Deep integrative models for large-scale human genomics.

Polygenic risk scores (PRSs) are expected to play a critical role in precision medicine. Currently, PRS predictors are generally based on linear models using summary statistics, and more recently individual-level data. However, these predictors mainly capture additive relationships and are limited in data modalities they can use. We developed a deep learning framework (EIR) for PRS prediction which includes a model, genome-local-net (GLN), specifically designed for large-scale genomics data. The framework supports multi-task learning, automatic integration of other clinical and biochemical data, and model explainability. When applied to individual-level data from the UK Biobank, the GLN model demonstrated a competitive performance compared to established neural network architectures, particularly for certain traits, showcasing its potential in modeling complex genetic relationships. Furthermore, the GLN model outperformed linear PRS methods for Type 1 Diabetes, likely due to modeling non-additive genetic effects and epistasis. This was supported by our identification of widespread non-additive genetic effects and epistasis in the context of T1D. Finally, we constructed PRS models that integrated genotype, blood, urine, and anthropometric data and found that this improved performance for 93% of the 290 diseases and disorders considered. EIR is available at https://github.com/arnor-sigurdsson/EIR.

BALDR: A Web-based platform for informed comparison and prioritization of biomarker candidates for type 2 diabetes mellitus.

Novel biomarkers are key to addressing the ongoing pandemic of type 2 diabetes mellitus. While new technologies have improved the potential of identifying such biomarkers, at the same time there is an increasing need for informed prioritization to ensure efficient downstream verification. We have built BALDR, an automated pipeline for biomarker comparison and prioritization in the context of diabetes. BALDR includes protein, gene, and disease data from major public repositories, text-mining data, and human and mouse experimental data from the IMI2 RHAPSODY consortium. These data are provided as easy-to-read figures and tables enabling direct comparison of up to 20 biomarker candidates for diabetes through the public website https://baldr.cpr.ku.dk.

Prospective reproductive outcomes according to sperm parameters, including DNA fragmentation, in recurrent pregnancy loss.

RESEARCH QUESTION: Are the prospective reproductive outcomes in couples experiencing recurrent pregnancy loss (RPL) related to the sperm DNA fragmentation index (DFI), as measured by sperm chromatin structure assay, sperm morphology and sperm concentration at referral? DESIGN: This prospective cohort study included 95 couples seen between 1 April 2018 and 1 December 2019 at the tertiary Copenhagen RPL Unit, Copenhagen University Hospital, Rigshospitalet and Hvidovre Hospital, Denmark. The couples had experienced three or more unexplained consecutive pregnancy losses or two late pregnancy losses (>12 weeks gestation). Follow-up was 12-31 months. RESULTS: Eighty-one of 95 (85.3%) couples achieved pregnancy after referral. In the first pregnancy after referral, 46 (56.8%) couples achieved a live birth, and 35 (43.2%) couples experienced another pregnancy loss. There was no significant difference in baseline DFI between couples that experienced pregnancy loss [median 11.7, interquartile range (IQR) 9.1-17.3] and couples that achieved a live birth (median 12.5, IQR 9.3-16.5; P = 0.971). Improving sperm morphology increased the odds of a live birth after referral (adjusted OR 1.26, 95% CI 1.05-1.52; P = 0.014). DFI and sperm concentration were not associated with the outcome of the first pregnancy after referral. Overall, 35.9% of the men had DFI ≥15 at inclusion. Couples that failed to achieve pregnancy had a higher median DFI of 17.7 (IQR 7.7-27.2) compared with the rest of the cohort (median 12.0, IQR 9.3-16.5; P = 0.041). CONCLUSIONS: At referral, sperm DFI, morphology and concentration cannot be used to identify RPL couples at risk of another pregnancy loss. Increased baseline DFI was associated with difficulty achieving another pregnancy, and improving sperm morphology was associated with increased odds of a live birth.

Genome-wide association study of febrile seizures implicates fever response and neuronal excitability genes.

Febrile seizures represent the most common type of pathological brain activity in young children and are influenced by genetic, environmental and developmental factors. In a minority of cases, febrile seizures precede later development of epilepsy. We conducted a genome-wide association study of febrile seizures in 7635 cases and 83 966 controls identifying and replicating seven new loci, all with P < 5 × 10-10. Variants at two loci were functionally related to altered expression of the fever response genes PTGER3 and IL10, and four other loci harboured genes (BSN, ERC2, GABRG2, HERC1) influencing neuronal excitability by regulating neurotransmitter release and binding, vesicular transport or membrane trafficking at the synapse. Four previously reported loci (SCN1A, SCN2A, ANO3 and 12q21.33) were all confirmed. Collectively, the seven novel and four previously reported loci explained 2.8% of the variance in liability to febrile seizures, and the single nucleotide polymorphism heritability based on all common autosomal single nucleotide polymorphisms was 10.8%. GABRG2, SCN1A and SCN2A are well-established epilepsy genes and, overall, we found positive genetic correlations with epilepsies (rg = 0.39, P = 1.68 × 10-4). Further, we found that higher polygenic risk scores for febrile seizures were associated with epilepsy and with history of hospital admission for febrile seizures. Finally, we found that polygenic risk of febrile seizures was lower in febrile seizure patients with neuropsychiatric disease compared to febrile seizure patients in a general population sample. In conclusion, this largest genetic investigation of febrile seizures to date implicates central fever response genes as well as genes affecting neuronal excitability, including several known epilepsy genes. Further functional and genetic studies based on these findings will provide important insights into the complex pathophysiological processes of seizures with and without fever.

Sequencing and de novo assembly of 150 genomes from Denmark as a population reference.

Hundreds of thousands of human genomes are now being sequenced to characterize genetic variation and use this information to augment association mapping studies of complex disorders and other phenotypic traits. Genetic variation is identified mainly by mapping short reads to the reference genome or by performing local assembly. However, these approaches are biased against discovery of structural variants and variation in the more complex parts of the genome. Hence, large-scale de novo assembly is needed. Here we show that it is possible to construct excellent de novo assemblies from high-coverage sequencing with mate-pair libraries extending up to 20 kilobases. We report de novo assemblies of 150 individuals (50 trios) from the GenomeDenmark project. The quality of these assemblies is similar to those obtained using the more expensive long-read technology. We use the assemblies to identify a rich set of structural variants including many novel insertions and demonstrate how this variant catalogue enables further deciphering of known association mapping signals. We leverage the assemblies to provide 100 completely resolved major histocompatibility complex haplotypes and to resolve major parts of the Y chromosome. Our study provides a regional reference genome that we expect will improve the power of future association mapping studies and hence pave the way for precision medicine initiatives, which now are being launched in many countries including Denmark.

Genetic insight into sick sinus syndrome.

AIMS: The aim of this study was to use human genetics to investigate the pathogenesis of sick sinus syndrome (SSS) and the role of risk factors in its development. METHODS AND RESULTS: We performed a genome-wide association study of 6469 SSS cases and 1 000 187 controls from deCODE genetics, the Copenhagen Hospital Biobank, UK Biobank, and the HUNT study. Variants at six loci associated with SSS, a reported missense variant in MYH6, known atrial fibrillation (AF)/electrocardiogram variants at PITX2, ZFHX3, TTN/CCDC141, and SCN10A and a low-frequency (MAF = 1.1-1.8%) missense variant, p.Gly62Cys in KRT8 encoding the intermediate filament protein keratin 8. A full genotypic model best described the p.Gly62Cys association (P = 1.6 × 10-20), with an odds ratio (OR) of 1.44 for heterozygotes and a disproportionally large OR of 13.99 for homozygotes. All the SSS variants increased the risk of pacemaker implantation. Their association with AF varied and p.Gly62Cys was the only variant not associating with any other arrhythmia or cardiovascular disease. We tested 17 exposure phenotypes in polygenic score (PGS) and Mendelian randomization analyses. Only two associated with the risk of SSS in Mendelian randomization, AF, and lower heart rate, suggesting causality. Powerful PGS analyses provided convincing evidence against causal associations for body mass index, cholesterol, triglycerides, and type 2 diabetes (P > 0.05). CONCLUSION: We report the associations of variants at six loci with SSS, including a missense variant in KRT8 that confers high risk in homozygotes and points to a mechanism specific to SSS development. Mendelian randomization supports a causal role for AF in the development of SSS.

