Knowledge of genetics and its implications for human health is rapidly evolving in accordance with recent events, such as discoveries of large numbers of disease susceptibility loci from genome-wide ...association studies, the US Supreme Court ruling of the non-patentability of human genes, and the development of a regulatory framework for commercial genetic tests. In anticipation of the increasing relevance of genetic testing for the assessment of disease risks, this Review provides a summary of the methodologies used for building, evaluating and applying risk prediction models that include information from genetic testing and environmental risk factors. Potential applications of models for primary and secondary disease prevention are illustrated through several case studies, and future challenges and opportunities are discussed.
The relationship between germline genetic variation and breast cancer survival is largely unknown, especially in understudied minority populations who often have poorer survival. Genome-wide ...association studies (GWAS) have interrogated breast cancer survival but often are underpowered due to subtype heterogeneity and clinical covariates and detect loci in non-coding regions that are difficult to interpret. Transcriptome-wide association studies (TWAS) show increased power in detecting functionally relevant loci by leveraging expression quantitative trait loci (eQTLs) from external reference panels in relevant tissues. However, ancestry- or race-specific reference panels may be needed to draw correct inference in ancestrally diverse cohorts. Such panels for breast cancer are lacking.
We provide a framework for TWAS for breast cancer in diverse populations, using data from the Carolina Breast Cancer Study (CBCS), a population-based cohort that oversampled black women. We perform eQTL analysis for 406 breast cancer-related genes to train race-stratified predictive models of tumor expression from germline genotypes. Using these models, we impute expression in independent data from CBCS and TCGA, accounting for sampling variability in assessing performance. These models are not applicable across race, and their predictive performance varies across tumor subtype. Within CBCS (N = 3,828), at a false discovery-adjusted significance of 0.10 and stratifying for race, we identify associations in black women near AURKA, CAPN13, PIK3CA, and SERPINB5 via TWAS that are underpowered in GWAS.
We show that carefully implemented and thoroughly validated TWAS is an efficient approach for understanding the genetics underpinning breast cancer outcomes in diverse populations.
Summary Background DNA hypomethylation has been suggested to cause genomic instability and increase cancer risk. We aimed to test the hypothesis that DNA hypomethylation is associated with increased ...risk of bladder cancer. Methods We measured cytosine methylation (5-mC) content in genomic DNA from blood cells from patients with bladder cancer enrolled in a large case–control study in Spain between Jan 1, 1998, and Dec 31, 2001. Cases were men and women with newly diagnosed and histologically confirmed urothelial carcinoma of the bladder. Controls were selected from patients admitted to the same hospital for diseases or conditions unrelated to smoking or other known risk factors for bladder cancer. Controls were individually matched to cases on age (within 5 years), sex, race, and area of hospital referral. 5-mC content was measured in leucocyte DNA by use of a combination of high-performance capillary electrophoresis, Hpa II digestion, and densitometry. Data on demographics, 34 polymorphisms in nine folate metabolism genes, and nutritional intake of six B vitamins (including folate), alcohol, and smoking were assessed as potential confounders. Relative 5-mC content was expressed as a percentage (%5-mC) with respect to the total cytosine content (the sum of methylated and non-methylated cytosines). The primary endpoint was median %5-mC DNA content. Findings %5-mC was measured in leucocyte DNA from 775 cases and 397 controls. Median %5-mC DNA was significantly lower in cases (3·03% IQR 2·17–3·56) than in controls (3·19% 2·46–3·68, p=0·0002). All participants were subsequently categorised into quartiles by %5-mC content in controls. When the highest quartile of %5-mC content was used as the reference category (Q4), the following adjusted odds ratios (OR) and 95% CI were recorded for decreasing methylation quartiles: OR(Q3) 2·05 (95% CI 1·37–3·06); OR(Q2) 1·62 (1·07–2·44); and OR(Q1) 2·67 (1·77–4·03), p for trend <0·0001. The lowest cancer risk was noted in never smokers in the highest methylation quartile (never smokers in Q4). By comparison with never smokers in the highest quartile, current smokers in the lowest methylation quartile had the highest risk of bladder cancer (Q1: OR 25·51 9·61–67·76, p for interaction 0·06). In analyses stratified by smoking, hypomethylation was a strong risk factor in never smokers (OR 6·39 2·37–17·22). Amount of methylation in controls were not associated with baseline characteristics, micronutrients, or selected genotypes in folate metabolism pathways. Interpretation For the first time, to our knowledge, we have shown in a large case–control study that leucocyte DNA hypomethylation is associated with increased risk of developing bladder cancer, and this association is independent of smoking and the other assessed risk factors. Amount of global methylation in genomic DNA could provide a useful biomarker of susceptibility to certain cancer types and further research is warranted. Funding Intramural Research Program of the National Institutes of Health, National Cancer Institute, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA, and Fondo de Investigacion Sanitaria, Spain (G03/174).
