Genetic correlation between amyotrophic lateral sclerosis and schizophrenia

A. Palotie on työryhmän Schizophrenia Working Grp Psychiat jäsen.We have previously shown higher-than-expected rates of schizophrenia in relatives of patients with amyotrophic lateral sclerosis (ALS), suggesting an aetiological relationship between the diseases. Here, we investigate the genetic relationship between ALS and schizophrenia using genome-wide association study data from over 100,000 unique individuals. Using linkage disequilibrium score regression, we estimate the genetic correlation between ALS and schizophrenia to be 14.3% (7.05-21.6; P = 1 x 10(-4)) with schizophrenia polygenic risk scores explaining up to 0.12% of the variance in ALS (P = 8.4 x 10(-7)). A modest increase in comorbidity of ALS and schizophrenia is expected given these findings (odds ratio 1.08-1.26) but this would require very large studies to observe epidemiologically. We identify five potential novel ALS-associated loci using conditional false discovery rate analysis. It is likely that shared neurobiological mechanisms between these two disorders will engender novel hypotheses in future preclinical and clinical studies.Peer reviewe

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

Genome sequencing analysis identifies new loci associated with Lewy body dementia and provides insights into its genetic architecture

The genetic basis of Lewy body dementia (LBD) is not well understood. Here, we performed whole-genome sequencing in large cohorts of LBD cases and neurologically healthy controls to study the genetic architecture of this understudied form of dementia and to generate a resource for the scientific community. Genome-wide association analysis identified five independent risk loci, whereas genome-wide gene-aggregation tests implicated mutations in the gene GBA. Genetic risk scores demonstrate that LBD shares risk profiles and pathways with Alzheimer’s and Parkinson’s disease, providing a deeper molecular understanding of the complex genetic architecture of this age-related neurodegenerative condition

Genome sequencing analysis identifies new loci associated with Lewy body dementia and provides insights into its genetic architecture

The genetic basis of Lewy body dementia (LBD) is not well understood. Here, we performed whole-genome sequencing in large cohorts of LBD cases and neurologically healthy controls to study the genetic architecture of this understudied form of dementia, and to generate a resource for the scientific community. Genome-wide association analysis identified five independent risk loci, whereas genome-wide gene-aggregation tests implicated mutations in the gene GBA. Genetic risk scores demonstrate that LBD shares risk profiles and pathways with Alzheimer's disease and Parkinson's disease, providing a deeper molecular understanding of the complex genetic architecture of this age-related neurodegenerative condition

Genome-wide structural variant analysis identifies risk loci for non-Alzheimer’s dementias

We characterized the role of structural variants, a largely unexplored type of genetic variation, in two non-Alzheimer’s dementias, namely Lewy body dementia (LBD) and frontotemporal dementia (FTD)/amyotrophic lateral sclerosis (ALS). To do this, we applied an advanced structural variant calling pipeline (GATK-SV) to short-read whole-genome sequence data from 5,213 European-ancestry cases and 4,132 controls. We discovered, replicated, and validated a deletion in TPCN1 as a novel risk locus for LBD and detected the known structural variants at the C9orf72 and MAPT loci as associated with FTD/ALS. We also identified rare pathogenic structural variants in both LBD and FTD/ALS. Finally, we assembled a catalog of structural variants that can be mined for new insights into the pathogenesis of these understudied forms of dementia

Search for gravitational-lensing signatures in the full third observing run of the LIGO-Virgo network

Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-signals; such distortions may reveal information about fundamental physics, cosmology and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO--Virgo network. We search for repeated signals from strong lensing by 1) performing targeted searches for subthreshold signals, 2) calculating the degree of overlap amongst the intrinsic parameters and sky location of pairs of signals, 3) comparing the similarities of the spectrograms amongst pairs of signals, and 4) performing dual-signal Bayesian analysis that takes into account selection effects and astrophysical knowledge. We also search for distortions to the gravitational waveform caused by 1) frequency-independent phase shifts in strongly lensed images, and 2) frequency-dependent modulation of the amplitude and phase due to point masses. None of these searches yields significant evidence for lensing. Finally, we use the non-detection of gravitational-wave lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects

Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M>70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0<e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level

Ultralight vector dark matter search using data from the KAGRA O3GK run

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM

Combining citizen science species distribution models and stable isotopes reveals migratory connectivity in the secretive V

© 2016 The Authors. Journal of Applied Ecology © 2016 British Ecological Society Stable hydrogen isotope (δD) methods for tracking animal movement are widely used yet often produce low resolution assignments. Incorporating prior knowledge of abundance, distribution or movement patterns can ameliorate this limitation, but data are lacking for most species. We demonstrate how observations reported by citizen scientists can be used to develop robust estimates of species distributions and to constrain δD assignments. We developed a Bayesian framework to refine isotopic estimates of migrant animal origins conditional on species distribution models constructed from citizen scientist observations. To illustrate this approach, we analysed the migratory connectivity of the Virginia rail Rallus limicola, a secretive and declining migratory game bird in North America. Citizen science observations enabled both estimation of sampling bias and construction of bias-corrected species distribution models. Conditioning δD assignments on these species distribution models yielded comparably high-resolution assignments. Most Virginia rails wintering across five Gulf Coast sites spent the previous summer near the Great Lakes, although a considerable minority originated from the Chesapeake Bay watershed or Prairie Pothole region of North Dakota. Conversely, the majority of migrating Virginia rails from a site in the Great Lakes most likely spent the previous winter on the Gulf Coast between Texas and Louisiana. Synthesis and applications. In this analysis, Virginia rail migratory connectivity does not fully correspond to the administrative flyways used to manage migratory birds. This example demonstrates that with the increasing availability of citizen science data to create species distribution models, our framework can produce high-resolution estimates of migratory connectivity for many animals, including cryptic species. Empirical evidence of links between seasonal habitats will help enable effective habitat management, hunting quotas and population monitoring and also highlight critical knowledge gaps

Combining citizen science species distribution models and stable isotopes reveals migratory connectivity in the secretive Virginia rail

© 2016 The Authors. Journal of Applied Ecology © 2016 British Ecological Society Stable hydrogen isotope (δD) methods for tracking animal movement are widely used yet often produce low resolution assignments. Incorporating prior knowledge of abundance, distribution or movement patterns can ameliorate this limitation, but data are lacking for most species. We demonstrate how observations reported by citizen scientists can be used to develop robust estimates of species distributions and to constrain δD assignments. We developed a Bayesian framework to refine isotopic estimates of migrant animal origins conditional on species distribution models constructed from citizen scientist observations. To illustrate this approach, we analysed the migratory connectivity of the Virginia rail Rallus limicola, a secretive and declining migratory game bird in North America. Citizen science observations enabled both estimation of sampling bias and construction of bias-corrected species distribution models. Conditioning δD assignments on these species distribution models yielded comparably high-resolution assignments. Most Virginia rails wintering across five Gulf Coast sites spent the previous summer near the Great Lakes, although a considerable minority originated from the Chesapeake Bay watershed or Prairie Pothole region of North Dakota. Conversely, the majority of migrating Virginia rails from a site in the Great Lakes most likely spent the previous winter on the Gulf Coast between Texas and Louisiana. Synthesis and applications. In this analysis, Virginia rail migratory connectivity does not fully correspond to the administrative flyways used to manage migratory birds. This example demonstrates that with the increasing availability of citizen science data to create species distribution models, our framework can produce high-resolution estimates of migratory connectivity for many animals, including cryptic species. Empirical evidence of links between seasonal habitats will help enable effective habitat management, hunting quotas and population monitoring and also highlight critical knowledge gaps