Genetic insight into sick sinus syndrome.

AIMS: The aim of this study was to use human genetics to investigate the pathogenesis of sick sinus syndrome (SSS) and the role of risk factors in its development. METHODS AND RESULTS: We performed a genome-wide association study of 6469 SSS cases and 1 000 187 controls from deCODE genetics, the Copenhagen Hospital Biobank, UK Biobank, and the HUNT study. Variants at six loci associated with SSS, a reported missense variant in MYH6, known atrial fibrillation (AF)/electrocardiogram variants at PITX2, ZFHX3, TTN/CCDC141, and SCN10A and a low-frequency (MAF = 1.1-1.8%) missense variant, p.Gly62Cys in KRT8 encoding the intermediate filament protein keratin 8. A full genotypic model best described the p.Gly62Cys association (P = 1.6 × 10-20), with an odds ratio (OR) of 1.44 for heterozygotes and a disproportionally large OR of 13.99 for homozygotes. All the SSS variants increased the risk of pacemaker implantation. Their association with AF varied and p.Gly62Cys was the only variant not associating with any other arrhythmia or cardiovascular disease. We tested 17 exposure phenotypes in polygenic score (PGS) and Mendelian randomization analyses. Only two associated with the risk of SSS in Mendelian randomization, AF, and lower heart rate, suggesting causality. Powerful PGS analyses provided convincing evidence against causal associations for body mass index, cholesterol, triglycerides, and type 2 diabetes (P > 0.05). CONCLUSION: We report the associations of variants at six loci with SSS, including a missense variant in KRT8 that confers high risk in homozygotes and points to a mechanism specific to SSS development. Mendelian randomization supports a causal role for AF in the development of SSS.

Chance of live birth: a nationwide, registry-based cohort study.

STUDY QUESTION: Does the sequence of prior pregnancy events (pregnancy losses, live births, ectopic pregnancies, molar pregnancy and still birth), obstetric complications and maternal age affect chance of live birth in the next pregnancy and are prior events predictive for the outcome? SUMMARY ANSWER: The sequence of pregnancy outcomes is significantly associated with chance of live birth; however, pregnancy history and age are insufficient to predict the outcome of an individual woman's next pregnancy. WHAT IS KNOWN ALREADY: Adverse pregnancy outcomes decrease the chance of live birth in the next pregnancy, whereas the impact of prior live births is less clear. STUDY DESIGN, SIZE, DURATION: Nationwide, registry-based cohort study of 1 285 230 women with a total of 2 722 441 pregnancies from 1977 to 2017. PARTICIPANTS/MATERIALS, SETTING, METHODS: All women living in Denmark in the study period with at least one pregnancy in either the Danish Medical Birth Registry or the Danish National Patient Registry. Data were analysed using logistic regression with a robust covariance model to account for women with more than one pregnancy. Model discrimination and calibration were ascertained using 20% of the women in the cohort randomly selected as an internal validation set. MAIN RESULTS AND THE ROLE OF CHANCE: Obstetric complications, still birth, ectopic pregnancies and pregnancy losses had a negative effect on the chance of live birth in the next pregnancy. Consecutive, identical pregnancy outcomes (pregnancy losses, live births or ectopic pregnancies) immediately preceding the next pregnancy had a larger impact than the total number of any outcome. Model discrimination was modest (C-index = 0.60, positive predictive value = 0.45), but the models were well calibrated. LIMITATIONS, REASONS FOR CAUTION: While prior pregnancy outcomes and their sequence significantly influenced the chance of live birth, the discriminative abilities of the predictive models demonstrate clearly that pregnancy history and maternal age are insufficient to reliably predict the outcome of a given pregnancy. WIDER IMPLICATIONS OF THE FINDINGS: Prior pregnancy history has a significant impact on the chance of live birth in the next pregnancy. However, the results emphasize that only taking age and number of losses into account does not predict if a pregnancy will end as a live birth or not. A better understanding of biological determinants for pregnancy outcomes is urgently needed. STUDY FUNDING/COMPETING INTEREST(S): The work was supported by the Novo Nordisk Foundation, Ole Kirk Foundation and Rigshospitalet's Research Foundation. The authors have no financial relationships that could appear to have influenced the work. TRIAL REGISTRATION NUMBER: N/A.

The impact of early pregnancy complications on completed family size-A nationwide, registry-based cohort study with 40 years of data.

INTRODUCTION: The impact of early pregnancy complications on completed family size is unknown. Here, we hypothesize that early pregnancy complications and adverse outcomes may influence family size. MATERIAL AND METHODS: In this nationwide, registry-based study we included all 458 475 women born 1957-1972 who lived in Denmark from age 20-45 years with at least one registered pregnancy. The main outcome of the study was number of children per woman by age 45, estimated using a Generalized Linear Mixed Model. Exposures were: (a) total number of pregnancy losses experienced (0, 1, 2, ≥3); (b) highest number of consecutive pregnancy losses (0, 1, 2, ≥3); (c) sex of firstborn child; (d) outcome of first pregnancy (live birth, stillbirth, pregnancy loss, ectopic pregnancy, or molar pregnancy). RESULTS: Number of live births was negatively influenced by maternal age and adverse first pregnancy outcomes, especially ectopic pregnancies. A 30-year-old woman with a first ectopic pregnancy was expected to have 1.16 children (95% CI 1.11-1.22) compared with 1.95 children (95% CI 1.86-2.03) with a first live birth. Three or more consecutive losses also decreased number of live births significantly: 1.57 (95% CI 1.50-1.65) compared with 1.92 (95% CI 1.84-2.0) with only live births. The total number of pregnancy losses had no effect before the age of 35 years. Sex of firstborn had no effect. CONCLUSIONS: Previous pregnancy history has a significant effect on number of children per woman, which is important at both individual and societal levels. Pathophysiological research of adverse pregnancy outcomes should be an urgent priority as the causes remain poorly understood.

Pregnancy loss is associated with type 2 diabetes: a nationwide case-control study.

AIMS/HYPOTHESIS: Type 2 diabetes is killing more people than ever, and early-life predictors remain critical for the development of effective preventive strategies. Pregnancy loss is a common event associated with later atherosclerotic disease and ischaemic heart failure and might constitute a predictor for type 2 diabetes. The objective of this study was to investigate whether pregnancy loss is associated with later development of type 2 diabetes. METHODS: Using a Danish nationwide cohort, we identified all women born from 1957 through to 1997 and who had a diagnosis of type 2 diabetes during the period 1977 to 2017. The women were matched 1:10 on year of birth and educational level to women without diabetes in the general Danish population. Conditional logistic regression models provided odds ratios for type 2 diabetes with different numbers of pregnancy losses. RESULTS: We identified 24,774 women with type 2 diabetes and selected 247,740 controls without diabetes. Women who had ever been pregnant (ever-pregnant women) with 1, 2 and ≥ 3 pregnancy losses had ORs of type 2 diabetes of 1.18 (95% CI 1.13, 1.23), 1.38 (95% CI 1.27, 1.49) and 1.71 (95% CI 1.53, 1.92) compared with ever-pregnant women with no pregnancy losses, respectively. Women who never achieved a pregnancy had an OR of type 2 diabetes of 1.56 (95% CI 1.51, 1.61) compared with ever-pregnant women with any number of losses. Similar results were found after adjustment for obesity and gestational diabetes. CONCLUSIONS/INTERPRETATION: We found a significant and consistent association between pregnancy loss and later type 2 diabetes that increased with increasing number of losses. Thus, pregnancy loss and recurrent pregnancy loss are significant risk factors for later type 2 diabetes. Future studies should explore whether this association is due to common background factors or whether prediabetic metabolic conditions are responsible for this association. Graphical abstract.

Klinefelter syndrome comorbidities linked to increased X chromosome gene dosage and altered protein interactome activity.

Klinefelter syndrome (KS) (47,XXY) is the most common male sex chromosome aneuploidy. Diagnosis and clinical supervision remain a challenge due to varying phenotypic presentation and insufficient characterization of the syndrome. Here we combine health data-driven epidemiology and molecular level systems biology to improve the understanding of KS and the molecular interplay influencing its comorbidities. In total, 78 overrepresented KS comorbidities were identified using in- and out-patient registry data from the entire Danish population covering 6.8 million individuals. The comorbidities extracted included both clinically well-known (e.g. infertility and osteoporosis) and still less established KS comorbidities (e.g. pituitary gland hypofunction and dental caries). Several systems biology approaches were applied to identify key molecular players underlying KS comorbidities: Identification of co-expressed modules as well as central hubs and gene dosage perturbed protein complexes in a KS comorbidity network build from known disease proteins and their protein-protein interactions. The systems biology approaches together pointed to novel aspects of KS disease phenotypes including perturbed Jak-STAT pathway, dysregulated genes important for disturbed immune system (IL4), energy balance (POMC and LEP) and erythropoietin signalling in KS. We present an extended epidemiological study that links KS comorbidities to the molecular level and identify potential causal players in the disease biology underlying the identified comorbidities.

Comorbidity landscape of the Danish patient population affected by chromosome abnormalities.

PURPOSE: Most chromosome abnormality patients require long-term clinical care. Awareness of mosaicism and comorbidities can potentially guide such health care. Here we present a population-wide analysis of direct and inverse comorbidities affecting patients with chromosome abnormalities. METHODS: We extracted direct and inverse comorbidities for the 11 most prevalent chromosome abnormalities from the Danish National Patient Registry (covering 6.9 million patients hospitalized between 1994 and 2015): trisomy 13, 18, and 21, Klinefelter (47,XXY), triple X, XYY, Turner (45,X), Wolf-Hirschhorn, Cri-du-chat, Angelman, and Fragile X syndromes (FXS). We also performed four sub-analyses for male/female Down syndrome (DS) and FXS and non-mosaic/mosaic DS and Turner syndrome. RESULTS: Our data cover 9,003 patients diagnosed with at least one chromosome abnormality. Each abnormality showed a unique comorbidity signature, but clustering of their profiles underlined common risk profiles for chromosome abnormalities with similar genetic backgrounds. We found that DS had a decreased risk for three inverse cancer comorbidities (lung, breast, and skin) and that male FXS and non-mosaic patients have a much more severe phenotype than female FXS and mosaic patients, respectively. CONCLUSION: Our study underlines the importance of considering mosaicism, sex, and the associated comorbidity profiles of chromosome abnormalities to guide long-term health care of affected patients.

Large-scale study of Toxoplasma and Cytomegalovirus shows an association between infection and serious psychiatric disorders.

BACKGROUND: Common infectious pathogens have been associated with psychiatric disorders, self-violence and risk-taking behavior. METHODS: This case-control study reviews register data on 81,912 individuals from the Danish Blood Donor Study to identify individuals who have a psychiatric diagnosis (N = 2591), have attempted or committed suicide (N = 655), or have had traffic accidents (N = 2724). For all cases, controls were frequency matched by age and sex, resulting in 11,546 participants. Plasma samples were analyzed for immunoglobulin G (IgG) antibodies against Toxoplasma gondii and cytomegalovirus (CMV). RESULTS: T. gondii was detected in 25·9% of the population and was associated with schizophrenia (odds ratio [OR], 1·47; 95% confidence interval [CI], 1·03-2·09). Accounting for temporality, with pathogen exposure preceding outcome, the association was even stronger (IRR, 2·78; 95% CI, 1·27-6·09). A very weak association between traffic accident and toxoplasmosis (OR, 1·11; 95% CI, 1·00-1·23, p = 0.054) was found. CMV was detected in 60·8% of the studied population and was associated with any psychiatric disorder (OR, 1·17; 95% CI, 1·06-1·29), but also with a smaller group of neurotic, stress-related, and somatoform disorders (OR, 1·27; 95% CI, 1·12-1·44), and with attempting or committing suicide (OR, 1·31; 95% CI, 1·10-1·56). Accounting for temporality, any psychiatric disorder (IRR, 1·37; 95% CI, 1·08-1·74) and mood disorders (IRR, 1·43; 95% CI, 1·01-2·04) were associated with exposure to CMV. No association between traffic accident and CMV (OR, 1·06; 95% CI, 0·97-1·17) was found. CONCLUSIONS: This large-scale serological study is the first study to examine temporality of pathogen exposure and to provide evidence of a causal relationship between T. gondii and schizophrenia, and between CMV and any psychiatric disorder.