Tissue-based functional genomics resources including molecular quantitative trait loci datasets lack diversity in ancestry and tissue types and thus are inadequate for comprehensively investigating ...gene regulation. Global efforts to increase the tissue diversity will help achieve more equitable medical care.
Analysis of gene expression data suggests that breast cancers are divisible into molecular subtypes which have distinct clinical
features. This study evaluates whether pathologic features and ...etiologic associations differ among molecular subtypes. We
evaluated 804 women with invasive breast cancers and 2,502 controls participating in a Polish Breast Cancer Study. Immunohistochemical
stains for estrogen receptor α, progesterone receptor, human epidermal growth factor receptors (HER2 and HER1), and cytokeratin
5 were used to classify cases into five molecular subtypes: luminal A, luminal B, HER2-expresing, basal-like, and unclassified.
Relative risks were estimated using adjusted odds ratios and 95% confidence intervals. We observed that compared with the
predominant luminal A tumors (69%), other subtypes were associated with unfavorable clinical features at diagnosis, especially
HER2-expressing (8%) and basal-like (12%) tumors. Increasing body mass index significantly reduced the risk of luminal A tumors
among premenopausal women (odds ratios, 0.71; 95% confidence intervals, 0.57-0.88 per five-unit increase), whereas it did
not reduce risk for basal-like tumors (1.18; 0.86-1.64; P heterogeneity = 0.003). On the other hand, reduced risk associated with increasing age at menarche was stronger for basal-like (0.78; 0.68-0.89
per 2-year increase) than luminal A tumors (0.90; 0.95-1.08; P heterogeneity = 0.0009). Although family history increased risk for all subtypes (except for unclassified tumors), the magnitude of the
relative risk was highest for basal-like tumors. Results from this study have shown that breast cancer risk factors may vary
by molecular subtypes identified in expression studies, suggesting etiologic, in addition to clinical, heterogeneity of breast
cancer. (Cancer Epidemiol Biomarkers Prev 2007;16(3):439–43)
Disease heterogeneity is ubiquitous in biomedical and clinical studies. In genetic studies, researchers are increasingly interested in understanding the distinct genetic underpinning of subtypes of ...diseases. However, existing set‐based analysis methods for genome‐wide association studies are either inadequate or inefficient to handle such multicategorical outcomes. In this paper, we proposed a novel set‐based association analysis method, sequence kernel association test (SKAT)‐MC, the sequence kernel association test for multicategorical outcomes (nominal or ordinal), which jointly evaluates the relationship between a set of variants (common and rare) and disease subtypes. Through comprehensive simulation studies, we showed that SKAT‐MC effectively preserves the nominal type I error rate while substantially increases the statistical power compared to existing methods under various scenarios. We applied SKAT‐MC to the Polish breast cancer study (PBCS), and identified gene FGFR2 was significantly associated with estrogen receptor (ER)+ and ER− breast cancer subtypes. We also investigated educational attainment using UK Biobank data (N
=
127
,
127 $N=127,127$) with SKAT‐MC, and identified 21 significant genes in the genome. Consequently, SKAT‐MC is a powerful and efficient analysis tool for genetic association studies with multicategorical outcomes. A freely distributed R package SKAT‐MC can be accessed at https://github.com/Zhiwen-Owen-Jiang/SKATMC.
