17q12‐q21 variants interact with early‐life exposures to modify asthma risk in Black children

2021 ◽  
Author(s):  
Jessica D Gereige ◽  
Andreanne Morin ◽  
Agustin Calatroni ◽  
Cynthia M Visness ◽  
Robert A Wood ◽  
...  
Keyword(s):  
Early Life ◽  
Black Children ◽  
Asthma Risk ◽  
Early Life Exposures

scholarly journals Association of a PAI-1 Gene Polymorphism and Early Life Infections with Asthma Risk, Exacerbations, and Reduced Lung Function

PLoS ONE ◽  
2016 ◽  
Vol 11 (8) ◽  
pp. e0157848 ◽  
Author(s):  
Seong H. Cho ◽  
Jin-Young Min ◽  
Dong Young Kim ◽  
Sam S. Oh ◽  
Dara R. Torgerson ◽  
...  
Keyword(s):  
Lung Function ◽  
Gene Polymorphism ◽  
Early Life ◽  
Asthma Risk ◽  
Pai 1

Early life factors as predictors of age-associated deficit accumulation across 17 years from midlife into old age

2022 ◽  
Author(s):  
Markus J Haapanen ◽  
Juulia Jylhävä ◽  
Lauri Kortelainen ◽  
Tuija M Mikkola ◽  
Minna Salonen ◽  
...  
Keyword(s):  
Old Age ◽  
Early Life ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Frailty Index ◽  
Rate Of Change ◽  
Birth Cohort Study ◽  
Maternal Body Mass Index ◽  
Early Life Factors ◽  
Early Life Exposures

Abstract Background Early life exposures have been associated with the risk of frailty in old age. We investigated whether early life exposures predict the level and rate of change in a frailty index (FI) from midlife into old age. Methods A linear mixed model analysis was performed using data from three measurement occasions over 17 years in participants from the Helsinki Birth Cohort Study (n=2000) aged 57-84 years. A 41-item FI was calculated on each occasion. Information on birth size, maternal body mass index (BMI), growth in infancy and childhood, childhood socioeconomic status (SES), and early life stress (wartime separation from both parents), was obtained from registers and healthcare records. Results At age 57 years the mean FI level was 0.186 and the FI levels increased by 0.34 percent/year from midlife into old age. Larger body size at birth associated with a slower increase in FI levels from midlife into old age. Per 1kg greater birth weight the increase in FI levels per year was -0.087 percentage points slower (95% CI=-0.163, -0.011; p=0.026). Higher maternal BMI was associated with a higher offspring FI level in midlife and a slower increase in FI levels into old age. Larger size, faster growth from infancy to childhood, and low SES in childhood were all associated with a lower FI level in midlife but not with its rate of change. Conclusions Early life factors seem to contribute to disparities in frailty from midlife into old age. Early life factors may identify groups that could benefit from frailty prevention, optimally initiated early in life.

scholarly journals Epigenetics and DOHaD: from basics to birth and beyond

2017 ◽  
Vol 8 (5) ◽  
pp. 513-519 ◽  
Author(s):  
T. Bianco-Miotto ◽  
J. M. Craig ◽  
Y. P. Gasser ◽  
S. J. van Dijk ◽  
S. E. Ozanne
Keyword(s):  
Dna Methylation ◽  
Chronic Disease ◽  
Chronic Diseases ◽  
Early Life ◽  
Later Life ◽  
Metabolic Health ◽  
Number Of Children ◽  
Early Life Environment ◽  
Increased Risk ◽  
Early Life Exposures

