A negative relationship between total bilirubin concentration (TBili) and CVD risk has been documented in a series of epidemiological studies. In addition, TBili is thought to be under strong genetic regulation via the UGT1A gene family, suggesting it may be a heritable CVD risk factor. However, few studies directly relate TBili-associated UGT1A variants to CVD severity or outcome. This study replicated the genetic association for TBili in the Diabetes Heart Study (DHS), and examined the relationships of TBili-associated SNPs with measures of subclinical CVD and mortality.
This investigation included 1220 self-described European American (EA) individuals from the DHS, a family-based study examining risk for macrovascular complications in type 2 diabetes (T2D). Genetic associations with TBili were examined using the Affymetrix Genome-wide Human SNP Array 5.0 and the Illumina Infinium Human Exome beadchip v1.0. Subsequent analyses assessed the relationships of the top TBili-associated SNPs with measures of vascular calcified plaque and mortality.
A genome-wide association study (GWAS) detected 18 SNPs within the UGT1A gene family associated with TBili at p<5×10-8. The top hit was rs887829 (p=8.67×10-20). There was no compelling evidence of association between the top TBili-associated SNPs and vascular calcified plaque (p=0.05-0.88). There was, however, evidence of association with all-cause mortality (p=0.0004-0.06), the top hit being rs2741034.
These findings support a potential role for UGT1A genetic variants in risk for mortality in T2D. Further quantification of the extent of CVD risk conferred by UGT1A gene family variants in a high risk cohort with T2D is still required.
bilirubin; genetics; cardiovascular disease; vascular calcified plaque
Metabolic syndrome (MetS) and functional limitation have been linked, but whether and how specific components of MetS and associated factors, such as inflammation, drive this relationship is unknown.
Data are from 2,822 men and women, aged 70–79 years, participating in the Health, Aging, and Body Composition (Health ABC) study and followed for 5 years. Presence of MetS at baseline was defined according to the National Cholesterol Education Program Adult Treatment Panel III guidelines. Interleukin-6, C-reactive protein, and body fat mass were measured at baseline. Measures of physical performance, including 400-m walk time, 20-m walking speed, and the Health ABC physical performance battery (PPB) were obtained at baseline and examination years 2, 4, and 6.
A total of 1,036 (37%) individuals met criteria for MetS. MetS was associated with poorer physical performance at baseline. Effect estimates between MetS and gait speed, and components of the Health ABC PPB (standing balance and repeated sit-to-stand performance) were modestly attenuated after adjustment for inflammation. All associations were attenuated to nonsignificance after adding total body fat mass to the model. Longitudinal analyses yielded similar results. Individual MetS component analysis revealed that abdominal obesity explained the largest fraction of the variation in physical performance.
Although inflammatory biomarkers partially accounted for the relationship between MetS and aspects of physical performance, overall findings implicate adiposity as the primary factor explaining poorer physical performance in older adults with MetS.
Metabolic syndrome; Physical function; Inflammation; Obesity.
Individuals with type 2 diabetes mellitus (DM) are at increased risk of cardiovascular disease (CVD) and mortality. Beyond traditional CVD risk factors, novel measures reflecting additional aspects of disease pathophysiology, such as biventricular volume (BiVV), may be useful for risk stratification. This study examined the relationship between BiVV and risk for mortality in European Americans with type 2 DM from the Diabetes Heart Study. BiVV was calculated from 771 non-contrast computed tomography scans performed to image coronary artery calcified plaque (CAC). Relationships between BiVV and traditional CVD risk factors were examined. Cox proportional hazards regression was performed to determine risk for mortality (all-cause and CVD-mortality) associated with increasing BiVV. Area under the curve analysis was used to assess BiVV utility in risk prediction models. During 8.4 ± 2.4 years (mean ± SD) of follow-up, 23% of the sample were deceased. In unadjusted analyses, BiVV was significantly associated with increasing body mass index, height, CAC, history of hypertension and prior myocardial infarction (p<0.0001–0.012). BiVV was significantly associated with all-cause (HR: 2.45; CI: 1.06–5.67; p=0.036) and CVD-mortality (HR: 4.36; CI: 1.36–14.03; p=0.014) in models adjusted for other known CVD risk factors. Area under the curve increased from 0.76 to 0.78 (p=0.04) and 0.74 to 0.77 (p=0.02) for all-cause and CVD-mortality on inclusion of BiVV. In conclusion, in the absence of echocardiography or other noninvasive imaging modalities to assess ventricular volumes, or when such methods are contra-indicated, BiVV from computed tomography may be considered as a tool for stratification of high-risk individuals, such as those with type 2 DM.
cardiovascular disease; heart size; diabetes; risk-prediction
Several germline single nucleotide polymorphisms (SNPs) have been consistently associated with prostate cancer (PCa) risk.
To determine whether there is an improvement in PCa risk prediction by adding these SNPs to existing predictors of PCa.
Design, setting, and participants
Subjects included men in the placebo arm of the randomized Reduction by Dutasteride of Prostate Cancer Events (REDUCE) trial in whom germline DNA was available. All men had an initial negative prostate biopsy and underwent study-mandated biopsies at 2 yr and 4 yr. Predictive performance of baseline clinical parameters and/or a genetic score based on 33 established PCa risk-associated SNPs was evaluated.
Outcome measurements and statistical analysis
Area under the receiver operating characteristic curves (AUC) were used to compare different models with different predictors. Net reclassification improvement (NRI) and decision curve analysis (DCA) were used to assess changes in risk prediction by adding genetic markers.
Results and limitations
Among 1654 men, genetic score was a significant predictor of positive biopsy, even after adjusting for known clinical variables and family history (p = 3.41 × 10−8). The AUC for the genetic score exceeded that of any other PCa predictor at 0.59. Adding the genetic score to the best clinical model improved the AUC from 0.62 to 0.66 (p < 0.001), reclassified PCa risk in 33% of men (NRI: 0.10; p = 0.002), resulted in higher net benefit from DCA, and decreased the number of biopsies needed to detect the same number of PCa instances. The benefit of adding the genetic score was greatest among men at intermediate risk (25th percentile to 75th percentile). Similar results were found for high-grade (Gleason score ≥7) PCa. A major limitation of this study was its focus on white patients only.
Adding genetic markers to current clinical parameters may improve PCa risk prediction. The improvement is modest but may be helpful for better determining the need for repeat prostate biopsy. The clinical impact of these results requires further study.
Prostate cancer; Genetics; AUC; Detection rate; Reclassification; SNPs; Prospective study; Clinical trial
The goal of this work is to introduce new metrics to assess risk of Alzheimer's disease (AD) which we call AD Pattern Similarity (AD-PS) scores. These metrics are the conditional probabilities modeled by large-scale regularized logistic regression. The AD-PS scores derived from structural MRI and cognitive test data were tested across different situations using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. The scores were computed across groups of participants stratified by cognitive status, age and functional status. Cox proportional hazards regression was used to evaluate associations with the distribution of conversion times from mild cognitive impairment to AD. The performances of classifiers developed using data from different types of brain tissue were systematically characterized across cognitive status groups. We also explored the performance of anatomical and cognitive-anatomical composite scores generated by combining the outputs of classifiers developed using different types of data. In addition, we provide the AD-PS scores performance relative to other metrics used in the field including the Spatial Pattern of Abnormalities for Recognition of Early AD (SPARE-AD) index and total hippocampal volume for the variables examined.
We present the most comprehensive comparison to date of the predictive benefit of genetics in addition to currently used clinical variables, using genotype data for 33 single-nucleotide polymorphisms (SNPs) in 1,547 Caucasian men from the placebo arm of the REduction by DUtasteride of prostate Cancer Events (REDUCE®) trial. Moreover, we conducted a detailed comparison of three techniques for incorporating genetics into clinical risk prediction. The first method was a standard logistic regression model, which included separate terms for the clinical covariates and for each of the genetic markers. This approach ignores a substantial amount of external information concerning effect sizes for these Genome Wide Association Study (GWAS)-replicated SNPs. The second and third methods investigated two possible approaches to incorporating meta-analysed external SNP effect estimates – one via a weighted PCa ‘risk’ score based solely on the meta analysis estimates, and the other incorporating both the current and prior data via informative priors in a Bayesian logistic regression model. All methods demonstrated a slight improvement in predictive performance upon incorporation of genetics. The two methods that incorporated external information showed the greatest receiver-operating-characteristic AUCs increase from 0.61 to 0.64. The value of our methods comparison is likely to lie in observations of performance similarities, rather than difference, between three approaches of very different resource requirements. The two methods that included external information performed best, but only marginally despite substantial differences in complexity.
prostate cancer; genetic clinical risk prediction; genetic scores; Bayesian logistic regression; predictive assessment
Obesity-related increases in multiple inflammatory markers may contribute to the
persistent subclinical inflammation common with advancing age. However, it is unclear if
a specific combination of markers reflects the underlying inflammatory state. We used
factor analysis to identify inflammatory factor(s) and examine their associations with
adiposity in older adults at risk for disability.
Adiponectin, CRP, IL-1ra, IL-1sRII, IL-2sRα, IL-6, IL-6sR, IL-8, IL-15, sTNFRI,
sTNFRII, and TNF-α were measured in 179 participants from the Lifestyle
Interventions and Independence for Elders Pilot (Mean ± SD age
77 ± 4 years, 76% white, 70% women). Body mass index, waist circumference, and
total fat mass were assessed by anthropometry and dual-energy x-ray absorptiometry.
IL-2sRα, sTNFRI, and sTNFRII loaded highest on the first factor (factor 1). CRP,
IL-1ra, and IL-6 loaded highest on the second factor (factor 2). Factor 2, but not
factor 1, was positively associated with 1-SD increments in waist
circumference (β = 0.160 ± 0.057, p = .005),
body mass index (β = 0.132 ± 0.053, p = .01),
and total fat mass (β = 0.126 ± 0.053, p =
.02) after adjusting for age, gender, race/ethnicity, site, smoking, anti-inflammatory
medications, comorbidity index, health-related quality of life, and physical function.
These associations remained significant after further adjustment for grip strength, but
only waist circumference remained associated with inflammation after adjusting for total
lean mass. There were no significant interactions between adiposity and muscle mass or
strength for either factor.
Greater total and abdominal adiposity are associated with higher levels of an
inflammatory factor related to CRP, IL-1ra, and IL-6 in older adults, which may provide
a clinically useful measure of inflammation in this population.
Aging; Adiposity; Inflammation; Muscle impairment; Factor analysis
We hypothesized that chronic administration of the angiotensin-converting enzyme inhibitor, ramipril, to young adult male rats would prevent/ameliorate fractionated whole-brain irradiation-induced perirhinal cortex-dependent cognitive impairment. Eighty 12–14-week-old young adult male Fischer 344 rats received either: (1) sham irradiation, (2) 40 Gy of fractionated whole-brain irradiation delivered as two 5 Gy fractions/week for 4 weeks, (3) sham irradiation plus continuous administration of 15 mg/L of ramipril in the drinking water starting 3 days before irradiation, or (4) fractionated whole-brain irradiation plus ramipril. Cognitive function was assessed using a perirhinal cortex-dependent version of the novel object recognition task 26 weeks after irradiation. Microglial activation was determined in the perirhinal cortex and the dentate gyrus of the hippocampus 28 weeks after irradiation using the ED1 antibody. Neurogenesis was assessed in the granular cell layer and subgranular zones of the dentate gyrus using a doublecortin antibody. Fractionated whole-brain irradiation led to: (1) a significant impairment in perirhinal cortex-dependent cognitive function, (2) a significant increase in activated microglia in the dentate gyrus but not in the perirhinal cortex, and (3) a significant decrease in neurogenesis. Continuous administration of ramipril before, during, and after irradiation prevented the fractionated whole-brain irradiation-induced changes in perirhinal cortex-dependent cognitive function, as well as in microglial activation in the dentate gyrus. Thus, as hypothesized, continuous administration of the angiotensin-converting enzyme inhibitor, ramipril, can prevent the fractionated whole-brain irradiation-induced impairment in perirhinal cortex-dependent cognitive function.
