Complex effects of sequence variants on lipid levels and coronary artery disease.

Many sequence variants have additive effects on blood lipid levels and, through that, on the risk of coronary artery disease (CAD). We show that variants also have non-additive effects and interact to affect lipid levels as well as affecting variance and correlations. Variance and correlation effects are often signatures of epistasis or gene-environmental interactions. These complex effects can translate into CAD risk. For example, Trp154Ter in FUT2 protects against CAD among subjects with the A1 blood group, whereas it associates with greater risk of CAD in others. His48Arg in ADH1B interacts with alcohol consumption to affect lipid levels and CAD. The effect of variants in TM6SF2 on blood lipids is greatest among those who never eat oily fish but absent from those who often do. This work demonstrates that variants that affect variance of quantitative traits can allow for the discovery of epistasis and interactions of variants with the environment.

The sequences of 150,119 genomes in the UK Biobank.

Detailed knowledge of how diversity in the sequence of the human genome affects phenotypic diversity depends on a comprehensive and reliable characterization of both sequences and phenotypic variation. Over the past decade, insights into this relationship have been obtained from whole-exome sequencing or whole-genome sequencing of large cohorts with rich phenotypic data1,2. Here we describe the analysis of whole-genome sequencing of 150,119 individuals from the UK Biobank3. This constitutes a set of high-quality variants, including 585,040,410 single-nucleotide polymorphisms, representing 7.0% of all possible human single-nucleotide polymorphisms, and 58,707,036 indels. This large set of variants allows us to characterize selection based on sequence variation within a population through a depletion rank score of windows along the genome. Depletion rank analysis shows that coding exons represent a small fraction of regions in the genome subject to strong sequence conservation. We define three cohorts within the UK Biobank: a large British Irish cohort, a smaller African cohort and a South Asian cohort. A haplotype reference panel is provided that allows reliable imputation of most variants carried by three or more sequenced individuals. We identified 895,055 structural variants and 2,536,688 microsatellites, groups of variants typically excluded from large-scale whole-genome sequencing studies. Using this formidable new resource, we provide several examples of trait associations for rare variants with large effects not found previously through studies based on whole-exome sequencing and/or imputation.

Hypoxia in tomato (Solanum lycopersicum) fruit during ripening: Biophysical elucidation by a 3D reaction-diffusion model.

Respiration provides energy, substrates, and precursors to support physiological changes of the fruit during climacteric ripening. A key substrate of respiration is oxygen that needs to be supplied to the fruit in a passive way by gas transfer from the environment. Oxygen gradients may develop within the fruit due to its bulky size and the dense fruit tissues, potentially creating hypoxia that may have a role in the spatial development of ripening. This study presents a 3D reaction-diffusion model using tomato (Solanum lycopersicum) fruit as a test subject, combining the multiscale fruit geometry generated from magnetic resonance imaging and microcomputed tomography with varying respiration kinetics and contrasting boundary resistances obtained through independent experiments. The model predicted low oxygen levels in locular tissue under atmospheric conditions, and the oxygen level was markedly lower upon scar occlusion, aligning with microsensor profiling results. The locular region was in a hypoxic state, leading to its low aerobic respiration with high CO2 accumulation by fermentative respiration, while the rest of the tissues remained well oxygenated. The model further revealed that the hypoxia is caused by a combination of diffusion resistances and respiration rates of the tissue. Collectively, this study reveals the existence of the respiratory gas gradients and its biophysical causes during tomato fruit ripening, providing richer information for future studies on localized endogenous ethylene biosynthesis and fruit ripening.

Leaf Gas Film 1 promotes glycerol ester accumulation and formation of a tight root barrier to radial O2 loss in rice.

