No abstract

A low maximal oxygen consumption (VO2max) is a strong risk factor for premature mortality. Supervised endurance exercise training increases VO2max with a very wide range of effectiveness in humans. Discovering the DNA variants that contribute to this heterogeneity typically requires substantial sample sizes. In the present study, we first use RNA expression profiling to produce a molecular classifier that predicts VO2max training response. We then hypothesized that the classifier genes would harbor DNA variants that contributed to the heterogeneous VO2max response. Two independent preintervention RNA expression data sets were generated (n=41 gene chips) from subjects that underwent supervised endurance training: one identified and the second blindly validated an RNA expression signature that predicted change in VO2max ("predictor" genes). The HERITAGE Family Study (n=473) was used for genotyping. We discovered a 29-RNA signature that predicted VO2max training response on a continuous scale; these genes contained approximately 6 new single-nucleotide polymorphisms associated with gains in VO2max in the HERITAGE Family Study. Three of four novel candidate genes from the HERITAGE Family Study were confirmed as RNA predictor genes (i.e., "reciprocal" RNA validation of a quantitative trait locus genotype), enhancing the performance of the 29-RNA-based predictor. Notably, RNA abundance for the predictor genes was unchanged by exercise training, supporting the idea that expression was preset by genetic variation. Regression analysis yielded a model where 11 single-nucleotide polymorphisms explained 23% of the variance in gains in VO2max, corresponding to approximately 50% of the estimated genetic variance for VO2max. In conclusion, combining RNA profiling with single-gene DNA marker association analysis yields a strongly validated molecular predictor with meaningful explanatory power. VO2max responses to endurance training can be predicted by measuring a approximately 30-gene RNA expression signature in muscle prior to training. The general approach taken could accelerate the discovery of genetic biomarkers, sufficiently discrete for diagnostic purposes, for a range of physiological and pharmacological phenotypes in humans.

We have developed an entirely sequence-based method that identifies and integrates relevant features that can be used to assign proteins of unknown function to functional classes, and enzyme categories for enzymes. We show that strategies for the elucidation of protein function may benefit from a number of functional attributes that are more directly related to the linear sequence of amino acids, and hence easier to predict, than protein structure. These attributes include features associated with post-translational modifications and protein sorting, but also much simpler aspects such as the length, isoelectric point and composition of the polypeptide chain.

Physical activity and molecular ageing presumably interact to precipitate musculoskeletal decline in humans with age. Herein, we have delineated molecular networks for these two major components of sarcopenic risk using multiple independent clinical cohorts. We generated genome-wide transcript profiles from individuals (n = 44) who then undertook 20 weeks of supervised resistance-exercise training (RET). Expectedly, our subjects exhibited a marked range of hypertrophic responses (3% to +28%), and when applying Ingenuity Pathway Analysis (IPA) up-stream analysis to ∼580 genes that co-varied with gain in lean mass, we identified rapamycin (mTOR) signaling associating with growth (P = 1.4×10−30). Paradoxically, those displaying most hypertrophy exhibited an inhibited mTOR activation signature, including the striking down-regulation of 70 rRNAs. Differential analysis found networks mimicking developmental processes (activated all-trans-retinoic acid (ATRA, Z-score = 4.5; P = 6×10−13) and inhibited aryl-hydrocarbon receptor signaling (AhR, Z-score = −2.3; P = 3×10−7)) with RET. Intriguingly, as ATRA and AhR gene-sets were also a feature of endurance exercise training (EET), they appear to represent “generic” physical activity responsive gene-networks. For age, we found that differential gene-expression methods do not produce consistent molecular differences between young versus old individuals. Instead, utilizing two independent cohorts (n = 45 and n = 52), with a continuum of subject ages (18–78 y), the first reproducible set of age-related transcripts in human muscle was identified. This analysis identified ∼500 genes highly enriched in post-transcriptional processes (P = 1×10−6) and with negligible links to the aforementioned generic exercise regulated gene-sets and some overlap with ribosomal genes. The RNA signatures from multiple compounds all targeting serotonin, DNA topoisomerase antagonism, and RXR activation were significantly related to the muscle age-related genes. Finally, a number of specific chromosomal loci, including 1q12 and 13q21, contributed by more than chance to the age-related gene list (P = 0.01–0.005), implying possible epigenetic events. We conclude that human muscle age-related molecular processes appear distinct from the processes regulated by those of physical activity.

