Project description:BackgroundQuantification of motor performance has a promising role in personalized medicine by diagnosing and monitoring, e.g. neurodegenerative diseases or health problems related to aging. New motion assessment technologies can evolve into patient-centered eHealth applications on a global scale to support personalized healthcare as well as treatment of disease. However, uncertainty remains on the limits of generalizability of such data, which is relevant specifically for preventive or predictive applications, using normative datasets to screen for incipient disease manifestations or indicators of individual risks.ObjectiveThis study explored differences between healthy German and Japanese adults in the performance of a short set of six motor tests.MethodsSix motor tasks related to gait and balance were recorded with a validated 3D camera system. Twenty-five healthy adults from Chiba, Japan, participated in this study and were matched for age, sex, and BMI to a sample of 25 healthy adults from Berlin, Germany. Recordings used the same technical setup and standard instructions and were supervised by the same experienced operator. Differences in motor performance were analyzed using multiple linear regressions models, adjusted for differences in body stature.ResultsFrom 23 presented parameters, five showed group-related differences after adjustment for height and weight (R 2 between .19 and .46, p<.05). Japanese adults transitioned faster between sitting and standing and used a smaller range of hand motion. In stepping-in-place, cadence was similar in both groups, but Japanese adults showed higher knee movement amplitudes. Body height was identified as relevant confounder (standardized beta >.5) for performance of short comfortable and maximum speed walks. For results of posturography, regression models did not reveal effects of group or body stature.ConclusionsOur results support the existence of a population-specific bias in motor function patterns in young healthy adults. This needs to be considered when motor function is assessed and used for clinical decisions, especially for personalized predictive and preventive medical purposes. The bias affected only the performance of specific items and parameters and is not fully explained by population-specific ethnic differences in body stature. It may be partially explained as cultural bias related to motor habits. Observed effects were small but are expected to be larger in a non-controlled cross-cultural application of motion assessment technologies with relevance for related algorithms that are being developed and used for data processing. In sum, the interpretation of individual data should be related to appropriate population-specific or even better personalized normative values to yield its full potential and avoid misinterpretation.Supplementary informationThe online version contains supplementary material available at 10.1007/s13167-021-00236-3.

Project description:Background:It is uncertain whether repeated measurements of a multi-target biomarker panel may help to personalize medical heart failure (HF) therapy to improve outcome in chronic HF. Methods:This analysis included 499 patients from the Trial of Intensified versus standard Medical therapy in Elderly patients with Congestive Heart Failure (TIME-CHF), aged ??60 years, LVEF ??45%, and NYHA ??II, who had repeated clinical visits within 19 months follow-up. The interaction between repeated measurements of biomarkers and treatment effects of loop diuretics, spironolactone, ?-blockers, and renin-angiotensin system (RAS) inhibitors on risk of HF hospitalization or death was investigated in a hypothesis-generating analysis. Generalized estimating equation (GEE) models were used to account for the correlation between recurrences of events in a patient. Results:One hundred patients (20%) had just one event (HF hospitalization or death) and 87 (17.4%) had at least two events. Loop diuretic up-titration had a beneficial effect for patients with high interleukin-6 (IL6) or high high-sensitivity C-reactive protein (hsCRP) (interaction, P?=?0.013 and P?=?0.001), whereas the opposite was the case with low hsCRP (interaction, P?=?0.013). Higher dosage of loop diuretics was associated with poor outcome in patients with high blood urea nitrogen (BUN) or prealbumin (interaction, P?=?0.006 and P?=?0.001), but not in those with low levels of these biomarkers. Spironolactone up-titration was associated with lower risk of HF hospitalization or death in patients with high cystatin C (CysC) (interaction, P?=?0.021). ?-Blockers up-titration might have a beneficial effect in patients with low soluble fms-like tyrosine kinase-1 (sFlt) (interaction, P?=?0.021). No treatment biomarker interactions were found for RAS inhibition. Conclusion:The data of this post hoc analysis suggest that decision-making using repeated biomarker measurements may be very promising in bringing treatment of heart failure to a new level in the context of predictive, preventive, and personalized medicine. Clearly, prospective testing is needed before this novel concept can be adopted. Clinical trial registration:isrctn.org, identifier: ISRCTN43596477.