Rice (Oryza sativa L.) and many other wetland plants form an apoplastic barrier in the outer parts of the roots to restrict radial O2 loss to the rhizosphere during soil flooding. This barrier facilitates longitudinal internal O2 diffusion via gas-filled tissues from shoot to root apices, enabling root growth in anoxic soils. We tested the hypothesis that Leaf Gas Film 1 (LGF1), which influences leaf hydrophobicity in rice, plays a crucial role in tight outer apoplastic barriers formation in rice roots. We examined the roots of a rice mutant (dripping wet leaf 7, drp7) lacking functional LGF1, its wild type, and an LGF1 overexpression line for their capacity to develop outer apoplastic barriers that restrict radial O2 loss. We quantified the chemical composition of the outer part of the root and measured radial O2 diffusion from intact roots. The drp7 mutant exhibited a weak barrier to radial O2 loss compared to the wild type. However, introducing functional LGF1 into the mutant fully restored tight barrier function. The formation of a tight barrier to radial O2 loss was associated with increased glycerol ester levels in exodermal cells, rather than differences in total root suberization or lignification. These results demonstrate that, in addition to its role in leaf hydrophobicity regulation, LGF1 plays an important role in controlling the function of the outer apoplastic barriers in roots. Our study suggests that increased deposition of glycerol esters in the suberized root exodermis establishes a tight barrier to radial O2 loss in rice roots.

A machine-learning method for biobank-scale genetic prediction of blood group antigens.

A key element for successful blood transfusion is compatibility of the patient and donor red blood cell (RBC) antigens. Precise antigen matching reduces the risk for immunization and other adverse transfusion outcomes. RBC antigens are encoded by specific genes, which allows developing computational methods for determining antigens from genomic data. We describe here a classification method for determining RBC antigens from genotyping array data. Random forest models for 39 RBC antigens in 14 blood group systems and for human platelet antigen (HPA)-1 were trained and tested using genotype and RBC antigen and HPA-1 typing data available for 1,192 blood donors in the Finnish Blood Service Biobank. The algorithm and models were further evaluated using a validation cohort of 111,667 Danish blood donors. In the Finnish test data set, the median (interquartile range [IQR]) balanced accuracy for 39 models was 99.9 (98.9-100)%. We were able to replicate 34 out of 39 Finnish models in the Danish cohort and the median (IQR) balanced accuracy for classifications was 97.1 (90.1-99.4)%. When applying models trained with the Danish cohort, the median (IQR) balanced accuracy for the 40 Danish models in the Danish test data set was 99.3 (95.1-99.8)%. The RBC antigen and HPA-1 prediction models demonstrated high overall accuracies suitable for probabilistic determination of blood groups and HPA-1 at biobank-scale. Furthermore, population-specific training cohort increased the accuracies of the models. This stand-alone and freely available method is applicable for research and screening for antigen-negative blood donors.

An apical hypoxic niche sets the pace of shoot meristem activity.

Complex multicellular organisms evolved on Earth in an oxygen-rich atmosphere1; their tissues, including stem-cell niches, require continuous oxygen provision for efficient energy metabolism2. Notably, the maintenance of the pluripotent state of animal stem cells requires hypoxic conditions, whereas higher oxygen tension promotes cell differentiation3. Here we demonstrate, using a combination of genetic reporters and in vivo oxygen measurements, that plant shoot meristems develop embedded in a low-oxygen niche, and that hypoxic conditions are required to regulate the production of new leaves. We show that hypoxia localized to the shoot meristem inhibits the proteolysis of an N-degron-pathway4,5 substrate known as LITTLE ZIPPER 2 (ZPR2)-which evolved to control the activity of the class-III homeodomain-leucine zipper transcription factors6-8-and thereby regulates the activity of shoot meristems. Our results reveal oxygen as a diffusible signal that is involved in the control of stem-cell activity in plants grown under aerobic conditions, which suggests that the spatially distinct distribution of oxygen affects plant development. In molecular terms, this signal is translated into transcriptional regulation by the N-degron pathway, thereby linking the control of metabolic activity to the regulation of development in plants.

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.

Meta-analysis of ACE inhibitor-induced angioedema identifies novel risk locus.

BACKGROUND: Angioedema is a rare but potentially life-threatening adverse drug reaction in patients receiving angiotensin-converting enzyme inhibitors (ACEis). Research suggests that susceptibility to ACEi-induced angioedema (ACEi-AE) involves both genetic and nongenetic risk factors. Genome- and exome-wide studies of ACEi-AE have identified the first genetic risk loci. However, understanding of the underlying pathophysiology remains limited. OBJECTIVE: We sought to identify further genetic factors of ACEi-AE to eventually gain a deeper understanding of its pathophysiology. METHODS: By combining data from 8 cohorts, a genome-wide association study meta-analysis was performed in more than 1000 European patients with ACEi-AE. Secondary bioinformatic analyses were conducted to fine-map associated loci, identify relevant genes and pathways, and assess the genetic overlap between ACEi-AE and other traits. Finally, an exploratory cross-ancestry analysis was performed to assess shared genetic factors in European and African-American patients with ACEi-AE. RESULTS: Three genome-wide significant risk loci were identified. One of these, located on chromosome 20q11.22, has not been implicated previously in ACEi-AE. Integrative secondary analyses highlighted previously reported genes (BDKRB2 [bradykinin receptor B2] and F5 [coagulation factor 5]) as well as biologically plausible novel candidate genes (PROCR [protein C receptor] and EDEM2 [endoplasmic reticulum degradation enhancing alpha-mannosidase like protein 2]). Lead variants at the risk loci were found with similar effect sizes and directions in an African-American cohort. CONCLUSIONS: The present results contributed to a deeper understanding of the pathophysiology of ACEi-AE by (1) providing further evidence for the involvement of bradykinin signaling and coagulation pathways and (2) suggesting, for the first time, the involvement of the fibrinolysis pathway in this adverse drug reaction. An exploratory cross-ancestry comparison implicated the relevance of the associated risk loci across diverse ancestries.

A partial loss-of-function variant in STAT6 protects against T2 asthma.

BACKGROUND: Signal Transducer and Activator of Transcription 6 (STAT6) is central to Type 2 (T2) inflammation and common non-coding variants at the STAT6 locus associate with various T2 inflammatory traits, including diseases, and its pathway is widely targeted in asthma treatment. OBJECTIVE: To test the association of a rare missense variant in STAT6, p.L406P, with T2 inflammatory traits, including the risk of asthma and allergic diseases, and to characterize its functional consequences in cell culture. METHODS: We tested association of p.L406P with plasma protein levels, white blood cell counts and the risk of asthma and allergic phenotypes. We tested significant associations in other cohorts using a burden test. The effects of p.L406P on STAT6 protein function were examined in cell lines and by comparing CD4+ T-cell responses from carriers and non-carriers of the variant. RESULTS: p.L406P associated with reduced plasma levels of STAT6 and IgE as well as with lower eosinophil and basophil counts in blood. It also protected against asthma, mostly driven by severe T2 high asthma. We showed that p.L406P led to lower IL-4-induced activation in luciferase reporter assays and lower levels of STAT6 in CD4+ T cells. We identified multiple genes with expression that was affected by the p.L406P genotype upon IL-4 treatment of CD4+ T cells; the effect was consistent with a weaker IL-4 response in carriers than non-carriers of p.L406P. CONCLUSIONS: We report a partial loss-of-function variant in STAT6, resulting in dampened IL-4 responses and protection from T2 high asthma, implicating STAT6 as an attractive therapeutic target.

Longitudinal metabolite and protein trajectories prior to diabetes mellitus diagnosis in Danish blood donors: a nested case-control study.

AIMS/HYPOTHESIS: Metabolic risk factors and plasma biomarkers for diabetes have previously been shown to change prior to a clinical diabetes diagnosis. However, these markers only cover a small subset of molecular biomarkers linked to the disease. In this study, we aimed to profile a more comprehensive set of molecular biomarkers and explore their temporal association with incident diabetes. METHODS: We performed a targeted analysis of 54 proteins and 171 metabolites and lipoprotein particles measured in three sequential samples spanning up to 11 years of follow-up in 324 individuals with incident diabetes and 359 individuals without diabetes in the Danish Blood Donor Study (DBDS) matched for sex and birth year distribution. We used linear mixed-effects models to identify temporal changes before a diabetes diagnosis, either for any incident diabetes diagnosis or for type 1 and type 2 diabetes mellitus diagnoses specifically. We further performed linear and non-linear feature selection, adding 28 polygenic risk scores to the biomarker pool. We tested the time-to-event prediction gain of the biomarkers with the highest variable importance, compared with selected clinical covariates and plasma glucose. RESULTS: We identified two proteins and 16 metabolites and lipoprotein particles whose levels changed temporally before diabetes diagnosis and for which the estimated marginal means were significant after FDR adjustment. Sixteen of these have not previously been described. Additionally, 75 biomarkers were consistently higher or lower in the years before a diabetes diagnosis. We identified a single temporal biomarker for type 1 diabetes, IL-17A/F, a cytokine that is associated with multiple other autoimmune diseases. Inclusion of 12 biomarkers improved the 10-year prediction of a diabetes diagnosis (i.e. the area under the receiver operating curve increased from 0.79 to 0.84), compared with clinical information and plasma glucose alone. CONCLUSIONS/INTERPRETATION: Systemic molecular changes manifest in plasma several years before a diabetes diagnosis. A particular subset of biomarkers shows distinct, time-dependent patterns, offering potential as predictive markers for diabetes onset. Notably, these biomarkers show shared and distinct patterns between type 1 diabetes and type 2 diabetes. After independent replication, our findings may be used to develop new clinical prediction models.

