Last data update: Jan 13, 2025. (Total: 48570 publications since 2009)
Records 1-2 (of 2 Records) |
Query Trace: Shipley M[original query] |
---|
The inflammatory response to birth requires MyD88 and is driven by both mother and offspring
Gray JM , Castillo-Ruiz A , Major KM , Shipley M , Gangappa S , Forger NG . Brain Behav Immun 2023 115 617-630 Birth is an inflammatory event for the newborn, characterized by elevations in interleukin (IL)-6, IL-10, and tumor necrosis factor (TNF)-α peripherally and/or centrally, as well as changes in brain microglia. However, the mechanism(s) underlying these responses is unknown. Toll-like receptors (TLRs) play crucial roles in innate immunity and initiate inflammatory cascades upon recognition of endogenous or exogenous antigens. Most TLR signaling depends on the adaptor molecule myeloid differentiation primary response 88 (MyD88). We independently varied MyD88 gene status in mouse dams and their offspring to determine whether the inflammatory response to birth depends on MyD88 signaling and, if so, whether that signaling occurs in the offspring, the mother, or both. We find that the perinatal surges in plasma IL-6 and brain expression of TNF-α depend solely on MyD88 gene status of the offspring, whereas postnatal increases in plasma IL-10 and TNF-α depend on MyD88 in both the pup and dam. Interestingly, MyD88 genotype of the dam primarily drives differences in offspring brain microglial density and has robust effects on developmental neuronal cell death. Milk cytokines were evaluated as a possible source of postnatal maternal influence; although we found high levels of CXCL1/GROα and several other cytokines in ingested post-partum milk, their presence did not require MyD88. Thus, the inflammatory response previously described in the late-term fetus and newborn depends on MyD88 (and, by extension, TLRs), with signaling in both the dam and offspring contributing. Unexpectedly, naturally-occuring neuronal cell death in the newborn is modulated primarily by maternal MyD88 gene status. |
Cardiovascular risk factors associated with venous thromboembolism
Gregson J , Kaptoge S , Bolton T , Pennells L , Willeit P , Burgess S , Bell S , Sweeting M , Rimm EB , Kabrhel C , Zoller B , Assmann G , Gudnason V , Folsom AR , Arndt V , Fletcher A , Norman PE , Nordestgaard BG , Kitamura A , Mahmoodi BK , Whincup PH , Knuiman M , Salomaa V , Meisinger C , Koenig W , Kavousi M , Volzke H , Cooper JA , Ninomiya T , Casiglia E , Rodriguez B , Ben-Shlomo Y , Despres JP , Simons L , Barrett-Connor E , Bjorkelund C , Notdurfter M , Kromhout D , Price J , Sutherland SE , Sundstrom J , Kauhanen J , Gallacher J , Beulens JWJ , Dankner R , Cooper C , Giampaoli S , Deen JF , Gomez de la Camara A , Kuller LH , Rosengren A , Svensson PJ , Nagel D , Crespo CJ , Brenner H , Albertorio-Diaz JR , Atkins R , Brunner EJ , Shipley M , Njolstad I , Lawlor DA , van der Schouw YT , Selmer RM , Trevisan M , Verschuren WMM , Greenland P , Wassertheil-Smoller S , Lowe GDO , Wood AM , Butterworth AS , Thompson SG , Danesh J , Di Angelantonio E , Meade T . JAMA Cardiol 2019 4 (2) 163-173 Importance: It is uncertain to what extent established cardiovascular risk factors are associated with venous thromboembolism (VTE). Objective: To estimate the associations of major cardiovascular risk factors with VTE, ie, deep vein thrombosis and pulmonary embolism. Design, Setting, and Participants: This study included individual participant data mostly from essentially population-based cohort studies from the Emerging Risk Factors Collaboration (ERFC; 731728 participants; 75 cohorts; years of baseline surveys, February 1960 to June 2008; latest date of follow-up, December 2015) and the UK Biobank (421537 participants; years of baseline surveys, March 2006 to September 2010; latest date of follow-up, February 2016). Participants without cardiovascular disease at baseline were included. Data were analyzed from June 2017 to September 2018. Exposures: A panel of several established cardiovascular risk factors. Main Outcomes and Measures: Hazard ratios (HRs) per 1-SD higher usual risk factor levels (or presence/absence). Incident fatal outcomes in ERFC (VTE, 1041; coronary heart disease [CHD], 25131) and incident fatal/nonfatal outcomes in UK Biobank (VTE, 2321; CHD, 3385). Hazard ratios were adjusted for age, sex, smoking status, diabetes, and body mass index (BMI). Results: Of the 731728 participants from the ERFC, 403396 (55.1%) were female, and the mean (SD) age at the time of the survey was 51.9 (9.0) years; of the 421537 participants from the UK Biobank, 233699 (55.4%) were female, and the mean (SD) age at the time of the survey was 56.4 (8.1) years. Risk factors for VTE included older age (ERFC: HR per decade, 2.67; 95% CI, 2.45-2.91; UK Biobank: HR, 1.81; 95% CI, 1.71-1.92), current smoking (ERFC: HR, 1.38; 95% CI, 1.20-1.58; UK Biobank: HR, 1.23; 95% CI, 1.08-1.40), and BMI (ERFC: HR per 1-SD higher BMI, 1.43; 95% CI, 1.35-1.50; UK Biobank: HR, 1.37; 95% CI, 1.32-1.41). For these factors, there were similar HRs for pulmonary embolism and deep vein thrombosis in UK Biobank (except adiposity was more strongly associated with pulmonary embolism) and similar HRs for unprovoked vs provoked VTE. Apart from adiposity, these risk factors were less strongly associated with VTE than CHD. There were inconsistent associations of VTEs with diabetes and blood pressure across ERFC and UK Biobank, and there was limited ability to study lipid and inflammation markers. Conclusions and Relevance: Older age, smoking, and adiposity were consistently associated with higher VTE risk. |
- Page last reviewed:Feb 1, 2024
- Page last updated:Jan 13, 2025
- Content source:
- Powered by CDC PHGKB Infrastructure