A comprehensive and quantitative comparison of text-mining in 15 million full-text articles versus their corresponding abstracts.

Across academia and industry, text mining has become a popular strategy for keeping up with the rapid growth of the scientific literature. Text mining of the scientific literature has mostly been carried out on collections of abstracts, due to their availability. Here we present an analysis of 15 million English scientific full-text articles published during the period 1823-2016. We describe the development in article length and publication sub-topics during these nearly 250 years. We showcase the potential of text mining by extracting published protein-protein, disease-gene, and protein subcellular associations using a named entity recognition system, and quantitatively report on their accuracy using gold standard benchmark data sets. We subsequently compare the findings to corresponding results obtained on 16.5 million abstracts included in MEDLINE and show that text mining of full-text articles consistently outperforms using abstracts only.

Acquisition of docetaxel resistance in breast cancer cells reveals upregulation of ABCB1 expression as a key mediator of resistance accompanied by discrete upregulation of other specific genes and pathways.

The microtubule-targeting taxanes are important in breast cancer therapy, but no predictive biomarkers have yet been identified with sufficient scientific evidence to allow clinical routine use. The purposes of the present study were to develop a cell-culture-based discovery platform for docetaxel resistance and thereby identify key molecular mechanisms and predictive molecular characteristics to docetaxel resistance. Two docetaxel-resistant cell lines, MCF7RES and MDARES, were generated from their respective parental cell lines MCF-7 and MDA-MB-231 by stepwise selection in docetaxel dose increments over 15 months. The cell lines were characterized regarding sensitivity to docetaxel and other chemotherapeutics and subjected to transcriptome-wide mRNA microarray profiling. MCF7RES and MDARES exhibited a biphasic growth inhibition pattern at increasing docetaxel concentrations. Gene expression analysis singled out ABCB1, which encodes permeability glycoprotein (Pgp), as the top upregulated gene in both MCF7RES and MDARES. Functional validation revealed Pgp as a key resistance mediator at low docetaxel concentrations (first-phase response), whereas additional resistance mechanisms appeared to be prominent at higher docetaxel concentrations (second-phase response). Additional resistance mechanisms were indicated by gene expression profiling, including genes in the interferon-inducible protein family in MCF7RES and cancer testis antigen family in MDARES. Also, upregulated expression of various ABC transporters, ECM-associated proteins, and lysosomal proteins was identified in both resistant cell lines. Finally, MCF7RES and MDARES presented with cross-resistance to epirubicin, but only MDARES showed cross-resistance to oxaliplatin. In conclusion, Pgp was identified as a key mediator of resistance to low docetaxel concentrations with other resistance mechanisms prominent at higher docetaxel concentrations. Supporting Pgp upregulation as one major mechanism of taxane resistance and cell-line-specific alterations as another, both MCF7RES and MDARES were cross-resistant to epirubicin (Pgp substrate), but only MDARES was cross-resistant to oxaliplatin (non-Pgp substrate).

Exploring mechanisms of diet-colon cancer associations through candidate molecular interaction networks.

