Dataset Information

Aging and the burden of multimorbidity: associations with inflammatory and anabolic hormonal biomarkers.

ABSTRACT:

Background

Multimorbidity increases with aging, but risk factors beyond age are unknown.

Objective

To investigate the association of inflammatory and anabolic hormonal biomarkers with presence and prospective development of multimorbidity.

Methods

Nine-year longitudinal study of 1018 participants aged 60 years or older (InCHIANTI Study). Multimorbidity was evaluated at baseline and follow-up visits as number of diagnosed diseases from a predefined list of 15 candidate chronic conditions, defined according to standard clinical criteria. Linear mixed models were used to test cross-sectional and longitudinal associations between candidate biomarkers and multimorbidity.

Results

At baseline, multimorbidity was significantly higher in older participants (p < .001) and higher IL-6, IL-1ra, TNF-? receptor II (TNFAR2), and lower dehydroepiandrosterone sulfate were associated with higher number of diseases, independent of age, sex, body mass index, and education. The rate of longitudinal increase in number of chronic diseases was significantly steeper in participants who were older at baseline (p < .001). In addition, higher baseline IL-6 and steeper increase of IL-6 levels were significantly and independently associated with a steeper increase in multimorbidity over time (p < .001 and p = .003, respectively). Sensitivity analyses, performed using 15 different models obtained by removing each of 15 conditions included in the original list of candidate diseases, confirmed that results were not driven by any specific condition.

Conclusions

Accumulation of chronic diseases accelerates at older ages and in persons with higher baseline levels and steeper increase over time of IL-6. High IL-6 and increase in IL-6 may serve as early warning sign to better target interventions aimed at reducing the burden of multimorbidity.

SUBMITTER: Fabbri E

PROVIDER: S-EPMC4296167 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Aging and the burden of multimorbidity: associations with inflammatory and anabolic hormonal biomarkers.

Fabbri Elisa E An Yang Y Zoli Marco M Simonsick Eleanor M EM Guralnik Jack M JM Bandinelli Stefania S Boyd Cynthia M CM Ferrucci Luigi L

The journals of gerontology. Series A, Biological sciences and medical sciences 20140807 1

<h4>Background</h4>Multimorbidity increases with aging, but risk factors beyond age are unknown.<h4>Objective</h4>To investigate the association of inflammatory and anabolic hormonal biomarkers with presence and prospective development of multimorbidity.<h4>Methods</h4>Nine-year longitudinal study of 1018 participants aged 60 years or older (InCHIANTI Study). Multimorbidity was evaluated at baseline and follow-up visits as number of diagnosed diseases from a predefined list of 15 candidate chron ...[more]

PMID: 25104822

Similar Datasets

Project description:Inflammatory cytokines and chemokines related to the innate and adaptive immune system have been linked to neuroinflammation in Alzheimer's Disease, dementia, and cognitive disorders. We examined the association of 11 plasma proteins (CD14, CD163, CD5L, CD56, CD40L, CXCL16, SDF1, DPP4, SGP130, sRAGE, and MPO) related to immune and inflammatory responses with measures of cognitive function, brain MRI and dementia risk. We identified Framingham Heart Study Offspring participants who underwent neuropsychological testing (n = 2358) or brain MRI (n = 2100) within five years of the seventh examination where a blood sample for quantifying the protein biomarkers was obtained; and who were followed for 10 years for incident all-cause dementia (n = 1616). We investigated the association of inflammatory biomarkers with neuropsychological test performance and brain MRI volumes using linear mixed effect models accounting for family relationships. We further used Cox proportional hazards models to examine the association with incident dementia. False discovery rate p-values were used to account for multiple testing. Participants included in the neuropsychological test and MRI samples were on average 61 years old and 54% female. Participants from the incident dementia sample (average 68 years old at baseline) included 124 participants with incident dementia. In addition to CD14, which has an established association, we found significant associations between higher levels of CD40L and myeloperoxidase (MPO) with executive dysfunction. Higher CD5L levels were significantly associated with smaller total brain volumes (TCBV), whereas higher levels of sRAGE were associated with larger TCBV. Associations persisted after adjustment for APOE ε4 carrier status and additional cardiovascular risk factors. None of the studied inflammatory biomarkers were significantly associated with risk of incident all-cause dementia. Higher circulating levels of soluble CD40L and MPO, markers of immune cell activation, were associated with poorer performance on neuropsychological tests, while higher CD5L, a key regulator of inflammation, was associated with smaller total brain volumes. Higher circulating soluble RAGE, a decoy receptor for the proinflammatory RAGE/AGE pathway, was associated with larger total brain volume. If confirmed in other studies, this data indicates the involvement of an activated immune system in abnormal brain aging.

Project description:BackgroundA relevant part of the genetic architecture of complex traits is still unknown; despite the discovery of many disease-associated common variants. Polygenic risk score (PRS) models are based on the evaluation of the additive effects attributable to common variants and have been successfully implemented to assess the genetic susceptibility for many phenotypes. In contrast, burden tests are often used to identify an enrichment of rare deleterious variants in specific genes. Both kinds of genetic contributions are typically analyzed independently. Many studies suggest that complex phenotypes are influenced by both low effect common variants and high effect rare deleterious variants. The aim of this paper is to integrate the effect of both common and rare functional variants for a more comprehensive genetic risk modeling.MethodsWe developed a framework combining gene-based scores based on the enrichment of rare functionally relevant variants with genome-wide PRS based on common variants for association analysis and prediction models. We applied our framework on UK Biobank dataset with genotyping and exome data and considered 28 blood biomarkers levels as target phenotypes. For each biomarker, an association analysis was performed on full cohort using gene-based scores (GBS). The cohort was then split into 3 subsets for PRS construction and feature selection, predictive model training, and independent evaluation, respectively. Prediction models were generated including either PRS, GBS or both (combined).ResultsAssociation analyses of the cohort were able to detect significant genes that were previously known to be associated with different biomarkers. Interestingly, the analyses also revealed heterogeneous effect sizes and directionality highlighting the complexity of the blood biomarkers regulation. However, the combined models for many biomarkers show little or no improvement in prediction accuracy compared to the PRS models.ConclusionThis study shows that rare variants play an important role in the genetic architecture of complex multifactorial traits such as blood biomarkers. However, while rare deleterious variants play a strong role at an individual level, our results indicate that classical common variant based PRS might be more informative to predict the genetic susceptibility at the population level.

Project description:DNA methylation data can be used to estimate proportions of leukocyte subsets retrospectively, when directly measured cell counts are unavailable. The methylation-derived neutrophil-to-lymphocyte and lymphocyte-to-monocyte ratios (mdNLRs and mdLMRs) have proven to be particularly useful as indicators of systemic inflammation. As with directly measured NLRs and LMRs, these methylation-derived ratios have been used as prognostic markers for cancer, although little is known about them in relation to other disorders with inflammatory components, such as cardiovascular disease (CVD). Recently, methylation of five genomic cytosine-phosphate-guanine sites (CpGs) was suggested as proxies for mdNLRs, potentially providing a cost-effective alternative when whole-genome methylation data are not available. This study compares seven methylation-derived inflammatory markers (mdNLR, mdLMR, and individual CpG sites) with five conventionally used protein-based inflammatory markers (C-reactive protein, interleukins 6 and 10, tumor-necrosis factor alpha, and interferon-gamma) and a protein-based inflammation score, in their associations with cardiovascular function (CVF) and risk. We found that markers of CVF were more strongly associated with methylation-derived than protein-based markers. In addition, the protein-based and methylation-derived inflammatory markers complemented rather than proxied one another in their contribution to the variance in CVF. There were no strong correlations between the methylation and protein markers either. Therefore, the methylation markers could offer unique information on the inflammatory process and are not just surrogate markers for inflammatory proteins. Although the five CpGs mirrored the mdNLR well in their capacity as proxies, they contributed to CVF above and beyond the mdNLR, suggesting possible added functional relevance. We conclude that methylation-derived indicators of inflammation enable individuals with increased CVD risk to be identified without measurement of protein-based inflammatory markers. In addition, the five CpGs investigated here could be useful surrogates for the NLR when the cost of array data cannot be met. Used in tandem, methylation-derived and protein-based inflammatory markers explain more variance than protein-based inflammatory markers alone.

Dataset Information

Aging and the burden of multimorbidity: associations with inflammatory and anabolic hormonal biomarkers.

Background

Objective

Methods

Results

Conclusions

Publications

Aging and the burden of multimorbidity: associations with inflammatory and anabolic hormonal biomarkers.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets