Biology subjects

Eliassen, A. H.

Publications and source records attributed to Eliassen, A. H..

6 recordsLinked to original sources

bioRxiv2022

Plasma and ovarian metabolomics responses to chronic stress in female mice

BackgroundChronic stress may affect metabolism of amino acids, lipids, and other small molecule metabolites, but these alterations may differ depending on tissue evaluated. We examined metabolomic changes in plasma and ovarian tissue samples from female mice due to chronic stress exposure. MethodsAt 12 weeks old, healthy, female, C57 black mice were randomly assigned to three weeks of chronic stress using daily restraint (2 hours/day; n=9) or normal care (n=10). Metabolomic profiling was conducted on plasma and ovarian tissues. Using the Wilcoxon Rank Test, Metabolite Set Enrichment Analysis, and Differential Network Analysis we identified metabolomic alterations occurring in response to restraint stress. All p-values were corrected for multiple testing using the false discovery rate approach. ResultsIn plasma, individual lysophosphatidylcholines (positively) and the metabolite classes carnitines (positively), diacylglycerols and triacylglycerols (inversely) were associated with restraint stress (adjusted-ps<0.2). In contrast, diacylglycerols and triacylglycerols were increased while carnitines were decreased in ovarian tissue from stressed mice (adjusted-ps<0.2). However, several metabolites (cholesteryl esters, phosphatidylcholines/ phosphatidylethanolamines plasmalogens and multiple amino acids) were consistently inversely associated with restraint stress in plasma and ovarian tissue (adjusted-ps<0.2). ConclusionWe identified differences in multiple lipid and amino acid metabolites in plasma and ovarian tissue of female mice after exposure to chronic stress. Some affected metabolites (primarily triacylglycerols and diacylglycerols) exhibited opposite associations with chronic stress in plasma (a marker of systemic influences) versus in ovarian tissue (representing local changes), suggesting research to understand the biological impact of chronic stress needs to consider both systemic and tissue-specific alterations.

animal behavior and cognition↗

bioRxiv2021

Rare copy number variants (CNVs) and breast cancer risk

BackgroundCopy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data. ResultsGene burden tests detected the strongest association for deletions in BRCA1 (P= 3.7E-18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P= 0.0008), ATM (P= 0.002) and BRCA2 (P= 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci. ConclusionsThis is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance.

genetics↗

bioRxiv2020

S-nitrosylated and non-nitrosylated COX2 has differential expression and distinct subcellular localization in normal and breast cancer tissue

Immunohistochemical staining in breast cancer shows both gain and loss of COX2 expression with disease risk and progression. We investigated four common COX2 antibody clones and found high specificity for purified human COX2 for three clones; however, recognition of COX2 in cell lysates was clone dependent. Biochemical characterization revealed two distinct forms of COX2, with SP21 recognizing an S-nitrosylated form and CX229 and CX294 appearing to recognize the same non-nitrosylated COX2 antigen. We found S-nitrosylated and non-nitrosylated COX2 occupy different subcellular locations in normal and breast cancer tissue, implicating distinct synthetic/trafficking pathways and function. Dual stains of ~2000 breast cancer cases show early onset breast cancer has increased expression of both forms of COX2 compared to postmenopausal cases. Our results highlight the strengths of using multiple, highly characterized antibody clones for COX2 immunohistochemical studies and raise the prospect that S-nitrosylation of COX2 may play a role in breast cancer biology.

cancer biology↗

bioRxiv2019

A prospective analysis of circulating plasma metabolomics and ovarian cancer risk