History of childhood maltreatment associated with hospitalization or death due to COVID-19: a cohort study.

BACKGROUND: Childhood maltreatment (CM) has been indicated in adverse health outcomes across the lifespan, including severe infection-related outcomes. Yet, data are scarce on the potential role of CM in severe COVID-19-related outcomes as well as on mechanisms underlying this association. METHODS: We included 151,427 individuals in the UK Biobank who responded to questions on the history of CM in 2016 and 2017 and were alive on January 31, 2020. Binomial logistic regression models were performed to estimate the association between a history of CM and severe COVID-19 outcomes (i.e. hospitalization or death due to COVID-19), as well as COVID-19 diagnosis and vaccination as secondary outcomes. We then explored the potential mediating roles of socio-economic status, lifestyle and pre-pandemic comorbidities, and the effect modification by polygenic risk score for severe COVID-19 outcomes. RESULTS: The mean age of the study population at the start of the pandemic was 67.7 (SD = 7.72) years, and 56.5% were female. We found the number of CM types was associated with the risk of severe COVID-19 outcomes in a graded manner (pfor trend < 0.01). Compared to individuals with no history of CM, individuals exposed to any CM were more likely to be hospitalized or die due to COVID-19 (odds ratio [OR] = 1.54 [95%CI 1.31-1.81]), particularly after physical neglect (2.04 [1.57-2.62]). Largely comparable risk patterns were observed across groups of high vs. low genetic risks for severe COVID-19 outcomes (pfor difference > 0.05). Mediation analysis revealed that 50.9% of the association between CM and severe COVID-19 outcomes was explained by suboptimal socio-economic status, lifestyle, and pre-pandemic diagnosis of psychiatric disorders or other chronic medical conditions. In contrast, any CM exposure was only weakly associated with COVID-19 diagnosis (1.06 [1.01-1.12]) while significantly associated with not being vaccinated for COVID-19 (1.21 [1.13-1.29]). CONCLUSIONS: Our results add to the growing knowledge base indicating the role of childhood maltreatment in negative health outcomes across the lifespan, including severe COVID-19-related outcomes. The identified factors underlying this association represent potential intervention targets for mitigating the harmful effects of childhood maltreatment in COVID-19 and similar future pandemics.

Net O2 exchange rates under dark and light conditions across different stem compartments.

Woody plants display some photosynthetic activity in stems, but the biological role of stem photosynthesis and the specific contributions of bark and wood to carbon uptake and oxygen evolution remain poorly understood. We aimed to elucidate the functional characteristics of chloroplasts in stems of different ages in Fraxinus ornus. Our investigation employed diverse experimental approaches, including microsensor technology to assess oxygen production rates in whole stem, bark, and wood separately. Additionally, we utilized fluorescence lifetime imaging microscopy (FLIM) to characterize the relative abundance of photosystems I and II (PSI : PSII chlorophyll ratio) in bark and wood. Our findings revealed light-induced increases in O2 production in whole stem, bark, and wood. We present the radial profile of O2 production in F. ornus stems, demonstrating the capability of stem chloroplasts to perform light-dependent electron transport. Younger stems exhibited higher light-induced O2 production and dark respiration rates than older ones. While bark emerged as the primary contributor to net O2 production under light conditions, our data underscored that wood chloroplasts are also photosynthetically active. The FLIM analysis unveiled a lower PSI abundance in wood than in bark, suggesting stem chloroplasts are not only active but also acclimate to the spectral composition of light reaching inner compartments.

Cluster Headache Genomewide Association Study and Meta-Analysis Identifies Eight Loci and Implicates Smoking as Causal Risk Factor.

