cigarettes per day CPDBI, and current versus former smoking). Association testing for each single nucleotide polymorphism (SNP) was conducted by study and adjusted for age, cohabitation/marital status, education, site, and principal components of population substructure. None of the SNPs achieved genome-wide significance (p<10(-7)) in any combined analysis pooling evidence for association across the two studies; we observed between two and seven SNPs with p<10(-5) for each of the seven measures. In the chr15q25.1 region spanning the nicotinic receptors CHRNA3 and CHRNA5, we identified multiple SNPs associated with CPD (p<10(-3)), including rs1051730, which has been associated with nicotine dependence, smoking intensity and lung cancer risk. In parallel, we selected 11,199 SNPs drawn from 359 a priori candidate genes and performed individual-gene and gene-group analyses. After adjusting for multiple tests conducted within each gene, we identified between two and five genes associated with each measure of smoking behavior. Besides CHRNA3 and CHRNA5, MAOA was associated with CPDBI (gene-level p<5.4x10(-5)), our analysis provides independent replication of the association between the chr15q25.1 region and smoking intensity and data for multiple other loci associated with smoking behavior that merit further follow-up.
There 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).
We 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.
We 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.
Populations in sub-Saharan Africa have historically been exposed to intense selection from chronic infection with falciparum malaria. Interestingly, populations with the highest malaria intensity can ...be identified by the increased occurrence of endemic Burkitt Lymphoma (eBL), a pediatric cancer that affects populations with intense malaria exposure, in the so called "eBL belt" in sub-Saharan Africa. However, the effects of intense malaria exposure and sub-Saharan populations' genetic histories remain poorly explored. To determine if historical migrations and intense malaria exposure have shaped the genetic composition of the eBL belt populations, we genotyped ~4.3 million SNPs in 1,708 individuals from Ghana and Northern Uganda, located on opposite sides of eBL belt and with ≥ 7 months/year of intense malaria exposure and published evidence of high incidence of BL. Among 35 Ghanaian tribes, we showed a predominantly West-Central African ancestry and genomic footprints of gene flow from Gambian and East African populations. In Uganda, the North West population showed a predominantly Nilotic ancestry, and the North Central population was a mixture of Nilotic and Southern Bantu ancestry, while the Southwest Ugandan population showed a predominant Southern Bantu ancestry. Our results support the hypothesis of diverse ancestral origins of the Ugandan, Kenyan and Tanzanian Great Lakes African populations, reflecting a confluence of Nilotic, Cushitic and Bantu migrations in the last 3000 years. Natural selection analyses suggest, for the first time, a strong positive selection signal in the ATP2B4 gene (rs10900588) in Northern Ugandan populations. These findings provide important baseline genomic data to facilitate disease association studies, including of eBL, in eBL belt populations.
Despite the large public health toll of smoking, genetic studies of smoking cessation have been limited with few discoveries of risk or protective loci. We investigated common and rare variant ...associations with success in quitting smoking using a cohort from 8 randomized controlled trials involving 2231 participants and a total of 10,020 common and 24,147 rare variants. We identified 14 novel markers including 6 mapping to genes previously related to psychiatric and substance use disorders, 4 of which were protective (CYP2B6 (rs1175607105), HTR3B (rs1413172952; rs1204720503), rs80210037 on chr15), and 2 of which were associated with reduced cessation (PARP15 (rs2173763), SCL18A2 (rs363222)). The others mapped to areas associated with cancer including FOXP1 (rs1288980) and ZEB1 (rs7349). Network analysis identified significant canonical pathways for the serotonin receptor signaling pathway, nicotine and bupropion metabolism, and several related to tumor suppression. Two novel markers (rs6749438; rs6718083) on chr2 are flanked by genes associated with regulation of bodyweight. The identification of novel loci in this study can provide new targets of pharmacotherapy and inform efforts to develop personalized treatments based on genetic profiles.
Addictive disorders are a class of chronic, relapsing mental disorders that are responsible for increased risk of mental and medical disorders and represent the largest, potentially modifiable cause ...of death. Tobacco dependence is associated with increased risk of disease and premature death. While tobacco control efforts and therapeutic interventions have made good progress in reducing smoking prevalence, challenges remain in optimizing their effectiveness based on patient characteristics, including genetic variation. In order to maximize collaborative efforts to advance addiction research, we have developed a genotyping array called Smokescreen. This custom array builds upon previous work in the analyses of human genetic variation, the genetics of addiction, drug metabolism, and response to therapy, with an emphasis on smoking and nicotine addiction.
The Smokescreen genotyping array includes 646,247 markers in 23 categories. The array design covers genome-wide common variation (65.67, 82.37, and 90.72% in African (YRI), East Asian (ASN), and European (EUR) respectively); most of the variation with a minor allele frequency ≥ 0.01 in 1014 addiction genes (85.16, 89.51, and 90.49% for YRI, ASN, and EUR respectively); and nearly all variation from the 1000 Genomes Project Phase 1, NHLBI GO Exome Sequencing Project and HapMap databases in the regions related to smoking behavior and nicotine metabolism: CHRNA5-CHRNA3-CHRNB4 and CYP2A6-CYP2B6. Of the 636 pilot DNA samples derived from blood or cell line biospecimens that were genotyped on the array, 622 (97.80%) passed quality control. In passing samples, 90.08% of markers passed quality control. The genotype reproducibility in 25 replicate pairs was 99.94%. For 137 samples that overlapped with HapMap2 release 24, the genotype concordance was 99.76%. In a genome-wide association analysis of the nicotine metabolite ratio in 315 individuals participating in nicotine metabolism laboratory studies, we identified genome-wide significant variants in the CYP2A6 region (min p = 9.10E-15).
We developed a comprehensive genotyping array for addiction research and demonstrated its analytic validity and utility through pilot genotyping of HapMap and study samples. This array allows researchers to perform genome-wide, candidate gene, and pathway-based association analyses of addiction, tobacco-use, treatment response, comorbidities, and associated diseases in a standardized, high-throughput platform.
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