In genomic research phenotype transformations are commonly used as a straightforward way to reach normality of the model outcome. Many researchers still believe it to be necessary for proper ...inference. Using regression simulations, we show that phenotype transformations are typically not needed and, when used in phenotype with heteroscedasticity, result in inflated Type I error rates. We further explain that important is to address a combination of rare variant genotypes and heteroscedasticity. Incorrectly estimated parameter variability or incorrect choice of the distribution of the underlying test statistic provide spurious detection of associations. We conclude that it is a combination of heteroscedasticity, minor allele frequency, sample size, and to a much lesser extent the error distribution, that matter for proper statistical inference.
Using a phenome-wide association study (PheWAS) approach, we comprehensively tested genetic variants for association with phenotypes available for 70,061 study participants in the Population ...Architecture using Genomics and Epidemiology (PAGE) network. Our aim was to better characterize the genetic architecture of complex traits and identify novel pleiotropic relationships. This PheWAS drew on five population-based studies representing four major racial/ethnic groups (European Americans (EA), African Americans (AA), Hispanics/Mexican-Americans, and Asian/Pacific Islanders) in PAGE, each site with measurements for multiple traits, associated laboratory measures, and intermediate biomarkers. A total of 83 single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) were genotyped across two or more PAGE study sites. Comprehensive tests of association, stratified by race/ethnicity, were performed, encompassing 4,706 phenotypes mapped to 105 phenotype-classes, and association results were compared across study sites. A total of 111 PheWAS results had significant associations for two or more PAGE study sites with consistent direction of effect with a significance threshold of p<0.01 for the same racial/ethnic group, SNP, and phenotype-class. Among results identified for SNPs previously associated with phenotypes such as lipid traits, type 2 diabetes, and body mass index, 52 replicated previously published genotype-phenotype associations, 26 represented phenotypes closely related to previously known genotype-phenotype associations, and 33 represented potentially novel genotype-phenotype associations with pleiotropic effects. The majority of the potentially novel results were for single PheWAS phenotype-classes, for example, for CDKN2A/B rs1333049 (previously associated with type 2 diabetes in EA) a PheWAS association was identified for hemoglobin levels in AA. Of note, however, GALNT2 rs2144300 (previously associated with high-density lipoprotein cholesterol levels in EA) had multiple potentially novel PheWAS associations, with hypertension related phenotypes in AA and with serum calcium levels and coronary artery disease phenotypes in EA. PheWAS identifies associations for hypothesis generation and exploration of the genetic architecture of complex traits.
We hypothesized that the sleep complaints of insomnia predict incident hypertension, particularly in African Americans. The purpose of this study was to analyze insomnia complaints as predictors of ...incident hypertension in the Cardiovascular Health Study (CHS), stratifying by gender and allowing for race and sleep variable interaction.
This is a prospective cohort study over a 6-year period of follow-up.
This is a community-based study of participants in Forsyth County, North Carolina; Pittsburgh, Pennsylvania; Sacramento County, California; and Washington County, Maryland.
The study analyzed data from 1419 older individuals (baseline mean age 73.4 +/- 4.4 years) from the Cardiovascular Health Study who were not hypertensive at baseline.
none.
We constructed relative risks of incident hypertension over a 6-year period for insomnia complaints singly and in combination.
Difficulty falling asleep, singly or in combination with other sleep complaints, predicted a statistically significant reduction of risk for incident hypertension for non-African American men in 6 years of follow-up. Insomnia complaints did not predict incident hypertension in 6 years of follow-up in women or in African Americans, although there may not have been enough power to show a significant association for African Americans.
Insomnia did not predict hypertension in this older cohort which was free of hypertension at baseline. Difficulty falling asleep was associated with reduced risk of hypertension in non-African American men.
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.