We assessed the association of pre-diagnostic plasma metabolites (N=420) with ovarian cancer risk. We included 252 cases and 252 matched controls from the Nurses Health Studies. Multivariable logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) comparing the 90th-10th percentile in metabolite levels, using permutation tests to account for testing multiple correlated hypotheses. Weighted gene co-expression network analysis (WGCNA) modules (n=10) and metabolite set enrichment analysis (MSEA; n=23) were also evaluated. Pseudouridine had the strongest statistical association with ovarian cancer risk overall (OR=2.56, 95%CI=1.48-4.45; p=0.001/adjusted-p=0.15). C36:2 phosphatidylcholine (PC) plasmalogen had the strongest statistical association with lower risk (OR=0.11, 95%CI=0.03-0.35; p<0.001/adjusted-p=0.06) and pseudouridine with higher risk (OR=9.84, 95%CI=2.89-37.82; p<0.001/adjusted-p=0.07) of non-serous tumors. Seven WGCNA modules and 15 classes were associated with risk at FDR[≤]0.20. Triacylglycerols (TAGs) showed heterogeneity by tumor aggressiveness (case-only heterogeneity-p<0.0001). TAG association with risk overall and serous tumors differed by acyl carbon content and saturation. Pseudouridine may be a novel risk factor for ovarian cancer. TAGs may also be important, particularly for rapidly fatal tumors, with associations differing by structural features. Validation in independent prospective studies and complementary experimental work to understand biological mechanisms is needed.

epidemiology↗

bioRxiv2019

Circulating Lysophosphatidylcholines, Phosphatidylcholines, Ceramides, and Sphingomyelins and Ovarian Cancer Risk: a 23-year Prospective Study

BackgroundExperimental evidence supports a role of lipid dysregulation in ovarian cancer progression and metastasis. We estimated associations with ovarian cancer risk for circulating levels of four lipid groups measured 3-23 years before diagnosis.\n\nMethodsAnalyses were conducted among cases (N = 252) and matched controls (N = 252) from the Nurses Health Studies. We used logistic regression adjusting for risk factors to investigate associations of lysophosphatidylcholines (LPC), phosphatidylcholines (PC), ceramides (CER), and sphingomyelins (SM) with ovarian cancer risk overall and by histotype. A Bonferroni adjusted p-value threshold of 0.0125 (0.05/4; 4 measured lipid groups) was used to evaluate statistical significance. Odds ratios (OR; 10th to the 90th percentile) and 95% confidence intervals of ovarian cancer risk were estimated.\n\nResultsC16:0 SM, C18:0 SM, C16:0 CER and SM sum were significantly positively associated with ovarian cancer risk, with ORs ranging from 1.95-2.10, with stronger ORs for postmenopausal women (2.02-3.22). ORs were generally similar for serous/poorly differentiated and endometrioid/clear cell tumors, although most did not meet the Bonferroni-adjusted p-value for significance. C18:1 LPC and the ratio of LPC to PC were significantly inversely, while C18:0 SM was significantly positively, associated with risk of endometrioid/clear cell tumors.\n\nConclusionElevated levels of circulating SMs 3-23 years before diagnosis were associated with increased risk of ovarian cancer, regardless of histotype, with stronger associations among postmenopausal women. Prospective and experimental studies are required to validate our findings and understand the role of lipid dysregulation, SMs in particular, in ovarian carcinogenesis.

epidemiology↗

bioRxiv2018

Genome-wide association study of anti-Mullerian hormone levels in pre-menopausal women of late reproductive age and relationship with genetic determinants of reproductive lifespan

Anti-Mullerian hormone (AMH) is required for sexual differentiation in the fetus, and in adult females AMH is produced by growing ovarian follicles. Consequently, AMH levels are correlated with ovarian reserve, declining towards menopause when the oocyte pool is exhausted. A previous genome-wide association study identified three genetic variants in and around the AMH gene that explained 25% of variation in AMH levels in adolescent males but did not identify any genetic associations reaching genome-wide significance in adolescent females. To explore the role of genetic variation in determining AMH levels in women of late reproductive age, we carried out a genome-wide meta-analysis in 3,344 pre-menopausal women from five cohorts (median age 44-48 years at blood draw). A single genetic variant, rs16991615, previously associated with age at menopause, reached genome-wide significance at P=3.48x10-10, with a per allele difference in age-adjusted inverse normal AMH of 0.26 SD (95% CI [0.18,0.34]). We investigated whether genetic determinants of female reproductive lifespan were more generally associated with pre-menopausal AMH levels. Genetically-predicted age at menarche had no robust association but genetically-predicted age at menopause was associated with lower AMH levels by 0.18 SD (95% CI [0.14,0.21]) in age-adjusted inverse normal AMH per one-year earlier age at menopause. Our findings support the hypothesis that AMH is a valid measure of ovarian reserve in pre-menopausal women and suggest that the underlying biology of ovarian reserve results in a causal link between pre-menopausal AMH levels and menopause timing.

genomics↗