Improved functional mapping of complex trait heritability with GSA-MiXeR implicates biologically specific gene sets.

While genome-wide association studies are increasingly successful in discovering genomic loci associated with complex human traits and disorders, the biological interpretation of these findings remains challenging. Here we developed the GSA-MiXeR analytical tool for gene set analysis (GSA), which fits a model for the heritability of individual genes, accounting for linkage disequilibrium across variants and allowing the quantification of partitioned heritability and fold enrichment for small gene sets. We validated the method using extensive simulations and sensitivity analyses. When applied to a diverse selection of complex traits and disorders, including schizophrenia, GSA-MiXeR prioritizes gene sets with greater biological specificity compared to standard GSA approaches, implicating voltage-gated calcium channel function and dopaminergic signaling for schizophrenia. Such biologically relevant gene sets, often with fewer than ten genes, are more likely to provide insights into the pathobiology of complex diseases and highlight potential drug targets.

Prognostic value of pulmonary diffusing capacity for carbon monoxide and ventilation-perfusion SPECT findings in pulmonary arterial hypertension.

Reduced pulmonary diffusing capacity for carbon monoxide (DLCO) can be observed in pulmonary arterial hypertension (PAH) and associates with increased mortality. However, the prognostic value of DLCO when corrected for haemoglobin (DLCOc), an independent modifier of DLCO, remains understudied. Additionally, the prognostic role of ventilation (V)-perfusion (Q) emission computed tomography (V/Q SPECT) findings in patients with PAH, which may concurrently be performed to rule out chronic thromboembolic pulmonary hypertension, is uncertain. A retrospective cohort study was conducted on 152 patients with PAH referred to a tertiary hospital for evaluation from January 2011 to January 2020. Lung function tests, clinical data and V/Q SPECT were ascertained. Cox regression analysis was performed to evaluate the association between DLCOc, DLCO and V/Q SPECT defects at referral with all-cause mortality. In equally adjusted Cox regression analysis, each percentage increase in DLCOc % predicted (%pred) (hazard ratio (HR) 0.97; 95% CI: 0.94-0.99) and DLCO%pred (HR 0.97; 95% CI: 0.94-0.99) was similarly associated with all-cause mortality. There was no detectable difference in area under the curve for prediction of all-cause mortality by DLCOc%pred and DLCO%pred (C-index 0.71 and 0.72, respectively, P = 0.85 for difference). None of the defects noted on V/Q SPECT were significantly associated with mortality, but mismatched defects were associated with lower values of DLCOc%pred and DLCO%pred. DLCOc%pred and DLCO%pred perform equally as prognostic markers in PAH, supporting the use of either metric when available for prognostic stratification.

H3.3-G34W in giant cell tumor of bone functionally aligns with the exon choice repressor hnRNPA1L2.

RNA processing is an essential post-transcriptional phenomenon that provides the necessary complexity of transcript diversity prior to translation. Aberrations in this process could contribute to tumourigenesis, and we have previously reported increased splicing alterations in giant cell tumor of bone (GCTB), which carries mutations in the histone variant H3.3 encoding glycine 34 substituted for tryptophan (H3.3-G34W). G34W interacts with several splicing factors, most notably the trans-acting splicing factor hnRNPA1L2. To gain a deeper understanding of RNA processing in GCTB and isogenic HeLa cells with H3.3-G34W, we generated RNA-immunoprecipitation sequencing data from hnRNPA1L2 and H3.3-G34W associated RNAs, which showed that 80% overlapped across genic regions and were frequently annotated as E2F transcription factor binding sites. Splicing aberrations in both GCTB and HeLa cells with H3.3-G34W were significantly enriched for known hnRNPA1L2 binding motifs (p value < 0.01). This splicing aberration differed from hnRNPA1L2 knockouts, which showed alterations independent of H3.3-G34W. Of functional significance, hnRNPA1L2 was redistributed to closely match the H3.3 pattern, likely driven by G34W, and to loci not occupied in normal parental cells. Taken together, our data reveal a functional overlap between hnRNPA1L2 and H3.3-G34W with likely significant consequences for RNA processing during GCTB pathogenesis. This provides novel opportunities for therapeutic intervention in future modus operandi.

The left atrial appendage closure by surgery 2 trial: statistical analysis plan for a randomized multicenter trial exploring if the closure of the left atrial appendage during open-heart surgery reduces stroke irrespective of patients' stroke risk and preoperative atrial fibrillation status.

BACKGROUND: Surgical left atrial appendage (LAA) closure concomitant to open-heart surgery prevents thromboembolism in high-risk patients. Nevertheless, high-level evidence does not exist for LAA closure performed in patients with any CHA2DS2-VASc score and preoperative atrial fibrillation or flutter (AF) status-the current trial attempts to provide such evidence. METHODS: The study is designed as a randomized, open-label, blinded outcome assessor, multicenter trial of adult patients undergoing first-time elective open-heart surgery. Patients with and without AF and any CHA2DS2-VASc score will be enrolled. The primary exclusion criteria are planned LAA closure, planned AF ablation, or ongoing endocarditis. Before randomization, a three-step stratification process will sort patients by site, surgery type, and preoperative or expected oral anticoagulation treatment. Patients will undergo balanced randomization (1:1) to LAA closure on top of the planned cardiac surgery or standard care. Block sizes vary from 8 to 16. Neurologists blinded to randomization will adjudicate the primary outcome of stroke, including transient ischemic attack (TIA). The secondary outcomes include a composite outcome of stroke, including TIA, and silent cerebral infarcts, an outcome of ischemic stroke, including TIA, and a composite outcome of stroke and all-cause mortality. LAA closure is expected to provide a 60% relative risk reduction. In total, 1500 patients will be randomized and followed for 2 years. DISCUSSION: The trial is expected to help form future guidelines within surgical LAA closure. This statistical analysis plan ensures transparency of analyses and limits potential reporting biases. TRIAL REGISTRATION: Clinicaltrials.gov, NCT03724318. Registered 26 October 2018, https://clinicaltrials.gov/study/NCT03724318 . PROTOCOL VERSION: https://doi.org/10.1016/j.ahj.2023.06.003 .

Dissecting the Shared Genetic Architecture of Common Epilepsies With Cortical Brain Morphology.

Background and Objectives: Epilepsies are associated with differences in cortical thickness (TH) and surface area (SA). However, the mechanisms underlying these relationships remain elusive. We investigated the extent to which these phenotypes share genetic influences. Methods: We analyzed genome-wide association study data on common epilepsies (n = 69,995) and TH and SA (n = 32,877) using Gaussian mixture modeling MiXeR and conjunctional false discovery rate (conjFDR) analysis to quantify their shared genetic architecture and identify overlapping loci. We biologically interrogated the loci using a variety of resources and validated in independent samples. Results: The epilepsies (2.4 k-2.9 k variants) were more polygenic than both SA (1.8 k variants) and TH (1.3 k variants). Despite absent genome-wide genetic correlations, there was a substantial genetic overlap between SA and genetic generalized epilepsy (GGE) (1.1 k), all epilepsies (1.1 k), and juvenile myoclonic epilepsy (JME) (0.7 k), as well as between TH and GGE (0.8 k), all epilepsies (0.7 k), and JME (0.8 k), estimated with MiXeR. Furthermore, conjFDR analysis identified 15 GGE loci jointly associated with SA and 15 with TH, 3 loci shared between SA and childhood absence epilepsy, and 6 loci overlapping between SA and JME. 23 loci were novel for epilepsies and 11 for cortical morphology. We observed a high degree of sign concordance in the independent samples. Discussion: Our findings show extensive genetic overlap between generalized epilepsies and cortical morphology, indicating a complex genetic relationship with mixed-effect directions. The results suggest that shared genetic influences may contribute to cortical abnormalities in epilepsies.

Associations of plasma neurofilament light chain with cognition and neuroimaging measures in community-dwelling early old age men.

