Genome-wide association studies (GWAS) have identified ∼30 single-nucleotide polymorphisms (SNPs) consistently associated with prostate cancer (PCa) risk. To test the hypothesis that other sequence variants in the genome may interact with those 32 known PCa risk-associated SNPs identified from GWAS to affect PCa risk, we performed a systematic evaluation among three existing PCa GWAS populations: CAncer of the Prostate in Sweden population, a Johns Hopkins Hospital population, and the Cancer Genetic Markers of Susceptibility population, with a total sample size of 4723 PCa cases and 4792 control subjects. Meta-analysis of the interaction term between each of those 32 SNPs and SNPs in the genome was performed in three PCa GWAS populations. The most significant interaction detected was between rs12418451 in MYEOV and rs784411 in CEP152, with a Pinteraction of 1.15 × 10−7 in the meta-analysis. In addition, we emphasized two pairs of interactions with potential biological implication, including an interaction between rs7127900 near insulin-like growth factor-2 (IGF2)/IGF2AS and rs12628051 in TNRC6B, with a Pinteraction of 3.39 × 10−6 and an interaction between rs7679763 near TET2 and rs290258 in SYK, with a Pinteraction of 1.49 × 10−6. Those results show statistical evidence for novel loci interacting with known risk-associated SNPs to modify PCa risk. The interacting loci identified provide hints on the underlying molecular mechanism of the associations with PCa risk for the known risk-associated SNPs. Additional studies are warranted to further confirm the interaction effects detected in this study.

Background

Reduced gait speed is associated with falls, late-life disability, hospitalization/institutionalization and cardiovascular morbidity and mortality. Aging is also accompanied by a widening of pulse pressure (PP) that contributes to ventricular-vascular uncoupling. The purpose of this study was to test the hypothesis that PP is associated with long-distance gait speed in community-dwelling older adults in the Lifestyle Interventions and Independence for Elders Pilot (LIFE-P) study.

Methods

Brachial blood pressure and 400-meter gait speed (average speed maintained over a 400-meter walk at “usual” pace) were assessed in 424 older adults between the ages of 70–89 yrs at risk for mobility disability (mean age = 77 yrs; 31% male). PP was calculated as systolic blood pressure (BP) – diastolic BP.

Results

Patients with a history of heart failure and stroke (n = 42) were excluded leaving 382 participants for final analysis. When categorized into tertiles of PP, participants within the highest PP tertile had significantly slower gait speed than those within the lowest PP tertile (p<0.05). Following stepwise multiple regression, PP was significantly and inversely associated with 400-meter gait speed (p<0.05). Other significant predictors of gait speed included: handgrip strength, body weight, age and history of diabetes mellitus (p<0.05). Mean arterial pressure, systolic BP and diastolic BP were not predictors of gait speed.

Conclusions

Pulse pressure is associated long-distance gait speed in community-dwelling older adults. Vascular senescence and altered ventricular-vascular coupling may be associated with the deterioration of mobility and physical function in older adults.

Background

Machine learning neuroimaging researchers have often relied on regularization techniques when classifying MRI images. Although these were originally introduced to deal with “ill-posed” problems it is rare to find studies that evaluate the ill-posedness of MRI image classification problems. In addition, to avoid the effects of the “curse of dimensionality” very often dimension reduction is applied to the data.

Methodology

Baseline structural MRI data from cognitively normal and Alzheimer's disease (AD) patients from the AD Neuroimaging Initiative database were used in this study. We evaluated here the ill-posedness of this classification problem across different dimensions and sample sizes and its relationship to the performance of regularized logistic regression (RLR), linear support vector machine (SVM) and linear regression classifier (LRC). In addition, these methods were compared with their principal components space counterparts.

Principal Findings

In voxel space the prediction performance of all methods increased as sample sizes increased. They were not only relatively robust to the increase of dimension, but they often showed improvements in accuracy. We linked this behavior to improvements in conditioning of the linear kernels matrices. In general the RLR and SVM performed similarly. Surprisingly, the LRC was often very competitive when the linear kernel matrices were best conditioned. Finally, when comparing these methods in voxel and principal component spaces, we did not find large differences in prediction performance.

