Physiological Fitness and the Pathophysiology of Chronic Lymphocytic Leukemia (CLL).

Chronic lymphocytic leukemia (CLL) is associated with physical dysfunction and low overall fitness that predicts poor survival following the commencement of treatment. However, it remains unknown whether higher fitness provides antioncogenic effects. We identified ten fit (CLL-FIT) and ten less fit (CLL-UNFIT) treatment-naïve CLL patients from 144 patients who completed a set of physical fitness and performance tests. Patient plasma was used to determine its effects on an in vitro 5-day growth/viability of three B-cell cell lines (OSU-CLL, Daudi, and Farage). Plasma exosomal miRNA profiles, circulating lipids, lipoproteins, inflammation levels, and immune cell phenotypes were also assessed. CLL-FIT was associated with fewer viable OSU-CLL cells at Day 1 (p = 0.003), Day 4 (p = 0.001), and Day 5 (p = 0.009). No differences between the groups were observed for Daudi and Farage cells. Of 455 distinct exosomal miRNAs identified, 32 miRNAs were significantly different between the groups. Of these, 14 miRNAs had ≤-1 or ≥1 log2 fold differences. CLL-FIT patients had five exosomal miRNAs with lower expression and nine miRNAs with higher expression. CLL-FIT patients had higher HDL cholesterol, lower inflammation, and lower levels of triglyceride components (all p < 0.05). CLL-FIT patients had lower frequencies of low-differentiated NKG2+/CD158a/bneg (p = 0.015 and p = 0.014) and higher frequencies of NKG2Aneg/CD158b+ mature NK cells (p = 0.047). The absolute number of lymphocytes, including CD19+/CD5+ CLL-cells, was similar between the groups (p = 0.359). Higher physical fitness in CLL patients is associated with altered CLL-like cell line growth in vitro and with altered circulating and cellular factors indicative of better immune functions and tumor control.

Association of Plasma Small-Molecule Intermediate Metabolites With Age and Body Mass Index Across Six Diverse Study Populations.

BACKGROUND: Older age and obesity are associated with metabolic dysregulation; the mechanism by which these factors impact metabolism across the lifespan is important, but relatively unknown. We evaluated a panel of amino acids (AAs) and acylcarnitines (ACs) to identify effects of age and adiposity (body mass index) on circulating small-molecule metabolites in a meta-analysis of six diverse study populations. METHODS: Targeted metabolic profiling was performed in six independent studies, representing 739 subjects with a broad range of age, body mass index, health states, and ethnic origin. Principal components analysis was performed on log-normalized values for AAs and ACs separately, generating one AC factor and two AA factors for each study. A common AC factor consisted primarily of acetylcarnitine, medium-chain AC, and several long-chain AC. AA Factor 1 consisted primarily of large neutral AAs. Glycine was its own factor. RESULTS: Metabolic profiling and factor analysis identified clusters of related metabolites of lipid and AA metabolism that were consistently associated with age and body mass in a series of studies with a broad range of age, body mass index, and health status. An inverse association of glycine with body mass index and male gender supports its role as a marker of favorable metabolic health. CONCLUSIONS: An important focus of future investigations should be to determine whether these clusters of metabolic intermediates are possible early predictors of health outcomes associated with body mass; are involved with accelerated aging; are involved in the causative pathway of aging; and how modification of these metabolic pathways impact the biology of aging.

A Novel Analytic Technique to Measure Associations Between Circulating Biomarkers and Physical Performance Across the Adult Life Span.

