Estrogen metabolism and mammographic density in postmenopausal women : a cross-sectional study

Background: Prospective studies have consistently found that postmenopausal breast cancer risk increases with circulating estrogens; however, findings from studies of estrogens and mammographic density (MD), an intermediate marker of breast cancer risk, have been inconsistent. We investigated the cross-sectional associations of urinary estrogens, and their 2-, 4-, and 16-hydroxylated metabolites with MD. Methods: Postmenopausal women without breast cancer (n = 194), ages 48 to 82 years, and reporting no current menopausal hormone therapy use were enrolled at a clinic in Western NY in 2005. Urinary estrogens and estrogen metabolites were measured using mass spectrometry. Percent MD and dense area (cm2) were measured using computer-assisted analyses of digitized films. Linear regression models were used to estimate associations of log-transformed estrogen measures with MD while adjusting for age, body mass index (BMI), parity, and past hormone therapy use. Results: Urinary concentrations of most individual estrogens and metabolites were not associated with MD; however, across the interdecile range of the ratio of parent estrogens (estrone and estradiol) to their metabolites, MD increased by 6.8 percentage points (P = 0.02) and dense area increased by 10.3 cm2 (P = 0.03). Across the interdecile ranges of the ratios of 2-, 4-, and 16-hydroxylation pathways to the parent estrogens, MD declined by 6.2 (P = 0.03), 6.4 (P = 0.04), and 5.7 (P = 0.05) percentage points, respectively. All associations remained apparent in models without adjustment for BMI. Conclusion: In this study of postmenopausal women, less extensive hydroxylation of parent estrogens was associated with higher MD. Impact: Hydroxylation of estrogens may modulate postmenopausal breast cancer risk through a pathway involving MD

Heterozygous ANKRD17 loss-of-function variants cause a syndrome with intellectual disability, speech delay, and dysmorphism

ANKRD17 is an ankyrin repeat-containing protein thought to play a role in cell cycle progression, whose ortholog in Drosophila functions in the Hippo pathway as a co-factor of Yorkie. Here, we delineate a neurodevelopmental disorder caused by de novo heterozygous ANKRD17 variants. The mutational spectrum of this cohort of 34 individuals from 32 families is highly suggestive of haploinsufficiency as the underlying mechanism of disease, with 21 truncating or essential splice site variants, 9 missense variants, 1 in-frame insertion-deletion, and 1 microdeletion (1.16 Mb). Consequently, our data indicate that loss of ANKRD17 is likely the main cause of phenotypes previously associated with large multi-gene chromosomal aberrations of the 4q13.3 region. Protein modeling suggests that most of the missense variants disrupt the stability of the ankyrin repeats through alteration of core structural residues. The major phenotypic characteristic of our cohort is a variable degree of developmental delay/intellectual disability, particularly affecting speech, while additional features include growth failure, feeding difficulties, non-specific MRI abnormalities, epilepsy and/or abnormal EEG, predisposition to recurrent infections (mostly bacterial), ophthalmological abnormalities, gait/balance disturbance, and joint hypermobility. Moreover, many individuals shared similar dysmorphic facial features. Analysis of single-cell RNA-seq data from the developing human telencephalon indicated ANKRD17 expression at multiple stages of neurogenesis, adding further evidence to the assertion that damaging ANKRD17 variants cause a neurodevelopmental disorder.Neurolog

Predicting marching capacity while carrying extremely heavy loads

The objective of this study was to establish the best prediction for endurance time of combat soldiers marching with extremely heavy loads. It was hypothesized that loads relative to individual characteristics (% maximal load carry capacity [MLCC], % body mass, % lean body mass) would better predict endurance time than load itself. Twenty-three male combat soldiers participated. MLCC was determined by increasing the load by 7.5 kg every 4 minutes until exhaustion. The marching velocity and gradient were 3 km·h−1 and 5%, respectively. Endurance time was determined carrying 70, 80, and 90% of MLCC. MLCC was on average 102.6 kg ± 11.6. Load expressed as % MLCC was the best predictor for endurance time (R2 = 0.45). Load expressed as % body mass, as % lean body mass, and absolute load predicted endurance time less well (R2 = 0.30, R2 = 0.24, and R2 = 0.23, respectively). On the basis of these results, it is recommended to assess the MLCC of individual combat soldiers