Characterization of the human ABO genotypes and their association to common inflammatory and cardiovascular diseases in the UK Biobank.

The ABO gene contains three major alleles that encodes different antigens; A, B, and O, which determine an individual's blood group. Previous studies have primarily focused on identifying associations between ABO blood groups and diseases risk. Here, we sought to test for association between ABO genotypes (OO, OA, AA; OB, BB, and AB) and a large set of common inflammatory and cardiovascular diseases in UK Biobank as well as disease-related protein biomarkers in NSPHS. We first tested for association by conducting a likelihood ratio test, testing whether ABO contributed significantly to the risk for 24 diseases, and 438 plasma proteins. For phenotypes with FDR < 0.05, we tested for pair-wise differences between genetically determined ABO genotypes using logistic or linear regression. Our study confirmed previous findings of a strong association between ABO and cardiovascular disease, identified associations for both type 1 and type 2 diabetes, and provide additional evidence of significant differences between heterozygous and homozygous allele carriers for pulmonary embolism, deep vein thrombosis, but also for von Willebrand factor levels. Furthermore, the results indicated an additive effect between genotypes, even between the two most common A subgroups, A1 and A2. Additionally, we found that ABO contributed significantly to 39 plasma proteins, of which 23 have never been linked to the ABO locus before. These results show the need of incorporating ABO genotype information in the consultation and management of patients at risk, rather than classifying patients into blood groups.

Polygenic risk scores and risk stratification in deep vein thrombosis.

INTRODUCTION: Deep vein thrombosis (DVT) is a complex disease, where 60 % of risk is due to genetic factors, such as the Factor V Leiden (FVL) variant. DVT is either asymptomatic or manifests with unspecific symptoms and, if left untreated, DVT leads to severe complications. The impact is dramatic and currently, there is still a research gap in DVT prevention. We characterized the genetic contribution and stratified individuals based on genetic makeup to evaluate if it favorably impacts risk prediction. METHODS: In the UK Biobank (UKB), we performed gene-based association tests using exome sequencing data, as well as a genome-wide association study. We also constructed polygenic risk scores (PRS) in a subset of the cohort (Number of cases = 8231; Number of controls = 276,360) and calculated the impact on the prediction capacity of the PRS in a non-overlapping part of the cohort (Number of cases = 4342; Number of controls = 142,822). We generated additional PRSs that excluded the known causative variants. RESULTS: We discovered and replicated a novel common variant (rs11604583) near the region where are located the TRIM51 and LRRC55 genes and identified a novel rare variant (rs187725533) located near the CREB3L1 gene, associated with 2.5-fold higher risk of DVT. In one of the PRS models constructed, the top decile of risk is associated with 3.4-fold increased risk, an effect that is 2.3-fold when excluding FVL carriers. In the top PRS decile, the cumulative risk of DVT at the age of 80 years is 10 % for FVL carriers, contraposed to 5 % for non-carriers. The population attributable fractions of having a high polygenic risk on the rate of DVT was estimated to be around 20 % in our cohort. CONCLUSION: Individuals with a high polygenic risk of DVT, and not only carriers of well-studied variants such as FVL, may benefit from prevention strategies.

Adiposity and sex-specific cancer risk.

Obesity is associated with several types of cancer and fat distribution, which differs dramatically between sexes, has been suggested to be an independent risk factor. However, sex-specific effects on cancer risk have rarely been studied. Here we estimate the effects of fat accumulation and distribution on cancer risk in females and males. We performed a prospective study in 442,519 UK Biobank participants, for 19 cancer types and additional histological subtypes, with a mean follow-up time of 13.4 years. Cox proportional hazard models were used to estimate the effect of 14 different adiposity phenotypes on cancer rates, and a 5% false discovery rate was considered statistically significant. Adiposity-related traits are associated with all but three cancer types, and fat accumulation is associated with a larger number of cancers compared to fat distribution. In addition, fat accumulation or distribution exhibit differential effects between sexes on colorectal, esophageal, and liver cancer.

Gene-Based Variant Analysis of Whole-Exome Sequencing in Relation to Eosinophil Count.

Eosinophils play important roles in the release of cytokine mediators in response to inflammation. Many associations between common genetic variants and eosinophils have already been reported, using single nucleotide polymorphism (SNP) array data. Here, we have analyzed 200,000 whole-exome sequences (WES) from the UK Biobank cohort and performed gene-based analyses of eosinophil count. We defined five different variant weighting schemes to incorporate information on both deleteriousness and frequency. A total of 220 genes in 55 distinct (>10 Mb apart) genomic regions were found to be associated with eosinophil count, of which seven genes (ALOX15, CSF2RB, IL17RA, IL33, JAK2, S1PR4, and SH2B3) are driven by rare variants, independent of common variants identified in genome-wide association studies. Two additional genes, NPAT and RMI1, have not been associated with eosinophil count before and are considered novel eosinophil loci. These results increase our knowledge about the effect of rare variants on eosinophil count, which can be of great value for further identification of therapeutic targets.

Investigating the Effect of Estradiol Levels on the Risk of Breast, Endometrial, and Ovarian Cancer.

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.

Contribution of rare whole-genome sequencing variants to plasma protein levels and the missing heritability.

Despite the success of genome-wide association studies, much of the genetic contribution to complex traits remains unexplained. Here, we analyse high coverage whole-genome sequencing data, to evaluate the contribution of rare genetic variants to 414 plasma proteins. The frequency distribution of genetic variants is skewed towards the rare spectrum, and damaging variants are more often rare. We estimate 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 identify Cis-associations for 237 of the proteins, which is slightly more compared to a GWAS (N = 213), and we identify 34 associated loci in Trans. Several associations are driven by rare variants, which have larger effects, on average. We therefore conclude that rare variants could be of importance for precision medicine applications, but have a more limited contribution to the missing heritability of complex diseases.

Time-Dependent Effects of Oral Contraceptive Use on Breast, Ovarian, and Endometrial Cancers.

Oral contraceptive use has been suggested to influence the risk of breast, ovarian, and endometrial cancer. The purpose of this study is to clarify the time-dependent effects between long-term oral contraceptive use and cancer risk. We performed an observational study in 256,661 women from UK Biobank, born between 1939 and 1970. Information on cancer diagnoses were collected from self-reported data and from national registers until March 2019. Cumulative risk of cancer over the timespan of the study, as measured by the OR, and instantaneous risk, as measured by the HR, were assessed using Logistic and Cox regression analyses, respectively. The odds were lower among ever users, compared with never users, for ovarian cancer [OR = 0.72; 95% confidence interval (CI), 0.65-0.81] and endometrial cancer (OR = 0.68; 95% CI, 0.62-0.75), an association that was stronger with longer use (P < 0.001). Increased odds were seen for breast cancer in women when limiting the follow-up to 55 years of age (OR = 1.10; 95% CI, 1.03-1.17), but not for the full timespan. We only found a higher HR for breast cancer in former users immediately (≤2 years) after discontinued oral contraceptive use (HR = 1.55; 95% CI, 1.06-2.28), whereas the protective association for ovarian and endometrial cancer remained significant up to 35 years after last use of oral contraceptives. Given the body of evidence presented in our study, we argue that oral contraceptives can dramatically reduce women's risk of ovarian and endometrial cancer, whereas their effect on lifetime risk of breast cancer is limited. SIGNIFICANCE: These results enable women and physicians to make more informed decisions considering oral contraceptive use, thus constituting an important step toward personalized medicine.

Causal effects of inflammatory protein biomarkers on inflammatory diseases.

Many circulating proteins are associated with the presence or severity of disease. However, whether these protein biomarkers are causal for disease development is usually unknown. We investigated the causal effect of 21 well-known or exploratory protein biomarkers of inflammation on 18 inflammatory diseases using two-sample Mendelian randomization. We identified six proteins to have causal effects on any of 11 inflammatory diseases (FDR < 0.05, corresponding to P < 1.4 × 10­3). IL-12B protects against psoriasis and psoriatic arthropathy, LAP-TGF-ß-1 protects against osteoarthritis, TWEAK protects against asthma, VEGF-A protects against ulcerative colitis, and LT-α protects against both type 1 diabetes and rheumatoid arthritis. In contrast, IL-18R1 increases the risk of developing allergy, hay fever, and eczema. Most proteins showed protective effects against development of disease rather than increasing disease risk, which indicates that many disease-related biomarkers are expressed to protect from tissue damage. These proteins represent potential intervention points for disease prevention and treatment.

Genome-wide Association Study of Estradiol Levels and the Causal Effect of Estradiol on Bone Mineral Density.