Understanding associations between circulating biomarkers and physical performance across the adult life span could aid in better describing mechanistic pathways leading to disability. We hypothesized that high concentrations of circulating biomarkers would be associated with lower functioning across study populations representing the adult life span. The data were from four intervention and two observational studies with ages ranging 22-89 years. Biomarkers assayed included inflammatory, coagulation, and endothelial function markers. Physical performance was measured either by VO2peak (studies of young and middle-aged adults) or usual gait speed (studies of older adults). Partialled (by age, body mass index, race, and sex) and weighted common correlations were calculated between biomarkers and physical performance. Homogeneity of the associations was also assessed. Interleukin-6 (weighted r = -.22), tumor necrosis factor receptor 2 (weighted r = -.19), D-dimer (weighted r = -.16), tumor necrosis factor receptor 1 (weighted r = -.15), granulocyte colony-stimulating factor (weighted r = -.14), and tumor necrosis factor alpha (weighted r = -.10) were all significantly inversely correlated with physical performance (p < .05). All significant correlations were homogeneous across studies. In summary, we observed consistent inverse associations between six circulating biomarkers and objective measures of physical performance. These results suggest that these serum biomarkers may be broadly applicable for detection, trajectory, and treatment monitoring of physical function across the life span or possibly for midlife predictors of functionally deleterious conditions.

Genome-wide linkage analysis of cardiovascular disease biomarkers in a large, multigenerational family.

Given the importance of cardiovascular disease (CVD) to public health and the demonstrated heritability of both disease status and its related risk factors, identifying the genetic variation underlying these susceptibilities is a critical step in understanding the pathogenesis of CVD and informing prevention and treatment strategies. Although one can look for genetic variation underlying susceptibility to CVD per se, it can be difficult to define the disease phenotype for such a qualitative analysis and CVD itself represents a convergence of diverse etiologic pathways. Alternatively, one can study the genetics of intermediate traits that are known risk factors for CVD, which can be measured quantitatively. Using the latter strategy, we have measured 21 cardiovascular-related biomarkers in an extended multigenerational pedigree, the CARRIAGE family (Carolinas Region Interaction of Aging, Genes, and Environment). These biomarkers belong to inflammatory and immune, connective tissue, lipid, and hemostasis pathways. Of these, 18 met our quality control standards. Using the pedigree and biomarker data, we have estimated the broad sense heritability (H2) of each biomarker (ranging from 0.09-0.56). A genome-wide panel of 6,015 SNPs was used subsequently to map these biomarkers as quantitative traits. Four showed noteworthy evidence for linkage in multipoint analysis (LOD score ≥ 2.6): paraoxonase (chromosome 8p11, 21), the chemokine RANTES (22q13.33), matrix metalloproteinase 3 (MMP3, 17p13.3), and granulocyte colony stimulating factor (GCSF, 8q22.1). Identifying the causal variation underlying each linkage score will help to unravel the genetic architecture of these quantitative traits and, by extension, the genetic architecture of cardiovascular risk.

Critical appraisal of four IL-6 immunoassays.

BACKGROUND: Interleukin-6 (IL-6) contributes to numerous inflammatory, metabolic, and physiologic pathways of disease. We evaluated four IL-6 immunoassays in order to identify a reliable assay for studies of metabolic and physical function. Serial plasma samples from intravenous glucose tolerance tests (IVGTTs), with expected rises in IL-6 concentrations, were used to test the face validity of the various assays. METHODS AND FINDINGS: IVGTTs, administered to 14 subjects, were performed with a single infusion of glucose (0.3 g/kg body mass) at time zero, a single infusion of insulin (0.025 U/kg body mass) at 20 minutes, and frequent blood collection from time zero to 180 minutes for subsequent Il-6 measurement. The performance metrics of four IL-6 detection methods were compared: Meso Scale Discovery immunoassay (MSD), an Invitrogen Luminex bead-based multiplex panel (LX), an Invitrogen Ultrasensitive Luminex bead-based singleplex assay (ULX), and R&D High Sensitivity ELISA (R&D). IL-6 concentrations measured with MSD, R&D and ULX correlated with each other (Pearson Correlation Coefficients r = 0.47-0.94, p<0.0001) but only ULX correlated (r = 0.31, p = 0.0027) with Invitrogen Luminex. MSD, R&D, and ULX, but not LX, detected increases in IL-6 in response to glucose. All plasma samples were measurable by MSD, while 35%, 1%, and 4.3% of samples were out of range when measured by LX, ULX, and R&D, respectively. Based on representative data from the MSD assay, baseline plasma IL-6 (0.90 ± 0.48 pg/mL) increased significantly as expected by 90 minutes (1.29 ± 0.59 pg/mL, p = 0.049), and continued rising through 3 hours (4.25 ± 3.67 pg/mL, p = 0.0048). CONCLUSION: This study established the face validity of IL-6 measurement by MSD, R&D, and ULX but not LX, and the superiority of MSD with respect to dynamic range. Plasma IL-6 concentrations increase in response to glucose and insulin, consistent with both an early glucose-dependent response (detectable at 1-2 hours) and a late insulin-dependent response (detectable after 2 hours).