Altered DNA methylation has been associated with various diseases.
We evaluated the association between levels of methylation in leukocyte DNA at long interspersed nuclear element 1 (LINE-1) and ...genetic and non-genetic characteristics of 892 control participants from the Spanish Bladder Cancer/EPICURO study.
We determined LINE-1 methylation levels by pyrosequencing. Individual data included demographics, smoking status, nutrient intake, toenail concentrations of 12 trace elements, xenobiotic metabolism gene variants, and 515 polymorphisms among 24 genes in the one-carbon metabolism pathway. To assess the association between LINE-1 methylation levels (percentage of methylated cytosines) and potential determinants, we estimated beta coefficients (βs) by robust linear regression.
Women had lower levels of LINE-1 methylation than men (β = -0.7, p = 0.02). Persons who smoked blond tobacco showed lower methylation than nonsmokers (β = -0.7, p = 0.03). Arsenic toenail concentration was inversely associated with LINE-1 methylation (β = -3.6, p = 0.003). By contrast, iron (β = 0.002, p = 0.009) and nickel (β = 0.02, p = 0.004) were positively associated with LINE-1 methylation. Single nucleotide polymorphisms (SNPs) in DNMT3A (rs7581217-per allele, β = 0.3, p = 0.002), TCN2 (rs9606756-GG, β = 1.9, p = 0.008; rs4820887-AA, β = 4.0, p = 4.8 × 10-7; rs9621049-TT, β = 4.2, p = 4.7 × 10-9), AS3MT (rs7085104-GG, β = 0.7, p = 0.001), SLC19A1 (rs914238, TC vs. TT: β = 0.5 and CC vs. TT: β = -0.3, global p = 0.0007) and MTHFS (rs1380642, CT vs. CC: β = 0.3 and TT vs. CC; β = -0.8, global p = 0.05) were associated with LINE-1 methylation.
We identified several characteristics, environmental factors, and common genetic variants that predicted DNA methylation among study participants.
Celotno besedilo
Dostopno za:
CEKLJ, DOBA, IZUM, KILJ, NUK, OILJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK, VSZLJ
Although racial/ethnic disparities in U.S. COVID-19 death rates are striking, focusing on COVID-19 deaths alone may underestimate the true effect of the pandemic on disparities. Excess death ...estimates capture deaths both directly and indirectly caused by COVID-19.
To estimate U.S. excess deaths by racial/ethnic group.
Surveillance study.
United States.
All decedents.
Excess deaths and excess deaths per 100 000 persons from March to December 2020 were estimated by race/ethnicity, sex, age group, and cause of death, using provisional death certificate data from the Centers for Disease Control and Prevention (CDC) and U.S. Census Bureau population estimates.
An estimated 2.88 million deaths occurred between March and December 2020. Compared with the number of expected deaths based on 2019 data, 477 200 excess deaths occurred during this period, with 74% attributed to COVID-19. Age-standardized excess deaths per 100 000 persons among Black, American Indian/Alaska Native (AI/AN), and Latino males and females were more than double those in White and Asian males and females. Non-COVID-19 excess deaths also disproportionately affected Black, AI/AN, and Latino persons. Compared with White males and females, non-COVID-19 excess deaths per 100 000 persons were 2 to 4 times higher in Black, AI/AN, and Latino males and females, including deaths due to diabetes, heart disease, cerebrovascular disease, and Alzheimer disease. Excess deaths in 2020 resulted in substantial widening of racial/ethnic disparities in all-cause mortality from 2019 to 2020.
Completeness and availability of provisional CDC data; no estimates of precision around results.
There were profound racial/ethnic disparities in excess deaths in the United States in 2020 during the COVID-19 pandemic, resulting in rapid increases in racial/ethnic disparities in all-cause mortality between 2019 and 2020.
National Institutes of Health Intramural Research Program.
The gut microbiota may play a role in breast cancer etiology by regulating hormonal, metabolic and immunologic pathways. We investigated associations of fecal bacteria with breast cancer and ...nonmalignant breast disease in a case‐control study conducted in Ghana, a country with rising breast cancer incidence and mortality. To do this, we sequenced the V4 region of the 16S rRNA gene to characterize bacteria in fecal samples collected at the time of breast biopsy (N = 379 breast cancer cases, N = 102 nonmalignant breast disease cases, N = 414 population‐based controls). We estimated associations of alpha diversity (observed amplicon sequence variants ASVs, Shannon index, and Faith's phylogenetic diversity), beta diversity (Bray‐Curtis and unweighted/weighted UniFrac distance), and the presence and relative abundance of select taxa with breast cancer and nonmalignant breast disease using multivariable unconditional polytomous logistic regression. All alpha diversity metrics were strongly, inversely associated with odds of breast cancer and for those in the highest relative to lowest tertile of observed ASVs, the odds ratio (95% confidence interval) was 0.21 (0.13‐0.36; Ptrend < .001). Alpha diversity associations were similar for nonmalignant breast disease and breast cancer grade/molecular subtype. All beta diversity distance matrices and multiple taxa with possible estrogen‐conjugating and immune‐related functions were strongly associated with breast cancer (all Ps < .001). There were no statistically significant differences between breast cancer and nonmalignant breast disease cases in any microbiota metric. In conclusion, fecal bacterial characteristics were strongly and similarly associated with breast cancer and nonmalignant breast disease. Our findings provide novel insight into potential microbially‐mediated mechanisms of breast disease.
What's new?
The gut microbiome has been shown to affect a variety of physiological systems throughout the body. These authors conducted the largest known study investigating the association of gut bacteria with breast disease in Ghana, where breast cancer incidence is rising. They sequenced the 16S rRNA gene of fecal bacteria among 895 women (N = 379 breast cancer cases, N = 102 nonmalignant breast disease cases, N = 414 population‐based controls). They found that patients with breast cancer and non‐malignant breast disease had a similar fecal microbial profile, which differed from that of controls. Microbial alpha diversity was inversely associated with odds of breast cancer and non‐malignant breast disease.
The associations of certain factors, such as age and menopausal hormone therapy, with breast cancer risk are known to differ for interval and screen-detected cancers. However, the extent to which ...associations of other established breast cancer risk factors differ by mode of detection is unclear. We investigated associations of a wide range of risk factors using data from a large UK cohort with linkage to the National Health Service Breast Screening Programme, cancer registration, and other health records. We used Cox regression to estimate adjusted relative risks (RRs) and 95% confidence intervals (CIs) for associations between risk factors and breast cancer risk. A total of 9421 screen-detected and 5166 interval cancers were diagnosed in 517,555 women who were followed for an average of 9.72 years. We observed the following differences in risk factor associations by mode of detection: greater body mass index (BMI) was associated with a smaller increased risk of interval (RR per 5 unit increase 1.07, 95% CI 1.03-1.11) than screen-detected cancer (RR 1.27, 1.23-1.30); having a first-degree family history was associated with a greater increased risk of interval (RR 1.81, 1.68-1.95) than screen-detected cancer (RR 1.52, 1.43-1.61); and having had previous breast surgery was associated with a greater increased risk of interval (RR 1.85, 1.72-1.99) than screen-detected cancer (RR 1.34, 1.26-1.42). As these differences in associations were relatively unchanged after adjustment for tumour grade, and are in line with the effects of these factors on mammographic density, they are likely to reflect the effects of these risk factors on screening sensitivity.
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