Cara L. Carty

Genetic risk factors for ischaemic stroke and its subtypes (the METASTROKE collaboration): a meta-analysis of genome-wide association studies.

Summary Background Various genome-wide association studies (GWAS) have been done in ischaemic stroke, identifying a few loci associated with the disease, but sample sizes have been 3500 cases or less. We established the METASTROKE collaboration with the aim of validating associations from previous GWAS and identifying novel genetic associations through meta-analysis of GWAS datasets for ischaemic stroke and its subtypes. Methods We meta-analysed data from 15 ischaemic stroke cohorts with a total of 12 389 individuals with ischaemic stroke and 62 004 controls, all of European ancestry. For the associations reaching genome-wide significance in METASTROKE, we did a further analysis, conditioning on the lead single nucleotide polymorphism in every associated region. Replication of novel suggestive signals was done in 13 347 cases and 29 083 controls. Findings We verified previous associations for cardioembolic stroke near PITX2 (p=2·8×10−16) and ZFHX3 (p=2·28×10−8), and for large-vessel stroke at a 9p21 locus (p=3·32×10−5) and HDAC9 (p=2·03×10−12). Additionally, we verified that all associations were subtype specific. Conditional analysis in the three regions for which the associations reached genome-wide significance (PITX2, ZFHX3, and HDAC9) indicated that all the signal in each region could be attributed to one risk haplotype. We also identified 12 potentially novel loci at p<5×10−6. However, we were unable to replicate any of these novel associations in the replication cohort. Interpretation Our results show that, although genetic variants can be detected in patients with ischaemic stroke when compared with controls, all associations we were able to confirm are specific to a stroke subtype. This finding has two implications. First, to maximise success of genetic studies in ischaemic stroke, detailed stroke subtyping is required. Second, different genetic pathophysiological mechanisms seem to be associated with different stroke subtypes. Funding Wellcome Trust, UK Medical Research Council (MRC), Australian National and Medical Health Research Council, National Institutes of Health (NIH) including National Heart, Lung and Blood Institute (NHLBI), the National Institute on Aging (NIA), the National Human Genome Research Institute (NHGRI), and the National Institute of Neurological Disorders and Stroke (NINDS).

DNA methylation-based measures of biological age: meta-analysis predicting time to death.

Estimates of biological age based on DNA methylation patterns, often referred to as “epigenetic age”, “DNAm age”, have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p≤8.2×10−9), independent of chronological age, even after adjusting for additional risk factors (p<5.4×10−4), and within the racial/ethnic groups that we examined (non-Hispanic whites, Hispanics, African Americans). Epigenetic age estimates that incorporated information on blood cell composition led to the smallest p-values for time to death (p=7.5×10−43). Overall, this study a) strengthens the evidence that epigenetic age predicts all-cause mortality above and beyond chronological age and traditional risk factors, and b) demonstrates that epigenetic age estimates that incorporate information on blood cell counts lead to highly significant associations with all-cause mortality.

Genetic Determinants of Lipid Traits in Diverse Populations from the Population Architecture using Genomics and Epidemiology (PAGE) Study

For the past five years, genome-wide association studies (GWAS) have identified hundreds of common variants associated with human diseases and traits, including high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels. Approximately 95 loci associated with lipid levels have been identified primarily among populations of European ancestry. The Population Architecture using Genomics and Epidemiology (PAGE) study was established in 2008 to characterize GWAS–identified variants in diverse population-based studies. We genotyped 49 GWAS–identified SNPs associated with one or more lipid traits in at least two PAGE studies and across six racial/ethnic groups. We performed a meta-analysis testing for SNP associations with fasting HDL-C, LDL-C, and ln(TG) levels in self-identified European American (∼20,000), African American (∼9,000), American Indian (∼6,000), Mexican American/Hispanic (∼2,500), Japanese/East Asian (∼690), and Pacific Islander/Native Hawaiian (∼175) adults, regardless of lipid-lowering medication use. We replicated 55 of 60 (92%) SNP associations tested in European Americans at p<0.05. Despite sufficient power, we were unable to replicate ABCA1 rs4149268 and rs1883025, CETP rs1864163, and TTC39B rs471364 previously associated with HDL-C and MAFB rs6102059 previously associated with LDL-C. Based on significance (p<0.05) and consistent direction of effect, a majority of replicated genotype-phentoype associations for HDL-C, LDL-C, and ln(TG) in European Americans generalized to African Americans (48%, 61%, and 57%), American Indians (45%, 64%, and 77%), and Mexican Americans/Hispanics (57%, 56%, and 86%). Overall, 16 associations generalized across all three populations. For the associations that did not generalize, differences in effect sizes, allele frequencies, and linkage disequilibrium offer clues to the next generation of association studies for these traits.

Overweight, Obesity, and Postmenopausal Invasive Breast Cancer Risk: A Secondary Analysis of the Women’s Health Initiative Randomized Clinical Trials

IMPORTANCE More than two-thirds of US women are overweight or obese, placing them at increased risk for postmenopausal breast cancer. OBJECTIVE To investigate in this secondary analysis the associations of overweight and obesity with risk of postmenopausal invasive breast cancer after extended follow-up in the Womens Health Initiative (WHI) clinical trials. DESIGN, SETTING, AND PARTICIPANTS The WHI clinical trial protocol incorporated measured height and weight, baseline and annual or biennial mammography, and adjudicated breast cancer end points in 67 142 postmenopausal women ages 50 to 79 years at 40 US clinical centers. The women were enrolled from 1993 to 1998 with a median of 13 years of follow-up through 2010; 3388 invasive breast cancers were observed. MAIN OUTCOMES AND MEASURES Height and weight were measured at baseline, and weight was measured annually thereafter. Data were collected on demographic characteristics, personal and family medical history, and personal habits (smoking, physical activity). Women underwent annual or biennial mammograms. Breast cancers were verified by medical records reviewed by physician adjudicators. RESULTS Women who were overweight and obese had an increased invasive breast cancer risk vs women of normal weight. Risk was greatest for obesity grade 2 plus 3 (body mass index [BMI], calculated as weight in kilograms divided by height in meters squared, >35.0) (hazard ratio [HR] for invasive breast cancer, 1.58; 95% CI, 1.40-1.79). A BMI of 35.0 or higher was strongly associated with risk for estrogen receptor-positive and progesterone receptor-positive breast cancers (HR, 1.86; 95% CI, 1.60-2.17) but was not associated with estrogen receptor-negative cancers. Obesity grade 2 plus 3 was also associated with advanced disease, including larger tumor size (HR, 2.12; 95% CI, 1.67-2.69; P = .02), positive lymph nodes (HR, 1.89; 95% CI, 1.46-2.45; P = .06), regional and/or distant stage (HR, 1.94; 95% CI, 1.52-2.47; P = .05), and deaths after breast cancer (HR, 2.11; 95% CI, 1.57-2.84; P < .001). Women with a baseline BMI of less than 25.0 who gained more than 5% of body weight over the follow-up period had an increased breast cancer risk (HR, 1.36; 95% CI, 1.1-1.65), but among women already overweight or obese we found no association of weight change (gain or loss) with breast cancer during follow-up. There was no effect modification of the BMI-breast cancer relationship by postmenopausal hormone therapy, and the direction of association across BMI categories was similar for never, past, and current hormone therapy use. CONCLUSIONS AND RELEVANCE Obesity is associated with increased invasive breast cancer risk in postmenopausal women. These clinically meaningful findings should motivate programs for obesity prevention. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00000611.

Generalization and dilution of association results from European GWAS in populations of non-European ancestry: the PAGE study.

A multi-ethnic study demonstrates that the extrapolation of genetic disease risk models from European populations to other ethnicities is compromised more strongly by genetic structure than by environmental or global genetic background in differential genetic risk associations across ethnicities.

Trans-ethnic fine-mapping of lipid loci identifies population-specific signals and allelic heterogeneity that increases the trait variance explained.

Genome-wide association studies (GWAS) have identified ∼100 loci associated with blood lipid levels, but much of the trait heritability remains unexplained, and at most loci the identities of the trait-influencing variants remain unknown. We conducted a trans-ethnic fine-mapping study at 18, 22, and 18 GWAS loci on the Metabochip for their association with triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), respectively, in individuals of African American (n = 6,832), East Asian (n = 9,449), and European (n = 10,829) ancestry. We aimed to identify the variants with strongest association at each locus, identify additional and population-specific signals, refine association signals, and assess the relative significance of previously described functional variants. Among the 58 loci, 33 exhibited evidence of association at P<1×10−4 in at least one ancestry group. Sequential conditional analyses revealed that ten, nine, and four loci in African Americans, Europeans, and East Asians, respectively, exhibited two or more signals. At these loci, accounting for all signals led to a 1.3- to 1.8-fold increase in the explained phenotypic variance compared to the strongest signals. Distinct signals across ancestry groups were identified at PCSK9 and APOA5. Trans-ethnic analyses narrowed the signals to smaller sets of variants at GCKR, PPP1R3B, ABO, LCAT, and ABCA1. Of 27 variants reported previously to have functional effects, 74% exhibited the strongest association at the respective signal. In conclusion, trans-ethnic high-density genotyping and analysis confirm the presence of allelic heterogeneity, allow the identification of population-specific variants, and limit the number of candidate SNPs for functional studies.