Promoter2.0 is available as a Web server at http://www.cbs.dtu. dk/services/promoter/

Objective. To evaluate the specificity of expression patterns of cell-free circulating microRNAs (miRNAs) in systemic lupus erythematosus (SLE).Methods. Total RNA was purified from plasma, and 45 different specific, mature miRNAs were determined using quantitative reverse transcriptionpolymerase chain reaction assays. A total of 409 plasma samples were obtained from 364 different patients with SLE, healthy control subjects, and control subjects with other autoimmune diseases. The results in the primary cohort of 62 patients with SLE and 29 healthy control subjects were validated in 2 independent cohorts: a validation cohort comprising 68 patients with SLE and 68 healthy control subjects, and a disease control cohort comprising 20 patients with SLE (19 of whom were from the other validation cohort), 46 healthy control subjects, 38 patients with vasculitis, 18 patients with rheumatoid arthritis, and 20 immunosuppressed patients.Results. Seven miRNAs were statistically significantly differentially expressed in plasma from patients with SLE. The expression of miRNA-142-3p (miR-142-3p) and miR-181a was increased, and the expression of miR-106a, miR-17, miR-20a, miR-203, and miR-92a was decreased. In addition, the expression of miR-342-3p, miR-223, and miR-20a was significantly decreased in SLE patients with active nephritis. A predictive model for SLE based on 2 or 4 miRNAs differentiated patients with SLE from control subjects (76% accuracy) when validated independently (P < 2 ؋ 10 ؊9 ). Use of the 4-miRNA model provided highly significant differentiation between the SLE group and disease controls, except for those with vasculitis.Conclusion. Circulating miRNAs are systematically altered in SLE. A 4-miRNA signature was diagnostic of SLE, and a specific subset of miRNA profiles was associated with nephritis. All of the signature miRNAs target genes in the transforming growth factor ␤ signaling pathways. Other targets include regulation of apoptosis, cytokine-cytokine receptors, T cell development, and cytoskeletal organization. These findings highlight possible dysregulated pathways in SLE and suggest that circulating miRNA patterns distinguish SLE from other immunoinflammatory phenotypes.The autoimmune disease systemic lupus erythematosus (SLE) is characterized by multiple immunologic abnormalities including the presence of circulating antinuclear antibodies and a sustained type I interferon (IFN) response (1), with up-regulation of type I IFN-

Prognostic markers that can predict the relapse of localized non-small cell lung cancer (NSCLC) have yet to be defined. We surveyed expression profiles of microRNA (miRNA) in stage I NSCLC to identify patterns that might predict recurrence after surgical resection of this common deadly cancer. Small RNAs extracted from formalin-fixed and paraffin-embedded tissues were hybridized to locked nucleic acid probes against 752 human miRNAs (representing 82% of the miRNAs in the miRBase 13.0 database) to obtain expression profiles for 37 cases with recurrence and 40 cases without recurrence (with clinical follow-up for at least 32 months). Differential expression between the two case groups was detected for 49% of the miRNAs (Wilcoxon rank sum test; P < 0.01). The performance of expression profiles at differentiating the two case groups was assessed by leave-one-out and Monte Carlo cross-validations. In leave-one-out cross-validation using support vector machines-or top-scoring gene pair classifier methods, which looked for six-or two-miRNA-based classifiers, the identified miRNA expression pattern predicted recurrence with an accuracy of 70% and 83%, and hazard ratio of 3.6 [95% confidence interval (95% CI), 1.8-7.1] and 9.0 (95% CI, 4.4-18.2), respectively. Mean accuracy in Monte Carlo cross-validation using 1,000 random 60-17 splits was 69% (95% CI, 68-70) and 72% (95% CI, 71-72), respectively. The specific miRNAs mir-200b*, mir-30c-1*, mir-510, mir-630, mir-657, and mir146b-3p and mir-124*, mir-585, and mir-708, respectively, represented most commonly among the 1,000 classifiers identified in Monte Carlo cross-validation by the two methods. MiRNAs mir-488, mir-503, and mir-647 were identified as potential reference miRNAs for future studies, based on the stability of their expression patterns across the 77 cases and the two case-groups. Our findings reinforce efforts to profile miRNA expression patterns for better prognostication of stage I NSCLC. Cancer Res; 70(1); 36-45. ©2010 AACR.

To investigate the cellular fate and function of polymorphonuclear neutrophilic granulocytes (PMNs) attracted to skin wounds, we used a human skin-wounding model and microarray technology to define differentially expressed genes in PMNs from peripheral blood, and PMNs that had transmigrated to skin lesions. After migration to skin lesions, PMNs demonstrated a significant transcriptional response including genes from several different functional categories. The up-regulation of anti-apoptotic genes concomitant with the down-regulation of proapoptotic genes suggested a transient anti-apoptotic priming of PMNs. Among the up-regulated genes were cytokines and chemokines critical for chemotaxis of macrophages, T cells, and PMNs, and for the modulation of their inflammatory responses. PMNs in skin lesions down-regulated receptors mediating chemotaxis and anti-microbial activity, but up-regulated other receptors involved in inflammatory responses. These findings indicate a change of responsiveness to chemotactic and immunoregulatory mediators once PMNs have migrated to skin lesions and have been activated. Other effects of the up-regulated cytokines/chemokines/enzymes were critical for wound healing. These included the breakdown of fibrin clots and degradation of extracellular matrix, the promotion of angiogenesis, the migration and proliferation of keratinocytes and fibroblasts, the adhesion of keratinocytes to the dermal layer, and finally, the induction of anti-microbial gene expression in keratinocytes. Notably, the up-regulation of genes, which activate lysosomal proteases, indicate a priming of skin lesion-PMNs for degradation of phagocytosed material. These findings demonstrate that migration of PMNs to skin lesions induces a transcriptional activation program, which regulates cellular fate and function, and promotes wound healing.