CONTEXT: Estradiol 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. OBJECTIVE: Identify genetic loci affecting estradiol levels and estimate causal effect of estradiol on bone mineral density (BMD). DESIGN: We 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. RESULTS: We 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). CONCLUSION: Our findings further support the importance of the body's own estrogen to maintain skeletal health in males and in females.

Owls lack UV-sensitive cone opsin and red oil droplets, but see UV light at night: Retinal transcriptomes and ocular media transmittance.

Most diurnal birds have cone-dominated retinae and tetrachromatic colour vision based on ultra-violet/violet-sensitive UV/V cones expressing short wavelength-sensitive opsin 1 (SWS1), S cones expressing short wavelength-sensitive opsin 2 (SWS2), M cones expressing medium wavelength-sensitive opsin (RH2) and L cones expressing long wavelength-sensitive opsin (LWS). Double cones (D) express LWS but do not contribute to colour vision. Each cone is equipped with an oil droplet, transparent in UV/V cones, but pigmented by carotenoids: galloxanthin in S, zeaxanthin in M, astaxanthin in L and a mixture in D cones. Owls (Strigiformes) are crepuscular or nocturnal birds with rod-dominated retinae and optical adaptations for high sensitivity. For eight species, the absence of functional SWS1 opsin has recently been documented, functional RH2 opsin was absent in three of these. Here we confirm the absence of SWS1 transcripts for the Long-eared owl (Asio otus) and demonstrate its absence for the Short-eared owl (Asio flammeus), Tawny owl (Strix aluco) and Boreal owl (Aegolius funereus). All four species had transcripts of RH2, albeit with low expression. All four species express all enzymes needed to produce galloxanthin, but lack CYP2J19 expression required to produce astaxanthin from dietary precursors. We also present ocular media transmittance of the Eurasian eagle owl (Bubo bubo) and Short-eared owl and predict spectral sensitivities of all photoreceptors of the Tawny owl. We conclude that owls, despite lacking UV/V cones, can detect UV light. This increases the sensitivity of their rod vision allowing them, for instance, to see UV-reflecting feathers as brighter signals at night.

Improved power and precision with whole genome sequencing data in genome-wide association studies of inflammatory biomarkers.

Genome-wide association studies (GWAS) have identified associations between thousands of common genetic variants and human traits. However, common variants usually explain a limited fraction of the heritability of a trait. A powerful resource for identifying trait-associated variants is whole genome sequencing (WGS) data in cohorts comprised of families or individuals from a limited geographical area. To evaluate the power of WGS compared to imputations, we performed GWAS on WGS data for 72 inflammatory biomarkers, in a kinship-structured cohort. When using WGS data, we identified 18 novel associations that were not detected when analyzing the same biomarkers with genotyped or imputed SNPs. Five of the novel top variants were low frequency variants with a minor allele frequency (MAF) of <5%. Our results suggest that, even when applying a GWAS approach, we gain power and precision using WGS data, presumably due to more accurate determination of genotypes. The lack of a comparable dataset for replication of our results is a limitation in our study. However, this further highlights that there is a need for more genetic epidemiological studies based on WGS data.

Contribution of genetics to visceral adiposity and its relation to cardiovascular and metabolic disease.

Visceral adipose tissue (VAT)-fat stored around the internal organs-has been suggested as an independent risk factor for cardiovascular and metabolic disease1-3, as well as all-cause, cardiovascular-specific and cancer-specific mortality4,5. Yet, the contribution of genetics to VAT, as well as its disease-related effects, are largely unexplored due to the requirement for advanced imaging technologies to accurately measure VAT. Here, we develop sex-stratified, nonlinear prediction models (coefficient of determination = 0.76; typical 95% confidence interval (CI) = 0.74-0.78) for VAT mass using the UK Biobank cohort. We performed a genome-wide association study for predicted VAT mass and identified 102 novel visceral adiposity loci. Predicted VAT mass was associated with increased risk of hypertension, heart attack/angina, type 2 diabetes and hyperlipidemia, and Mendelian randomization analysis showed visceral fat to be a causal risk factor for all four diseases. In particular, a large difference in causal effect between the sexes was found for type 2 diabetes, with an odds ratio of 7.34 (95% CI = 4.48-12.0) in females and an odds ratio of 2.50 (95% CI = 1.98-3.14) in males. Our findings bolster the role of visceral adiposity as a potentially independent risk factor, in particular for type 2 diabetes in Caucasian females. Independent validation in other cohorts is necessary to determine whether the findings can translate to other ethnicities, or outside the UK.