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Fulltext Distribution of Angiostrongylus vasorum and its gastropod intermediate hosts along the rural-urban gradient in two cities in the United Kingdom, using real time PCR

Aziz NA, Daly E, Allen S, Rowson B, Greig C, Forman D, et al.

Parasit Vectors, 2016;9:56.
PMID: 26830203 DOI: 10.1186/s13071-016-1338-3

Angiostrongylus vasorum is a highly pathogenic metastrongylid nematode affecting dogs, which uses gastropod molluscs as intermediate hosts. The geographical distribution of the parasite appears to be heterogeneous or patchy and understanding of the factors underlying this heterogeneity is limited. In this study, we compared the species of gastropod present and the prevalence of A. vasorum along a rural-urban gradient in two cities in the south-west United Kingdom.
The relationship between Type D personality and insomnia

Akram U, McCarty K, Akram A, Gardani M, Tan A, Villarreal D, et al.

Sleep Health, 2018 08;4(4):360-363.
PMID: 30031529 DOI: 10.1016/j.sleh.2018.04.005

OBJECTIVES: Type D personality is characterized by the combination of social inhibition and negative affectivity. This study examined the relationship between Type D personality and insomnia symptoms amongst a sample of the general-population.
METHODS: Adults from the general-population (n = 392) completed online measures of Type D personality (DS14) and insomnia severity.
RESULTS: Individuals with the Type D personality trait reported significantly greater symptoms of insomnia relative to Non-Type Ds. Moreover, insomnia-symptoms were independently related to negative affectivity (NA) and social inhibition (SI) and the Type D interaction (i.e. synergistic product of SI and NA). Linear regression analysis determined that NA but not SI significantly predicted insomnia symptoms after controlling for age and sex. However, after accounting for the Type D interaction, negative affectivity remained the only significant predictor of insomnia-symptoms.
CONCLUSIONS: The Type D personality type appears to be related to insomnia-symptoms, both as a categorical and dimensional construct. These outcomes support prior research evidencing that whilst Type D personality is related to poor sleep in adolescents, NA appears to be the main contributor.
Fulltext Genetic Signatures of Positive Selection in Human Populations Adapted to High Altitude in Papua New Guinea

González-Buenfil R, Vieyra-Sánchez S, Quinto-Cortés CD, Oppenheimer SJ, Pomat W, Laman M, et al.

Genome Biol Evol, 2024 Aug 05;16(8).
PMID: 39173139 DOI: 10.1093/gbe/evae161

Papua New Guinea (PNG) hosts distinct environments mainly represented by the ecoregions of the Highlands and Lowlands that display increased altitude and a predominance of pathogens, respectively. Since its initial peopling approximately 50,000 years ago, inhabitants of these ecoregions might have differentially adapted to the environmental pressures exerted by each of them. However, the genetic basis of adaptation in populations from these areas remains understudied. Here, we investigated signals of positive selection in 62 highlanders and 43 lowlanders across 14 locations in the main island of PNG using whole-genome genotype data from the Oceanian Genome Variation Project (OGVP) and searched for signals of positive selection through population differentiation and haplotype-based selection scans. Additionally, we performed archaic ancestry estimation to detect selection signals in highlanders within introgressed regions of the genome. Among highland populations we identified candidate genes representing known biomarkers for mountain sickness (SAA4, SAA1, PRDX1, LDHA) as well as candidate genes of the Notch signaling pathway (PSEN1, NUMB, RBPJ, MAML3), a novel proposed pathway for high altitude adaptation in multiple organisms. We also identified candidate genes involved in oxidative stress, inflammation, and angiogenesis, processes inducible by hypoxia, as well as in components of the eye lens and the immune response. In contrast, candidate genes in the lowlands are mainly related to the immune response (HLA-DQB1, HLA-DQA2, TAAR6, TAAR9, TAAR8, RNASE4, RNASE6, ANG). Moreover, we find two candidate regions to be also enriched with archaic introgressed segments, suggesting that archaic admixture has played a role in the local adaptation of PNG populations.
Mammographic density assessed on paired raw and processed digital images and on paired screen-film and digital images across three mammography systems

Burton A, Byrnes G, Stone J, Tamimi RM, Heine J, Vachon C, et al.