Project description:The premise of disease-related phenotypes is the definition of the counterpart normality in medical sciences. Contrary to clinical practices that can be carefully planned according to clinical needs, heterogeneity and uncontrollability is the essence of humans in carrying out health studies. Full characterization of consistent phenotypes that define the general population is the basis to individual difference normalization in personalized medicine. Self-claimed normal status may not represent health because asymptomatic subjects may carry chronic diseases at their early stage, such as cancer, diabetes mellitus and atherosclerosis. Currently, treatments for non-communicable chronic diseases (NCD) are implemented after disease onset, which is a very much delayed approach from the perspective of predictive, preventive and personalized medicine (PPPM). A NCD pandemic will develop and be accompanied by increased global economic burden for healthcare systems throughout both developed and developing countries. This paper examples the characterization of the suboptimal health status (SHS) which represents a new PPPM challenge in a population with ambiguous health complaints such as general weakness, unexplained medical syndrome (UMS), chronic fatigue syndrome (CFS), myalgic encephalomyelitis (ME), post-viral fatigue syndrome (PVFS) and chronic fatigue immune dysfunction syndrome (CFIDS).We applied clinical informatic approaches and developed a questionnaire-suboptimal health status questionnaire-25 (SHSQ-25) for measuring SHS. The validity and reliability of this approach were evaluated in a small pilot study and then in a cross-sectional study of 3,405 participants in China.We found a correlation between SHS and systolic blood pressure, diastolic blood pressure, plasma glucose, total cholesterol and high-density lipoprotein (HDL) cholesterol among men, and a correlation between SHS and systolic blood pressure, diastolic blood pressure, total cholesterol, triglycerides and HDL cholesterol among women.The SHSQ-25 is a self-rated questionnaire of perceived health complaints, which can be used as a new instrument for PPPM. An ongoing longitudinal SHS cohort survey (China Sub-optimal Health Cohort Study, COACS) consisting of 50,000 participants will provide a powerful health trial to use SHSQ-25 for its application to PPPM through patient stratification and therapy monitoring using innovative technologies of predictive diagnostics and prognosis: an effort of paradigm shift from reactive to predictive medicine.

Project description:Background: Personalized medicine is predicated on the notion that individual biochemical and genomic profiles are relatively constant in times of good health and to some extent predictive of disease or therapeutic response. We report a pilot study quantifying gene expression and methylation profile consistency over time, addressing the reasons for individual uniqueness, and its relation to N=1 phenotypes. Methods: Whole blood samples from 4 African American women, 4 Caucasian women, and 4 Caucasian men drawn from the Atlanta Center for Health Discovery and Well Being study at three successive 6-month intervals were profiled by RNASeq, miRNASeq, and Illumina Methyl-450 arrays. Standard regression approaches were used to evaluate the proportion of variance for each type of omic measure that is among individuals, and to quantify correlations among measures and with clinical attributes related to wellness. Results: Longitudinal omic profiles are in general highly consistent over time, with an average of 67% of the variance in transcript abundance, 42% of CpG methylation level (but 88% for the most differentiated CpG per gene), and 50% of miRNA abundance among individuals, which are all comparable to 74% of the variance among individuals for 74 clinical traits. One third of the variance can be attributed to differential blood cell type abundance, which is also fairly stable over time, and a lesser amount to eQTL effects, whereas seven conserved axes of covariance that capture diverse aspects of immune function explain over half of the variance. These axes also explain a considerable proportion of individually extreme transcript abundance, namely approximately 100 genes that are significantly up- or down-regulated in each person and are in some cases enriched for relevant gene activities that plausibly associate with clinical attributes. A similar fraction of genes have individually divergent methylation levels, but these do not overlap with the transcripts, and fewer than 20% of genes have significantly correlated methylation and gene expression. Conclusions: People express an “omic personality” consisting of peripheral blood transcriptional and epigenetic profiles that are constant over the course of a year and reflect various types of immune activity. Baseline genomic profiles can provide a window into the molecular basis of traits that might be useful for explaining medical conditions or guiding personalized health decisions.

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The role of the personality traits and work characteristics in the prediction of the burnout syndrome among nurses-a new approach within predictive, preventive, and personalized medicine concept.

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The role of the personality traits and work characteristics in the prediction of the burnout syndrome among nurses-a new approach within predictive, preventive, and personalized medicine concept.

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