scholarly journals Improved prediction of chronological age from DNA methylation limits it as a biomarker of ageing

2018 ◽  
Author(s):  
Qian Zhang ◽  
Costanza L. Vallerga ◽  
Rosie M Walker ◽  
Tian Lin ◽  
Anjali K. Henders ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Sample Size ◽  
Prediction Error ◽  
Small Samples ◽  
Chronological Age ◽  
Prediction Errors ◽  
Biological Ageing ◽  
Cell Composition ◽  
Illumina Humanmethylation450 ◽  
Age Range

AbstractDNA methylation is associated with age. The deviation of age predicted from DNA methylation from actual age has been proposed as a biomarker for ageing. However, a better prediction of chronological age implies less opportunity for biological age. Here we used 13,661 samples (from blood and saliva) in the age range of 2 to 104 years from 14 cohorts measured on Illumina HumanMethylation450/EPIC arrays to perform prediction analyses. We show that increasing the sample size achieves a smaller prediction error and higher correlations in test datasets. We demonstrate that smaller prediction errors provide a limit to how much variation in biological ageing can be captured by methylation and provide evidence that age predictors from small samples are prone to confounding by cell composition. Our predictor shows a similar or better performance in non-blood tissues including saliva, endometrium, breast, liver, adipose and muscle, compared with Horvath’s across-tissue age predictor.

scholarly journals S14. ANALYSIS OF METHYLATION AGE AND BLOOD CELL COMPOSITION IN SUBJECTS WITH CURRENT SUICIDE IDEATION

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S36-S36
Author(s):  
Oluwagbenga Dada ◽  
Vincenzo De Luca ◽  
Ali Bani-Fatemi ◽  
Vincenzo De Luca
Keyword(s):  
Dna Methylation ◽  
Blood Cell ◽  
Life Events ◽  
Stressful Life Events ◽  
Suicide Ideation ◽  
Accelerated Aging ◽  
Stressful Life ◽  
Chronological Age ◽  
Epigenetic Clock ◽  
Cell Composition

Abstract Background Suicidal Ideation (SI) remain an important and common risk factor affecting people with SCZ, who eventually attempt or complete suicide. Then the question is, what if factors (such as stressful life events and related molecular biomarkers) known to be involved in the aetiology of SCZ could help in predicting SI in this population? The accelerated aging hypothesis of SCZ posits that physiological changes associated with normal aging occur at an earlier age in individuals with SCZ than in the general population. Importantly, epigenetic changes may constitute an important component of aging process. Based on this, the chronological age can be predicted by the epigenetic clock in a highly consistent manner. The aims of this research were to determine the effect chronological and biological age on current SI and secondly, to determine the effect of the variation of cellular blood cell composition on current SI. Methods A total of 103 participants with a DSM-IV diagnosis of schizophrenia spectrum and other psychotic disorders were recruited from the Center of Addiction and Mental Health. The SI was assessed by the Columbia-Suicide Severity Rating Scale. Genome-wide DNA methylation analysis was generated from whole blood cells. The DNA methylation was assessed using the Illumina Infinium HumanMethylation450 Bead Chip while the DNA methylation-based age prediction and white blood cell composition were performed using the statistical pipeline developed by Horvath. Results Out of 103 participants, 18 had current SI (17%) while 85 had NSI. The DNAm age correlated with chronological age in the overall sample (r=0.814, p<0.0001), NSI (r=0.823, p<0.0001) and SI subjects (r=0.734, p=0.001). The strong linear relationship between DNAm age and chronological age showed a high accuracy of the epigenetic clock. However, DNAm age acceleration residuals did not differ between NSI and SI groups (t=1.532, p= 0.129). Comparison of the cellular cell blood composition between the NSI and SI groups indicated no significant differences between the NSI and SI groups (lymphocytes (t= -0.338, p=0.736), monocytes (t=-1.405, p=0.163) and granulocytes (t=0.924, p=0.358)). Furthermore, there were no significant differences between the SI and NSI groups in the analysis of the plasmablast (t=0.138, p=0.890), CD4 naïve (t=0.010, p=0.992) and CD8 naïve (t=0.681, p=0.497) Discussion Stressful life events may change DNA methylation, which in turn can affect suicide ideation and suicidal behavior. Although SCZ is associated with age-related physiological factors, we were unable to find accelerated aging in our study. Nevertheless, we cannot rule out the possibility of other aging mechanism independent of epigenetic aging in SCZ patients. Conclusion: Further studies aimed at investigating the accelerated aging hypothesis in peripheral tissue are warranted to identify individuals with SCZ at risk for suicide. This will permit a tailored treatment and will prevent suicide in SCZ individuals.

