Classification of advanced stages of Parkinson's disease: translation into stratified treatments.

Advanced stages of Parkinson's disease (advPD) still impose a challenge in terms of classification and related stage-adapted treatment recommendations. Previous concepts that define advPD by certain milestones of motor disability apparently fall short in addressing the increasingly recognized complexity of motor and non-motor symptoms and do not allow to account for the clinical heterogeneity that require more personalized approaches. Therefore, deep phenotyping approaches are required to characterize the broad-scaled, continuous and multidimensional spectrum of disease-related motor and non-motor symptoms and their progression under real-life conditions. This will also facilitate the reasoning for clinical care and therapeutic decisions, as neurologists currently have to refer to clinical trials that provide guidance on a group level; however, this does not always account for the individual needs of patients. Here, we provide an overview on different classifications for advPD that translate into critical phenotypic patterns requiring the differential therapeutic adjustments. New concepts refer to precision medicine approaches also in PD and first studies on genetic stratification for therapeutic outcomes provide a potential for more objective treatment recommendations. We define novel treatment targets that align with this concept and make use of emerging device-based assessments of real-life information on PD symptoms. As these approaches require empowerment of patients and integration into treatment decisions, we present communication strategies and decision support based on new technologies to adjust treatment of advPD according to patient demands and safety

Pandemic babies? Fertility in the aftermath of the first COVID-19 wave across European regions

Early evidence demonstrates that the fertility response to the COVID-19 pandemic has varied across European countries. Yet, prior research indicates that fertility responses to disasters are often localized sub-nationally. Moreover, SARS-CoV-2 incidence, economic pandemic impacts, and the affectedness by virus containment measures varied subnationally across Europe during the first year of the COVID-19 pandemic. Sub-national variation in the fertility response seems therefore possible. We conducted a rigorous data collection effort in 28 European countries (equaling 241 European sub-national regions) and used cutting-edge forecasting methods to assess sub-national variation in the fertility response to the first six months of the COVID-19 pandemic. While we find sub-national variation, our results reveal that the fertility response to the pandemic was dominated by the country level, with Southern European countries witnessing more negative fertility response to the early pandemic than Northern Europe. Variance decomposition even indicates a ‘nationalization’ of birth rates during the winter months of 2020, as the withincountry variance in fertility declined and between-country variance increased. Nonetheless, highly urbanized areas in Europe experienced significantly steeper fertility declines as a response to the beginning of the pandemic, which is partly explained by their higher SARSCoV-2 incidence rates. SARS-CoV-2 incidence rates emerged as another important predictor of the fertility response more broadly. Higher incidences were associated with steeper fertility declines across the regions. Overall, country-level estimates represent fertility responses to the COVID-19 pandemic generally well, but the regional dimension provides additional important insight into how the COVID-19 pandemic has impacted fertility.publishedVersio

Pandemic babies? Fertility in the aftermath of the first COVID-19 wave across European regions

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Improving crop yield potential: Underlying biological processes and future prospects

The growing world population and global increases in the standard of living both result in an increasing demand for food, feed and other plant‐derived products. In the coming years, plant‐based research will be among the major drivers ensuring food security and the expansion of the bio‐based economy. Crop productivity is determined by several factors, including the available physical and agricultural resources, crop management, and the resource use efficiency, quality and intrinsic yield potential of the chosen crop. This review focuses on intrinsic yield potential, since understanding its determinants and their biological basis will allow to maximize the plant's potential in food and energy production. Yield potential is determined by a variety of complex traits that integrate strictly regulated processes and their underlying gene regulatory networks. Due to this inherent complexity, numerous potential targets have been identified that could be exploited to increase crop yield. These encompass diverse metabolic and physical processes at the cellular, organ and canopy level. We present an overview of some of the distinct biological processes considered to be crucial for yield determination that could further be exploited to improve future crop productivity

Standards in semen examination:publishing reproducible and reliable data based on high-quality methodology

Biomedical science is rapidly developing in terms of more transparency, openness and reproducibility of scientific publications. This is even more important for all studies that are based on results from basic semen examination. Recently two concordant documents have been published: the 6th edition of the WHO Laboratory Manual for the Examination and Processing of Human Semen, and the International Standard ISO 23162:2021. With these tools, we propose that authors should be instructed to follow these laboratory methods in order to publish studies in peer-reviewed journals, preferable by using a checklist as suggested in an Appendix to this article.Peer reviewe

Paving the way towards future-proofing our crops

To meet the increasing global demand for food, feed, fibre and other plant-derived products, a steep increase in crop productivity is a scientifically and technically challenging imperative. The CropBooster-P project, a response to the H2020 call ‘Future proofing our plants’, is developing a roadmap for plant research to improve crops critical for the future of European agriculture by increasing crop yield, nutritional quality, value for non-food applications and sustainability. However, if we want to efficiently improve crop production in Europe and prioritize methods for crop trait improvement in the coming years, we need to take into account future socio-economic, technological and global developments, including numerous policy and socio-economic challenges and constraints. Based on a wide range of possible global trends and key uncertainties, we developed four extreme future learning scenarios that depict complementary future developments. Here, we elaborate on how the scenarios could inform and direct future plant research, and we aim to highlight the crop improvement approaches that could be the most promising or appropriate within each of these four future world scenarios. Moreover, we discuss some key plant technology options that would need to be developed further to meet the needs of multiple future learning scenarios, such as improving methods for breeding and genetic engineering. In addition, other diverse platforms of food production may offer unrealized potential, such as underutilized terrestrial and aquatic species as alternative sources of nutrition and biomass production. We demonstrate that although several methods or traits could facilitate a more efficient crop production system in some of the scenarios, others may offer great potential in all four of the future learning scenarios. Altogether, this indicates that depending on which future we are heading toward, distinct plant research fields should be given priority if we are to meet our food, feed and non-food biomass production needs in the coming decades

Association of the PHACTR1/EDN1 genetic locus with spontaneous coronary artery dissection

Background: Spontaneous coronary artery dissection (SCAD) is an increasingly recognized cause of acute coronary syndromes (ACS) afflicting predominantly younger to middle-aged women. Observational studies have reported a high prevalence of extracoronary vascular anomalies, especially fibromuscular dysplasia (FMD) and a low prevalence of coincidental cases of atherosclerosis. PHACTR1/EDN1 is a genetic risk locus for several vascular diseases, including FMD and coronary artery disease, with the putative causal noncoding variant at the rs9349379 locus acting as a potential enhancer for the endothelin-1 (EDN1) gene. Objectives: This study sought to test the association between the rs9349379 genotype and SCAD. Methods: Results from case control studies from France, United Kingdom, United States, and Australia were analyzed to test the association with SCAD risk, including age at first event, pregnancy-associated SCAD (P-SCAD), and recurrent SCAD. Results: The previously reported risk allele for FMD (rs9349379-A) was associated with a higher risk of SCAD in all studies. In a meta-analysis of 1,055 SCAD patients and 7,190 controls, the odds ratio (OR) was 1.67 (95% confidence interval [CI]: 1.50 to 1.86) per copy of rs9349379-A. In a subset of 491 SCAD patients, the OR estimate was found to be higher for the association with SCAD in patients without FMD (OR: 1.89; 95% CI: 1.53 to 2.33) than in SCAD cases with FMD (OR: 1.60; 95% CI: 1.28 to 1.99). There was no effect of genotype on age at first event, P-SCAD, or recurrence. Conclusions: The first genetic risk factor for SCAD was identified in the largest study conducted to date for this condition. This genetic link may contribute to the clinical overlap between SCAD and FMD

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders