A new statistical method for curve group analysis of longitudinal gene expression data illustrated for breast cancer in the NOWAC postgenome cohort as a proof of principle

International audienceA new statistical method for curve group analysis of longitudinal gene expression data illustrated for breast cancer in the NOWAC postgenome cohort as a proof of principle Abstract Background: The understanding of changes in temporal processes related to human carcinogenesis is limited. One approach for prospective functional genomic studies is to compile trajectories of differential expression of genes, based on measurements from many case-control pairs. We propose a new statistical method that does not assume any parametric shape for the gene trajectories. Methods: The trajectory of a gene is defined as the curve representing the changes in gene expression levels in the blood as a function of time to cancer diagnosis. In a nested case–control design it consists of differences in gene expression levels between cases and controls. Genes can be grouped into curve groups, each curve group corresponding to genes with a similar development over time. The proposed new statistical approach is based on a set of hypothesis testing that can determine whether or not there is development in gene expression levels over time, and whether this development varies among different strata. Curve group analysis may reveal significant differences in gene expression levels over time among the different strata considered. This new method was applied as a " proof of concept " to breast cancer in the Norwegian Women and Cancer (NOWAC) postgenome cohort, using blood samples collected prospectively that were specifically preserved for transcriptomic analyses (PAX tube). Cohort members diagnosed with invasive breast cancer through 2009 were identified through linkage to the Cancer Registry of Norway, and for each case a random control from the postgenome cohort was also selected, matched by birth year and time of blood sampling, to create a case-control pair. After exclusions, 441 case-control pairs were available for analyses, in which we considered strata of lymph node status at time of diagnosis and time of diagnosis with respect to breast cancer screening visits. Results: The development of gene expression levels in the NOWAC postgenome cohort varied in the last years before breast cancer diagnosis, and this development differed by lymph node status and participation in the Norwegian Breast Cancer Screening Program. The differences among the investigated strata appeared larger in the year before breast cancer diagnosis compared to earlier years.ConclusionsThis approach shows good properties in term of statistical power and type 1 error under minimal assumptions. When applied to a real data set it was able to discriminate between groups of genes with non-linear similar patterns before diagnosis

Genome-Wide Transcriptome Differences Associated with Perceived Discrimination in an Urban, Community-Dwelling Middle-Aged Cohort

Discrimination is a social adversity that is linked to several age-related outcomes. However, the molecular drivers of these observations are poorly understood. Social adverse factors are associated with proinflammatory and interferon gene expression, but little is known about whether additional genes are associated with discrimination among both African American and White adults. In this study, we examined how perceived discrimination in African American and White adults was associated with genome-wide transcriptome differences using RNA sequencing. Perceived discrimination was measured based on responses to self-reported lifetime discrimination and racial discrimination. Differential gene expression and pathway analysis were conducted in a cohort (N = 59) stratified by race, sex, and overall discrimination level. We found 28 significantly differentially expressed genes associated with race among those reporting high discrimination. Several of the upregulated genes for African American versus White adults reporting discrimination were related to immune function IGLV2-11, S100B, IGKV3-20, and IGKV4-1; the most significantly downregulated genes were associated with immune modulation and cancer, LUCAT1, THBS1, and ARPIN. The most enriched gene ontology biological process between African American and White men reporting high discrimination was the regulation of cytokine biosynthetic processes. The immune response biological process was significantly lower for African American women compared to White women reporting high discrimination. Discrimination was associated with the expression of small nucleolar RNAs, long noncoding RNAs, and microRNAs associated with energy homeostasis, cancer, and actin. Understanding the pathways through which adverse social factors like discrimination are associated with gene expression is crucial in advancing knowledge of age-related health disparities

Overdiagnosis of breast cancer in the Norwegian Breast Cancer Screening Program estimated by the Norwegian Women and Cancer cohort study

