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Biomedical subjects

Elad Ziv

Publications and source records attributed to Elad Ziv.

At least 19 recordsLinked to original sources

Evaluation of Multiple Breast Cancer Polygenic Risk Score Panels in Women of Latin American Heritage.

BACKGROUND: A substantial portion of the genetic predisposition for breast cancer is explained by multiple common genetic variants of relatively small effect. A subset of these variants, which have been identified mostly in individuals of European (EUR) and Asian ancestries, have been combined to construct a polygenic risk score (PRS) to predict breast cancer risk, but the prediction accuracy of existing PRSs in Hispanic/Latinx individuals (H/L) remain relatively low. We assessed the performance of several existing PRS panels with and without addition of H/L-specific variants among self-reported H/L women. METHODS: PRS performance was evaluated using multivariable logistic regression and the area under the ROC curve. RESULTS: Both EUR and Asian PRSs performed worse in H/L samples compared with original reports. The best EUR PRS performed better than the best Asian PRS in pooled H/L samples. EUR PRSs had decreased performance with increasing Indigenous American (IA) ancestry, while Asian PRSs had increased performance with increasing IA ancestry. The addition of two H/L SNPs increased performance for all PRSs, most notably in the samples with high IA ancestry, and did not impact the performance of PRSs in individuals with lower IA ancestry. CONCLUSIONS: A single PRS that incorporates risk variants relevant to the multiple ancestral components of individuals from Latin America, instead of a set of ancestry-specific panels, could be used in clinical practice. IMPACT: The results highlight the importance of population-specific discovery and suggest a straightforward approach to integrate ancestry-specific variants into PRSs for clinical application.

Adult↗

African ancestry, socioeconomic status, and kidney function in elderly African Americans: a genetic admixture analysis.

Kidney disease is a major public health problem in the United States that affects African Americans disproportionately. The relative contribution of environmental and genetic factors to the increased burden of kidney disease among African Americans is unknown. The associations of genetic African ancestry and socioeconomic status with kidney function were studied cross-sectionally and longitudinally among 736 community-dwelling African Americans who were aged >65 yr and participating in the Cardiovascular Health Study. Genetic African ancestry was determined by genotyping 24 biallelic ancestry-informative markers and combining this information statistically to generate an estimate of ancestry for each individual. Kidney function was evaluated by cystatin C and estimated GFR (eGFR) using the Modification of Diet in Renal Disease equation. Longitudinal changes in serum creatinine and eGFR were estimated using baseline and follow-up values. In cross-sectional analyses, there was no association between genetic African ancestry and either measure of kidney function (P = 0.36 for cystatin C and 0.68 for eGFR). African ancestry was not associated with change in serum creatinine > or =0.05 mg/dl per yr (odds ratio [OR] 0.94; 95% confidence interval [CI] 0.83 to 1.06) or with change in eGFR > or =3 ml/min per 1.73 m(2) per yr (OR 1.02; 95% CI 0.92 to 1.13). In contrast, self reported African-American race was strongly associated with increased risk for kidney disease progression compared with white individuals for change in creatinine (OR 1.77; 95% CI 1.33 to 2.36) and for change in eGFR (OR 3.21; 95% CI 2.54 to 4.06). Among self-identified African Americans, low income (< US dollars 8000/yr) was strongly associated with prevalent kidney dysfunction by cystatin C >1.29 g/dl (adjusted OR 2.7; 95% CI 1.0 to 7.5) or by eGFR <60 ml/min per 1.73 m(2) (adjusted OR 3.2; 95% CI 1.1 to 9.4) compared with those with incomes >US dollars 35,000/yr. Alleles that are known to be present more frequently in the African ancestral group were not associated with kidney dysfunction or kidney disease progression. Rather, kidney dysfunction in elderly African Americans seems more attributable to differences in environmental and social factors.

Black or African American↗

Ancestry-environment interactions and asthma risk among Puerto Ricans.

BACKGROUND: Puerto Ricans, an admixed population of African, European, and Native American ancestries, have the highest asthma prevalence, morbidity, and mortality rates of any United States' population. Although socioeconomic status (SES) is negatively correlated with asthma incidence in most populations, no such relationship has been identified among Puerto Ricans. We hypothesized that, in this admixed population, the association between SES and asthma may interact with genetic ancestry. METHODS: We analyzed 135 Puerto Rican subjects with asthma and 156 control subjects recruited from six different recruitment centers in Puerto Rico. Individual ancestry for each subject was estimated using 44 ancestry informative markers. SES was assigned using the census tracts' median family income. Analyses of SES were based on the SES of the clinic site from which the subjects were recruited and on a subset of individuals on whom home address-based SES was available. RESULTS: In the two (independent) analyses, we found a significant interaction between SES, ancestry, and asthma disease status. At lower SES, European ancestry was associated with increased risk of asthma, whereas African ancestry was associated with decreased risk. The opposite was true for their higher SES counterparts. CONCLUSIONS: The observed interaction may help to explain the unique pattern of risk for asthma in Puerto Ricans and the lack of association with SES observed in previous studies when not accounting for varying proportions of ancestry.

Adolescent↗

Genetic ancestry and risk factors for breast cancer among Latinas in the San Francisco Bay Area.

BACKGROUND: Genetic association studies using case-control designs are susceptible to false-positive and false-negative results if there are differences in genetic ancestry between cases and controls. We measured genetic ancestry among Latinas in a population-based case-control study of breast cancer and tested the association between ancestry and known breast cancer risk factors. We reasoned that if genetic ancestry is associated with known breast cancer risk factors, then the results of genetic association studies would be confounded. METHODS: We used 44 ancestry informative markers to estimate individuals' genetic ancestry in 563 Latina participants. To test whether ancestry is a predictor of hormone therapy use, parity, and body mass index (BMI), we used multivariate logistic regression models to estimate odds ratios (OR) and 95% confidence intervals (95% CI) associated with a 25% increase in Indigenous American ancestry, adjusting for age, education, and the participant's and grandparents' place of birth. RESULTS: Hormone therapy use was significantly less common among women with higher Indigenous American ancestry (OR, 0.78; 95% CI, 0.63-0.96). Higher Indigenous American ancestry was also significantly associated with overweight (BMI, 25-29.9 versus <25) and obesity (BMI, > or =30 versus <25), but only among foreign-born Latina women (OR, 3.44; 95% CI, 1.97-5.99 and OR, 1.95; 95% CI, 1.24-3.06, respectively). CONCLUSION: Some breast cancer risk factors are associated with genetic ancestry among Latinas in the San Francisco Bay Area. Therefore, case-control genetic association studies for breast cancer should directly measure genetic ancestry to avoid potential confounding.

Adult↗

Population stratification confounds genetic association studies among Latinos.

In the United States, asthma prevalence and mortality are the highest among Puerto Ricans and the lowest among Mexicans. Case-control association studies are a powerful strategy for identifying genes of modest effect in complex diseases. However, studies of complex disorders in admixed populations such as Latinos may be confounded by population stratification. We used ancestry informative markers (AIMs) to identify and correct for population stratification among Mexican and Puerto Rican subjects participating in case-control studies of asthma. Three hundred and sixty-two subjects with asthma (Mexican: 181, Puerto Rican: 181) and 359 ethnically matched controls (Mexican: 181, Puerto Rican: 178) were genotyped for 44 AIMs. We observed a greater than expected degree of association between pairs of AIMs on different chromosomes in Mexicans (P < 0.00001) and Puerto Ricans (P < 0.00002) providing evidence for population substructure and/or recent admixture. To assess the effect of population stratification on association studies of asthma, we measured differences in genetic background of cases and controls by comparing allele frequencies of the 44 AIMs. Among Puerto Ricans but not in Mexicans, we observed a significant overall difference in allele frequencies between cases and controls (P = 0.0002); of 44 AIMs tested, 8 (18%) were significantly associated with asthma. However, after adjustment for individual ancestry, only two of these markers remained significantly associated with the disease. Our findings suggest that empirical assessment of the effects of stratification is critical to appropriately interpret the results of case-control studies in admixed populations.

Alleles↗

Admixture-matched case-control study: a practical approach for genetic association studies in admixed populations.

Case-control genetic association studies in admixed populations are known to be susceptible to genetic confounding due to population stratification. The transmission/disequilibrium test (TDT) approach can avoid this problem. However, the TDT is expensive and impractical for late-onset diseases. Case-control study designs, in which, cases and controls are matched by admixture, can be an appealing and a suitable alternative for genetic association studies in admixed populations. In this study, we applied this matching strategy when recruiting our African American participants in the Study of African American, Asthma, Genes and Environments. Group admixture in this cohort consists of 83% African ancestry and 17% European ancestry, which was consistent with reports from other studies. By carrying out several complementary analyses, our results show that there is a substructure in the cohort, but that the admixture distributions are almost identical in cases and controls, and also in cases only. We performed association tests for asthma-related traits with ancestry, and only found that FEV(1), a measure for baseline pulmonary function, was associated with ancestry after adjusting for socio-economic and environmental risk factors (P=0.01). We did not observe an excess of type I error rate in our association tests for ancestry informative markers and asthma-related phenotypes when ancestry was not adjusted in the analyses. Furthermore, using the association tests between genetic variants in a known asthma candidate gene, beta(2) adrenergic receptor (beta(2)AR) and DeltaFEF(25-75), an asthma-related phenotype, as an example, we demonstrated population stratification was not a confounder in our genetic association. Our present work demonstrates that admixture-matched case-control strategies can efficiently control population stratification confounding in admixed populations.

Adolescent↗

Latino populations: a unique opportunity for the study of race, genetics, and social environment in epidemiological research.

Latinos are the largest minority population in the United States. Although usually classified as a single ethnic group by researchers, Latinos are heterogeneous from cultural, socioeconomic, and genetic perspectives. From a cultural and social perspective, Latinos represent a wide variety of national origins and ethnic and cultural groups, with a full spectrum of social class. From a genetic perspective, Latinos are descended from indigenous American, European, and African populations. We review the historical events that led to the formation of contemporary Latino populations and use results from recent genetic and clinical studies to illustrate the unique opportunity Latino groups offer for studying the interaction between racial, genetic, and environmental contributions to disease occurrence and drug response.

Asthma↗

Association of estrogen receptor alpha polymorphisms with breast cancer risk in older Caucasian women.

Estrogens exert their effect on the breast through the estrogen receptor. We prospectively investigated breast cancer risk associated with 2 polymorphic sites in the estrogen receptor alpha gene (ESR1). A total of 4,248 Caucasian women from the Study of Osteoporotic Fractures were genotyped for the -401 T/C and -354 A/G polymorphisms in ESR1. Cox proportional hazards models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for the associations between genotypes and breast cancer. During a mean follow-up of 12.4 years, 252 (5.9%) women developed breast cancer. The HR (95% CI) for breast cancer were 0.928 (0.708, 1.22) and 0.834 (0.538, 1.29) for the -354 A/G and A/A genotypes, respectively. Interactions with -354 variant were observed for smoking (HR = 1.52 and 1.56 for A/G and A/A smokers, respectively; HR = 0.74 and 0.60 for A/G and A/A non-smokers, respectively; interaction p = 0.03) and walking (HR = 0.75 and 1.15 for A/G and A/A walkers, respectively; HR = 0.18 and 0.49 for A/G and A/A non-walkers, respectively; interaction p = 0.01). There were no differences in the HR for the -401 T/C genotypes. An interaction between parity and carriage of the T allele was found (HR = 0.60 vs. 1.12 for nulliparous vs. parous women; interaction p = 0.03). ESR1 polymorphisms in combination with lifestyle factors may be associated with breast cancer risk in older Caucasian women.

Aged↗

Comparison of three methods to estimate genetic ancestry and control for stratification in genetic association studies among admixed populations.

Population stratification may confound the results of genetic association studies among unrelated individuals from admixed populations. Several methods have been proposed to estimate the ancestral information in admixed populations and used to adjust the population stratification in genetic association tests. We evaluate the performances of three different methods: maximum likelihood estimation, ADMIXMAP and Structure through various simulated data sets and real data from Latino subjects participating in a genetic study of asthma. All three methods provide similar information on the accuracy of ancestral estimates and control type I error rate at an approximately similar rate. The most important factor in determining accuracy of the ancestry estimate and in minimizing type I error rate is the number of markers used to estimate ancestry. We demonstrate that approximately 100 ancestry informative markers (AIMs) are required to obtain estimates of ancestry that correlate with correlation coefficients more than 0.9 with the true individual ancestral proportions. In addition, after accounting for the ancestry information in association tests, the excess of type I error rate is controlled at the 5% level when 100 markers are used to estimate ancestry. However, since the effect of admixture on the type I error rate worsens with sample size, the accuracy of ancestry estimates also needs to increase to make the appropriate correction. Using data from the Latino subjects, we also apply these methods to an association study between body mass index and 44 AIMs. These simulations are meant to provide some practical guidelines for investigators conducting association studies in admixed populations.

Asthma↗

CD14 tobacco gene-environment interaction modifies asthma severity and immunoglobulin E levels in Latinos with asthma.

BACKGROUND: A recent family-based genomewide screen revealed linkage between the 5q31 region and the diagnosis of asthma, but only in those exposed to environmental tobacco smoke (ETS). Among the candidate genes in this region is CD14. METHODS: To determine whether polymorphisms in the CD14 gene are related to this gene-by-environment interaction in Latinos, we used both family-based and cross-sectional cohort analysis to test for interactions between CD14 genotypes/haplotypes, exposure to ETS, and asthma-related phenotypes in 659 Mexican and Puerto Rican families. RESULTS: We identified 21 single nucleotide polymorphisms (SNPs) in the CD14 gene by sequencing 72 Puerto Ricans, Mexicans, and African Americans with asthma. Three SNPs, -810, -159, and +1437, were further genotyped in families with asthma. Among all subjects with asthma exposed to ETS, without regard to ethnicity, CD14 +1437 genotypes were associated with asthma severity. SNP +1437 GG or GC genotypes were significantly associated with lower baseline FEV1 using both family-based (p = 0.0009) and cross-sectional cohort (p = 0.03) analyses. Subjects with asthma with the GG or GC genotypes who were exposed to ETS had mean baseline FEV1 (% predicted) values 8.6% lower than subjects not exposed to ETS (p = 0.03). As previously observed in whites, we found an interaction between plasma IgE levels, SNP -159 genotypes, and ETS exposure (p = 0.0002). The lowest IgE levels were in those subjects with the TT genotype and who were exposed to ETS regardless of ethnicity. CONCLUSIONS: Our data suggest a gene-by-environment interaction between CD14 genotypes and ETS, which affects pulmonary function and IgE levels among Latinos with asthma.

Adolescent↗

Are breast density and bone mineral density independent risk factors for breast cancer?

BACKGROUND: Mammographic breast density and bone mineral density (BMD) are markers of cumulative exposure to estrogen. Previous studies have suggested that women with high mammographic breast density or high BMD are at increased risk of breast cancer. We determined whether mammographic breast density and BMD of the hip and spine are correlated and independently associated with breast cancer risk. METHODS: We conducted a cross-sectional study (N = 15,254) and a nested case-control study (of 208 women with breast cancer and 436 control subjects) among women aged 28 years or older who had a screening mammography examination and hip BMD measurement within 2 years. Breast density for 3105 of the women was classified using the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) categories, and percentage mammographic breast density among the case patients and control subjects was quantified with a computer-based threshold method. Spearman rank partial correlation coefficient and Pearson's correlation coefficient were used to examine correlations between BI-RADS breast density and BMD and between percentage mammographic breast density and BMD, respectively, in women without breast cancer. Logistic regression was used to examine the association of breast cancer with percentage mammographic breast density and BMD. All statistical tests were two-sided. RESULTS: Neither BI-RADS breast density nor percentage breast density was correlated with hip or spine BMD (correlation coefficient = -.02 and -.01 for BI-RADS, respectively, and -.06 and .01 for percentage breast density, respectively). Neither hip BMD nor spine BMD had a statistically significant relationship with breast cancer risk. Women with breast density in the highest sextile had an approximately threefold increased risk of breast cancer compared with women in the lowest sextile (odds ratio = 2.7, 95% confidence interval = 1.4 to 5.4); adjusting for hip or spine BMD did not change the association between breast density and breast cancer risk. CONCLUSION: Breast density is strongly associated with increased risk of breast cancer, even after taking into account reproductive and hormonal risk factors, whereas BMD, although a possible marker of lifetime exposure to estrogen, is not. Thus, a component of breast density that is independent of estrogen-mediated effects may contribute to breast cancer risk.

Adult↗

Population structure, admixture, and aging-related phenotypes in African American adults: the Cardiovascular Health Study.