Daily Variation of Serum Acylcarnitines and Amino Acids.

To characterize daily variation of amino acids (AAs) and acylcarnitines (ACs) in response to feeding and activity, we measured serum metabolites at various times and after various activities during the day. Subjects were admitted overnight for serial serum sampling, collected in the evening (6-8pm, n=40), before rising from bed or eating (8AM, n=40), 1 hour after rising but before eating (9 AM, n=20), 1-2 hours after rising and breakfast (9-10 AM, n=40), and at noon (12 PM, n=20). Measurements of 15 AAs and 45 ACs were performed by quantitative tandem mass spectrometry using stable-isotope dilution. Coefficients of variation within and between patients were calculated for individual metabolite values and factors derived from principal components analysis. The change of state between timepoints was evaluated by nearest neighbor non-parametric analysis of values at one timepoint compared to the next subsequent value. Relative to baseline AM recumbent concentrations, AA concentrations rose after activity and feeding while AC concentrations rose after activity and decreased with feeding. Furthermore, for all AAs, ACs, and their factors, biological variation was quantifiably evident and distinct from daily variation. This study confirms the daily variation of AAs and provides the first report of daily variation for a large panel of ACs. Although standardization of sample collection is highly desirable to control for daily variation (within a subject due to activity or feeding), this study demonstrated measurable biological variability (across subjects) suggesting that non-standardized sample collections could potentially provide insights into specific AA and AC metabolic pathways and disease mechanisms.

Plasma acylcarnitines are associated with physical performance in elderly men.

BACKGROUND: Metabolic profiling might provide insight into the biologic underpinnings of disability in older adults. METHODS: A targeted mass spectrometry-based platform was used to identify and quantify 45 plasma acylcarnitines in 77 older men with a mean age of 79 years and average body mass index of 28.4 kg/m(2). To control for type I error inherent in a test of multiple analytes, principal components analysis was employed to reduce the acylcarnitines from 45 separate metabolites, into a single "acylcarnitine factor." We then tested for an association between this acylcarnitine factor and multiple indices of physical performance and self-reported function. RESULTS: The acylcarnitine factor accounted for 40% of the total variance in 45 acylcarnitines. Of the metabolites analyzed, those that contributed most to our one-factor solution were even-numbered medium and long-chain species with side chains containing 10-18 carbons (factor loadings ≥0.70). Odd-numbered chain species, in contrast, had factor loadings 0.50 or less. Acylcarnitine factor scores were inversely related to physical performance as measured by the Short Physical Performance Battery total score, two of its three component scores (gait and chair stands Short Physical Performance Battery), and usual and maximal gait speeds (ρ = -0.324, -0.348, -0.309, -0.241, and -0.254, respectively; p < .05). CONCLUSIONS: Higher acylcarnitine factor scores were associated with lower levels of objectively measured physical performance in this group of older, largely overweight men. Metabolic profiles of rodents exhibiting lipid-induced mitochondrial dysfunction show a similar phenotypic predominance of medium- and long-chain acylcarnitines.