Is chronic asthma associated with shorter leukocyte telomere length at midlife?

RATIONALE: Asthma is prospectively associated with age-related chronic diseases and mortality, suggesting the hypothesis that asthma may relate to a general, multisystem phenotype of accelerated aging. OBJECTIVES: To test whether chronic asthma is associated with a proposed biomarker of accelerated aging, leukocyte telomere length. METHODS: Asthma was ascertained prospectively in the Dunedin Multidisciplinary Health and Development Study cohort (n = 1,037) at nine in-person assessments spanning ages 9-38 years. Leukocyte telomere length was measured at ages 26 and 38 years. Asthma was classified as life-course-persistent, childhood-onset not meeting criteria for persistence, and adolescent/adult-onset. We tested associations between asthma and leukocyte telomere length using regression models. We tested for confounding of asthma-leukocyte telomere length associations using covariate adjustment. We tested serum C-reactive protein and white blood cell counts as potential mediators of asthma-leukocyte telomere length associations. MEASUREMENTS AND MAIN RESULTS: Study members with life-course-persistent asthma had shorter leukocyte telomere length as compared with sex- and age-matched peers with no reported asthma. In contrast, leukocyte telomere length in study members with childhood-onset and adolescent/adult-onset asthma was not different from leukocyte telomere length in peers with no reported asthma. Adjustment for life histories of obesity and smoking did not change results. Study members with life-course-persistent asthma had elevated blood eosinophil counts. Blood eosinophil count mediated 29% of the life-course-persistent asthma-leukocyte telomere length association. CONCLUSIONS: Life-course-persistent asthma is related to a proposed biomarker of accelerated aging, possibly via systemic eosinophilic inflammation. Life histories of asthma can inform studies of aging.

Making marine life count: a new baseline for policy.

The Census of Marine Life aids practical work of the Convention on Biological Diversity, discovers and tracks ocean biodiversity, and supports marine environmental planning.

Impact of Leukocyte Function-Associated Antigen-1 Blockade on Endogenous Allospecific T Cells to Multiple Minor Histocompatibility Antigen Mismatched Cardiac Allograft.

BACKGROUND: Blocking leukocyte function-associated antigen (LFA)-1 in organ transplant recipients prolongs allograft survival. However, the precise mechanisms underlying the therapeutic potential of LFA-1 blockade in preventing chronic rejection are not fully elucidated. Cardiac allograft vasculopathy (CAV) is the preeminent cause of late cardiac allograft failure characterized histologically by concentric intimal hyperplasia. METHODS: Anti-LFA-1 monoclonal antibody was used in a multiple minor antigen-mismatched, BALB.B (H-2B) to C57BL/6 (H-2B), cardiac allograft model. Endogenous donor-specific CD8 T cells were tracked down using major histocompatibility complex multimers against the immunodominant H4, H7, H13, H28, and H60 minor Ags. RESULTS: The LFA-1 blockade prevented acute rejection and preserved palpable beating quality with reduced CD8 T-cell graft infiltration. Interestingly, less CD8 T cell infiltration was secondary to reduction of T-cell expansion rather than less trafficking. The LFA-1 blockade significantly suppressed the clonal expansion of minor histocompatibility antigen-specific CD8 T cells during the expansion and contraction phase. The CAV development was evaluated with morphometric analysis at postoperation day 100. The LFA-1 blockade profoundly attenuated neointimal hyperplasia (61.6 vs 23.8%; P < 0.05), CAV-affected vessel number (55.3 vs 15.9%; P < 0.05), and myocardial fibrosis (grade 3.29 vs 1.8; P < 0.05). Finally, short-term LFA-1 blockade promoted long-term donor-specific regulation, which resulted in attenuated transplant arteriosclerosis. CONCLUSIONS: Taken together, LFA-1 blockade inhibits initial endogenous alloreactive T-cell expansion and induces more regulation. Such a mechanism supports a pulse tolerance induction strategy with anti-LFA-1 rather than long-term treatment.

Advances in Dynamic Modeling and Computation for Count Data

A class of multi-process models is developed for collections of time indexed count data. Autocorrelation in counts is achieved with dynamic models for the natural parameter of the binomial distribution. In addition to modeling binomial time series, the framework includes dynamic models for multinomial and Poisson time series. Markov chain Monte Carlo (MCMC) and Po ́lya-Gamma data augmentation (Polson et al., 2013) are critical for fitting multi-process models of counts. To facilitate computation when the counts are high, a Gaussian approximation to the P ́olya- Gamma random variable is developed.

Three applied analyses are presented to explore the utility and versatility of the framework. The first analysis develops a model for complex dynamic behavior of themes in collections of text documents. Documents are modeled as a “bag of words”, and the multinomial distribution is used to characterize uncertainty in the vocabulary terms appearing in each document. State-space models for the natural parameters of the multinomial distribution induce autocorrelation in themes and their proportional representation in the corpus over time.

The second analysis develops a dynamic mixed membership model for Poisson counts. The model is applied to a collection of time series which record neuron level firing patterns in rhesus monkeys. The monkey is exposed to two sounds simultaneously, and Gaussian processes are used to smoothly model the time-varying rate at which the neuron’s firing pattern fluctuates between features associated with each sound in isolation.

The third analysis presents a switching dynamic generalized linear model for the time-varying home run totals of professional baseball players. The model endows each player with an age specific latent natural ability class and a performance enhancing drug (PED) use indicator. As players age, they randomly transition through a sequence of ability classes in a manner consistent with traditional aging patterns. When the performance of the player significantly deviates from the expected aging pattern, he is identified as a player whose performance is consistent with PED use.

All three models provide a mechanism for sharing information across related series locally in time. The models are fit with variations on the P ́olya-Gamma Gibbs sampler, MCMC convergence diagnostics are developed, and reproducible inference is emphasized throughout the dissertation.