Conclusions and Significance

We analyzed the problem of classifying AD MRI images from the perspective of linear ill-posed problems. We demonstrate empirically the impact of the linear kernel matrix conditioning on different classifiers' performance. This dependence is characterized across sample sizes and dimensions. In this context we also show that increased dimensionality does not necessarily degrade performance of machine learning methods. In general, this depends on the nature of the problem and the type of machine learning method.

BACKGROUND

Prostate specific antigen (PSA) is widely used for prostate cancer screening but its levels are influenced by many non cancer-related factors. The goal of the study is to estimate the effect of genetic variants on PSA levels.

METHODS

We evaluated the association of SNPs that were reported to be associated with prostate cancer risk in recent genome-wide association studies with plasma PSA levels in a Swedish study population, including 1,722 control subjects without a diagnosis of prostate cancer.

RESULTS

Of the 16 SNPs analyzed in control subjects, significant associations with PSA levels (P≤0.05) were found for six SNPs. These six SNPs had a cumulative effect on PSA levels; the mean PSA levels in men were almost twofold increased across increasing quintile of number of PSA associated alleles, P-trend=3.4×10−14. In this Swedish study population risk allele frequencies were similar among T1c case patients (cancer detected by elevated PSA levels alone) as compared to T2 and above prostate cancer case patients.

CONCLUSIONS

Results from this study may have two important clinical implications. The cumulative effect of six SNPs on PSA levels suggests genetic-specific PSA cutoff values may be used to improve the discriminatory performance of this test for prostate cancer; and the dual associations of these SNPs with PSA levels and prostate cancer risk raise a concern that some of reported prostate cancer risk-associated SNPs may be confounded by the prevalent use of PSA screening.

Background and Aims

Arterial stiffness is a prominent feature of vascular aging and a risk factor for cardiovascular disease (CVD). Fat around the heart and blood vessels (i.e. pericardial fat, Pfat) may contribute to arterial stiffness via a local paracrine effect of adipose tissue on the surrounding vasculature. Thus, we determined the association between Pfat and carotid stiffness in 5,770 participants (mean age 62 yrs, 53% female, 25% African American, 24% Hispanic, and 13% Chinese) from the Multi-Ethnic Study of Atherosclerosis.

Methods and Results

Pfat was measured by computed tomography, and ultrasonography of the common carotid artery was used to calculate the distensibility coefficient (DC) and young’s modulus (YM). Lower DC and higher YM values indicate stiffer arteries. Pfat quartile was highly associated with demographic, behavioral, anthropometric, hemodynamic, metabolic, and disease variables in both men and women. After adjusting for height, clinical site, CVD risk factors, and medications, a 1-standard deviation (41.91 cm3) increment in Pfat was associated with a 0.00007±0.00002 1/mmHg lower DC (p=0.0002) in men and a 48.1±15.1 mmHg/mm higher YM in women (p=0.002). Additional adjustment for C-reactive protein, coronary artery calcification, and carotid intima-media thickness had only modest effects. More importantly, adjusting for body mass index and waist circumference did not significantly change the overall results.

Conclusion

Higher Pfat is associated with higher carotid stiffness, independent of traditional CVD risk factors and obesity.

OBJECTIVES

To determine whether the presence of high depressive symptoms diminished physical performance benefits after a comprehensive physical activity intervention in older adults.

STUDY DESIGN

A post-hoc analysis of data from the Lifestyle Interventions and Independence for Elders Pilot (LIFE-P) study which was a single blind randomized controlled trial comparing a moderate intensity physical activity intervention (PA) with a successful aging control (SA).

SETTING

Multi-center U.S. sites participating in the LIFE-P trial.

PARTICIPANTS

LIFE-P trial participants included 424 sedentary, non-institutionalized adults (70–89 years).

MEASUREMENTS

Depressive symptoms were assessed by the Centers for Epidemiological Studies Depression Scale (CES-D). Physical performance tests included the Short Physical Performance Battery (SPPB) and 400 meter walk time (400 mw) at baseline, 6 and 12 months.

RESULTS

Of the participants, 15.8% had high depressive symptom scores (CES-D ≥ 14). For participants with low depressive symptoms, SPPB scores improved in the PA versus the SA group over 12 months (adjusted score difference: +0.70; p = <0.001 at 6 months and +0.58; p=0.004 at 12 months) while the 400 mw times improved in the PA group at 6 months (adjusted score difference −0.41 min.; p=0.021). For those with high depressive symptoms, a trend toward statistical improvement in the SPPB was observed in the PA versus SA group (adjusted score difference +0.76 (p=0.176) at 6 months and +0.94 (p=0.116) at 12 months).

