Apolipoprotein E and protection against hepatitis E viral infection in American non-Hispanic blacks.

UNLABELLED: Hepatitis E viral (HEV) infection imposes a heavy health burden worldwide and is common in the United States. Previous investigations of risks addressed environmental and host behavioral/lifestyle factors, but host genetic factors have not been examined. We assessed strength of associations between antibody to HEV (anti-HEV) immunoglobulin G seropositivity indicating past or recent HEV infection and human genetic variants among three major racial/ethnic populations in the United States, involving 2434 non-Hispanic whites, 1919 non-Hispanic blacks, and 1919 Mexican Americans from the Third National Health and Nutrition Examination Survey, 1991-1994. We studied 497 single-nucleotide polymorphisms across 190 genes (particularly those associated with lipid metabolism). The genomic control method was used to adjust for potential population stratification. Non-Hispanic blacks had the lowest seroprevalence of anti-HEV immunoglobulin G (15.3%, 95% confidence interval [CI] 12.3%-19.0%) compared with non-Hispanic whites (22.3%, 95% CI 19.1%-25.7%) and Mexican Americans (21.8%, 95% CI 19.0%-25.3%; P<0.01). Non-Hispanic blacks were the only population that showed association between anti-HEV seropositivity and functional ε3 and ε4 alleles of the apolipoprotein E (APOE) gene, encoding the apolipoprotein E protein that mediates lipoprotein metabolism. Seropositivity was significantly lower in participants carrying APOE ε4 (odds ratio=0.5, 95% CI 0.4-0.7; P=0.00004) and ε3 (odds ratio=0.6, 95% CI 0.4-0.8; P=0.001) compared to those carrying APOE ε2. No significant associations were observed between other single-nucleotide polymorphisms and anti-HEV seropositivity in non-Hispanic blacks or between any single-nucleotide polymorphisms and anti-HEV seropositivity in non-Hispanic whites or Mexican Americans. CONCLUSION: Both APOE ε3 and ε4 are significantly associated with protection against HEV infection in non-Hispanic blacks; additional studies are needed to understand the basis of protection so that preventive services can be targeted to at-risk persons.

Evaluation of Diverse Health Professionals' Learning Experience in a Continuing Education Activity for Quality Practices in Molecular Genetic Testing.

OBJECTIVE: This study was conducted to evaluate the responses of 3,265 health professionals who took a continuing education (CE) activity during June 2009 - April 2012 for a comprehensive set of good laboratory practice recommendations for molecular genetic testing. DESIGN: Participants completed an evaluation questionnaire as part of the CE activity. Responses were summarized to assess the participants' learning outcomes and commitment to applying the knowledge gained. PARTICIPANTS: Participants included nurses (47%), laboratory professionals (18%), physicians (14%), health educators (4%), public health professionals (2%), office staff (1%), and other health professionals (10%). RESULTS: Only 32% of all participants correctly answered all 12 open-book knowledge-check questions, ranging from 4 to 42% among the different professional groups (P<0.0001). However, over 80% of all participants expressed confidence in describing the practice recommendations, and 75% indicated the recommendations would improve the quality of their practice. Developing health education materials and local practice guidelines represented the common areas in which participants planned to use the knowledge gained (49% and 18% of all participants, respectively). CONCLUSION: Despite perceived self-efficacy in most participants, as high as 68% did not fully use the learning materials provided to answer the knowledge-check questions. These findings suggest the need for improved CE activities that motivate effective learning and address the specific needs of different health professions.

Variants in ABCB1, TGFB1, and XRCC1 genes and susceptibility to viral hepatitis A infection in Mexican Americans.

UNLABELLED: Hepatitis A vaccination has dramatically reduced the incidence of hepatitis A virus (HAV) infection, but new infections continue to occur. To identify human genetic variants conferring a risk for HAV infection among the three major racial/ethnic populations in the United States, we assessed associations between 67 genetic variants (single nucleotide polymorphisms [SNPs]) among 31 candidate genes and serologic evidence of prior HAV infection using a population-based, cross-sectional study of 6,779 participants, including 2,619 non-Hispanic whites, 2,095 non-Hispanic blacks, and 2,065 Mexican Americans enrolled in phase 2 (1991-1994) of the Third National Health and Nutrition Examination Survey. Among the three racial/ethnic groups, the number (weighted frequency) of seropositivity for antibody to HAV was 958 (24.9%), 802 (39.2%), and 1540 (71.5%), respectively. No significant associations with any of the 67 SNPs were observed among non-Hispanic whites or non-Hispanic blacks. In contrast, among Mexican Americans, variants in two genes were found to be associated with an increased risk of HAV infection: TGFB1 rs1800469 (adjusted odds ratio [OR], 1.38; 95% confidence interval [CI], 1.14-1.68; P value adjusted for false discovery rate [FDR-P] = 0.017) and XRCC1 rs1799782 (OR, 1.57; 95% CI, 1.27-1.94; FDR-P = 0.0007). A decreased risk was found with ABCB1 rs1045642 (OR, 0.79; 95% CI, 0.71-0.89; FDR-P = 0.0007). CONCLUSION: Genetic variants in ABCB1, TGFB1, and XRCC1 appear to be associated with susceptibility to HAV infection among Mexican Americans. Replication studies involving larger population samples are warranted.

Race-ethnic differences in the association of genetic loci with HbA1c levels and mortality in U.S. adults: the third National Health and Nutrition Examination Survey (NHANES III).

BACKGROUND: Hemoglobin A1c (HbA1c) levels diagnose diabetes, predict mortality and are associated with ten single nucleotide polymorphisms (SNPs) in white individuals. Genetic associations in other race groups are not known. We tested the hypotheses that there is race-ethnic variation in 1) HbA1c-associated risk allele frequencies (RAFs) for SNPs near SPTA1, HFE, ANK1, HK1, ATP11A, FN3K, TMPRSS6, G6PC2, GCK, MTNR1B; 2) association of SNPs with HbA1c and 3) association of SNPs with mortality. METHODS: We studied 3,041 non-diabetic individuals in the NHANES (National Health and Nutrition Examination Survey) III. We stratified the analysis by race/ethnicity (NHW: non-Hispanic white; NHB: non-Hispanic black; MA: Mexican American) to calculate RAF, calculated a genotype score by adding risk SNPs, and tested associations with SNPs and the genotype score using an additive genetic model, with type 1 error = 0.05. RESULTS: RAFs varied widely and at six loci race-ethnic differences in RAF were significant (p < 0.0002), with NHB usually the most divergent. For instance, at ATP11A, the SNP RAF was 54% in NHB, 18% in MA and 14% in NHW (p < .0001). The mean genotype score differed by race-ethnicity (NHW: 10.4, NHB: 11.0, MA: 10.7, p < .0001), and was associated with increase in HbA1c in NHW (ß = 0.012 HbA1c increase per risk allele, p = 0.04) and MA (ß = 0.021, p = 0.005) but not NHB (ß = 0.007, p = 0.39). The genotype score was not associated with mortality in any group (NHW: OR (per risk allele increase in mortality) = 1.07, p = 0.09; NHB: OR = 1.04, p = 0.39; MA: OR = 1.03, p = 0.71). CONCLUSION: At many HbA1c loci in NHANES III there is substantial RAF race-ethnic heterogeneity. The combined impact of common HbA1c-associated variants on HbA1c levels varied by race-ethnicity, but did not influence mortality.

A Hardy-Weinberg equilibrium test for analyzing population genetic surveys with complex sample designs.

Testing for deviations from Hardy-Weinberg equilibrium is a widely recommended practice for population-based genetic association studies. However, current methods for this test assume a simple random sample and may not be appropriate for sample surveys with complex survey designs. In this paper, the authors present a test for Hardy-Weinberg equilibrium that adjusts for the sample weights and correlation of data collected in complex surveys. The authors perform this test by using a simple adjustment to procedures developed to analyze data from complex survey designs available within the SAS statistical software package (SAS Institute, Inc., Cary, North Carolina). Using 90 genetic markers from the Third National Health and Nutrition Examination Survey, the authors found that survey-adjusted and -unadjusted estimates of the disequilibrium coefficient were generally similar within self-reported races/ethnicities. However, estimates of the variance of the disequilibrium coefficient were significantly different between the 2 methods. Because the results of the survey-adjusted tests account for correlation among participants sampled within the same cluster, and the possibility of having related individuals sampled from the same household, the authors recommend use of this test when analyzing genetic data originating from sample surveys with complex survey designs to assess deviations from Hardy-Weinberg equilibrium.

Genetic variants associated with fasting blood lipids in the U.S. population: Third National Health and Nutrition Examination Survey.

BACKGROUND: The identification of genetic variants related to blood lipid levels within a large, population-based and nationally representative study might lead to a better understanding of the genetic contribution to serum lipid levels in the major race/ethnic groups in the U.S. population. METHODS: Using data from the second phase (1991-1994) of the Third National Health and Nutrition Examination Survey (NHANES III), we examined associations between 22 polymorphisms in 13 candidate genes and four serum lipids: high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TG). Univariate and multivariable linear regression and within-gene haplotype trend regression were used to test for genetic associations assuming an additive mode of inheritance for each of the three major race/ethnic groups in the United States (non-Hispanic white, non-Hispanic black, and Mexican American). RESULTS: Variants within APOE (rs7412, rs429358), PON1 (rs854560), ITGB3 (rs5918), and NOS3 (rs2070744) were found to be associated with one or more blood lipids in at least one race/ethnic group in crude and adjusted analyses. In non-Hispanic whites, no individual polymorphisms were associated with any lipid trait. However, the PON1 A-G haplotype was significantly associated with LDL-C and TC. In non-Hispanic blacks, APOE variant rs7412 and haplotype T-T were strongly associated with LDL-C and TC; whereas, rs5918 of ITGB3 was significantly associated with TG. Several variants and haplotypes of three genes were significantly related to lipids in Mexican Americans: PON1 in relation to HDL-C; APOE and NOS3 in relation to LDL-C; and APOE in relation to TC. CONCLUSIONS: We report the significant associations of blood lipids with variants and haplotypes in APOE, ITGB3, NOS3, and PON1 in the three main race/ethnic groups in the U.S. population using a large, nationally representative and population-based sample survey. Results from our study contribute to a growing body of literature identifying key determinants of plasma lipoprotein concentrations and could provide insight into the biological mechanisms underlying serum lipid and cholesterol concentrations.

Inflammation gene variants and susceptibility to albuminuria in the U.S. population: analysis in the Third National Health and Nutrition Examination Survey (NHANES III), 1991-1994.