BACKGROUND: Plasma neurofilament light chain (NfL) is a promising biomarker of neurodegeneration with potential clinical utility in monitoring the progression of neurodegenerative diseases. However, the cross-sectional associations of plasma NfL with measures of cognition and brain have been inconsistent in community-dwelling populations. METHODS: We examined these associations in a large community-dwelling sample of early old age men (N = 969, mean age = 67.57 years, range = 61-73 years), who are either cognitively unimpaired (CU) or with mild cognitive impairment (MCI). Specifically, we investigated five cognitive domains (executive function, episodic memory, verbal fluency, processing speed, visual-spatial ability), as well as neuroimaging measures of gray and white matter. RESULTS: After adjusting for age, health status, and young adult general cognitive ability, plasma NfL level was only significantly associated with processing speed and white matter hyperintensity (WMH) volume, but not with other cognitive or neuroimaging measures. The association with processing speed was driven by individuals with MCI, as it was not detected in CU individuals. CONCLUSIONS: These results suggest that in early old age men without dementia, plasma NfL does not appear to be sensitive to cross-sectional individual differences in most domains of cognition or neuroimaging measures of gray and white matter. The revealed plasma NfL associations were limited to WMH for all participants and processing speed only within the MCI cohort. Importantly, considering cognitive status in community-based samples will better inform the interpretation of the relationships of plasma NfL with cognition and brain and may help resolve mixed findings in the literature.

Unraveling the shared genetics of common epilepsies and general cognitive ability.

Objective: Cognitive impairment is prevalent among individuals with epilepsy, and it is possible that genetic factors can underlie this relationship. Here, we investigated the potential shared genetic basis of common epilepsies and general cognitive ability (COG). Methods: We applied linkage disequilibrium score (LDSC) regression, MiXeR and conjunctional false discovery rate (conjFDR) to analyze different aspects of genetic overlap between COG and epilepsies. We used the largest available genome-wide association study data on COG (n = 269,867) and common epilepsies (n = 27,559 cases, 42,436 controls), including the broad phenotypes 'all epilepsy', focal epilepsies and genetic generalized epilepsies (GGE), and as well as specific subtypes. We functionally annotated the identified loci using a variety of biological resources and validated the results in independent samples. Results: Using MiXeR, COG (11.2k variants) was estimated to be almost four times more polygenic than 'all epilepsy', GGE, juvenile myoclonic epilepsy (JME), and childhood absence epilepsy (CAE) (2.5k - 2.9k variants). The other epilepsy phenotypes were insufficiently powered for analysis. We show extensive genetic overlap between COG and epilepsies with significant negative genetic correlations (-0.23 to -0.04). COG was estimated to share 2.9k variants with both GGE and 'all epilepsy', and 2.3k variants with both JME and CAE. Using conjFDR, we identified 66 distinct loci shared between COG and epilepsies, including novel associations for GGE (27), 'all epilepsy' (5), JME (5) and CAE (5). The implicated genes were significantly expressed in multiple brain regions. The results were validated in independent samples (COG: p = 1.0 × 10-14; 'all epilepsy': p = 5.6 × 10-3). Significance: Our study demonstrates a substantial genetic basis shared between epilepsies and COG and identifies novel overlapping genomic loci. Enhancing our understanding of the relationship between epilepsies and COG may lead to the development of novel comorbidity-targeted epilepsy treatments.

Genome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder.

Post-traumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 new). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (for example, GRIA1, GRM8 and CACNA1E), developmental, axon guidance and transcription factors (for example, FOXP2, EFNA5 and DCC), synaptic structure and function genes (for example, PCLO, NCAM1 and PDE4B) and endocrine or immune regulators (for example, ESR1, TRAF3 and TANK). Additional top genes influence stress, immune, fear and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation.

Genetic evidence for the causal effects of C-reactive protein on self-reported habitual sleep duration.

Inflammatory responses to acute stimuli are proposed to regulate sleep, but the relationship between chronic inflammation and habitual sleep duration is elusive. Here, we study this relation using genetically predicted level of chronic inflammation, indexed by CRP and IL6 signaling, and self-reported sleep duration. By Mendelian randomization analysis, we show that elevated CRP level within <10 mg/L has a homeostatic effect that facilitates maintaining 7-8 h sleep duration per day - making short-sleepers sleep longer (p = 2.42 × 10-2) and long-sleepers sleep shorter (1.87 × 10-7); but it is not associated with the overall sleep duration (p = 0.17). This homeostatic effect replicated in an independent CRP dataset. We observed causal effects of the soluble interleukin 6 receptor and gp130 on overall sleep duration (p = 1.62 × 10-8, p = 2.61 × 10-58, respectively), but these effects disappeared when CRP effects were accounted for in the model. Using polygenic score analysis, we found that the homeostatic effect of CRP on sleep duration stems primarily from the genetic variants within the CRP gene region: when genetic variants outside of this region were used to predict CRP levels, the opposite direction of effect was observed. In conclusion, we show that elevated CRP level may causally facilitate maintaining an optimal sleep duration that is beneficial to health, thus updating our current knowledge of immune regulation on sleep.

Dissecting the genetic overlap between three complex phenotypes with trivariate MiXeR.

Comorbidities are an increasing global health challenge. Accumulating evidence suggests overlapping genetic architectures underlying comorbid complex human traits and disorders. The bivariate causal mixture model (MiXeR) can quantify the polygenic overlap between complex phenotypes beyond global genetic correlation. Still, the pattern of genetic overlap between three distinct phenotypes, which is important to better characterize multimorbidities, has previously not been possible to quantify. Here, we present and validate the trivariate MiXeR tool, which disentangles the pattern of genetic overlap between three phenotypes using summary statistics from genome-wide association studies (GWAS). Our simulations show that the trivariate MiXeR can reliably reconstruct different patterns of genetic overlap. We further demonstrate how the tool can be used to estimate the proportions of genetic overlap between three phenotypes using real GWAS data, providing examples of complex patterns of genetic overlap between diverse human traits and diseases that could not be deduced from bivariate analyses. This contributes to a better understanding of the etiology of complex phenotypes and the nature of their relationship, which may aid in dissecting comorbidity patterns and their biological underpinnings.

FEMA: Fast and efficient mixed-effects algorithm for large sample whole-brain imaging data.

The linear mixed-effects model (LME) is a versatile approach to account for dependence among observations. Many large-scale neuroimaging datasets with complex designs have increased the need for LME; however LME has seldom been used in whole-brain imaging analyses due to its heavy computational requirements. In this paper, we introduce a fast and efficient mixed-effects algorithm (FEMA) that makes whole-brain vertex-wise, voxel-wise, and connectome-wide LME analyses in large samples possible. We validate FEMA with extensive simulations, showing that the estimates of the fixed effects are equivalent to standard maximum likelihood estimates but obtained with orders of magnitude improvement in computational speed. We demonstrate the applicability of FEMA by studying the cross-sectional and longitudinal effects of age on region-of-interest level and vertex-wise cortical thickness, as well as connectome-wide functional connectivity values derived from resting state functional MRI, using longitudinal imaging data from the Adolescent Brain Cognitive DevelopmentSM Study release 4.0. Our analyses reveal distinct spatial patterns for the annualized changes in vertex-wise cortical thickness and connectome-wide connectivity values in early adolescence, highlighting a critical time of brain maturation. The simulations and application to real data show that FEMA enables advanced investigation of the relationships between large numbers of neuroimaging metrics and variables of interest while considering complex study designs, including repeated measures and family structures, in a fast and efficient manner. The source code for FEMA is available via: https://github.com/cmig-research-group/cmig_tools/.

Anti-obesity effect of butyrate links to modulation of gut microbiome and epigenetic regulation of muscular circadian clock.