OBJECTIVE: The objective of this study was to aggregate data for the first genomewide association study meta-analysis of cluster headache, to identify genetic risk variants, and gain biological insights. METHODS: A total of 4,777 cases (3,348 men and 1,429 women) with clinically diagnosed cluster headache were recruited from 10 European and 1 East Asian cohorts. We first performed an inverse-variance genomewide association meta-analysis of 4,043 cases and 21,729 controls of European ancestry. In a secondary trans-ancestry meta-analysis, we included 734 cases and 9,846 controls of East Asian ancestry. Candidate causal genes were prioritized by 5 complementary methods: expression quantitative trait loci, transcriptome-wide association, fine-mapping of causal gene sets, genetically driven DNA methylation, and effects on protein structure. Gene set and tissue enrichment analyses, genetic correlation, genetic risk score analysis, and Mendelian randomization were part of the downstream analyses. RESULTS: The estimated single nucleotide polymorphism (SNP)-based heritability of cluster headache was 14.5%. We identified 9 independent signals in 7 genomewide significant loci in the primary meta-analysis, and one additional locus in the trans-ethnic meta-analysis. Five of the loci were previously known. The 20 genes prioritized as potentially causal for cluster headache showed enrichment to artery and brain tissue. Cluster headache was genetically correlated with cigarette smoking, risk-taking behavior, attention deficit hyperactivity disorder (ADHD), depression, and musculoskeletal pain. Mendelian randomization analysis indicated a causal effect of cigarette smoking intensity on cluster headache. Three of the identified loci were shared with migraine. INTERPRETATION: This first genomewide association study meta-analysis gives clues to the biological basis of cluster headache and indicates that smoking is a causal risk factor. ANN NEUROL 2023;94:713-726.

Recent progress in understanding the cellular and genetic basis of plant responses to low oxygen holds promise for developing flood-resilient crops.

With recent progress in active research on flooding and hypoxia/anoxia tolerance in native and agricultural crop plants, vast knowledge has been gained on both individual tolerance mechanisms and the general mechanisms of flooding tolerance in plants. Research on carbohydrate consumption, ethanolic and lactic acid fermentation, and their regulation under stress conditions has been accompanied by investigations on aerenchyma development and the emergence of the radial oxygen loss barrier in some plant species under flooded conditions. The discovery of the oxygen-sensing mechanism in plants and unravelling the intricacies of this mechanism have boosted this very international research effort. Recent studies have highlighted the importance of oxygen availability as a signalling component during plant development. The latest developments in determining actual oxygen concentrations using minute probes and molecular sensors in tissues and even within cells have provided new insights into the intracellular effects of flooding. The information amassed during recent years has been used in the breeding of new flood-tolerant crop cultivars. With the wealth of metabolic, anatomical, and genetic information, novel holistic approaches can be used to enhance crop species and their productivity under increasing stress conditions due to climate change and the subsequent changes in the environment.

Blood donation and migraine relief: A national population cohort study in Denmark.

INTRODUCTION: Migraine is a prevalent neurological headache disorder. Due to challenges associated with finding effective treatment, many individuals with migraine feel compelled to explore alternative treatment strategies, such as blood donation, hypothesized to provide migraine relief. METHODS: Through logistic, Poisson, and Cox regression methods, we examined the links between migraine and blood donation activities in two population cohorts: Danish blood donors in the Scandinavian Donations and Transfusions Database (SCANDAT-DK, N >1 million) and the Danish Blood Donor Study (N ~ 100,000). RESULTS: SCANDAT-DK analyses showed no link between migraine and the propensity to become a blood donor among males (odds ratio [OR]Males = 0.95 [95% Confidence Interval: 0.86-1.04], and a reduced propensity among females ORFemales = 0.88 [0.83-0.93]). The incidence of migraine was not reduced upon blood donation (standardized incidence ratio [SIR]Males = 0.94 [0.83-1.06]; SIRFemales = 1.04 [0.99-1.10]). Donors with migraine demonstrated longer intervals between donations (hazard ratio [HR]Males = 0.87 [0.85-0.91], HRFemales = 0.80 [0.78-0.82]), and an increased risk of donor lapse (ORMales = 1.23 [1.14-1.32]; ORFemales = 1.28 [1.22-1.33]). Results were corroborated in DBDS using self-reported migraine. Genetic predisposition to migraine associated with longer intervals in females (HRFemales = 0.98 [0.97-0.99]), but not in males. DISCUSSION: Our findings do not support the hypothesis that blood donation serves as a viable treatment strategy among migraine patients. Future prospective investigations may help to elucidate the underlying biological mechanisms by which blood donation may influence migraine pathology.