Patients with type 2 diabetes (T2D) are at elevated risk for cardiovascular disease (CVD) events and mortality. Recent studies have assessed the impact of genetic variants affecting high-density lipoprotein cholesterol (HDL) concentrations on CVD risk in the general population. This study examined the utility of HDL-associated single nucleotide polymorphisms (SNPs) for CVD risk prediction in European Americans with T2D enrolled in the Diabetes Heart Study (DHS).
Genetic risk scores (GRS) of HDL-associated SNPs were constructed and evaluated for potential associations with mortality and with coronary artery calcified atherosclerotic plaque (CAC), a measure of subclinical CVD strongly associated with CVD events and mortality. Two sets of SNPs were used to construct GRS; while all SNPs were selected primarily for their impacts on HDL, one set of SNPs had pleiotropic effects on other lipid parameters, while the other set lacked effects on low-density lipoprotein cholesterol (LDL) or triglyceride concentrations.
The GRS were specifically associated with HDL concentrations (4.90 × 10-7 < p < 0.02) in models adjusted for age, sex, and body mass index (BMI), but were not associated with LDL or triglycerides. Cox proportional hazards regression analysis suggested the HDL-associated GRS had no impact on risk of CVD-mortality (0.48 < p < 0.99) in models adjusted for other known CVD risk factors. However, associations between several of the GRS and CAC were observed (3.85 × 10-4 < p < 0.03) in models adjusted for other known CVD risk factors.
The GRS analyzed in this study provide a tool for assessment of HDL-associated SNPs and their impact on CVD risk in T2D. The observed associations between several of the GRS and CAC suggest a potential role for HDL-associated SNPs on subclinical CVD risk in patients with T2D.
High-density lipoprotein cholesterol; Type 2 diabetes; Coronary artery calcified plaque; Mortality; Genetic risk score
Partial or whole-brain irradiation is often required to treat both primary and metastatic brain cancer. Radiation-induced normal tissue injury, including progressive cognitive impairment, however, can significantly affect the well-being of the approximately 200,000 patients who receive these treatments each year in the US. Although the exact mechanisms underlying radiation-induced late effects remain unclear, oxidative stress and inflammation are thought to play a critical role. Microglia are key mediators of neuroinflammation. Peroxisomal proliferator-activated receptor (PPAR)δ has been shown to be a potent regulator of anti-inflammatory responses. Thus, we hypothesized that PPARδ activation would modulate the radiation-induced inflammatory response in microglia. Incubating BV-2 murine microglial cells with the PPARδ agonist, L-165041, prevented the radiation-induced increase in: i) intracellular reactive oxygen species generation, ii) Cox-2 and MCP-1 expression, and iii) IL-1β and TNF-α message levels. This occured, in part, through PPARδ-mediated modulation of stress activated kinases and proinflammatory transcription factors. PPARδ inhibited NF-κB via transrepression by physically interacting with the p65 subunit, and prevented activation of the PKCα/MEK1/2/ERK1/2/AP-1 pathway by inhibiting the radiation-induced increase in intracellular reactive oxygen species generation. These data support the hypothesis that PPARδ activation can modulate radiation-induced oxidative stress and inflammatory responses in microglia.
Ionizing radiation; PPARδ; radiation-induced brain injury; microglia; inflammation; NF-κB; PKCα/MEK1/2/ERK1/2/AP-1 pathway
To assess the association between angiotensin converting enzyme inhibitors (ACEis) and improvements in the physical function of older adults in response to chronic exercise training.
Secondary analysis of the Lifestyle Interventions and Independence for Elders Pilot (LIFE-P) study, a multisite randomized clinical trial to evaluate the effects of chronic exercise on the physical function of older adults at risk for mobility disability.
