Elad Ziv

Association of common genetic variation in the insulin/IGF1 signaling pathway with human longevity.

The insulin/IGF1 signaling pathways affect lifespan in several model organisms, including worms, flies and mice. To investigate whether common genetic variation in this pathway influences lifespan in humans, we genotyped 291 common variants in 30 genes encoding proteins in the insulin/IGF1 signaling pathway in a cohort of elderly Caucasian women selected from the Study of Osteoporotic Fractures (SOF). The cohort included 293 long‐lived cases (lifespan ≥ 92 years (y), mean ± standard deviation (SD) = 95.3 ± 2.2y) and 603 average‐lifespan controls (lifespan ≤ 79y, mean = 75.7 ± 2.6y). Variants were selected for genotyping using a haplotype‐tagging approach. We found a modest excess of variants nominally associated with longevity. Nominally significant variants were then replicated in two additional Caucasian cohorts including both males and females: the Cardiovascular Health Study and Ashkenazi Jewish Centenarians. An intronic single nucleotide polymorphism in AKT1, rs3803304, was significantly associated with lifespan in a meta‐analysis across the three cohorts (OR = 0.78 95%CI = 0.68–0.89, adjusted P = 0.043); two intronic single nucleotide polymorphisms in FOXO3A demonstrated a significant lifespan association among women only (rs1935949, OR = 1.35, 95%CI = 1.15–1.57, adjusted P = 0.0093). These results demonstrate that common variants in several genes in the insulin/IGF1 pathway are associated with human lifespan.

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.

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.

Prevention of Breast Cancer in Postmenopausal Women: Approaches to Estimating and Reducing Risk

BACKGROUND It is uncertain whether evidence supports routinely estimating a postmenopausal womans risk of breast cancer and intervening to reduce risk. METHODS We systematically reviewed prospective studies about models and sex hormone levels to assess breast cancer risk and used meta-analysis with random effects models to summarize the predictive accuracy of breast density. We also reviewed prospective studies of the effects of exercise, weight management, healthy diet, moderate alcohol consumption, and fruit and vegetable intake on breast cancer risk, and used random effects models for a meta-analyses of tamoxifen and raloxifene for primary prevention of breast cancer. All studies reviewed were published before June 2008, and all statistical tests were two-sided. RESULTS Risk models that are based on demographic characteristics and medical history had modest discriminatory accuracy for estimating breast cancer risk (c-statistics range = 0.58-0.63). Breast density was strongly associated with breast cancer (relative risk [RR] = 4.03, 95% confidence interval [CI] = 3.10 to 5.26, for Breast Imaging Reporting and Data System category IV vs category I; RR = 4.20, 95% CI = 3.61 to 4.89, for >75% vs <5% of dense area), and adding breast density to models improved discriminatory accuracy (c-statistics range = 0.63-0.66). Estradiol was also associated with breast cancer (RR range = 2.0-2.9, comparing the highest vs lowest quintile of estradiol, P < .01). Most studies found that exercise, weight reduction, low-fat diet, and reduced alcohol intake were associated with a decreased risk of breast cancer. Tamoxifen and raloxifene reduced the risk of estrogen receptor-positive invasive breast cancer and invasive breast cancer overall. CONCLUSIONS Evidence from this study supports screening for breast cancer risk in all postmenopausal women by use of risk factors and breast density and considering chemoprevention for those found to be at high risk. Several lifestyle changes with the potential to prevent breast cancer should be recommended regardless of risk.

Reduced Neutrophil Count in People of African Descent Is Due To a Regulatory Variant in the Duffy Antigen Receptor for Chemokines Gene

Persistently low white blood cell count (WBC) and neutrophil count is a well-described phenomenon in persons of African ancestry, whose etiology remains unknown. We recently used admixture mapping to identify an approximately 1-megabase region on chromosome 1, where ancestry status (African or European) almost entirely accounted for the difference in WBC between African Americans and European Americans. To identify the specific genetic change responsible for this association, we analyzed genotype and phenotype data from 6,005 African Americans from the Jackson Heart Study (JHS), the Health, Aging and Body Composition (Health ABC) Study, and the Atherosclerosis Risk in Communities (ARIC) Study. We demonstrate that the causal variant must be at least 91% different in frequency between West Africans and European Americans. An excellent candidate is the Duffy Null polymorphism (SNP rs2814778 at chromosome 1q23.2), which is the only polymorphism in the region known to be so differentiated in frequency and is already known to protect against Plasmodium vivax malaria. We confirm that rs2814778 is predictive of WBC and neutrophil count in African Americans above beyond the previously described admixture association (P = 3.8×10−5), establishing a novel phenotype for this genetic variant.

Mammographic Breast Density and the Gail Model for Breast Cancer Risk Prediction in a Screening Population

SummaryBackground. 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.

Genetic ancestry in lung-function predictions

BACKGROUND Self-identified race or ethnic group is used to determine normal reference standards in the prediction of pulmonary function. We conducted a study to determine whether the genetically determined percentage of African ancestry is associated with lung function and whether its use could improve predictions of lung function among persons who identified themselves as African American. METHODS We assessed the ancestry of 777 participants self-identified as African American in the Coronary Artery Risk Development in Young Adults (CARDIA) study and evaluated the relation between pulmonary function and ancestry by means of linear regression. We performed similar analyses of data for two independent cohorts of subjects identifying themselves as African American: 813 participants in the Health, Aging, and Body Composition (HABC) study and 579 participants in the Cardiovascular Health Study (CHS). We compared the fit of two types of models to lung-function measurements: models based on the covariates used in standard prediction equations and models incorporating ancestry. We also evaluated the effect of the ancestry-based models on the classification of disease severity in two asthma-study populations. RESULTS African ancestry was inversely related to forced expiratory volume in 1 second (FEV(1)) and forced vital capacity in the CARDIA cohort. These relations were also seen in the HABC and CHS cohorts. In predicting lung function, the ancestry-based model fit the data better than standard models. Ancestry-based models resulted in the reclassification of asthma severity (based on the percentage of the predicted FEV(1)) in 4 to 5% of participants. CONCLUSIONS Current predictive equations, which rely on self-identified race alone, may misestimate lung function among subjects who identify themselves as African American. Incorporating ancestry into normative equations may improve lung-function estimates and more accurately categorize disease severity. (Funded by the National Institutes of Health and others.)

Admixture mapping of an allele affecting interleukin 6 soluble receptor and interleukin 6 levels.

Circulating levels of inflammatory markers can predict cardiovascular disease risk. To identify genes influencing the levels of these markers, we genotyped 1,343 single-nucleotide polymorphisms (SNPs) in 1,184 African Americans from the Health, Aging and Body Composition (Health ABC) Study. Using admixture mapping, we found a significant association of interleukin 6 soluble receptor (IL-6 SR) with European ancestry on chromosome 1 (LOD 4.59), in a region that includes the gene for this receptor (IL-6R). Genotyping 19 SNPs showed that the effect is largely explained by an allele at 4% frequency in West Africans and at 35% frequency in European Americans, first described as associated with IL-6 SR in a Japanese cohort. We replicate this association (P<<1.0x10-12) and also demonstrate a new association with circulating levels of a different molecule, IL-6 (P<3.4x10-5). After replication in 1,674 European Americans from Health ABC, the combined result is even more significant: P<<1.0x10-12 for IL-6 SR, and P<2.0x10-9 for IL-6. These results also serve as an important proof of principle, showing that admixture mapping can not only coarsely localize but can also fine map a phenotypically important variant.

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.

Development of a panel of genome-wide ancestry informative markers to study admixture throughout the americas

Most individuals throughout the Americas are admixed descendants of Native American, European, and African ancestors. Complex historical factors have resulted in varying proportions of ancestral contributions between individuals within and among ethnic groups. We developed a panel of 446 ancestry informative markers (AIMs) optimized to estimate ancestral proportions in individuals and populations throughout Latin America. We used genome-wide data from 953 individuals from diverse African, European, and Native American populations to select AIMs optimized for each of the three main continental populations that form the basis of modern Latin American populations. We selected markers on the basis of locus-specific branch length to be informative, well distributed throughout the genome, capable of being genotyped on widely available commercial platforms, and applicable throughout the Americas by minimizing within-continent heterogeneity. We then validated the panel in samples from four admixed populations by comparing ancestry estimates based on the AIMs panel to estimates based on genome-wide association study (GWAS) data. The panel provided balanced discriminatory power among the three ancestral populations and accurate estimates of individual ancestry proportions (R2>0.9 for ancestral components with significant between-subject variance). Finally, we genotyped samples from 18 populations from Latin America using the AIMs panel and estimated variability in ancestry within and between these populations. This panel and its reference genotype information will be useful resources to explore population history of admixture in Latin America and to correct for the potential effects of population stratification in admixed samples in the region.