| 1. |
- Johansson, Åsa, et al.
(author)
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Investigating the Effect of Estradiol Levels on the Risk of Breast, Endometrial, and Ovarian Cancer
- 2022
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In: Journal of the Endocrine Society. - : The Endocrine Society. - 2472-1972. ; 6:8
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Journal article (peer-reviewed)abstract
- Background: High levels of estrogen are associated with increased risk of breast and endometrial cancer and have been suggested to also play a role in the development of ovarian cancer. Cancerogenic effects of estradiol, the most prominent form of estrogen, have been highlighted as a side effect of estrogen-only menopausal hormone therapy. However, whether high levels of endogenous estrogens, produced within the body, promote cancer development, has not been fully established.Objective: We aimed to examine causal effects of estradiol on breast, endometrial, and ovarian cancer.Methods: Here we performed a two-sample Mendelian randomization (MR) to estimate the effect of endogenous estradiol on the risk of developing breast, endometrial, and ovarian cancer, using the UK Biobank as well as 3 independent cancer cohorts.Results: Using 3 independent instrumental variables, we showed that higher estradiol levels significantly increase the risk for ovarian cancer (OR = 3.18 [95% CI, 1.47-6.87], P = 0.003). We also identified a nominally significant effect for ER-positive breast cancer (OR = 2.16 [95% CI, 1.09-4.26], P = 0.027). However, we could not establish a clear link to the risk of endometrial cancer (OR = 1.93 [95% CI, 0.77-4.80], P = 0.160).Conclusion: Our results suggest that high estradiol levels promote the development of ovarian and ER-positive breast cancer.
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| 2. |
- Kierczak, Marcin, 1981-, et al.
(author)
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Contribution of rare whole-genome sequencing variants to plasma protein levels and the missing heritability
- 2022
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In: Nature Communications. - : Springer Nature. - 2041-1723. ; 13
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Journal article (peer-reviewed)abstract
- Despite the success of genome-wide association studies, much of the genetic contribution to complex traits remains unexplained. Here, we analysed high coverage whole genome sequencing data, to evaluate the contribution of rare genetic variants to 414 plasma proteins. The frequency distribution of genetic variants was skewed towards the rare spectrum, and damaging variants were more often rare. We estimated that less than 4.3% of the narrow-sense heritability is expected to be explained by rare variants in our cohort. Using a gene-based approach, we identified Cis-associations for 237 of the proteins, which is slightly more compared to a GWAS (N=213), and we identified 34 loci in Trans. Several associations were driven by rare variants, and rare variants had on average larger phenotypic effects. We conclude therefore that rare variants could be of importance for precision medicine applications, but have a more limited contribution to the missing heritability of complex diseases.
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| 3. |
- Schmitz, Daniel, 1995-
(author)
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Beyond GWAS : Novel Methods and Resources for Genetic Epidemiology
- 2024
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Doctoral thesis (other academic/artistic)abstract
- Since the first human genome assembly’s release, our knowledge of the genetic architecture of complex traits and diseases has grown steadily. Genome-wide association studies (GWAS) played a major role but are limited to common traits and single-nucleotide polymorphisms (SNPs). Technologies and resources like next-generation sequencing, Mendelian Randomization (MR), long-read sequencing and improved reference genomes enable the investigation of variants inaccessible to GWAS, such as copy number variations (CNVs), rare variants and variants in previously unresolved regions.In project I, we performed a GWAS of estradiol measurements using data from UK Biobank and quantified estradiol’s effect on bone mineral density (BMD) using MR. 14 loci were associated with estradiol levels in males, of which one was also significant in females and an additional female-specific locus. We found a significant effect of estradiol on BMD, confirming previous research of estrogen’s importance for skeletal health.In project II, we used the GWAS results from project I to investigate the effect of endogenous estradiol on breast, endometrial and ovarian cancer using MR. Estradiol was associated with ovarian cancer and nominally associated with estrogen receptor-positive breast cancer, demonstrating the effect of endogenous estrogen on cancer risk. In project III, we quantified the effect of 184,182 CNVs on 438 blood plasma proteins using whole-genome sequencing (WGS) data from a Northern Swedish cohort and validated our findings using long-read sequencing in a subcohort. 15 CNVs were associated with 16 proteins of which four could be validated using long reads and three more were more complex variation. Our findings show the effects of CNVs on the plasma proteome and highlight the application different sequencing technologies for CNV detection.In project IV, we evaluated the use of T2T-CHM13 as reference for the SweGen cohort. Compared to GRCh38, mapping quality improved and we identified 9.8 million more variants. Sensitivity for rare, singleton and functionally relevant variants was higher. These findings show how research and clinical applications benefit from T2T-CHM13 by improving detection of previously unknown functionally relevant variation.This thesis demonstrates the application of novel technologies and resources in genomics to detect variation and study its impact on quantitative traits. By using genotyping and WGS variants from short and long reads, I showed how we can leverage these technologies for research beyond GWAS.