scholarly journals Blood and skeletal muscle ageing determined by epigenetic clocks and their associations with physical activity and functioning

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Elina Sillanpää ◽  
Aino Heikkinen ◽  
Anna Kankaanpää ◽  
Aini Paavilainen ◽  
Urho M. Kujala ◽  
...  
Keyword(s):  
Physical Activity ◽  
Dna Methylation ◽  
Body Composition ◽  
Physical Function ◽  
Muscle Tissue ◽  
Vastus Lateralis ◽  
Monozygotic Twin ◽  
Chronological Age ◽  
Epigenetic Clock ◽  
Biological Ageing

AbstractThe aim of this study was to investigate the correspondence of different biological ageing estimates (i.e. epigenetic age) in blood and muscle tissue and their associations with physical activity (PA), physical function and body composition. Two independent cohorts (N = 139 and N = 47) were included, whose age span covered adulthood (23–69 years). Whole blood and m. vastus lateralis samples were collected, and DNA methylation was analysed. Four different DNA methylation age (DNAmAge) estimates were calculated using genome-wide methylation data and publicly available online tools. A novel muscle-specific methylation age was estimated using the R-package ‘MEAT’. PA was measured with questionnaires and accelerometers. Several tests were conducted to estimate cardiorespiratory fitness and muscle strength. Body composition was estimated by dual-energy X-ray absorptiometry. DNAmAge estimates from blood and muscle were highly correlated with chronological age, but different age acceleration estimates were weakly associated with each other. The monozygotic twin within-pair similarity of ageing pace was higher in blood (r = 0.617–0.824) than in muscle (r = 0.523–0.585). Associations of age acceleration estimates with PA, physical function and body composition were weak in both tissues and mostly explained by smoking and sex. The muscle-specific epigenetic clock MEAT was developed to predict chronological age, which may explain why it did not associate with functional phenotypes. The Horvath’s clock and GrimAge were weakly associated with PA and related phenotypes, suggesting that higher PA would be linked to accelerated biological ageing in muscle. This may, however, be more reflective of the low capacity of epigenetic clock algorithms to measure functional muscle ageing than of actual age acceleration. Based on our results, the investigated epigenetic clocks have rather low value in estimating muscle ageing with respect to the physiological adaptations that typically occur due to ageing or PA. Thus, further development of methods is needed to gain insight into muscle tissue-specific ageing and the underlying biological pathways.

scholarly journals The Effects of Bipolar Disorder Risk on a Mobile Phone Keystroke Dynamics Based Biomarker of Brain Age

2021 ◽  
Vol 12 ◽  
Author(s):  
John Zulueta ◽  
Alexander Pantelis Demos ◽  
Claudia Vesel ◽  
Mindy Ross ◽  
Andrea Piscitello ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Mobile Phone ◽  
Prediction Error ◽  
Chronological Age ◽  
Prediction Errors ◽  
Age Related ◽  
Brain Changes ◽  
Mood And Cognition ◽  
Study Participants ◽  
Brain Age

Background: Research by our group and others have demonstrated the feasibility of using mobile phone derived metadata to model mood and cognition. Given the effects of age and mood on cognitive performance, it was hypothesized that using such data a model could be built to predict chronological age and that differences between predicted age and actual age could be a marker of pathology.Methods: These data were collected via the ongoing BiAffect study. Participants complete the Mood Disorders Questionnaire (MDQ), a screening questionnaire for bipolar disorder, and self-reported their birth year. Data were split into training and validation sets. Features derived from the smartphone kinematics were used to train random forest regression models to predict age. Prediction errors were compared between participants screening positive and negative on the MDQ.Results: Three hundred forty-four participants had analyzable data of which 227 had positive screens for bipolar disorder and 117 had negative screens. The absolute prediction error tended to be lower for participants with positive screens (median 4.50 years) than those with negative screens (median 7.92 years) (W = 508, p = 0.0049). The raw prediction error tended to be lower for participants with negative screens (median = −5.95 years) than those with positive screens (median = 0.55 years) (W = 1,037, p= 0.037).Conclusions: The tendency to underestimate the chronological age of participants screening negative for bipolar disorder compared to those screening positive is consistent with the finding that bipolar disorder may be associated with brain changes that could reflect pathological aging. This interesting result could also reflect that those who screen negative for bipolar disorder and who engaged in the study were more likely to have higher premorbid functioning. This work demonstrates that age-related changes may be detected via a passive smartphone kinematics based digital biomarker.

scholarly journals Blood and skeletal muscle ageing determined by epigenetic clocks and their associations with physical activity and functioning

2021 ◽  
Author(s):  
Elina Sillanpää ◽  
Aino Heikkinen ◽  
Anna Kankaanpää ◽  
Aini Paavilainen ◽  
Urho M. Kujala ◽  
...  
Keyword(s):  
Physical Activity ◽  
Dna Methylation ◽  
Body Composition ◽  
Physical Function ◽  
Muscle Tissue ◽  
Vastus Lateralis ◽  
Monozygotic Twin ◽  
Chronological Age ◽  
Epigenetic Clock ◽  
Biological Ageing

AbstractThe aim of this study was to investigate the correspondence of different biological ageing estimates (i.e. epigenetic age) in blood and muscle tissue and their associations with physical activity (PA), physical function and body composition.Two independent cohorts were included, whose age span covered adulthood (23–69 years). Whole blood and m. vastus lateralis samples were collected, and DNA methylation analysed. Four different DNA methylation age (DNAmAge) estimates were calculated using genome-wide methylation data and publicly available online tools. A novel muscle-specific methylation age was estimated using the R-package ‘MEAT’. PA was measured with questionnaires and accelerometers. Several tests were conducted to estimate cardiorespiratory fitness and muscle strength. Body composition was estimated by dual-energy X-ray absorptiometry.DNAmAge estimates from blood and muscle were highly correlated with chronological age, but different age acceleration estimates were weakly associated with each other. The monozygotic twin within-pair similarity of ageing pace was higher in blood (r=0.617–0.824) than in muscle (r=0.523–0.585). Associations of age acceleration estimates with PA, physical function and body composition were weak in both tissues and mostly explained by smoking and sex. The muscle-specific epigenetic clock MEAT was developed to predict chronological age, which may explain why it did not associate with functional phenotypes. The Horvath’s clock and GrimAge were weakly associated with PA and related phenotypes, suggesting that higher PA would be linked to accelerated biological ageing in muscle. This may, however, be more reflective of the low capacity of epigenetic clock algorithms to measure functional muscle ageing than of actual age acceleration.Based our results, the investigated epigenetic clocks have rather low value in estimating muscle ageing with respect to the physiological adaptations that typically occur due to ageing or PA. Thus, further development of methods is needed to gain further insight into muscle tissue-specific ageing and the underlying biological pathways.

Growth in Self-Actualization (Personal Orientation Inventory) in Adult Encounter Groups

1981 ◽  
Vol 1 (1) ◽  
pp. 5-8
Author(s):  
Les Beach
Keyword(s):  
Sample Size ◽  
Personal Growth ◽  
Total Sample ◽  
Small Samples ◽  
Total Sample Size ◽  
Personal Orientation Inventory ◽  
Self Actualization ◽  
Personal Orientation

To test the efficacy of the Personal Orientation Inventory in assessing growth in self-actualization in relation to encounter groups and to provide a more powerful measure of such changes, pre- and posttest data from 3 highly comparable encounter groups (N = 43) were combined for analysis. Results indicated that the Personal Orientation Inventory is a sensitive instrument for assessing personal growth in encounter groups and that a larger total sample size provides more significant results than those reported for small samples (e. g., fewer than 15 participants).

scholarly journals Gender differences in refraction prediction error of five formulas for cataract surgery

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yibing Zhang ◽  
Tingyang Li ◽  
Aparna Reddy ◽  
Nambi Nallasamy
Keyword(s):  
Gender Differences ◽  
Cataract Surgery ◽  
Prediction Error ◽  
Statistical Difference ◽  
Independent Predictor ◽  
Study Data ◽  
Prediction Errors ◽  
Optical Biometry ◽  
Iol Power ◽  
Lens Power

Abstract Objectives To evaluate gender differences in optical biometry measurements and lens power calculations. Methods Eight thousand four hundred thirty-one eyes of five thousand five hundred nineteen patients who underwent cataract surgery at University of Michigan’s Kellogg Eye Center were included in this retrospective study. Data including age, gender, optical biometry, postoperative refraction, implanted intraocular lens (IOL) power, and IOL formula refraction predictions were gathered and/or calculated utilizing the Sight Outcomes Research Collaborative (SOURCE) database and analyzed. Results There was a statistical difference between every optical biometry measure between genders. Despite lens constant optimization, mean signed prediction errors (SPEs) of modern IOL formulas differed significantly between genders, with predictions skewed more hyperopic for males and myopic for females for all 5 of the modern IOL formulas tested. Optimization of lens constants by gender significantly decreased prediction error for 2 of the 5 modern IOL formulas tested. Conclusions Gender was found to be an independent predictor of refraction prediction error for all 5 formulas studied. Optimization of lens constants by gender can decrease refraction prediction error for certain modern IOL formulas.

Youthful and Older Biases as Special Cases of a Self-Age Optimization Bias

1996 ◽  
Vol 43 (4) ◽  
pp. 267-276 ◽  
Author(s):  
Sara Staats
Keyword(s):  
College Students ◽  
Older Persons ◽  
Older Age ◽  
Chronological Age ◽  
Subjective Age ◽  
Special Cases ◽  
Age Range

Two concepts of subjective age are measured for two cohorts (college students and older persons with an age range of 50 to 91 years). Functional age (Kastenbaum et al., 1972 Ages-of-Me Scale [1]) shows the typical youthful bias for the older cohort. An older bias is shown for the Best/Ideal Age by the older cohort in comparison to the younger cohort. Taken together, the youthful bias, being like someone of younger chronological age, and the bias of selecting a relatively older age as best represents a “Self Age Optimization Bias.” A sub-set of Best Age items dealing with work and career are identified for gender and cohort comparisons.

scholarly journals W.S. Gosset and Some Neglected Concepts in Experimental Statistics: Guinnessometrics II

2011 ◽  
Vol 6 (2) ◽  
pp. 252-277 ◽  
Author(s):  
Stephen T. Ziliak
Keyword(s):  
Experimental Design ◽  
Sample Size ◽  
Large Scale ◽  
Statistical Significance ◽  
Small Sample ◽  
Small Samples ◽  
Significant Advance ◽  
Economic Approach ◽  
Barley Malt ◽  
Level Of Significance

AbstractStudent's exacting theory of errors, both random and real, marked a significant advance over ambiguous reports of plant life and fermentation asserted by chemists from Priestley and Lavoisier down to Pasteur and Johannsen, working at the Carlsberg Laboratory. One reason seems to be that William Sealy Gosset (1876–1937) aka “Student” – he of Student'st-table and test of statistical significance – rejected artificial rules about sample size, experimental design, and the level of significance, and took instead an economic approach to the logic of decisions made under uncertainty. In his job as Apprentice Brewer, Head Experimental Brewer, and finally Head Brewer of Guinness, Student produced small samples of experimental barley, malt, and hops, seeking guidance for industrial quality control and maximum expected profit at the large scale brewery. In the process Student invented or inspired half of modern statistics. This article draws on original archival evidence, shedding light on several core yet neglected aspects of Student's methods, that is, Guinnessometrics, not discussed by Ronald A. Fisher (1890–1962). The focus is on Student's small sample, economic approach to real error minimization, particularly in field and laboratory experiments he conducted on barley and malt, 1904 to 1937. Balanced designs of experiments, he found, are more efficient than random and have higher power to detect large and real treatment differences in a series of repeated and independent experiments. Student's world-class achievement poses a challenge to every science. Should statistical methods – such as the choice of sample size, experimental design, and level of significance – follow the purpose of the experiment, rather than the other way around? (JEL classification codes: C10, C90, C93, L66)

scholarly journals A Location Map Reduced Reversible Data Hiding Method Using Prediction Error Modification

2012 ◽  
Vol 6-7 ◽  
pp. 428-433
Author(s):  
Yan Wei Li ◽  
Mei Chen Wu ◽  
Tung Shou Chen ◽  
Wien Hong
Keyword(s):  
Image Quality ◽  
Data Hiding ◽  
Prediction Error ◽  
Reversible Data Hiding ◽  
Experimental Results ◽  
Cover Image ◽  
Prediction Errors ◽  
Secret Data ◽  
Location Map ◽  
Comparable Image Quality

We propose a reversible data hiding technique to improve Hong and Chen’s (2010) method. Hong and Chen divide the cover image into pixel group, and use reference pixels to predict other pixel values. Data are then embedded by modifying the prediction errors. However, when solving the overflow and underflow problems, they employ a location map to record the position of saturated pixels, and these pixels will not be used to carry data. In their method, if the image has a plenty of saturated pixels, the payload is decreased significantly because a lot of saturated pixels will not joint the embedment. We improve Hong and Chen’s method such that the saturated pixels can be used to carry data. The positions of these saturated pixels are then recorded in a location map, and the location map is embedded together with the secret data. The experimental results illustrate that the proposed method has better payload, will providing a comparable image quality.

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