CONCLUSION

The presence of high depressive symptoms did not substantially diminish physical performance benefits realized after a PA intervention in sedentary older adults.

BACKGROUND

Prostate cancer (PCa) risk-associated single nucleotide polymorphisms (SNPs) are continuously being discovered. Their ability to identify men at high risk and the impact of increasing numbers of SNPs on predictive performance are not well understood.

METHODS

Absolute risk for PCa was estimated in a population-based case-control study in Sweden (2,899 cases and 1,722 controls) using family history and three sets of sequentially discovered PCa risk-associated SNPs. Their performance in predicting PCa was assessed by positive predictive values (PPV) and sensitivity.

RESULTS

SNPs and family history were able to differentiate individual risk for PCa and identify men at higher risk; ~18% and ~8% of men in the study had 20-year (55–74 years) absolute risks that were two-fold (0.24) or three-fold (0.36) greater than the population median risk (0.12), respectively. When predictive performances were compared at absolute risk cutoffs of 0.12, 0.24 or 0.36, PPV increased considerably (~20%, ~30% and ~37%, respectively) while sensitivity decreased considerably (~55%, ~20% and ~10%, respectively). In contrast, when increasing numbers of SNPs (5, 11 and 28 SNPs) were used in risk prediction, PPV approached a constant value while sensitivity increased steadily.

CONCLUSIONS

SNPs discovered to date are suitable for risk prediction while additional SNPs discovered in the future may identify more subjects at higher risk. Men identified as high-risk by SNP-based testing may be targeted for PCa screening or chemoprevention. The clinical impact on improving the effectiveness of these interventions can be and should be assessed.

Background

Excessive non-subcutaneous fat deposition may impair the functions of surrounding tissues and organs through the release of inflammatory cytokines and free fatty acids.

Objective

We examined the cross-sectional association between non-subcutaneous adiposity and calcified coronary plaque, a non-invasive measure of coronary artery disease burden.

Design

Participants in the Multi-Ethnic Study of Atherosclerosis underwent CT assessment of calcified coronary plaque. We measured multiple fat depots in 398 white and black participants (47% men and 43% black), ages 47–86 years, from Forsyth County, NC during 2002–2005, using cardiac and abdominal CT scans. In addition to examining each depot separately, we also created a non-subcutaneous fat index using the standard scores of non-subcutaneous fat depots.

Results

A total of 219 participants (55%) were found to have calcified coronary plaque. After adjusting for demographics, lifestyle factors and height, calcified coronary plaque was associated with a one standard deviation increment in the non-subcutaneous fat index (OR = 1.41; 95% CI: 1.08, 1.84), pericardial fat (OR = 1.38; 95% CI: 1.04, 1.84), abdominal visceral fat (OR = 1.35; 95% CI: 1.03, 1.76), but not with fat content in the liver, intermuscular fat, or abdominal subcutaneous fat. The relation between non-subcutaneous fat index and calcified coronary plaque remained after further adjustment for abdominal subcutaneous fat (OR = 1.40; 95% CI: 1.00, 1.94). The relation did not differ by gender and ethnicity.

Conclusions

The overall burden of non-subcutaneous fat deposition, but not abdominal subcutaneous fat, may be a correlate of coronary atherosclerosis.

Purpose

To determine the effects of a 12-month physical activity intervention on inflammatory biomarkers in elderly men and women.

Methods

424 elderly (aged 70–89 years), nondisabled, community-dwelling men and women at risk for physical disability were enrolled in a multicenter, single-blind, randomized controlled-trial. Participants were randomized to participate in either a 12-month moderate-intensity physical activity (PA) intervention or a successful aging (SA) health education intervention. Biomarkers of inflammation (IL-6sR, IL-1sRII, sTNFRI, sTNFRII, IL-8, IL-15, adiponectin, IL-1ra, IL-2sRα, and TNF-α) were measured at baseline, 6 and 12 months.

Results

A baseline blood sample was successfully collected from 368 participants. After adjustment for gender, clinic site, diabetes status, and baseline outcome measure, IL-8 was the only inflammatory biomarker affected by the PA intervention (p=0.03). The adjusted mean IL-8 at month 12 was 9.9% (0.87 pg/mL) lower in the PA compared to the SA group. Secondary interaction analyses between baseline biomarker status and treatment showed one significant interaction (p=0.02) such that the PA intervention reduced IL-15 concentrations in participants with a baseline IL-15 above the median value of 1.67 pg/mL. However, these associations were no longer significant after consideration for multiple comparisons.

Conclusions

Overall, this study does not provide definitive evidence for an effect of regular exercise for altering systemic concentrations of the measured inflammatory biomarkers in older adults.

BACKGROUND

Genome-wide association studies (GWAS) have led to the discovery of multiple SNPs that are associated with prostate cancer (PCa) risk. These SNPs may potentially be used for risk prediction. To date, there is not a stable estimate of their effect on PCa risk and their contribution to the genetic variation both of which are important for future risk prediction.

METHODS

A literature review was conducted to identify SNPs associated with PCa risk with the following criteria: (1) GWAS in the Caucasian population; (2) SNPs with p-value < 1.0×10−6; and (3) one SNP from each independent LD block. A meta-analysis was performed to estimate combined odds ratio (OR) and its 95% confidence interval (CI) for the identified SNPs. The proportion of total genetic variance that is attributable by each of these SNPs was also estimated.

RESULTS

Thirty PCa risk-associated SNPs were identified. These SNPs had OR estimates between 1.12 – 1.47 except for marker rs16901979 (OR = 1.80). Significant heterogeneity in OR estimates was found among different studies for 13 SNPs. The proportion of total genetic variance attributed by each SNP ranged between 0.2% – 0.9%. These 30 SNPs explained ~13 .5% of the total genetic variance of PCa risk in the Caucasian population.

CONCLUSION

This study provides more stable OR estimates for PCa risk-associated SNPs, which is an important baseline for the effect of these SNPs in risk prediction. These SNPs explain a considerable proportion of genetic variance, however, the majority of genetic variance has yet to be explained.

A fine mapping study in the HNF1B gene at 17q12 among two study populations revealed a second prostate cancer locus, ~26 kb centromeric to the first known locus (rs4430796); these are separated by a recombination hotspot. A SNP in the second locus (rs11649743) was confirmed in five additional populations, and P=1.7×10−9 for an allelic test in the seven combined studies. The association at each SNP remains significant after adjusting for the other SNP.

Purpose

While PSA is the best biomarker for predicting prostate cancer, its predictive performance needs to be improved. Results from the Prostate Cancer Prevention Trial (PCPT) revealed the overall performance measured by the areas under curve (AUC) of the receiver operating characteristic (ROC) at 0.68. The goal of the present study is to assess the ability of genetic variants as a PSA independent method to predict prostate cancer risk.

Experimental Design

We systematically evaluated all prostate cancer risk variants that were identified from genome-wide association studies during the past year in a large population-based prostate cancer case-control study population in Sweden, including 2,893 prostate cancer patients and 1,781 men without prostate cancer.

Results

Twelve SNPs were independently associated with prostate cancer risk in this Swedish study population. Using a cutoff of any 11 risk alleles or family history, the sensitivity and specificity for predicting prostate cancer were 0.25 and 0.86, respectively. The overall predictive performance of prostate cancer using genetic variants, family history, and age, measured by AUC was 0.65 (95% CI: 0.63–0.66), significantly improved over that of family history and age (0.61%, 95% CI: 0.59–0.62), P = 2.3 × 10−10.

Conclusion

The predictive performance for prostate cancer using genetic variants and family history is similar to that of PSA. The utility of genetic testing, alone and in combination with PSA levels, should be evaluated in large studies such as the European Randomized Study for Prostate Cancer trial and PCPT.

Multiple SNPs at 17q12 and 17q24.3 were recently identified to be associated with prostate cancer risk using a genome-wide association study. Although these associations reached genome-wide significance level in a combined analysis of several study populations of European descent in the original report, confirmation in independent populations, including African Americans (AA), is critical to increase confidence that they represent true disease associations and whether the results can be generalized. Therefore, we evaluated these 7 SNPs in two populations recruited from Johns Hopkins Hospital, including European Americans (EA) (1,563 cases and 576 controls) and AA (364 cases and 353 controls). Each of the previously reported risk alleles of these 7 SNPs were more common in cases than in controls among EA and AA. The differences were highly significant in EA (P = 10−4) and marginally significant in AA (P = 0.04) for 17q12SNPs. In contrast, the differences were not statistically significant in EA or AA for SNPs at 17q24.3, but were marginally significant for two SNPs (P = 0.04 - 0.06) when subjects from EA and AA were combined. Similar results were obtained for genotype and haplotype frequencies. These risk variants were not associated with aggressiveness of prostate cancer or other clinical variables such as TNM stage, pre-operative PSA, or age at diagnosis. Our results provide the first confirmation of these novel prostate loci and the first demonstration that these two loci may also play roles in prostate cancer risk among AA.

Background.

As the number of older adults in the United States rises, maintaining functional independence among older Americans has emerged as a major clinical and public health priority. Older people who lose mobility are less likely to remain in the community; demonstrate higher rates of morbidity, mortality, and hospitalizations; and experience a poorer quality of life. Several studies have shown that regular physical activity improves functional limitations and intermediate functional outcomes, but definitive evidence showing that major mobility disability can be prevented is lacking. A Phase 3 randomized controlled trial is needed to fill this evidence gap.

Methods.

The Lifestyle Interventions and Independence for Elders (LIFE) Study is a Phase 3 multicenter randomized controlled trial designed to compare a supervised moderate-intensity physical activity program with a successful aging health education program in 1,600 sedentary older persons followed for an average of 2.7 years.

Results.

LIFE's primary outcome is major mobility disability, defined as the inability to walk 400 m. Secondary outcomes include cognitive function, serious fall injuries, persistent mobility disability, the combined outcome of major mobility disability or death, disability in activities of daily living, and cost-effectiveness.

Conclusions.

Results of this study are expected to have important public health implications for the large and growing population of older sedentary men and women.

Disease risk-associated single nucleotide polymorphisms (SNPs) identified from genome-wide association studies have the potential to be used for disease risk prediction. An important feature of these risk-associated SNPs is their weak individual effect but stronger cumulative effect on disease risk. Several approaches are commonly used to model the combined effect in risk prediction but their performance is unclear. We compared two methods to model the combined effect of 14 prostate cancer (PCa) risk-associated SNPs and family history for the estimation of absolute risk for PCa in a population-based case-control study in Sweden (2,899 cases and 1,722 controls). Method 1 weighs each risk allele equally using a simple method of counting the number of risk alleles while Method 2 weighs each risk SNP differently based on their respective Odds Ratios. We found considerable differences between the two methods. Absolute risk estimates from Method 1 were generally higher than that of Method 2, especially among men at higher risk. The difference in the overall discriminative performance, measured by area under the curve (AUC) of the receiver operating characteristic was small between Method 1 (0.614) and Method 2 (0.618), P = 0.20. However, the performance of these two methods in identifying high-risk individuals (two-fold or three-fold higher than average risk), measured by positive predictive values (PPV), was higher for Method 2 than Method 1. In conclusion, these results suggest that Method 2 is superior to Method 1 in estimating absolute risk if the purpose of risk prediction is to identify high-risk individuals.

Introduction

Carotid intima-media thickness (IMT) is a sub-clinical marker of atherosclerosis and a strong predictor of stroke. Pericardial fat (PF), the fat depot around the heart, has been associated with several atherosclerosis risk factors. We sought to examine the association between carotid IMT and PF, and to examine whether such an association is independent from common atherosclerosis risk factors including measures of overall adiposity.

Methods

Unadjusted and multivariable adjusted linear regression analysis was used to examine associations between common (CCA-IMT) and internal (ICA-IMT) carotid IMT with PF in a random sample of 996 participants from the Multi-Ethnic Study of Atherosclerosis (MESA) who underwent carotid ultrasound and chest CT at baseline examination.

Results

A significant positive correlation was observed between PF and CCA-IMT (r =0.27, P<0.0001) and ICA-IMT (r =0.17, P<0.0001). In an unadjusted sex-specific linear regression analysis, there was a significant association between PF (1-SD difference) and CCA-IMT (mm) in both women (β coefficient (95% CI): 0.06 (0.04, 0.08), P<0.0001) and men (0.03 (0.01, 0.05), P<0.0002), an association that persisted after further adjusting for age and ethnicity (0.02 (+0.00, 0.04), P=0.0120 for women, and 0.02 (+0.00, 0.03), P=0.0208 for men). However, after additional adjustment for atherosclerosis risk factors and either BMI or waist circumference, these relations were no longer significant in either sex. In similar analyses, PF was significantly associated with ICA-IMT in both men (0.11 (0.06, 0.15), P<0.0001) and women (0.08 (0.02, 0.13), P=041). These relations were no longer significant in women in multivariable adjusted models, but persisted in men in all models except after adjusting for age, ethnicity and waist circumference.