Breast Cancer Res, 2016 12 19;18(1):130.
PMID: 27993168

BACKGROUND: Inter-women and intra-women comparisons of mammographic density (MD) are needed in research, clinical and screening applications; however, MD measurements are influenced by mammography modality (screen film/digital) and digital image format (raw/processed). We aimed to examine differences in MD assessed on these image types.
METHODS: We obtained 1294 pairs of images saved in both raw and processed formats from Hologic and General Electric (GE) direct digital systems and a Fuji computed radiography (CR) system, and 128 screen-film and processed CR-digital pairs from consecutive screening rounds. Four readers performed Cumulus-based MD measurements (n = 3441), with each image pair read by the same reader. Multi-level models of square-root percent MD were fitted, with a random intercept for woman, to estimate processed-raw MD differences.
RESULTS: Breast area did not differ in processed images compared with that in raw images, but the percent MD was higher, due to a larger dense area (median 28.5 and 25.4 cm2 respectively, mean √dense area difference 0.44 cm (95% CI: 0.36, 0.52)). This difference in √dense area was significant for direct digital systems (Hologic 0.50 cm (95% CI: 0.39, 0.61), GE 0.56 cm (95% CI: 0.42, 0.69)) but not for Fuji CR (0.06 cm (95% CI: -0.10, 0.23)). Additionally, within each system, reader-specific differences varied in magnitude and direction (p
Fulltext International Consortium on Mammographic Density: Methodology and population diversity captured across 22 countries

McCormack VA, Burton A, dos-Santos-Silva I, Hipwell JH, Dickens C, Salem D, et al.

Cancer Epidemiol, 2016 Feb;40:141-51.
PMID: 26724463 DOI: 10.1016/j.canep.2015.11.015

Mammographic density (MD) is a quantitative trait, measurable in all women, and is among the strongest markers of breast cancer risk. The population-based epidemiology of MD has revealed genetic, lifestyle and societal/environmental determinants, but studies have largely been conducted in women with similar westernized lifestyles living in countries with high breast cancer incidence rates. To benefit from the heterogeneity in risk factors and their combinations worldwide, we created an International Consortium on Mammographic Density (ICMD) to pool individual-level epidemiological and MD data from general population studies worldwide. ICMD aims to characterize determinants of MD more precisely, and to evaluate whether they are consistent across populations worldwide. We included 11755 women, from 27 studies in 22 countries, on whom individual-level risk factor data were pooled and original mammographic images were re-read for ICMD to obtain standardized comparable MD data. In the present article, we present (i) the rationale for this consortium; (ii) characteristics of the studies and women included; and (iii) study methodology to obtain comparable MD data from original re-read films. We also highlight the risk factor heterogeneity captured by such an effort and, thus, the unique insight the pooled study promises to offer through wider exposure ranges, different confounding structures and enhanced power for sub-group analyses.
Fulltext Mammographic density and ageing: A collaborative pooled analysis of cross-sectional data from 22 countries worldwide

Burton A, Maskarinec G, Perez-Gomez B, Vachon C, Miao H, Lajous M, et al.

PLoS Med, 2017 Jun;14(6):e1002335.
PMID: 28666001 DOI: 10.1371/journal.pmed.1002335

BACKGROUND: Mammographic density (MD) is one of the strongest breast cancer risk factors. Its age-related characteristics have been studied in women in western countries, but whether these associations apply to women worldwide is not known.
METHODS AND FINDINGS: We examined cross-sectional differences in MD by age and menopausal status in over 11,000 breast-cancer-free women aged 35-85 years, from 40 ethnicity- and location-specific population groups across 22 countries in the International Consortium on Mammographic Density (ICMD). MD was read centrally using a quantitative method (Cumulus) and its square-root metrics were analysed using meta-analysis of group-level estimates and linear regression models of pooled data, adjusted for body mass index, reproductive factors, mammogram view, image type, and reader. In all, 4,534 women were premenopausal, and 6,481 postmenopausal, at the time of mammography. A large age-adjusted difference in percent MD (PD) between post- and premenopausal women was apparent (-0.46 cm [95% CI: -0.53, -0.39]) and appeared greater in women with lower breast cancer risk profiles; variation across population groups due to heterogeneity (I2) was 16.5%. Among premenopausal women, the √PD difference per 10-year increase in age was -0.24 cm (95% CI: -0.34, -0.14; I2 = 30%), reflecting a compositional change (lower dense area and higher non-dense area, with no difference in breast area). In postmenopausal women, the corresponding difference in √PD (-0.38 cm [95% CI: -0.44, -0.33]; I2 = 30%) was additionally driven by increasing breast area. The study is limited by different mammography systems and its cross-sectional rather than longitudinal nature.
CONCLUSIONS: Declines in MD with increasing age are present premenopausally, continue postmenopausally, and are most pronounced over the menopausal transition. These effects were highly consistent across diverse groups of women worldwide, suggesting that they result from an intrinsic biological, likely hormonal, mechanism common to women. If cumulative breast density is a key determinant of breast cancer risk, younger ages may be the more critical periods for lifestyle modifications aimed at breast density and breast cancer risk reduction.