Developmental origins of health and disease (DOHaD) is the study of how the early life environment can impact the risk of chronic diseases from childhood to adulthood and the mechanisms involved. Epigenetic modifications such as DNA methylation, histone modifications and non-coding RNAs are involved in mediating how early life environment impacts later health. This review is a summary of the Epigenetics and DOHaD workshop held at the 2016 DOHaD Society of Australia and New Zealand Conference. Our extensive knowledge of how the early life environment impacts later risk for chronic disease would not have been possible without animal models. In this review we highlight some animal model examples that demonstrate how an adverse early life exposure results in epigenetic and gene expression changes that may contribute to increased risk of chronic disease later in life. Type 2 diabetes and cardiovascular disease are chronic diseases with an increasing incidence due to the increased number of children and adults that are obese. Epigenetic changes such as DNA methylation have been shown to be associated with metabolic health measures and potentially predict future metabolic health status. Although more difficult to elucidate in humans, recent studies suggest that DNA methylation may be one of the epigenetic mechanisms that mediates the effects of early life exposures on later life risk of obesity and obesity related diseases. Finally, we discuss the role of the microbiome and how it is a new player in developmental programming and mediating early life exposures on later risk of chronic disease.

scholarly journals The Infant Gut Resistome is Associated with E. coli and Early-life Exposures

2020 ◽  
Author(s):  
Rebecca M. Lebeaux ◽  
Modupe O. Coker ◽  
Erika F. Dade ◽  
Thomas J. Palys ◽  
Hilary G. Morrison ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Relative Risk ◽  
Relative Abundance ◽  
Gut Microbiome ◽  
Early Life ◽  
The United States ◽  
Delivery Mode ◽  
Metagenomic Sequencing ◽  
E Coli ◽  
Early Life Exposures

Abstract Background: Antibiotic resistance is an increasing threat to human health. The human gut microbiome harbors a collection of bacterial antimicrobial resistance genes (ARGs) known as the resistome. The factors associated with establishment of the resistome in early life are not well understood and clarifying these factors would inform strategies to decrease antibiotic resistance. We investigated the early-life exposures and taxonomic signatures associated with resistome development over the first year of life in a large, prospective cohort in the United States. Shotgun metagenomic sequencing was used to profile both microbial composition and ARGs in stool samples collected at 6 weeks and 1 year of age from infants enrolled in the New Hampshire Birth Cohort Study. Negative binomial regression and statistical modeling was used to examine infant factors such as sex, delivery mode, feeding method, gestational age, antibiotic exposure, and infant gut microbiome composition in relation to the diversity and relative abundance of ARGs.Results: Metagenomic sequencing was performed on paired samples from 195 full term (at least 37 weeks’ gestation) and 15 late preterm (33-36 weeks’ gestation) infants. 6-week samples compared to 1-year samples had 4.37 times (95% CI: 3.54-5.39) the rate of harboring ARGs. The majority of ARGs that were at a greater relative abundance at 6 weeks (chi-squared p < 0.01) worked through the mechanism of antibiotic efflux (i.e., by pumping antibiotics out of the cell). The overall relative abundance of the resistome was strongly correlated with Proteobacteria (Spearman correlation = 78.9%) and specifically E. coli (62.2%) relative abundance in the gut microbiome. Among infant characteristics, delivery mode was most strongly associated with the diversity and relative abundance of ARGs. Infants born via cesarean delivery had a higher risk of harboring unique ARGs [relative risk = 1.12 (95% CI: 0.97 – 1.29)] as well as a having an increased risk for overall ARG relative abundance [relative risk = 1.43 (95% CI: 1.12 – 1.84)] at 1 year compared to infants born vaginally. Additionally, 6 specific ARGs were at a greater relative abundance in infants delivered by cesarean section compared to vaginally delivered infants across both time points. Conclusions: Our findings suggest that the developing infant gut resistome may be alterable by early-life exposures. Establishing the extent to which infant characteristics and early-life exposures impact the resistome can ultimately lead to interventions that decrease the transmission of ARGs and thus the possibility of antibiotic resistant life threatening infections.

scholarly journals Do early‐life exposures explain why more advantaged children get eczema? Findings from the U.K. Millennium Cohort Study

2016 ◽  
Vol 174 (3) ◽  
pp. 569-578 ◽  
Author(s):  
D.C. Taylor‐Robinson ◽  
H. Williams ◽  
A. Pearce ◽  
C. Law ◽  
S. Hope
Keyword(s):  
Cohort Study ◽  
Early Life ◽  
Millennium Cohort Study ◽  
Early Life Exposures
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