U.S. populations are genetically admixed, but surprisingly little empirical data exists documenting the impact of such heterogeneity on type I and type II error in genetic-association studies of unrelated individuals. By applying several complementary analytical techniques, we characterize genetic background heterogeneity among 810 self-identified African American subjects sampled as part of a multisite cohort study of cardiovascular disease in older adults. On the basis of the typing of 24 ancestry-informative biallelic single-nucleotide-polymorphism markers, there was evidence of substantial population substructure and admixture. We used an allele-sharing-based clustering algorithm to infer evidence for four genetically distinct subpopulations. Using multivariable regression models, we demonstrate the complex interplay of genetic and socioeconomic factors on quantitative phenotypes related to cardiovascular disease and aging. Blood glucose level correlated with individual African ancestry, whereas body mass index was associated more strongly with genetic similarity. Blood pressure, HDL cholesterol level, C-reactive protein level, and carotid wall thickness were not associated with genetic background. Blood pressure and HDL cholesterol level varied by geographic site, whereas C-reactive protein level differed by occupation. Both ancestry and genetic similarity predicted the number and quality of years lived during follow-up, but socioeconomic factors largely accounted for these associations. When the 24 genetic markers were tested individually, there were an excess number of marker-trait associations, most of which were attenuated by adjustment for genetic ancestry. We conclude that the genetic demography underlying older individuals who self identify as African American is complex, and that controlling for both genetic admixture and socioeconomic characteristics will be required in assessing genetic associations with chronic-disease-related traits in African Americans. Complementary methods that identify discrete subgroups on the basis of genetic similarity may help to further characterize the complex biodemographic structure of human populations.

Black or African American↗

Genetic admixture and asthma-related phenotypes in Mexican American and Puerto Rican asthmatics.

Genetic association studies in admixed populations may be biased if individual ancestry varies within the population and the phenotype of interest is associated with ancestry. However, recently admixed populations also offer potential benefits in association studies since markers informative for ancestry may be in linkage disequilibrium across large distances. In particular, the enhanced LD in admixed populations may be used to identify alleles that underlie a genetically determined difference in a phenotype between two ancestral populations. Asthma is known to have different prevalence and severity among ancestrally distinct populations. We investigated several asthma-related phenotypes in two ancestrally admixed populations: Mexican Americans and Puerto Ricans. We used ancestry informative markers to estimate the individual ancestry of 181 Mexican American asthmatics and 181 Puerto Rican asthmatics and tested whether individual ancestry is associated with any of these phenotypes independently of known environmental factors. We found an association between higher European ancestry and more severe asthma as measured by both forced expiratory volume at 1 second (r=-0.21, p=0.005) and by a clinical assessment of severity among Mexican Americans (OR: 1.55; 95% CI 1.25 to 1.93). We found no significant associations between ancestry and severity or drug responsiveness among Puerto Ricans. These results suggest that asthma severity may be influenced by genetic factors differentiating Europeans and Native Americans in Mexican Americans, although differing results for Puerto Ricans require further investigation.

Adolescent↗

Mammographic breast density and the Gail model for breast cancer risk prediction in a screening population.

BACKGROUND: Estimating an individual woman's absolute risk for breast cancer is essential for decision making about screening and preventive recommendations. Although the current standard, the Gail model, is well calibrated in populations, it performs poorly for individuals. Mammographic breast density (BD) may improve the predictive accuracy of the Gail model. METHODS: Prospective observational cohort of 81,777 women in the San Francisco Mammography Registry presenting for mammography during 1993 through 2002 who had no prior diagnosis of breast cancer. Breast density was rated by clinical radiologists using the Breast Imaging Reporting and Data System classification (almost entirely fat; scattered fibroglandular densities; heterogeneously dense; extremely dense). Breast cancer cases were identified through linkage to Northern California Surveillance Epidemiology End Results (SEER) program. We compared the predictive accuracy of models with Gail risk, breast density, and the combination. All models were adjusted for age and ethnicity. RESULTS: During 5.1 years of follow-up, 955 women were diagnosed with invasive breast cancer. The Gail model had modest predictive accuracy (concordance index (c-index) 0.67; 95% CI 0.65-0.68). Adding breast density to the model increased the predictive accuracy to 0.68 (95% CI .66-.70, p < 0.01 compared with the Gail model alone). The model containing only breast density adjusted for age and ethnicity had predictive accuracy equivalent to the Gail model (c-index 0.67, 95% CI 0.65-0.68). CONCLUSION: The addition of breast density measured by BI-RADS categories minimally improved the predictive accuracy of the Gail model. A model based on breast density alone adjusted for age and ethnicity was as accurate as the Gail model.

Adult↗

Estrogen metabolizing polymorphisms and breast cancer risk among older white women.

OBJECTIVE: To investigate breast cancer risk according to metabolizing genes polymorphisms in older women. METHODS: A subset (43.8%) of 4248 older, white women from the Study of Osteoporotic Fractures (SOF) were genotyped for the catechol-O-methyltransferase (COMT) Val108Met polymorphism and the CYP1A1*2C locus. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations between genotypes and breast cancer while controlling for potential confounders. RESULTS: During a mean follow up of 12.4 years, 252 women (5.9%) developed breast cancer. The HR (95% CI) for breast cancer was 1.24 (0.87-1.75) for COMT(Val/Met) and 1.35 (0.93-1.97) for COMT(Met/Met). No interactions with lifestyle and reproductive factors were found. The HR associated with the CYP1A1*2C Val allele was 0.80 (0.46, 1.39) with little evidence for interactions with lifestyle or reproductive factors. CONCLUSIONS: Among older white women, neither the COMT Val108/158Met polymorphism nor the CYP1A*2C Val allele plays a major role in breast cancer risk either alone or in combination with lifestyle and reproductive factors.

Aged↗

The genetics of human longevity.

Many of the genes that affect aging and longevity in model organisms, such as mice, fruit flies, and worms, have human homologs. This article reviews several genetic pathways that may extend lifespan through effects on aging, rather than through effects on diseases such as atherosclerosis or cancer. These include some of the genes involved in the regulation of DNA repair and nuclear structure, which cause the progeroid syndromes when mutated, as well as those that may affect telomere length, since shorter telomeres have been associated with shorter survival. Other potential longevity genes, such as sirtuins, are involved in regulating the response to cellular stress, including caloric restriction. The best-studied pathway involves insulin and insulin-like growth factor 1 signaling; mutations in homologs of these genes have extended lifespan up to sixfold in model organisms. Other potential candidates include mitochondrial DNA and the genes that regulate the inflammatory response. Despite the challenges in study design and analysis that face investigators in this area, the identification of genetic pathways that regulate longevity may suggest potential targets for therapy.

Aging↗

Pharmacogenetic differences in response to albuterol between Puerto Ricans and Mexicans with asthma.

BACKGROUND: In the United States, Puerto Ricans and Mexicans have the highest and lowest asthma prevalence, morbidity, and mortality, respectively. Ethnic-specific differences in the response to drug treatment may contribute to differences in disease outcomes. Genetic variants at the beta(2)-adrenergic receptor (beta(2)AR) may modify asthma severity and albuterol responsiveness. We tested the association of beta(2)AR genotypes with asthma severity and bronchodilator response to albuterol in Puerto Ricans and Mexicans with asthma. METHODS: We used both family-based and cross-sectional tests of association with 8 beta(2)AR single nucleotide polymorphisms in 684 Puerto Rican and Mexican families. Regression analyses were used to determine the interaction between genotype, asthma severity, and bronchodilator drug responsiveness. RESULTS: Among Puerto Ricans with asthma, the arginine (Arg) 16 allele was associated with greater bronchodilator response using both family-based and cross-sectional tests (p = 0.00001-0.01). We found a strong interaction of baseline FEV(1) with the Arg16Glycine (Gly) polymorphism in predicting bronchodilator response. Among Puerto Ricans with asthma with baseline FEV(1) < 80% of predicted, but not in those with FEV(1) > 80%, there was a very strong association between the Arg16 genotype and greater bronchodilator responsiveness. No association was observed between Arg16Gly genotypes and drug responsiveness among Mexicans with asthma. CONCLUSIONS: Ethnic-specific pharmacogenetic differences exist between Arg16Gly genotypes, asthma severity, and bronchodilator response in Puerto Ricans and Mexicans with asthma. These findings underscore the need for additional research on racial/ethnic differences in asthma morbidity and drug responsiveness.

Adolescent↗

Potential public health impact of new tuberculosis vaccines.

Developing effective tuberculosis (TB) vaccines is a high priority. We use mathematical models to predict the potential public health impact of new TB vaccines in high-incidence countries. We show that preexposure vaccines would be almost twice as effective as postexposure vaccines in reducing the number of new infections. Postexposure vaccines would initially have a substantially greater impact, compared to preexposure vaccines, on reducing the number of new cases of disease. However, the effectiveness of postexposure vaccines would diminish over time, whereas the effectiveness of preexposure vaccines would increase. Thus, after 20 to 30 years, post- or preexposure vaccination campaigns would be almost equally effective in terms of cumulative TB cases prevented. Even widely deployed and highly effective (50%-90% efficacy) pre- or postexposure vaccines would only be able to reduce the number of TB cases by one third. We discuss the health policy implications of our analyses.

Disease Outbreaks↗