Seasonal variability of endotoxin in ambient fine particulate matter

Endotoxin is a toxic, pro-inflammatory compound that has been detected in indoor air and dust in homes and occupational settings, and also in outdoor air. Data on the outdoor sampling of endotoxin are limited. Currently, little is known about the seasonal variation and influence of temperature on outdoor endotoxin levels. In the present study, we report endotoxin levels in fine fraction particulate matter with a 50% aerodynamic cutoff diameter of 2.5 microm (PM2.5) and describe the seasonal variation of endotoxin in Munich, Germany. In 1999-2000, PM2.5 was collected at forty outdoor monitoring sites across Munich. Approximately four samples were collected at each site for a total of 158 samples. Endotoxin concentrations in the PM2.5 samples were determined using the kinetic chromogenic Limulus Amebocyte Lysate (LAL) assay. The geometric mean endotoxin concentration was 1.07 EU mg PM2.5(-1) (95% C.I.: 0.915-1.251) or 0.015 EU m(-3) of sampled air (95% C.I.: 0.013-0.018). Munich endotoxin levels were significantly related to ambient temperature (p < 0.0001) and percent relative humidity (p < 0.0001). Sampling periods with higher average temperatures yielded higher levels of endotoxin in PM2.5 (r = 0.641), whereas decreases in percent relative humidity were associated with increased endotoxin levels in PM2.5 (r = -0.388). Endotoxin levels were significantly higher during the warmer seasons of spring [means ratio (MR): 2.5-2.7] and summer (MR: 2.1-3.0) than during winter. Although temperature and relative humidity do not explain all of the variability in endotoxin levels, their effects were significant in our data set. Temperature effects and seasonal variation of endotoxin should be considered in future studies of outdoor endotoxin.

Polymorphisms of the IL1-Receptor Antagonist Gene (IL1RN) Are Associated With Multiple Markers of Systemic Inflammation

Background—Circulating levels of acute phase reactant proteins such as plasma C-reactive protein (CRP) are likely influenced by multiple genes regulating the innate immune response. Methods and Results—We screened a set of 16 inflammation-related genes for association with CRP in a large population-based study of healthy young adults (n=1627). Results were validated in 2 independent studies (n=1208 and n=4310), including a pooled analysis of all 3 studies. In the pooled analysis, the minor allele of IL1RN 1018 (rs4251961) within the gene encoding interleukin (IL)-1 receptor antagonist (IL-1RA) was significantly associated with higher mean plasma log(CRP) level (P<1×10−4). The same IL1RN 1018 allele was associated with higher mean plasma log(IL-6) levels (P=0.004). In the pooled analysis, the minor allele of IL1RN 13888 (rs2232354) was associated with higher fibrinogen, (P=0.001). The IL1RN 1018 and 13888 variant alleles tag a clade of IL1RN haplotypes linked to allele 1 of an 86-bp VNTR polymorphism. We confirmed that the IL1RN 1018 variant (rs4251961) was associated with decreased cellular IL-1RA production ex vivo. Conclusions—Common functional polymorphisms of the IL1RN gene are associated with several markers of systemic inflammation.

Evaluation of the Metabochip Genotyping Array in African Americans and Implications for Fine Mapping of GWAS-Identified Loci: The PAGE Study

The Metabochip is a custom genotyping array designed for replication and fine mapping of metabolic, cardiovascular, and anthropometric trait loci and includes low frequency variation content identified from the 1000 Genomes Project. It has 196,725 SNPs concentrated in 257 genomic regions. We evaluated the Metabochip in 5,863 African Americans; 89% of all SNPs passed rigorous quality control with a call rate of 99.9%. Two examples illustrate the value of fine mapping with the Metabochip in African-ancestry populations. At CELSR2/PSRC1/SORT1, we found the strongest associated SNP for LDL-C to be rs12740374 (p = 3.5×10−11), a SNP indistinguishable from multiple SNPs in European ancestry samples due to high correlation. Its distinct signal supports functional studies elsewhere suggesting a causal role in LDL-C. At CETP we found rs17231520, with risk allele frequency 0.07 in African Americans, to be associated with HDL-C (p = 7.2×10−36). This variant is very rare in Europeans and not tagged in common GWAS arrays, but was identified as associated with HDL-C in African Americans in a single-gene study. Our results, one narrowing the risk interval and the other revealing an associated variant not found in Europeans, demonstrate the advantages of high-density genotyping of common and rare variation for fine mapping of trait loci in African American samples.

Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms

Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP–CAD associations (P < 5 × 10−8, in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms.