Early Life Residence, Fish Consumption, and Risk of Breast Cancer.

Neðst á síðunni er hægt að nálgast greinina í heild sinni með því að smella á hlekkinn View/Open To access publisher's full text version of this article click on the hyperlink at the bottom of the pageBackground: Little is known about fish intake throughout the life course and the risk of breast cancer.Methods: We used data on the first residence of 9,340 women born 1908 to 1935 in the Reykjavik Study as well as food frequency data for different periods of life from a subgroup of the cohort entering the Age, Gene/Environment Susceptibility (AGES)-Reykjavik Study (n = 2,882).Results: During a mean follow-up of 27.3 years, 744 women were diagnosed with breast cancer in the Reykjavik Study. An inverse association of breast cancer was observed among women who lived through the puberty period in coastal villages, compared with women residing in the capital area [HR, 0.78; 95% confidence interval (CI), 0.61-0.99]. In the subgroup analysis of this Icelandic population, generally characterized by high fish intake, we found an indication of lower risk of breast cancer among women with high fish consumption (more than 4 portions per week) in adolescence (HR, 0.71; 95% CI, 0.44-1.13) and midlife (HR, 0.46; 95% CI, 0.22-0.97), compared with low consumers (2 portions per week or less). No association was found for fish liver oil consumption in any time period, which could be due to lack of a reference group with low omega-3 fatty acids intake in the study group.Conclusions: Our findings suggest that very high fish consumption in early to midlife may be associated with a reduced risk of breast cancer.Impact: Very high fish consumption in early adulthood to midlife may be associated with decreased risk of breast cancer. Cancer Epidemiol Biomarkers Prev; 26(3); 346-54. ©2016 AACR.NIH Intramural Research Program of the National Institute on Aging Icelandic Heart Association Icelandic Parliament Icelandic Centre for Research, RANNIS Public Health Fund of the Icelandic Directorate of Healt

Antihypertensive medication uses and serum ACE2 levels

The current coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is associated with major respiratory failure where the old and those with an underlying chronic disease are at highest risk of mortality1. Several factors have been proposed that may be underlying the higher mortality rates in these high-risk groups. The most frequent comorbidities associated with COVID-19 related mortality are clinical hypertension and type 2 diabetes (T2D)2,3. Although lower survival can simply be attributed to the frailty of this population, it has been suggested that administration of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) may affect the susceptibility to COVID-19 related outcomes by upregulating ACE24. It is well known that ACE2 is the cellular receptor that COVID-19 and other SARS coronaviruses bind to for entering the host cell5

Coding and regulatory variants are associated with serum protein levels and disease.

Circulating proteins can be used to diagnose and predict disease-related outcomes. A deep serum proteome survey recently revealed close associations between serum protein networks and common disease. In the current study, 54,469 low-frequency and common exome-array variants were compared to 4782 protein measurements in the serum of 5343 individuals from the AGES Reykjavik cohort. This analysis identifies a large number of serum proteins with genetic signatures overlapping those of many diseases. More specifically, using a study-wide significance threshold, we find that 2021 independent exome array variants are associated with serum levels of 1942 proteins. These variants reside in genetic loci shared by hundreds of complex disease traits, highlighting serum proteins' emerging role as biomarkers and potential causative agents of a wide range of diseases

Drug-gene interactions of antihypertensive medications and risk of incident cardiovascular disease: a pharmacogenomics study from the CHARGE consortium

Background Hypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals. Methods Using a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk of major cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regression models to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases). Results Although drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (Pinteraction > 5.0×10−8). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genome-wide association studies (Pinteraction ≥ 0.01). Our results suggest that there are no major pharmacogenetic influences of common SNPs on the relationship between blood pressure medications and the risk of incident CVD

Best Practices and Joint Calling of the HumanExome BeadChip: The CHARGE Consortium

Genotyping arrays are a cost effective approach when typing previously-identified genetic polymorphisms in large numbers of samples. One limitation of genotyping arrays with rare variants (e.g., minor allele frequency [MAF] <0.01) is the difficulty that automated clustering algorithms have to accurately detect and assign genotype calls. Combining intensity data from large numbers of samples may increase the ability to accurately call the genotypes of rare variants. Approximately 62,000 ethnically diverse samples from eleven Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium cohorts were genotyped with the Illumina HumanExome BeadChip across seven genotyping centers. The raw data files for the samples were assembled into a single project for joint calling. To assess the quality of the joint calling, concordance of genotypes in a subset of individuals having both exome chip and exome sequence data was analyzed. After exclusion of low performing SNPs on the exome chip and non-overlap of SNPs derived from sequence data, genotypes of 185,119 variants (11,356 were monomorphic) were compared in 530 individuals that had whole exome sequence data. A total of 98,113,070 pairs of genotypes were tested and 99.77% were concordant, 0.14% had missing data, and 0.09% were discordant. We report that joint calling allows the ability to accurately genotype rare variation using array technology when large sample sizes are available and best practices are followed. The cluster file from this experiment is available at www.chargeconsortium.com/main/exomechip

Coding and regulatory variants are associated with serum protein levels and disease.

Circulating proteins can be used to diagnose and predict disease-related outcomes. A deep serum proteome survey recently revealed close associations between serum protein networks and common disease. In the current study, 54,469 low-frequency and common exome-array variants were compared to 4782 protein measurements in the serum of 5343 individuals from the AGES Reykjavik cohort. This analysis identifies a large number of serum proteins with genetic signatures overlapping those of many diseases. More specifically, using a study-wide significance threshold, we find that 2021 independent exome array variants are associated with serum levels of 1942 proteins. These variants reside in genetic loci shared by hundreds of complex disease traits, highlighting serum proteins' emerging role as biomarkers and potential causative agents of a wide range of diseases

ATP5H/KCTD2 locus is associated with Alzheimer's disease risk

To identify loci associated with Alzheimer disease, we conducted a three-stage analysis using existing genome-wide association studies (GWAS) and genotyping in a new sample. In Stage I, all suggestive single-nucleotide polymorphisms (at P<0.001) in a previously reported GWAS of seven independent studies (8082 Alzheimer's disease (AD) cases; 12 040 controls) were selected, and in Stage II these were examined in an in silico analysis within the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium GWAS (1367 cases and 12904 controls). Six novel signals reaching P<5 × 10-6 were genotyped in an independent Stage III sample (the Fundació ACE data set) of 2200 sporadic AD patients and 2301 controls. We identified a novel association with AD in the adenosine triphosphate (ATP) synthase, H+ transporting, mitochondrial F0 (ATP5H)/Potassium channel tetramerization domain-containing protein 2 (KCTD2) locus, which reached genome-wide significance in the combined discovery and genotyping sample (rs11870474, odds ratio (OR)=1.58, P=2.6 × 10 -7 in discovery and OR=1.43, P=0.004 in Fundació ACE data set; combined OR=1.53, P=4.7 × 10 -9). This ATP5H/KCTD2 locus has an important function in mitochondrial energy production and neuronal hyperpolarization during cellular stress conditions, such as hypoxia or glucose deprivation