BACKGROUND: Epidemiological studies in the recent years have investigated the relationship between dietary habits and disease risk demonstrating that diet has a direct effect on public health. Especially plant-based diets -fruits, vegetables and herbs- are known as a source of molecules with pharmacological properties for treatment of several malignancies. Unquestionably, for developing specific intervention strategies to reduce cancer risk there is a need for a more extensive and holistic examination of the dietary components for exploring the mechanisms of action and understanding the nutrient-nutrient interactions. Here, we used colon cancer as a proof-of-concept for understanding key regulatory sites of diet on the disease pathway. RESULTS: We started from a unique vantage point by having a database of 158 plants positively associated to colon cancer reduction and their molecular composition (~3,500 unique compounds). We generated a comprehensive picture of the interaction profile of these edible and non-edible plants with a predefined candidate colon cancer target space consisting of ~1,900 proteins. This knowledge allowed us to study systematically the key components in colon cancer that are targeted synergistically by phytochemicals and identify statistically significant and highly correlated protein networks that could be perturbed by dietary habits. CONCLUSION: We propose here a framework for interrogating the critical targets in colon cancer processes and identifying plant-based dietary interventions as important modifiers using a systems chemical biology approach. Our methodology for better delineating prevention of colon cancer by nutritional interventions relies heavily on the availability of information about the small molecule constituents of our diet and it can be expanded to any other disease class that previous evidence has linked to lifestyle.

Variant in the synaptonemal complex protein SYCE2 associates with pregnancy loss through effect on recombination.

Two-thirds of all human conceptions are lost, in most cases before clinical detection. The lack of detailed understanding of the causes of pregnancy losses constrains focused counseling for future pregnancies. We have previously shown that a missense variant in synaptonemal complex central element protein 2 (SYCE2), in a key residue for the assembly of the synaptonemal complex backbone, associates with recombination traits. Here we show that it also increases risk of pregnancy loss in a genome-wide association analysis on 114,761 women with reported pregnancy loss. We further show that the variant associates with more random placement of crossovers and lower recombination rate in longer chromosomes but higher in the shorter ones. These results support the hypothesis that some pregnancy losses are due to failures in recombination. They further demonstrate that variants with a substantial effect on the quality of recombination can be maintained in the population.

A genome-wide association study of social trust in 33,882 Danish blood donors.

Social trust is a heritable trait that has been linked with physical health and longevity. In this study, we performed genome-wide association studies of self-reported social trust in n = 33,882 Danish blood donors. We observed genome-wide and local evidence of genetic similarity with other brain-related phenotypes and estimated the single nucleotide polymorphism-based heritability of trust to be 6% (95% confidence interval = (2.1, 9.9)). In our discovery cohort (n = 25,819), we identified one significantly associated locus (lead variant: rs12776883) in an intronic enhancer region of PLPP4, a gene highly expressed in brain, kidneys, and testes. However, we could not replicate the signal in an independent set of donors who were phenotyped a year later (n = 8063). In the subsequent meta-analysis, we found a second significantly associated variant (rs71543507) in an intergenic enhancer region. Overall, our work confirms that social trust is heritable, and provides an initial look into the genetic factors that influence it.

Genome-wide analyses identify 21 infertility loci and over 400 reproductive hormone loci across the allele frequency spectrum.

Genome-wide association studies (GWASs) may help inform treatments for infertility, whose causes remain unknown in many cases. Here we present GWAS meta-analyses across six cohorts for male and female infertility in up to 41,200 cases and 687,005 controls. We identified 21 genetic risk loci for infertility (P≤5E-08), of which 12 have not been reported for any reproductive condition. We found positive genetic correlations between endometriosis and all-cause female infertility (rg=0.585, P=8.98E-14), and between polycystic ovary syndrome and anovulatory infertility (rg=0.403, P=2.16E-03). The evolutionary persistence of female infertility-risk alleles in EBAG9 may be explained by recent directional selection. We additionally identified up to 269 genetic loci associated with follicle-stimulating hormone (FSH), luteinising hormone, oestradiol, and testosterone through sex-specific GWAS meta-analyses (N=6,095-246,862). While hormone-associated variants near FSHB and ARL14EP colocalised with signals for anovulatory infertility, we found no rg between female infertility and reproductive hormones (P>0.05). Exome sequencing analyses in the UK Biobank (N=197,340) revealed that women carrying testosterone-lowering rare variants in GPC2 were at higher risk of infertility (OR=2.63, P=1.25E-03). Taken together, our results suggest that while individual genes associated with hormone regulation may be relevant for fertility, there is limited genetic evidence for correlation between reproductive hormones and infertility at the population level. We provide the first comprehensive view of the genetic architecture of infertility across multiple diagnostic criteria in men and women, and characterise its relationship to other health conditions.