Four academic research centers within the United States.
Four hundred twenty-four individuals aged 70 to 89 with mild to moderate functional impairments categorized for this analysis as ACEi users, users of other antihypertensive drugs, or antihypertensive nonusers.
A 12-month intervention of structured physical activity (PA) or health education promoting successful aging (SA).
Change in walking speed during a 400-m test and performance on a battery of short-duration mobility tasks (Short Physical Performance Battery (SPPB)).
Physical activity significantly improved the adjusted walking speed of ACEi users (P < .001) but did not of nonusers. PA improved the adjusted SPPB score of ACEi users (P < .001) and of persons who used other antihypertensive drugs (P = .005) but not of antihypertensive nonusers (P = .91). The percentage of ACEi users deriving clinically significant benefit from exercise training for walking speed (30%) and SPPB score (48%) was dramatically higher than for nonusers (14% and 12%, respectively).
For older adults at risk for disability, exercise-derived improvements in physical function were greater for ACEi users than users of other antihypertensive drugs and antihypertensive nonusers.
aging; exercise; physical function; LIFE Study; ACE inhibitors
There is a lack of information on whether exercise training alone can reduce the prevalence of metabolic syndrome (MetS) in elderly men and women.
This study was an ancillary to the Lifestyle Interventions and Independence for Elders Pilot Study, a four-site, single-blind, randomized controlled clinical trial comparing a 12-month physical activity (PA) intervention (N = 180) with a successful aging intervention (N = 181) in elderly (70–89 years) community-dwelling men and women at risk for physical disability. The PA intervention included aerobic, strength, and flexibility exercises, with walking as the primary mode. MetS was defined using the National Cholesterol Education Program criteria.
There was no significant change in body weight or fat mass after either intervention. The trend of MetS prevalence over the intervention period was similar between PA and successful aging groups (p = .77). Overall, the prevalence of MetS decreased significantly from baseline to 6 months (p = .003) but did not change further from 6- to 12-month visits (p = .11). There were no group differences in any individual MetS components (p > .05 for all group by visit interactions). However, in individuals not using medications at any visit to treat MetS components, those in the PA intervention had lower odds of having MetS than those in the successful aging group during follow-up (odds ratio = 0.28, 95% confidence interval = 0.08–0.96).
In this sample, a 12-month PA intervention did not reduce the prevalence of MetS more than a successful aging intervention, perhaps due to the large proportion of individuals taking medications for treating MetS components.
Metabolic syndrome; Elderly; Physical activity
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
genetic; bias; KLK3
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.
Higher Pfat is associated with higher carotid stiffness, independent of traditional CVD risk factors and obesity.
pericardial fat; arterial stiffness; distensibility; carotid artery
To determine whether the presence of high depressive symptoms diminished physical performance benefits after a comprehensive physical activity intervention in older adults.
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).
Multi-center U.S. sites participating in the LIFE-P trial.
LIFE-P trial participants included 424 sedentary, non-institutionalized adults (70–89 years).
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.
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).
The presence of high depressive symptoms did not substantially diminish physical performance benefits realized after a PA intervention in sedentary older adults.
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.
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.
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.
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.
Absolute risk; SNPs; association; screening; chemoprevention
Excessive non-subcutaneous fat deposition may impair the functions of surrounding tissues and organs through the release of inflammatory cytokines and free fatty acids.
We examined the cross-sectional association between non-subcutaneous adiposity and calcified coronary plaque, a non-invasive measure of coronary artery disease burden.
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.
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.
The overall burden of non-subcutaneous fat deposition, but not abdominal subcutaneous fat, may be a correlate of coronary atherosclerosis.
To determine the effects of a 12-month physical activity intervention on inflammatory biomarkers in elderly men and women.
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.
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.
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.
exercise; aging; inflammation; cytokines; soluble receptors
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.
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.
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.
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.
PCa; GWAS; meta-analysis; heterogeneity; genetic variation
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.
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.
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.
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.
prostate cancer; prediction; PSA; association
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.