Conclusions

In the general population PF is associated with carotid IMT, an association that possibly not independent from markers of overall adiposity or common atherosclerosis risk factors.

Purpose

Whole-brain irradiation (WBI) leads to cognitive impairment months to years after radiation. Numerous studies suggest that decreased hippocampal neurogenesis and microglial activation are involved in the pathogenesis of WBI-induced brain injury. The goal of this study was to investigate whether administration of the peroxisomal proliferator-activated receptor (PPAR)α agonist, fenofibrate, would prevent the detrimental effect of WBI on hippocampal neurogenesis.

Methods and Materials

129S1/SvImJ wild-type (WT) and PPARα knock-out (KO) mice that were fed either regular or 0.2% w/w fenofibrate-containing chow received either sham irradiation or WBI (10 Gy single dose of 137Cs γ rays). Mice were injected i.p. with bromodeoxyuridine (BrdU) to label the surviving cells at 1 month post-WBI and the newborn neurons were counted at 2 months post-WBI using BrdU/NeuN double-immunofluorescence. Proliferation in the sub-granular zone (SGZ) and microglial activation were measured at 1 week and 2 months post-WBI using Ki-67 and CD68 immunohistochemistry, respectively.

Results

WBI led to a significant decrease in the number of newborn hippocampal neurons 2 months post-WBI. Fenofibrate prevented this decrease by promoting the survival of newborn cells in the dentate gyrus (DG). In addition, fenofibrate treatment was associated with decreased microglial activation in the DG following WBI. The neuroprotective effects of fenofibrate were abolished in the KO mice, indicating a PPARα-dependent mechanism(s).

Conclusion

These data highlight a novel role for PPARα ligands in improving neurogenesis following WBI, and offer the promise of improving the quality of life for brain cancer patients receiving radiotherapy.

Background

The late life disability instrument (LLDI) was developed to assess limitations in instrumental and management roles using a small and restricted sample. In this paper we examine the measurement properties of the LLDI using data from the Lifestyle Interventions and Independence for Elders Pilot (LIFE-P) study.

Methods

LIFE-P participants, aged 70-89 years, were at elevated risk of disability. The 424 participants were enrolled at the Cooper Institute, Stanford University, University of Pittsburgh, and Wake Forest University. Physical activity and successful aging health education interventions were compared after 12-months of follow-up. Using factor analysis, we determined whether the LLDI's factor structure was comparable with that reported previously. We further examined how each item related to measured disability using item response theory (IRT).

Results

The factor structure for the limitation domain within the LLDI in the LIFE-P study did not corroborate previous findings. However, the factor structure using the abbreviated version was supported. Social and personal role factors were identified. IRT analysis revealed that each item in the social role factor provided a similar level of information, whereas the items in the personal role factor tended to provide different levels of information.

Conclusions

Within the context of community-based clinical intervention research in aged populations, an abbreviated version of the LLDI performed better than the full 16-item version. In addition, the personal subscale would benefit from additional research using IRT.

Trial registration

The protocol of LIFE-P is consistent with the principles of the Declaration of Helsinki and is registered at http://www.ClinicalTrials.gov (registration # NCT00116194).

Background

Multiple DNA sequence variants in the form of single nucleotide polymorphisms (SNPs) have been found to be reproducibly associated with prostate cancer (PCa) risk.

Methods

Absolute risk for PCa among men with various numbers of inherited risk alleles and family history of PCa was estimated in a population-based case-control study in Sweden (2,893 cases and 1,781 controls), and a nested case-control study from the Prostate, Lung, Colon and Ovarian (PLCO) Cancer Screening Trial in the U.S (1,172 cases and 1,157 controls).

Results

Increased number of risk alleles and positive family history were independently associated with PCa risk. Considering men with 11 risk alleles (mode) and negative family history as having baseline risk, men who had ≥ 14 risk alleles and positive family history had an Odds Ratio (OR) of 4.92 [95% confidence interval (CI): 3.64-6.64] in the Swedish study. These associations were confirmed in the U.S. population. Once a man's SNP genotypes and family history are known, his absolute risk for PCa can be readily calculated and easily interpreted. For example, 55 year old men with a family history and ≥ 14 risk alleles have a 52% and 41% risk of being diagnosed with PCa in the next 20 years in the Swedish and U.S. populations, respectively. In comparison, without knowledge of genotype and family history, these men had an average population absolute risk of 13%.

Conclusion

This risk prediction model may be used to identify men at considerably elevated PCa risk who may be selected for chemoprevention.

Background

Organophosphate pesticides act as cholinesterase inhibitors. For those with agricultural exposure to these chemicals, risk of potential exposure-related health effects may be modified by genetic variability in cholinesterase metabolism. Cholinesterase activity is a useful, indirect measurement of pesticide exposure, especially in high-risk individuals such as farmworkers. To understand fully the links between pesticide exposure and potential human disease, analyses must be able to consider genetic variability in pesticide metabolism.

Objectives

We studied participants in the Community Participatory Approach to Measuring Farmworker Pesticide Exposure (PACE3) study to determine whether cholinesterase levels are associated with single-nucleotide polymorphisms (SNPs) involved in pesticide metabolism.

Methods

Cholinesterase levels were measured from blood samples taken from 287 PACE3 participants at up to four time points during the 2007 growing season. We performed association tests of cholinesterase levels and 256 SNPs in 30 candidate genes potentially involved in pesticide metabolism. A false discovery rate (FDR) p-value was used to account for multiple testing.

Results

Thirty-five SNPs were associated (unadjusted p < 0.05) based on at least one of the genetic models tested (general, additive, dominant, and recessive). The strongest evidence of association with cholinesterase levels was observed with two SNPs, rs2668207 and rs2048493, in the butyrylcholinesterase (BCHE) gene (FDR adjusted p = 0.15 for both; unadjusted p = 0.00098 and 0.00068, respectively). In participants with at least one minor allele, cholinesterase levels were lower by 4.3–9.5% at all time points, consistent with an effect that is independent of pesticide exposure.

Conclusions

Common genetic variation in the BCHE gene may contribute to subtle changes in cholinesterase levels.

Although it is well known that multiple genes may influence prostate cancer risk, most current efforts at identifying prostate cancer risk variants rely on single-gene approaches. In previous work using mostly single-gene approaches, we observed significant associations (P < 0.05) for 6 of 46 polymorphisms in five genes in a Swedish prostate cancer case-control study population. We now report on the higher-order gene-gene interactions among those 46 genetic variants and the combined effect of the six polymorphisms with significant main effects for association with prostate cancer risk in 795 controls and 1,461 cases. Classification and regression tree analysis was used to evaluate higher-order gene-gene interactions. No interactions were confirmed by the result from logistic regressions. For the combined analysis, we tested the hypothesis that individuals carrying multiple copies of risk variants are at increased risk for prostate cancer. Individuals carrying more than eight copies of any risk variant were almost twofold more likely to get prostate cancer (OR = 1.99, P = 0.0014). A significant trend relationship was observed (P < 0.0001). In the present study, additive effects but not multiplicative effects among these six polymorphisms with significant main effects were observed.

Four genome-wide association studies, all in populations of European descent, have identified 20 independent single nucleotide polymorphisms (SNPs) in 20 regions that are associated with prostate cancer risk. We evaluated these 20 SNPs in a combined African American (AA) study, with 868 prostate cancer patients and 878 control subjects. For 17 of these 20 SNPs, implicated risk-associated alleles were found to be more common in these AA cases than controls, significantly more than expected under the null hypothesis (P = 0.03). Two of these 17 SNPs, located at 3p12, and Region 2 at 8q24, were significantly associated with prostate cancer risk (P < 0.05), and only SNP rs16901979 at Region 2 of 8q24 remained significant after accounting for 20 tests. A multivariate analysis of additional SNPs across the broader 8q24 region revealed three independent prostate cancer risk-associated SNPs, including rs16901979, rs13254738, and rs10086908. The first two SNPs were ∼20 kb apart and the last SNP, a novel finding from this study, was ∼100 kb centromeric to the first two SNPs. These results suggest that a systematic evaluation of regions harboring known prostate cancer risk SNPs implicated in other races is an efficient approach to identify risk alleles for AA. However, studies with larger numbers of AA subjects are needed, and this will likely require a major collaborative effort to combine multiple AA study populations.

SNPs at 11q13 were recently implicated in prostate cancer risk by two genome-wide association studies and were consistently replicated in multiple study populations. To explore prostate cancer association in the regions flanking these SNPs, we genotyped 31 tagging SNPs in a ~110 kb region at 11q13 in a Swedish case-control study (CAPS), including 2,899 cases and 1,722 controls. We found evidence of prostate cancer association for the previously implicated SNPs including rs10896449, which we termed locus 1. In addition, multiple SNPs on the centromeric side of the region, including rs12418451, were also significantly associated with prostate cancer risk (termed locus 2). The two groups of SNPs were separated by a recombination hotspot. We then evaluated these two representative SNPs in an additional ~4,000 cases and ~3,000 controls from three study populations and confirmed both loci at 11q13. In the combined allelic test of all four populations, P = 4.0 × 10−11 for rs10896449 at locus 1, and P = 1.2 × 10−6 for rs12418451 at locus 2, and both remained significant after adjusting for the other locus and study population. The prostate cancer association at these two 11q13 loci was unlikely confounded by PSA detection bias because neither SNP was associated with PSA levels in controls. Unlike locus 1 where no known gene is located, several putative mRNAs are in close proximity to locus 2. Additional confirmation studies at locus 2 and functional studies for both loci are needed to advance our knowledge on the etiology of prostate cancer.

Background

In older adults, studies demonstrate an inverse relationship between physical function and individual inflammatory biomarkers. Given that the inflammatory response is a complex system, a combination of biomarkers may increase the strength and consistency of these associations. This study uses principal component analysis to identify inflammatory “component(s)” and evaluates associations between the identified component(s) and measures of physical function.

Methods

Principal component analysis with a varimax rotation was used to identify two components from eight inflammatory biomarkers measured in 1,269 older persons. The study sample is a subset of the Health, Aging, and Body Composition study.

Results

The two components explained 56% of the total variance in the data (34%, component 1 and 22%, component 2). Five markers (tumor necrosis factor-alpha [TNF-α], sTNFRI, sTNFRII, interleukin [IL]-6sR, IL-2sR) loaded highest on the first component (TNF-α related), whereas three markers (C-reactive protein [CRP], IL-6, plasminogen activator inhibitor-1) loaded highest on the second component (CRP related). After adjusting for age, sex, race, site, sampling indicator, total lean and fat mass, physical activity, smoking, and anti-inflammatory drug use, knee strength and a physical performance battery score were inversely related to the TNF-α-related component, but not to the CRP-related component (knee strength: β^TNFα = −2.71, p = .002; β^CRP = −0.88, p = .325; physical performance battery score: β^TNFα = −0.05, p < .001; β^CRP = −0.02, p = .171). Both components were positively associated with 400-m walk time, inversely associated with grip strength, and not associated with 20-m walking speed.

Conclusions

At least two inflammatory components can be identified in an older population, and these components have inconsistent associations with different aspects of physical performance.

A two-stage genome-wide association study (GWAS) of the Cancer Genetic Markers of Susceptibility (CGEMS) initiative identified SNPs in 150 regions across the genome that may be associated with prostate cancer (PCa) risk. We filtered these results to identify 43 independent single nucleotide polymorphisms (SNPs) where the frequency of the risk allele was consistently higher in cases than in controls in each of the five CGEMS study populations. Genotype information for 22 of these 43 SNPs was obtained either directly by genotyping or indirectly by imputation in our PCa GWAS of 500 cases and 500 controls selected from a population-based case-control study in Sweden (CAPS). Two of these 22 SNPs were significantly associated with PCa risk (P<0.05). We then genotyped these two SNPs in the remaining cases (N=2,393) and controls (N=1,222) from CAPS and found rs887391 at 19q13 was highly associated with PCa risk (P=9.4 × 10−4). A similar trend of association was found for this SNP in a case-control study from Johns Hopkins Hospital, albeit the result was not statistically significant. Altogether, the frequency of the risk allele of rs887391 was consistently higher in cases than controls among each of seven study populations examined, with an overall P=3.2 × 10−7 from a combined allelic test. A fine mapping study in a 110 Kb region at 19q13 among CAPS and JHH study populations revealed rs887391 was the most strongly associated SNP in the region. Additional confirmation studies of this region are warranted.