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| 4. |
- Schmitz, Daniel, 1995-, et al.
(author)
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Genome-Wide Association Study of Estradiol Levels and the Causal Effect of Estradiol on Bone Mineral Density
- 2021
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In: Journal of Clinical Endocrinology and Metabolism. - : Endocrine Society. - 0021-972X .- 1945-7197. ; 106:11, s. e4471-e4486
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Journal article (peer-reviewed)abstract
- ContextEstradiol is the primary female sex hormone and plays an important role for skeletal health in both sexes. Several enzymes are involved in estradiol metabolism, but few genome-wide association studies (GWAS) have been performed to characterize the genetic contribution to variation in estrogen levels.ObjectiveIdentify genetic loci affecting estradiol levels and estimate causal effect of estradiol on bone mineral density (BMD).DesignWe performed GWAS for estradiol in males (n = 147 690) and females (n = 163 985) from UK Biobank. Estradiol was analyzed as a binary phenotype above/below detection limit (175 pmol/L). We further estimated the causal effect of estradiol on BMD using Mendelian randomization.ResultsWe identified 14 independent loci associated (P < 5 × 10−8) with estradiol levels in males, of which 1 (CYP3A7) was genome-wide and 7 nominally (P < 0.05) significant in females. In addition, 1 female-specific locus was identified. Most loci contain functionally relevant genes that have not been discussed in relation to estradiol levels in previous GWAS (eg, SRD5A2, which encodes a steroid 5-alpha reductase that is involved in processing androgens, and UGT3A1 and UGT2B7, which encode enzymes likely to be involved in estradiol elimination). The allele that tags the O blood group at the ABO locus was associated with higher estradiol levels. We identified a causal effect of high estradiol levels on increased BMD in both males (P = 1.58 × 10−11) and females (P = 7.48 × 10−6).ConclusionOur findings further support the importance of the body’s own estrogen to maintain skeletal health in males and in females.
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| 5. |
- Schmitz, Daniel, 1995-, et al.
(author)
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T2T-CHM13 improves read mapping and detection of clinically relevant variation
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Other publication (other academic/artistic)abstract
- Whole genome sequencing (WGS) is emerging as a first-tier diagnostic tool for rare diseases as it allows the simultaneous detection of single nucleotide variants (SNVs) and structural variants (SVs). Rare diseases together affect between 3% and 6% of the population and even if they are often caused by a single SNV or SV, less than half of the patients receive a diagnosis. This could partly be attributed to gaps and errors in the reference genome used to detect and annotate disease mutations. Recently, the new T2T-CHM13 reference genome was released, filling in the 8 % of the human genome that were not resolved in GRCh38, but it remains to be estimated how T2T-CHM13 can improve clinical diagnostics. In this study we aim to determine the increment of mapping quality and variant call performance with the T2T-CHM13 as a reference. We used a cross-sectional Swedish cohort (SweGen) comprising 1000 individuals with short-read Illumina WGS data available and re-mapping and variant calling was performed using the nf-core/sarek pipeline. Using T2T-CHM13, a higher fraction of reads were successfully mapped (99.8% vs 99.4%) and properly paired (99.4% vs 98.2%), and mismatch rate was lower (0.53% vs 0.73%), giving higher confidence in the mapping results. The fraction of alignments with mapping quality 0 was higher, indicating that alignments that appeared unique, were actually ambiguous. Coverage of gene regions was more uniform. In comparison to GRCh38, we identified 10 million additional variants, including 5.5 million singletons, across the cohort, and observed an increased sensitivity for rare variants. SnpEff assigned impact ratings of moderate or high for 30 % more variants in T2T-CHM13. We conclude that the T2T-CHM13 improves alignment metrics with higher mapping quality , better variant calling performance and more accurate annotations. Using T2T-CHM13 as reference genome will enable the discovery of unknown disease-causing variants and improve diagnostic yield.
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