BACKGROUND: Albuminuria, a common marker of kidney damage, serves as an important predictive factor for the progression of kidney disease and for the development of cardiovascular disease. While the underlying etiology is unclear, chronic, low-grade inflammation is a suspected key factor. Genetic variants within genes involved in inflammatory processes may, therefore, contribute to the development of albuminuria. METHODS: We evaluated 60 polymorphisms within 27 inflammatory response genes in participants from the second phase (1991-1994) of the Third National Health and Nutrition Examination Survey (NHANES III), a population-based and nationally representative survey of the United States. Albuminuria was evaluated as logarithm-transformed albumin-to-creatinine ratio (ACR), as ACR ≥ 30 mg/g, and as ACR above sex-specific thresholds. Multivariable linear regression and haplotype trend analyses were conducted to test for genetic associations in 5321 participants aged 20 years or older. Differences in allele and genotype distributions among non-Hispanic whites, non-Hispanic blacks, and Mexican Americans were tested in additive and codominant genetic models. RESULTS: Variants in several genes were found to be marginally associated (uncorrected P value < 0.05) with log(ACR) in at least one race/ethnic group, but none remained significant in crude or fully-adjusted models when correcting for the false-discovery rate (FDR). In analyses of sex-specific albuminuria, IL1B (rs1143623) among Mexican Americans remained significantly associated with increased odds, while IL1B (rs1143623), CRP (rs1800947) and NOS3 (rs2070744) were significantly associated with ACR ≥ 30 mg/g in this population (additive models, FDR-P < 0.05). In contrast, no variants were found to be associated with albuminuria among non-Hispanic blacks after adjustment for multiple testing. The only variant among non-Hispanic whites significantly associated with any outcome was TNF rs1800750, which failed the test for Hardy-Weinberg proportions in this population. Haplotypes within MBL2, CRP, ADRB2, IL4R, NOS3, and VDR were significantly associated (FDR-P < 0.05) with log(ACR) or albuminuria in at least one race/ethnic group. CONCLUSIONS: Our findings suggest a small role for genetic variation within inflammation-related genes to the susceptibility to albuminuria. Additional studies are needed to further assess whether genetic variation in these, and untested, inflammation genes alter the susceptibility to kidney damage.

Gene polymorphisms in association with emerging cardiovascular risk markers in adult women.

BACKGROUND: Evidence on the associations of emerging cardiovascular disease risk factors/markers with genes may help identify intermediate pathways of disease susceptibility in the general population. This population-based study is aimed to determine the presence of associations between a wide array of genetic variants and emerging cardiovascular risk markers among adult US women. METHODS: The current analysis was performed among the National Health and Nutrition Examination Survey (NHANES) III phase 2 samples of adult women aged 17 years and older (sample size n = 3409). Fourteen candidate genes within ADRB2, ADRB3, CAT, CRP, F2, F5, FGB, ITGB3, MTHFR, NOS3, PON1, PPARG, TLR4, and TNF were examined for associations with emerging cardiovascular risk markers such as serum C-reactive protein, homocysteine, uric acid, and plasma fibrinogen. Linear regression models were performed using SAS-callable SUDAAN 9.0. The covariates included age, race/ethnicity, education, menopausal status, female hormone use, aspirin use, and lifestyle factors. RESULTS: In covariate-adjusted models, serum C-reactive protein concentrations were significantly (P value controlling for false-discovery rate < or = 0.05) associated with polymorphisms in CRP (rs3093058, rs1205), MTHFR (rs1801131), and ADRB3 (rs4994). Serum homocysteine levels were significantly associated with MTHFR (rs1801133). CONCLUSION: The significant associations between certain gene variants with concentration variations in serum C-reactive protein and homocysteine among adult women need to be confirmed in further genetic association studies.

Prevalence in the United States of selected candidate gene variants: Third National Health and Nutrition Examination Survey, 1991-1994.

Population-based allele frequencies and genotype prevalence are important for measuring the contribution of genetic variation to human disease susceptibility, progression, and outcomes. Population-based prevalence estimates also provide the basis for epidemiologic studies of gene-disease associations, for estimating population attributable risk, and for informing health policy and clinical and public health practice. However, such prevalence estimates for genotypes important to public health remain undetermined for the major racial and ethnic groups in the US population. DNA was collected from 7,159 participants aged 12 years or older in Phase 2 (1991-1994) of the Third National Health and Nutrition Examination Survey (NHANES III). Certain age and minority groups were oversampled in this weighted, population-based US survey. Estimates of allele frequency and genotype prevalence for 90 variants in 50 genes chosen for their potential public health significance were calculated by age, sex, and race/ethnicity among non-Hispanic whites, non-Hispanic blacks, and Mexican Americans. These nationally representative data on allele frequency and genotype prevalence provide a valuable resource for future epidemiologic studies in public health in the United States.

GAPscreener: an automatic tool for screening human genetic association literature in PubMed using the support vector machine technique.

BACKGROUND: Synthesis of data from published human genetic association studies is a critical step in the translation of human genome discoveries into health applications. Although genetic association studies account for a substantial proportion of the abstracts in PubMed, identifying them with standard queries is not always accurate or efficient. Further automating the literature-screening process can reduce the burden of a labor-intensive and time-consuming traditional literature search. The Support Vector Machine (SVM), a well-established machine learning technique, has been successful in classifying text, including biomedical literature. The GAPscreener, a free SVM-based software tool, can be used to assist in screening PubMed abstracts for human genetic association studies. RESULTS: The data source for this research was the HuGE Navigator, formerly known as the HuGE Pub Lit database. Weighted SVM feature selection based on a keyword list obtained by the two-way z score method demonstrated the best screening performance, achieving 97.5% recall, 98.3% specificity and 31.9% precision in performance testing. Compared with the traditional screening process based on a complex PubMed query, the SVM tool reduced by about 90% the number of abstracts requiring individual review by the database curator. The tool also ascertained 47 articles that were missed by the traditional literature screening process during the 4-week test period. We examined the literature on genetic associations with preterm birth as an example. Compared with the traditional, manual process, the GAPscreener both reduced effort and improved accuracy. CONCLUSION: GAPscreener is the first free SVM-based application available for screening the human genetic association literature in PubMed with high recall and specificity. The user-friendly graphical user interface makes this a practical, stand-alone application. The software can be downloaded at no charge.

HuGE Watch: tracking trends and patterns of published studies of genetic association and human genome epidemiology in near-real time.

HuGE Watch is a web-based application for tracking the evolution of published studies on genetic association and human genome epidemiology in near-real time. The application allows users to display temporal trends and spatial distributions as line charts and google maps, providing a quick overview of progress in the field. http://www.hugenavigator.net/HuGENavigator/startPageWatch.do

Reporting of human genome epidemiology (HuGE) association studies: an empirical assessment.

BACKGROUND: Several thousand human genome epidemiology association studies are published every year investigating the relationship between common genetic variants and diverse phenotypes. Transparent reporting of study methods and results allows readers to better assess the validity of study findings. Here, we document reporting practices of human genome epidemiology studies. METHODS: Articles were randomly selected from a continuously updated database of human genome epidemiology association studies to be representative of genetic epidemiology literature. The main analysis evaluated 315 articles published in 2001-2003. For a comparative update, we evaluated 28 more recent articles published in 2006, focusing on issues that were poorly reported in 2001-2003. RESULTS: During both time periods, most studies comprised relatively small study populations and examined one or more genetic variants within a single gene. Articles were inconsistent in reporting the data needed to assess selection bias and the methods used to minimize misclassification (of the genotype, outcome, and environmental exposure) or to identify population stratification. Statistical power, the use of unrelated study participants, and the use of replicate samples were reported more often in articles published during 2006 when compared with the earlier sample. CONCLUSION: We conclude that many items needed to assess error and bias in human genome epidemiology association studies are not consistently reported. Although some improvements were seen over time, reporting guidelines and online supplemental material may help enhance the transparency of this literature.

An open source infrastructure for managing knowledge and finding potential collaborators in a domain-specific subset of PubMed, with an example from human genome epidemiology.

BACKGROUND: Identifying relevant research in an ever-growing body of published literature is becoming increasingly difficult. Establishing domain-specific knowledge bases may be a more effective and efficient way to manage and query information within specific biomedical fields. Adopting controlled vocabulary is a critical step toward data integration and interoperability in any information system. We present an open source infrastructure that provides a powerful capacity for managing and mining data within a domain-specific knowledge base. As a practical application of our infrastructure, we presented two applications - Literature Finder and Investigator Browser - as well as a tool set for automating the data curating process for the human genome published literature database. The design of this infrastructure makes the system potentially extensible to other data sources. RESULTS: Information retrieval and usability tests demonstrated that the system had high rates of recall and precision, 90% and 93% respectively. The system was easy to learn, easy to use, reasonably speedy and effective. CONCLUSION: The open source system infrastructure presented in this paper provides a novel approach to managing and querying information and knowledge from domain-specific PubMed data. Using the controlled vocabulary UMLS enhanced data integration and interoperability and the extensibility of the system. In addition, by using MVC-based design and Java as a platform-independent programming language, this system provides a potential infrastructure for any domain-specific knowledge base in the biomedical field.

