Human and pathogen factors associated with chlamydia trachomatis-related infertility in women

Chlamydia trachomatis is the most common bacterial sexually transmitted pathogen worldwide. Infection can result in serious reproductive pathologies, including pelvic inflammatory disease, ectopic pregnancy, and infertility, in women. However, the processes that result in these reproductive pathologies have not been well defined. Here we review the evidence for the human disease burden of these chlamydial reproductive pathologies. We then review human-based evidence that links Chlamydia with reproductive pathologies in women. We present data supporting the idea that host, immunological, epidemiological, and pathogen factors may all contribute to the development of infertility. Specifically, we review the existing evidence that host and pathogen genotypes, host hormone status, age of sexual debut, sexual behavior, coinfections, and repeat infections are all likely to be contributory factors in development of infertility. Pathogen factors such as infectious burden, treatment failure, and tissue tropisms or ascension capacity are also potential contributory factors. We present four possible processes of pathology development and how these processes are supported by the published data. We highlight the limitations of the evidence and propose future studies that could improve our understanding of how chlamydial infertility in women occurs and possible future interventions to reduce this disease burden.

Evaluation of a 7-gene genetic profile for athletic endurance phenotype in Ironman championship triathletes

Polygenic profiling has been proposed for elite endurance performance, using an additive model determining the proportion of optimal alleles in endurance athletes. To investigate this model’s utility for elite triathletes, we genotyped seven polymorphisms previously associated with an endurance polygenic profile (ACE Ins/Del, ACTN3 Arg577Ter, AMPD1 Gln12Ter, CKMM 1170bp/985+185bp, HFE His63Asp, GDF8 Lys153Arg and PPARGC1A Gly482Ser) in a cohort of 196 elite athletes who participated in the 2008 Kona Ironman championship triathlon. Mean performance time (PT) was not significantly different in individual marker analysis. Age, sex, and continent of origin had a significant influence on PT and were adjusted for. Only the AMPD1 endurance-optimal Gln allele was found to be significantly associated with an improvement in PT (model p=5.79 x 10-17, AMPD1 genotype p=0.01). Individual genotypes were combined into a total genotype score (TGS); TGS distribution ranged from 28.6 to 92.9, concordant with prior studies in endurance athletes (mean±SD: 60.75±12.95). TGS distribution was shifted toward higher TGS in the top 10% of athletes, though the mean TGS was not significantly different (p=0.164) and not significantly associated with PT even when adjusted for age, sex, and origin. Receiver operating characteristic curve analysis determined that TGS alone could not significantly predict athlete finishing time with discriminating sensitivity and specificity for three outcomes (less than median PT, less than mean PT, or in the top 10%), though models with the age, sex, continent of origin, and either TGS or AMPD1 genotype could. These results suggest three things: that more sophisticated genetic models may be necessary to accurately predict athlete finishing time in endurance events; that non-genetic factors such as training are hugely influential and should be included in genetic analyses to prevent confounding; and that large collaborations may be necessary to obtain sufficient sample sizes for powerful and complex analyses of endurance performance.