Dataset Information

Cardiorespiratory fitness alters the influence of a polygenic risk score on biomarkers of AD.

ABSTRACT:

Objective

To examine whether a polygenic risk score (PRS) derived from APOE4, CLU, and ABCA7 is associated with CSF biomarkers of Alzheimer disease (AD) pathology and whether higher cardiorespiratory fitness (CRF) modifies the association between the PRS and CSF biomarkers.

Methods

Ninety-five individuals from the Wisconsin Registry for Alzheimer's Prevention were included in these cross-sectional analyses. They were genotyped for APOE4, CLU, and ABCA7, from which a PRS was calculated for each participant. The participants underwent lumbar puncture for CSF collection. β-Amyloid 42 (Aβ₄₂), Aβ₄₀, total tau (t-tau), and phosphorylated tau (p-tau) were quantified by immunoassays, and Aβ₄₂/Aβ₄₀ and tau/Aβ₄₂ ratios were computed. CRF was estimated from a validated equation incorporating sex, age, body mass index, resting heart rate, and self-reported physical activity. Covariate-adjusted regression analyses were used to test for associations between the PRS and CSF biomarkers. In addition, by including a PRS×CRF term in the models, we examined whether these associations were modified by CRF.

Results

A higher PRS was associated with lower Aβ₄₂/Aβ₄₀ (p < 0.001), higher t-tau/Aβ₄₂ (p = 0.012), and higher p-tau/Aβ₄₂ (p = 0.040). Furthermore, we observed PRS × CRF interactions for Aβ₄₂/Aβ₄₀ (p = 0.003), t-tau/Aβ₄₂ (p = 0.003), and p-tau/Aβ₄₂ (p = 0.001). Specifically, the association between the PRS and these CSF biomarkers was diminished in those with higher CRF.

Conclusions

In a late-middle-aged cohort, CRF attenuates the adverse influence of genetic vulnerability on CSF biomarkers. These findings support the notion that increased cardiorespiratory fitness may be beneficial to those at increased genetic risk for AD.

SUBMITTER: Schultz SA

PROVIDER: S-EPMC5405766 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Publications

Cardiorespiratory fitness alters the influence of a polygenic risk score on biomarkers of AD.

Schultz Stephanie A SA Boots Elizabeth A EA Darst Burcu F BF Zetterberg Henrik H Blennow Kaj K Edwards Dorothy F DF Koscik Rebecca L RL Carlsson Cynthia M CM Gallagher Catherine L CL Bendlin Barbara B BB Asthana Sanjay S Sager Mark A MA Hogan Kirk J KJ Hermann Bruce P BP Cook Dane B DB Johnson Sterling C SC Engelman Corinne D CD Okonkwo Ozioma C OC

Neurology 20170324 17

<h4>Objective</h4>To examine whether a polygenic risk score (PRS) derived from <i>APOE4, CLU,</i> and <i>ABCA7</i> is associated with CSF biomarkers of Alzheimer disease (AD) pathology and whether higher cardiorespiratory fitness (CRF) modifies the association between the PRS and CSF biomarkers.<h4>Methods</h4>Ninety-five individuals from the Wisconsin Registry for Alzheimer's Prevention were included in these cross-sectional analyses. They were genotyped for <i>APOE4</i>, <i>CLU</i>, and <i>ABC ...[more]

PMID: 28341646

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Project description:BackgroundThe polygenic risk score (PRS) has been perceived as advantageous in predicting the risk of complex diseases compared to other measures. We aimed to systematically evaluate the influence of PRS on disease outcome and to explore its predictive value.MethodsWe comprehensively assessed the relationship between PRS and 32 complex diseases in the UK Biobank. We used Cox models to estimate the effects of PRS on the incidence risk. Then, we constructed prediction models to assess the clinical utility of PRS in risk prediction. For 16 diseases, we further compared the disease risk and prediction capability of PRS across early and late-onset cases.ResultsHigher PRS led to greater incident risk, with hazard ratio (HR) ranging from 1.07 (95% confidence interval (CI) = 1.06-1.08) for panic/anxiety disorder to 4.17 (95% CI = 4.03-4.31) for acute pancreatitis. This effect was more pronounced in early-onset cases for 12 diseases, increasing by 52.8% on average. Particularly, the early-onset risk of heart failure associated with PRS (HR = 3.02; 95% CI = 2.53-3.59) was roughly twice compared to the late-onset risk (HR = 1.48; 95% CI = 1.46-1.51). Compared to average PRS (20-80%), individuals positioned within the top 2.5% of the PRS distribution exhibited varying degrees of elevated risk, corresponding to a more than five times greater risk on average. PRS showed additional value in clinical risk prediction, causing an average improvement of 6.1% in prediction accuracy. Further, PRS demonstrated higher predictive accuracy for early-onset cases of 11 diseases, with heart failure displaying the most significant (37.5%) improvement when incorporating PRS into the prediction model (concordance index (C-index) = 0.546; standard error (SE) = 0.011 vs. C-index = 0.751; SE = 0.010, P = 2.47 × 10-12).ConclusionsAs a valuable complement to traditional clinical risk tools, PRS is closely related to disease risk and can further enhance prediction accuracy, especially for early-onset cases, underscoring its potential role in targeted prevention for high-risk groups.

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Project description:Background: Asthma is common chronic inflammatory disease of the airways with a heterogenous clinical presentation. Individual differences in asthma susceptibility remain poorly understood, although genetics is thought to play a major role. Aim: To build a polygenic risk score (PRS) for asthma and determine whether predictive genetic variants can be epigenomically linked to specific pathophysiological mechanisms. Methods: PRSs were constructed using data from genome-wide association studies and performance was validated using data generated in the Rotterdam Study, a Dutch prospective cohort of 14,926 individuals. Outcomes used were asthma, childhood-onset asthma, adulthood-onset asthma, eosinophilic asthma and exacerbations. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-Seq) data from 14 primary cell types, including lung epithelial cells and T lymphocytes was used for epigenomic PRS partitioning. Results: All PRSs successfully predicted risk to develop asthma and related outcomes, with the strongest predictive power (2.42 odds ratios per PRS standard deviation, area under the curve of 0.736) achieved for childhood-onset asthma. PRSs allowed for stratification of the Rotterdam Study cohort into groups at low or high risk to develop asthma. PRS partitioning using genome-wide epigenomic profiles identified 5 clusters of variants within gene regulatory regions linked to specific asthma-relevant cells, genes and biological pathways. Conclusions: PRSs can predict whether individuals in a Dutch cohort developed asthma and asthma-related phenotypes, which is most effective for childhood-onset asthma. Importantly, we show that PRS partitioning based on epigenomics data dissects a genetic risk score into blocks of regulatory variants with differential predictive power, which likely represent distinct genetically driven disease pathways. These findings have potential implications for personalized risk mitigation and treatment strategies.

Dataset Information

Cardiorespiratory fitness alters the influence of a polygenic risk score on biomarkers of AD.

Objective

Methods

Results

Conclusions

Publications

Cardiorespiratory fitness alters the influence of a polygenic risk score on biomarkers of AD.

Similar Datasets

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