Using time-varying quantile regression approaches to model the influence of prenatal and infant exposures on childhood growth

<p>For many applications, it is valuable to assess whether the effects of exposures over time vary by quantiles of the outcome. We have previously shown that quantile methods complement the traditional mean-based analyses, and are useful for studies of body size. Here, we extended previous work to time-varying quantile associations. Using data from over 18,000 children in the U.S. Collaborative Perinatal Project, we investigated the impact of maternal pre-pregnancy body mass index (BMI), maternal pregnancy weight gain, placental weight, and birth weight on childhood body size measured 4 times between 3 months and 7 years, using both parametric and non-parametric time-varying quantile regressions. Using our proposed model assessment tool, we found that non-parametric models fit the childhood growth data better than the parametric approaches. We also observed that quantile analysis resulted in difference inferences than the conditional mean models in three of the four constructs (maternal per-pregancy BMI, maternal weight gain, and placental weight). Overall, these results suggest the utility of applying time-varying quantile models for longitudinal outcome data. They also suggest that in the studies of body size, merely modelling the conditional mean may lead to incomplete summary of the data.</p

Association between alcohol consumption and overall, breast cancer- specific, and non-breast cancer mortality.

<p>Association between alcohol consumption and overall, breast cancer- specific, and non-breast cancer mortality.</p

Association between alcohol consumption and overall, breast cancer- specific, and non-breast cancer mortality.

<p>Association between alcohol consumption and overall, breast cancer- specific, and non-breast cancer mortality.</p

Adjusted log hazard ratios and 95% confidence intervals for overall and non-breast cancer mortality in breast cancer survivors by age at baseline.

<p>Adjusted log hazard ratios and 95% confidence intervals for overall and non-breast cancer mortality in breast cancer survivors by age at baseline.</p

Average alcohol intake by demographic characteristics and lifestyle variables in a cohort of breast cancer survivors from the New York site of the Breast Cancer Family Registry.

<p>Average alcohol intake by demographic characteristics and lifestyle variables in a cohort of breast cancer survivors from the New York site of the Breast Cancer Family Registry.</p

Characteristics of sisters in the New York site of the BCFR.

*<p>Among ever smokers;</p><p>#HRT: Hormone replacement therapy;</p>**<p>OC: Oral contraceptive.</p

Association between characteristics of unaffected sisters (N = 335) and telomere length, New York site of the BCFR.

*<p>adjusted by age of blood donation;</p>**<p>adjusted by age of blood donation and ethnicity;</p><p>#HRT: Hormone replacement therapy;</p><p>##OC: Oral contraceptive;</p>†<p><i>p</i><0.05.</p

Breast cancer risk estimates by conditional logistic regression and GEE models in sister-sets for genotypes of telomere maintenance genes, New York site of the BCFR.

*<p>Conditional logistic regression model adjusted by age of blood donation;</p>**<p>GEE model adjusted by age of blood donation.</p

Maternal cigarette smoking during pregnancy and offspring DNA methylation in midlife

<p>Maternal smoking in pregnancy (MSP) has been associated with DNA methylation in specific CpG sites (CpGs) in infants and children. We investigated whether MSP, independent of own personal active smoking, was associated with midlife DNA methylation in CpGs that were previously identified in studies of MSP-DNA methylation in children. We used data on MSP collected from pregnant mothers of 89 adult women born in 1959–1964 and measured DNA methylation in blood (granulocytes) collected in 2001–2007 (mean age: 43 years). Seventeen CpGs were differentially methylated by MSP, with multiple CpGs mapping to <i>CYP1A1, MYO1G, AHRR</i>, and <i>GFI1</i>. These associations were consistent in direction with prior studies (e.g., MSP associated with more and less methylation in <i>AHRR</i> and <i>CYP1A1</i>, respectively) and, with the exception of <i>AHRR</i> CpGs, were not substantially altered by adjustment for active smoking. These preliminary results confirm prior prospective reports that MSP influences the offspring DNA methylation, and extends the timeframe to midlife, and suggest that these effects may persist into adulthood, independently of active smoking.</p

Associations between SNPs in 9p22.2 with ovarian cancer risk for <i>BRCA1</i> and <i>BRCA2</i> mutation carriers.

<p>In each plot, the purple diamond corresponds to the strongest associated SNP and the colour code indicates the linkage disequilibrium with respect to this variant. Horizontal lines indicate the -log₁₀ p-value such that the SNPs above the line are the potential causal ones. This set was defined based on a likelihood ratio for a particular SNP as being less or equal than 100, relative to the most likely variant and r²>0.1. (A) <i>BRCA1</i> mutation carriers, (B) <i>BRCA2</i> mutation carriers.</p