Genome-wide association studies (GWASs) primarily performed in European-ancestry (EA) populations have identified numerous loci associated with body mass index (BMI). However, it is still unclear ...whether these GWAS loci can be generalized to other ethnic groups, such as African Americans (AAs). Furthermore, the putative functional variant or variants in these loci mostly remain under investigation. The overall lower linkage disequilibrium in AA compared to EA populations provides the opportunity to narrow in or fine-map these BMI-related loci. Therefore, we used the Metabochip to densely genotype and evaluate 21 BMI GWAS loci identified in EA studies in 29,151 AAs from the Population Architecture using Genomics and Epidemiology (PAGE) study. Eight of the 21 loci (SEC16B, TMEM18, ETV5, GNPDA2, TFAP2B, BDNF, FTO, and MC4R) were found to be associated with BMI in AAs at 5.8 × 10−5. Within seven out of these eight loci, we found that, on average, a substantially smaller number of variants was correlated (r2 > 0.5) with the most significant SNP in AA than in EA populations (16 versus 55). Conditional analyses revealed GNPDA2 harboring a potential additional independent signal. Moreover, Metabochip-wide discovery analyses revealed two BMI-related loci, BRE (rs116612809, p = 3.6 × 10−8) and DHX34 (rs4802349, p = 1.2 × 10−7), which were significant when adjustment was made for the total number of SNPs tested across the chip. These results demonstrate that fine mapping in AAs is a powerful approach for both narrowing in on the underlying causal variants in known loci and discovering BMI-related loci.
Abstract Purpose Uric acid inhibits vitamin D activation experimentally and higher serum urate levels are associated with higher parathyroid hormone levels in humans suggesting a link between uric ...acid and bone health. We hypothesized that hyperuricemia may increase the risk of fractures in older adults. Methods 1963 men and 2729 women ≥ 65 years of age who participated in the Cardiovascular Health Study and had baseline serum urate levels were included in the study. The primary outcome was incident hip fracture, assessed prospectively through June, 2008 by inpatient and outpatient records. The analysis was stratified by sex a priori. Results There was a U-shaped relationship between serum urate levels and hip fractures in men. Men in the lowest and the highest urate quartiles (< 4.88 and ≥ 6.88 mg/dL respectively) had a significantly higher rate of fractures in unadjusted analysis. However, upon multivariate adjustment, only the HR for hip fracture in highest quartile versus the reference remained significant (HR 1.9; 95% C.I. 1.1, 3.1; p value 0.02). High serum urate levels were not associated with hip fractures in women. Conclusion In this large prospective cohort of community-dwelling older adults, increased serum urate levels were associated with an increased risk of hip fractures in men. Further studies are needed to confirm these findings and to understand the mechanisms that underlie them.
In geriatric research of non-fatal events, participants often die during the study follow-up without having the non-fatal event of interest. Cause-specific (CS) hazard regression and Fine-Gray (FG) ...subdistribution hazard regression are the two most common estimation approaches addressing such competing risk. We explain how the conventional CS approach and the FG approach differ and why many FG estimates of associations are counter-intuitive. Additionally, we clarify the indirect link between models for hazard and models for cumulative incidence. The methodologies are contrasted on data from the Cardiovascular Health Study, a population-based study in adults aged 65 years and older.
Précis:
In a large, well-characterized study of adults aged 65 years and older, we showed that post-OGTT levels of GH/IGF axis components IGFBP-1 and ghrelin predict major age-related health events ...and mortality.
Abstract
Context:
Multiple diseases may explain the association of the growth hormone/insulinlike growth factor-I (GH/IGF-I) axis with longevity.
Objective:
To relate circulating GH/IGF-I system protein levels with major health events
Design and Setting:
This is a cohort study set in 4 US communities.
Participants:
Adults (N = 2268) 65 years and older free of diabetes and cardiovascular disease
Measurements:
We assessed insulinlike growth factor binding protein-1 (IGFBP-1) and ghrelin in fasting and 2-hour oral glucose tolerance test (OGTT) blood samples, as well as fasting IGF-I and IGFBP-3. Hazard ratios for mortality and a composite outcome for first incident myocardial infarction, stroke, heart failure, hip fracture, or death were adjusted for sociodemographic, behavioral, and physiological covariates.
Results:
During 13,930 person-years of follow-up, 48.1% of individuals sustained one or more components of the composite outcome and 31.8% died. Versus the lowest quartiles, the highest quartiles of fasting and 2-hour ghrelin were associated with 27% higher (95% confidence interval CI: 6%, 53%) and 39% higher (95% CI: 14%, 71%) risks of the composite outcome, respectively. The highest quartile of 2-hour IGFBP-1 was associated with 35% higher (95% CI: 1%, 52%) risk of the composite end point. Similarly, higher mortality was significantly associated with higher fasting and 2-hour ghrelin levels and with 2-hour IGFBP-1 level. When examined together, 2-hour post-OGTT levels of IGFBP-1 and ghrelin tended to predict outcomes better than fasting levels.
Conclusions:
Circulating IGFBP-1 and ghrelin measured during an OGTT predicted major health events and death in older adults, which may explain the influence of the GH/IGF-I axis on lifespan and health.
PDF