An automatic method to generate domain-specific investigator networks using PubMed abstracts.

BACKGROUND: Collaboration among investigators has become critical to scientific research. This includes ad hoc collaboration established through personal contacts as well as formal consortia established by funding agencies. Continued growth in online resources for scientific research and communication has promoted the development of highly networked research communities. Extending these networks globally requires identifying additional investigators in a given domain, profiling their research interests, and collecting current contact information. We present a novel strategy for building investigator networks dynamically and producing detailed investigator profiles using data available in PubMed abstracts. RESULTS: We developed a novel strategy to obtain detailed investigator information by automatically parsing the affiliation string in PubMed records. We illustrated the results by using a published literature database in human genome epidemiology (HuGE Pub Lit) as a test case. Our parsing strategy extracted country information from 92.1% of the affiliation strings in a random sample of PubMed records and in 97.0% of HuGE records, with accuracies of 94.0% and 91.0%, respectively. Institution information was parsed from 91.3% of the general PubMed records (accuracy 86.8%) and from 94.2% of HuGE PubMed records (accuracy 87.0). We demonstrated the application of our approach to dynamic creation of investigator networks by creating a prototype information system containing a large database of PubMed abstracts relevant to human genome epidemiology (HuGE Pub Lit), indexed using PubMed medical subject headings converted to Unified Medical Language System concepts. Our method was able to identify 70-90% of the investigators/collaborators in three different human genetics fields; it also successfully identified 9 of 10 genetics investigators within the PREBIC network, an existing preterm birth research network. CONCLUSION: We successfully created a web-based prototype capable of creating domain-specific investigator networks based on an application that accurately generates detailed investigator profiles from PubMed abstracts combined with robust standard vocabularies. This approach could be used for other biomedical fields to efficiently establish domain-specific investigator networks.

Trends in laboratory test volumes for Medicare Part B reimbursements, 2000-2010.

CONTEXT: Changes in reimbursements for clinical laboratory testing may help us assess the effect of various variables, such as testing recommendations, market forces, changes in testing technology, and changes in clinical or laboratory practices, and provide information that can influence health care and public health policy decisions. To date, however, there has been no report, to our knowledge, of longitudinal trends in national laboratory test use. OBJECTIVE: To evaluate Medicare Part B-reimbursed volumes of selected laboratory tests per 10,000 enrollees from 2000 through 2010. DESIGN: Laboratory test reimbursement volumes per 10,000 enrollees in Medicare Part B were obtained from the Centers for Medicare & Medicaid Services (Baltimore, Maryland). The ratio of the most recent (2010) reimbursed test volume per 10,000 Medicare enrollees, divided by the oldest data (usually 2000) during this decade, called the volume ratio, was used to measure trends in test reimbursement. Laboratory tests with a reimbursement claim frequency of at least 10 per 10,000 Medicare enrollees in 2010 were selected, provided there was more than a 50% change in test reimbursement volume during the 2000-2010 decade. We combined the reimbursed test volumes for the few tests that were listed under more than one code in the Current Procedural Terminology (American Medical Association, Chicago, Illinois). A 2-sided Poisson regression, adjusted for potential overdispersion, was used to determine P values for the trend; trends were considered significant at P < .05. RESULTS: Tests with the greatest decrease in reimbursement volumes were electrolytes, digoxin, carbamazepine, phenytoin, and lithium, with volume ratios ranging from 0.27 to 0.64 (P < .001). Tests with the greatest increase in reimbursement volumes were meprobamate, opiates, methadone, phencyclidine, amphetamines, cocaine, and vitamin D, with volume ratios ranging from 83 to 1510 (P < .001). CONCLUSIONS: Although reimbursement volumes increased for most of the selected tests, other tests exhibited statistically significant downward trends in annual reimbursement volumes. The observed changes in reimbursement volumes may be explained by disease prevalence and severity, patterns of drug use, clinical or laboratory practices, and testing recommendations and guidelines, among others. These data may be useful to policy makers, health systems researchers, laboratory directors, and industry scientists to understand, address, and anticipate trends in laboratory testing in the Medicare population.

A systematic review of cancer GWAS and candidate gene meta-analyses reveals limited overlap but similar effect sizes.

Candidate gene and genome-wide association studies (GWAS) represent two complementary approaches to uncovering genetic contributions to common diseases. We systematically reviewed the contributions of these approaches to our knowledge of genetic associations with cancer risk by analyzing the data in the Cancer Genome-wide Association and Meta Analyses database (Cancer GAMAdb). The database catalogs studies published since January 1, 2000, by study and cancer type. In all, we found that meta-analyses and pooled analyses of candidate genes reported 349 statistically significant associations and GWAS reported 269, for a total of 577 unique associations. Only 41 (7.1%) associations were reported in both candidate gene meta-analyses and GWAS, usually with similar effect sizes. When considering only noteworthy associations (defined as those with false-positive report probabilities≤0.2) and accounting for indirect overlap, we found 202 associations, with 27 of those appearing in both meta-analyses and GWAS. Our findings suggest that meta-analyses of well-conducted candidate gene studies may continue to add to our understanding of the genetic associations in the post-GWAS era.

Association between alcohol and cardiovascular disease: Mendelian randomisation analysis based on individual participant data.

OBJECTIVE: To use the rs1229984 variant in the alcohol dehydrogenase 1B gene (ADH1B) as an instrument to investigate the causal role of alcohol in cardiovascular disease. DESIGN: Mendelian randomisation meta-analysis of 56 epidemiological studies. PARTICIPANTS: 261 991 individuals of European descent, including 20 259 coronary heart disease cases and 10 164 stroke events. Data were available on ADH1B rs1229984 variant, alcohol phenotypes, and cardiovascular biomarkers. MAIN OUTCOME MEASURES: Odds ratio for coronary heart disease and stroke associated with the ADH1B variant in all individuals and by categories of alcohol consumption. RESULTS: Carriers of the A-allele of ADH1B rs1229984 consumed 17.2% fewer units of alcohol per week (95% confidence interval 15.6% to 18.9%), had a lower prevalence of binge drinking (odds ratio 0.78 (95% CI 0.73 to 0.84)), and had higher abstention (odds ratio 1.27 (1.21 to 1.34)) than non-carriers. Rs1229984 A-allele carriers had lower systolic blood pressure (-0.88 (-1.19 to -0.56) mm Hg), interleukin-6 levels (-5.2% (-7.8 to -2.4%)), waist circumference (-0.3 (-0.6 to -0.1) cm), and body mass index (-0.17 (-0.24 to -0.10) kg/m(2)). Rs1229984 A-allele carriers had lower odds of coronary heart disease (odds ratio 0.90 (0.84 to 0.96)). The protective association of the ADH1B rs1229984 A-allele variant remained the same across all categories of alcohol consumption (P=0.83 for heterogeneity). Although no association of rs1229984 was identified with the combined subtypes of stroke, carriers of the A-allele had lower odds of ischaemic stroke (odds ratio 0.83 (0.72 to 0.95)). CONCLUSIONS: Individuals with a genetic variant associated with non-drinking and lower alcohol consumption had a more favourable cardiovascular profile and a reduced risk of coronary heart disease than those without the genetic variant. This suggests that reduction of alcohol consumption, even for light to moderate drinkers, is beneficial for cardiovascular health.