A deep learning approach to prediction of blood group antigens from genomic data.

BACKGROUND: Deep learning methods are revolutionizing natural science. In this study, we aim to apply such techniques to develop blood type prediction models based on cheap to analyze and easily scalable screening array genotyping platforms. METHODS: Combining existing blood types from blood banks and imputed screening array genotypes for ~111,000 Danish and 1168 Finnish blood donors, we used deep learning techniques to train and validate blood type prediction models for 36 antigens in 15 blood group systems. To account for missing genotypes a denoising autoencoder initial step was utilized, followed by a convolutional neural network blood type classifier. RESULTS: Two thirds of the trained blood type prediction models demonstrated an F1-accuracy above 99%. Models for antigens with low or high frequencies like, for example, Cw, low training cohorts like, for example, Cob, or very complicated genetic underpinning like, for example, RhD, proved to be more challenging for high accuracy (>99%) DL modeling. However, in the Danish cohort only 4 out of 36 models (Cob, Cw, D-weak, Kpa) failed to achieve a prediction F1-accuracy above 97%. This high predictive performance was replicated in the Finnish cohort. DISCUSSION: High accuracy in a variety of blood groups proves viability of deep learning-based blood type prediction using array chip genotypes, even in blood groups with nontrivial genetic underpinnings. These techniques are suitable for aiding in identifying blood donors with rare blood types by greatly narrowing down the potential pool of candidate donors before clinical grade confirmation.

Initial steps towards developing a predictive algorithm of disease progression for hidradenitis suppurativa (HS): results from a Cox proportional hazard regression analysis on disease progression among a cohort of 335 Danish patients with HS.

BACKGROUND: Hidradenitis suppurativa (HS) is a chronic inflammatory and scarring disease with a wide spectrum of disease severity. The amount of scarring is proportional to the preceding tissue damage and poses a challenge to patients. Severe HS is most often treatment recalcitrant, but hypothetically avoidable through early biologic treatment. Early prediction of individual risk of disease progression is therefore essential for patient management. OBJECTIVES: To investigate risk factors associated with disease progression and to design an algorithm capable of predicting disease -progression. METHODS: A prospective cohort study of 335 Hurley III-naïve patients with HS, not treated with biologics, was followed for a median of 2 years. Potential risk factors covered basic demographics, HS anamnestic factors and clinical HS factors collected during physical examination. Two separate Cox proportional hazard regression (CPHR) analyses were conducted. A summated 'progression score' was calculated and used in the predictive algorithm of severe disease. Subsequent bootstrap sampling was used to validate the predictability of the predictive algorithm. RESULTS: The CPHR analysis of Transition to severe disease found that active smoking [hazard ratio (HR) 4.01, 95% confidence interval (CI) 1.71-9.40, P = 0.001]; body mass index (BMI) points > 25 at baseline (each point: HR 1.06, 95% CI 1.02-1.09, P < 0.001); active disease in 2 (HR 4.26, 95% CI 1.23-14.84, P = 0.02) and ≥ 3 areas (HR 6.54, 95% CI 1.89-22.72, P = 0.003) all constituted substantial risk factors. Conversely, the CPHR analysis of Disease progression did not yield results of clinical relevance. A 'progression score' of 3.04 was used as a threshold in the predictive algorithm of Transition to severe disease and achieved the following test specifics: sensitivity = 0.51, specificity = 0.86, positive predictive value = 0.50, negative predictive value = 0.86. CONCLUSIONS: We found a disparity between factors increasing the risk of simple Disease progression and those increasing the risk of Transition to severe disease. For the latter, active smoking, BMI points > 25, active disease in 2 or ≥ 3 areas were all shown to be the clinically relevant factors that could be used to construct an algorithm that correctly predicted progression to severe HS in more than half of all instances.

Investigations of the migraine-provoking effect of levcromakalim in patients with migraine with aura.

BACKGROUND/HYPOTHESIS: Experimental provocation studies have yielded important insights in migraine pathophysiology. Levcromakalim has been previously shown to induce migraine-like attacks with and without aura. In this study, we aim to further explore the migraine aura-inducing potential of levcromakalim. METHODS: In a double-blind, randomized, placebo-controlled cross-over study, 27 adult participants with migraine with aura received intravenous infusions of levcromakalim and saline. Headache, aura and associated symptoms were evaluated for 24 hours following administration of the study drug. The primary endpoint was occurrence of migraine-like attacks with or without aura in the 24-hour observation period. RESULTS: Thirteen participants developed migraine-like attacks on the active day only (P = 0.0098), and four participants developed aura on the active day only (P = 0.68). The median time to onset of migraine-like headache was three hours, and the median time to onset of aura was 27.5 minutes. CONCLUSION/INTERPRETATION: Our findings affirm the potent migraine-inducing effect of levcromakalim. We observed a lower induction-rate of migraine aura than previously reported. Further studies are warranted to identify predictors of migraine aura following levcromakalim. CLINICALTRIALS.GOV IDENTIFIER: NCT04905654.

Anatomical and physiological responses of roots and rhizomes in Oryza longistaminata to soil water gradients.

BACKGROUND AND AIMS: Roots and rhizomes are critical for the adaptation of clonal plants to soil water gradients. Oryza longistaminata, a rhizomatous wild rice, is of particular interest for perennial rice breeding due to its resilience under abiotic stress conditions. While root responses to soil flooding are well-studied, rhizome responses to water gradients remain underexplored. We hypothesize that physiological integration of Oryza longistaminata mitigates heterogeneous water deficit stress through interconnected rhizomes, and both roots and rhizomes respond to contrasting water conditions. METHODS: We investigated the physiological integration between mother plants and ramets, measuring key photosynthetic parameters (photosynthetic and transpiration rate, and stomatal conductance) using an Infrared Gas Analyzer. Moreover, root and rhizome responses to three water regimes (flooding, well-watered, and water deficit) were examined by measuring radial water loss and apparent permeance to O2, along with histochemical and anatomical characterization. KEY RESULTS: Our experiment highlights the role of physiological integration via interconnected rhizomes in mitigating water deficit stress. Severing rhizome connections from mother plants or ramets exposed to water deficit conditions led to significant decreases in key photosynthetic parameters, underscoring the importance of rhizome connections in bidirectional stress mitigation. Additionally, O. longistaminata rhizomes exhibited constitutive suberized and lignified apoplastic barriers, while such barriers were induced in roots under water stress. Anatomically, both rhizomes and roots respond similarly to water gradients, showing thinner diameters under water deficit conditions and larger diameters under flooding conditions. CONCLUSION: Our findings indicate that physiological integration through interconnected rhizomes helps alleviate water deficit stress when either the mother plant or the ramet is experiencing water deficit, while the counterpart is in control conditions. Moreover, O. longistaminata can adapt to various soil water regimes by regulating anatomical and physiological traits of roots and rhizomes.

Increased cancer incidence among patients with hidradenitis suppurativa - a Danish nationwide register study 1977-2017.

BACKGROUND: The chronic, inflammatory skin disease hidradenitis suppurativa (HS) (prevalence: 0.5%-1%, diagnostic delay: 7-10 years) primarily arises in younger adults and frequently coincides with autoimmune comorbidities and unhealthy life-styles (smoking and obesity). These factors are known to increase cancer risk, but despite this, information on cancer occurrence among HS patients is scarce. MATERIALS AND METHODS: A nationwide retrospective register-based study assessing relative risk of cancer - overall and by anatomical site - following HS diagnosis expressed as standardized incidence ratios (SIRs), which is ratios between observed cases among all Danes diagnosed with HS since 1977 and expected cases based on cancer incidence rates of the entire Danish population during the same period. RESULTS: Participants consisted of a cohort of 13,919 Danes with HS, who during an average of 14.2 years of follow-up developed a total of 1,193 incident cancers, corresponding to a 40% increased risk (SIR = 1.4, 95% CI: 1.3 to 1.4, p < 0.001). Increased risks were observed for cancers of the respiratory system, oral cavity and pharynx, digestive organs and peritoneum, urinary tract, and the lymphatic tissues. INTERPRETATION: These findings underline an unmet need for health monitoring, lifestyle interventions and cancer screening if and when relevant.