Background: There is increasing ambiguity towards national mammographic screening programs due to varying publicized estimates of overdiagnosis, i.e., breast cancer that would not have been diagnosed in the women’s lifetime outside screening. This analysis compares the cumulative incidence of breast cancer in screened and unscreened women in Norway from the start of the fully implemented Norwegian Breast Cancer Screening Program (NBCSP) in 2005. Methods: Subjects were 53 363 women in the Norwegian Women and Cancer (NOWAC) study, aged 52–79 years, with follow-up through 2010. Mammogram and breast cancer risk factor information were taken from the most recent questionnaire (2002–07) before the start of individual follow-up. The analysis differentiated screening into incidence (52–69 years) and post screening (70–79 years). Relative risks (RR) were estimated by Poisson regression. Results: The analysis failed to detect a significantly increased cumulative incidence rate in screened versus other women 52–79 years. RR of breast cancer among women outside the NBCSP, the “control group”, was non-significantly reduced by 7% (RR = 0∙93; 95% confidence interval 0∙79 to 1∙10) compared to those in the program. The RR was attenuated when adjusted for risk factors; RRadj = 0∙97 (0∙82 to 1∙15). The control group consisted of two subpopulations, those who only had a mammogram outside the program (RRadj =1∙04; 0∙86 to 1∙26) and those who never had a mammogram (RRadj= 0∙77; 0∙59 to 1∙01). These groups differed significantly with respect to risk factors for breast cancer, partly as a consequence of the prescription rules for hormone therapy which indicate a mammogram. Conclusions: In the fully implemented NBCSP, no significant difference was found in cumulative incidence rates of breast cancer between NOWAC women screened and not screened. Naïve comparisons of screened and unscreened women may be affected by important differences in risk factors. The current challenge for the screening program is to improve the diagnostics used at prevalence screenings (ages 50–51)

Validity of self-reported body mass index among middle-aged participants in the Norwegian Women and Cancer study

Background: Body mass index (BMI) based on self-reported height and weight has been criticized as being biased because of an observed tendency for overweight and obese people to overestimate height and underestimate weight, resulting in higher misclassification for these groups. We examined the validity of BMI based on self-reported values in a sample of Norwegian women aged 44–64 years. Methods: The study sample of 1,837 participants in the Norwegian Women and Cancer study self-reported height and weight, and then, within 1 year, either self-reported anthropometric again, or were measured by medical staff. Demographic and anthropometric were compared using t-tests and chi-square tests of independence. Misclassification of BMI categories was assessed by weighted Cohen’s kappa and Bland–Altman plot. Results: On average, the two measurements were taken 8 months apart, and self-reported weight increased by 0.6 kg (P,0.05), and BMI by 0.2 kg/m2 (P,0.05). The distribution of BMI categories did not differ between self-reported and measured values. There was substantial agreement between self-reported values and those measured by medical staff (weighted kappa 0.73). Under-reporting resulting in misclassification of BMI category was most common among overweight women (36%), but the highest proportion of extreme under-reporting was found in obese women (18% outside the 95% limits of agreement). The cumulative distribution curves for the measured and self-reported values closely followed each other, but measurements by medical staff were shifted slightly toward higher BMI values. Conclusion: While there was substantial agreement between self-reported and measured BMI values, there was small but statistically significant under-reporting of weight and thus self-reported BMI. The tendency to under-report was largest among overweight women, while the largest degree of under-reporting was found in the obese group. Self-reported weight and height provide a valid ranking of BMI for middle-aged Norwegian women

Race, Neighborhood Economic Status, Income Inequality and Mortality

<div><p>Mortality rates in the United States vary based on race, individual economic status and neighborhood. Correlations among these variables in most urban areas have limited what conclusions can be drawn from existing research. Our study employs a unique factorial design of race, sex, age and individual poverty status, measuring time to death as an objective measure of health, and including both neighborhood economic status and income inequality for a sample of middle-aged urban-dwelling adults (N = 3675). At enrollment, African American and White participants lived in 46 unique census tracts in Baltimore, Maryland, which varied in neighborhood economic status and degree of income inequality. A Cox regression model for 9-year mortality identified a three-way interaction among sex, race and individual poverty status (p = 0.03), with African American men living below poverty having the highest mortality. Neighborhood economic status, whether measured by a composite index or simply median household income, was negatively associated with overall mortality (p<0.001). Neighborhood income inequality was associated with mortality through an interaction with individual poverty status (p = 0.04). While racial and economic disparities in mortality are well known, this study suggests that several social conditions associated with health may unequally affect African American men in poverty in the United States. Beyond these individual factors are the influences of neighborhood economic status and income inequality, which may be affected by a history of residential segregation. The significant association of neighborhood economic status and income inequality with mortality beyond the synergistic combination of sex, race and individual poverty status suggests the long-term importance of small area influence on overall mortality.</p></div

Multivariable Cox Regression Analysis on Overall Mortality, Healthy Aging in Neighborhoods of Diversity across the Life Span Study, Baltimore, Maryland, 2004–2013 (N = 3675).

Multivariable Cox Regression Analysis on Overall Mortality, Healthy Aging in Neighborhoods of Diversity across the Life Span Study, Baltimore, Maryland, 2004–2013 (N = 3675).</p