Dataset Information

Protein profiling reveals consequences of lifestyle choices on predicted biological aging.

ABSTRACT: Ageing is linked to a number of changes in how the body and its organs function. On a molecular level, ageing is associated with a reduction of telomere length, changes in metabolic and gene-transcription profiles and an altered DNA-methylation pattern. Lifestyle factors such as smoking or stress can impact some of these molecular processes and thereby affect the ageing of an individual. Here we demonstrate by analysis of 77 plasma proteins in 976 individuals, that the abundance of circulating proteins accurately predicts chronological age, as well as anthropometrical measurements such as weight, height and hip circumference. The plasma protein profile can also be used to identify lifestyle factors that accelerate and decelerate ageing. We found smoking, high BMI and consumption of sugar-sweetened beverages to increase the predicted chronological age by 2-6 years, while consumption of fatty fish, drinking moderate amounts of coffee and exercising reduced the predicted age by approximately the same amount. This method can be applied to dried blood spots and may thus be useful in forensic medicine to provide basic anthropometrical measures for an individual based on a biological evidence sample.

SUBMITTER: Enroth S

PROVIDER: S-EPMC4664859 | biostudies-other | 2015

REPOSITORIES: biostudies-other

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Protein profiling reveals consequences of lifestyle choices on predicted biological aging.

Enroth Stefan S Enroth Sofia Bosdotter SB Johansson Åsa Å Gyllensten Ulf U

Scientific reports 20151201

Ageing is linked to a number of changes in how the body and its organs function. On a molecular level, ageing is associated with a reduction of telomere length, changes in metabolic and gene-transcription profiles and an altered DNA-methylation pattern. Lifestyle factors such as smoking or stress can impact some of these molecular processes and thereby affect the ageing of an individual. Here we demonstrate by analysis of 77 plasma proteins in 976 individuals, that the abundance of circulating p ...[more]

PMID: 26619799

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Project description:BackgroundLifestyle choices reflect the beliefs that individuals attribute to aspects of life. This construct can be assessed with the Individual Lifestyle Profile (PEVI) questionnaire, which measures elements of Nutrition, Physical Activity, Preventive Behaviors, Social Relationships and Stress Management.ObjectiveThe objective of this study was to estimate the psychometric properties of the PEVI applied to a sample of Brazilian university students, identifying the prevalence of each lifestyle component according to participants' age, sex, weight status, course area/field and economic stratum and to estimate the contribution of these characteristics on physical and psychological lifestyle.MethodsThe PEVI data was analyzed by confirmatory factor analysis, using the indexes chi-square per degrees of freedom ratio (χ2/df), Comparative Fit Index (CFI), Tucker-Lewis Index (TLI) and Root Mean Square Error of Approximation (RMSEA). First-order and second-order models (physical and psychological lifestyle) were tested. Prevalences of lifestyle components were calculated and compared by participants' age, sex, weight status, course area/field and economic stratum. A hypothetical causal structural model was elaborated to investigate the impact of sample characteristics on physical and psychological lifestyles. This model was evaluated considering the global fit to the data (χ2/df, CFI, TLI and RMSEA) and the hypothetical causal trajectories (β) (α = 5%).ResultsA sample of 1,303 students was used. The mean age was 20.9 (standard deviation = 2.8) years, 66.8% of participants were females, 63.4% had weights in the normal range and 73.7% were students of the social and exact sciences. The PEVI data showed an adequate fit for both the first- (χ2/df = 2.03, CFI = 0.98; TLI = 0.97; RMSEA = 0.04) and second-order (χ2/df = 2.25; CFI = 0.97; TLI = 0.97; RMSEA = 0.04) models. There was a higher prevalence of unfavorable physical and psychological lifestyle choices among females, among underweight and obese individuals, in older students and in those with lower economic strata. Moreover, negative behaviors in physical lifestyle were more prevalent in students from human/social/exact sciences and worse psychological lifestyle was observed among health sciences students. These results were confirmed by a structural model.ConclusionThe PEVI data presented validity and reliability. Negative lifestyle choices had high prevalence among students. Moreover, individual characteristics had different impact on physical and psychological lifestyle choices.

Project description:Worldwide, crop production is intrinsically intertwined with biological, environmental and economic systems, all of which involve complex, inter-related and spatially-sensitive phenomena. Thus knowing the location of agriculture matters much for a host of reasons. There are several widely cited attempts to model the spatial pattern of crop production worldwide, not least by pixilating crop production statistics originally reported on an areal (administrative boundary) basis. However, these modeled measures have had little scrutiny regarding the robustness of their results to alternative data and modeling choices. Our research casts a critical eye over the nature and empirical plausibility of these types of datasets. To do so, we determine the sensitivity of the 2005 variant of the spatial production allocation model data series (SPAM2005) to eight methodological-cum-data choices in nine agriculturally-large and developmentally-variable countries: Brazil, China, Ethiopia, France, India, Indonesia, Nigeria, Turkey and the United States. We compare the original published estimates with those obtained from a series of robustness tests using various aggregations of the pixelized spatial production indicators (specifically, commodity-specific harvested area, production quantity and yield). Spatial similarity is empirically assessed using a pixel-level spatial similarity index (SSI). We find that the SPAM2005 estimates are most dependent on the degree of disaggregation of the underlying national and subnational production statistics. The results are also somewhat sensitive to the use of a simple spatial allocation method based solely on cropland proportions versus a cross-entropy allocation method, as well as the set of crops or crop aggregates being modeled, and are least sensitive to the inclusion of crude economic elements. Finally, we assess the spatial concordance between the SPAM2005 estimates of the area harvested of major crops in the United States and pixelated measures derived from remote-sensed data.

Project description:Diffusion-weighted imaging (DWI) is known to be prone to artifacts related to motion originating from subject movement, cardiac pulsation, and breathing, but also to mechanical issues such as table vibrations. Given the necessity for rigorous quality control and motion correction, users are often left to use simple heuristics to select correction schemes, which involves simple qualitative viewing of the set of DWI data, or the selection of transformation parameter thresholds for detection of motion outliers. The scientific community offers strong theoretical and experimental work on noise reduction and orientation distribution function (ODF) reconstruction techniques for HARDI data, where post-acquisition motion correction is widely performed, e.g., using the open-source DTIprep software (1), FSL (the FMRIB Software Library) (2), or TORTOISE (3). Nonetheless, effects and consequences of the selection of motion correction schemes on the final analysis, and the eventual risk of introducing confounding factors when comparing populations, are much less known and far beyond simple intuitive guessing. Hence, standard users lack clear guidelines and recommendations in practical settings. This paper reports a comprehensive evaluation framework to systematically assess the outcome of different motion correction choices commonly used by the scientific community on different DWI-derived measures. We make use of human brain HARDI data from a well-controlled motion experiment to simulate various degrees of motion corruption and noise contamination. Choices for correction include exclusion/scrubbing or registration of motion corrupted directions with different choices of interpolation, as well as the option of interpolation of all directions. The comparative evaluation is based on a study of the impact of motion correction using four metrics that quantify (1) similarity of fiber orientation distribution functions (fODFs), (2) deviation of local fiber orientations, (3) global brain connectivity via graph diffusion distance (GDD), and (4) the reproducibility of prominent and anatomically defined fiber tracts. Effects of various motion correction choices are systematically explored and illustrated, leading to a general conclusion of discouraging users from setting ad hoc thresholds on the estimated motion parameters beyond which volumes are claimed to be corrupted.

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Protein profiling reveals consequences of lifestyle choices on predicted biological aging.

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Protein profiling reveals consequences of lifestyle choices on predicted biological aging.

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