The role of the muscle circadian clock in regulating oxidative metabolism exerts a significant influence on whole-body energy metabolism; however, research on the connection between the muscle circadian clock and obesity is limited. Moreover, there is a lack of studies demonstrating the regulatory effects of dietary butyrate on muscle circadian clock and the resulting antiobesity effects. This study aimed to investigate the impacts of dietary butyrate on metabolic and microbiome alterations and muscle circadian clock in a diet-induced obesity model. Male Sprague-Dawley rats were fed a high-fat diet with or without butyrate. Gut microbiota and serum metabolome were analyzed, and molecular changes were examined using tissues and a cell line. Further correlation analysis was performed on butyrate-induced results. Butyrate supplementation reduced weight gain, even with increased food intake. Gut microbiome analysis revealed an increased abundance of Firmicutes in butyrate group. Serum metabolite profile in butyrate group exhibited reduced amino acid and increased fatty acid content. Muscle circadian clock genes were upregulated, resulting in increased transcription of fatty acid oxidation-related genes. In myoblast cells, butyrate also enhanced pan-histone acetylation via histone deacetylase inhibition, particularly modulating acetylation at the promoter of circadian clock genes. Correlation analysis revealed potential links between Firmicutes phylum, including certain genera within it, and butyrate-induced molecular changes in muscle as well as phenotypic alterations. The butyrate-driven effects on diet-induced obesity were associated with alterations in gut microbiota and a muscle-specific increase in histone acetylation, leading to the transcriptional activation of circadian clock genes and their controlled genes.

Individual sleep need is flexible and dynamically related to cognitive function.

Given that sleep deprivation studies consistently show that short sleep causes neurocognitive deficits, the effects of insufficient sleep on brain health and cognition are of great interest and concern. Here we argue that experimentally restricted sleep is not a good model for understanding the normal functions of sleep in naturalistic settings. Cross-disciplinary research suggests that human sleep is remarkably dependent on environmental conditions and social norms, thus escaping universally applicable rules. Sleep need varies over time and differs between individuals, showing a complex relationship with neurocognitive function. This aspect of sleep is rarely addressed in experimental work and is not reflected in expert recommendations about sleep duration. We recommend focusing on the role of individual and environmental factors to improve our understanding of the relationship between human sleep and cognition.

Elevated plasma triglycerides increase risk of psoriasis: A cohort and Mendelian randomization study.

BACKGROUND: It is increasingly clear that triglyceride-rich lipoproteins are proinflammatory and cause low-grade systemic inflammation. However, it is currently unknown whether elevated plasma triglycerides are causally related to development of psoriasis, a skin disorder driven by chronic inflammation. OBJECTIVE: To determine if elevated plasma triglycerides are associated with increased risk of psoriasis in observational and Mendelian randomization analysis. METHODS: Consecutive individuals from the Copenhagen General Population Study (CGPS) were included. We used plasma triglycerides (n = 108,043) and a weighted triglyceride allele score (n = 92,579) on nine known triglyceride-altering genetic variants. Genetic results were replicated in 337,159 individuals from the UK biobank. Psoriasis was ICD10-code hospital contact in main analyses, and prescription of topical antipsoriatics for mild psoriasis in sensitivity analysis. RESULTS: During a median 9.3 years (0.1-15.1) of follow-up (from 2003-2015 through 2018), 855 (1%) individuals were diagnosed with psoriasis by ICD-10 in observational analysis and 772 (1%) in Mendelian randomization analysis. In observational analysis, multivariable adjusted hazard ratio for psoriasis by ICD-10 were 1.26 (95% CI:1.15-1.39) per doubling in plasma triglycerides with a corresponding causal, genetic risk ratio of 2.10 (1.30-3.38). Causality was confirmed in the UK biobank. Results were similar but slightly attenuated when we used topical antipsoriatics prescription for mild psoriasis. CONCLUSION: Elevated plasma triglycerides are associated with increased risk of psoriasis in observational and Mendelian randomization analysis.

Development and validation of the ASGARD risk score for safe monitoring in asymptomatic nonsevere aortic stenosis.

AIMS: Current guidelines recommend serial echocardiography at minimum 1-2 year intervals for monitoring patients with nonsevere aortic valve stenosis (AS), which is costly and often clinically inconsequential.We aimed to develop and test whether the biomarker-based ASGARD risk score (Aortic Valve Stenosis Guarded by Amplified Risk Determination) can guide the timing of echocardiograms in asymptomatic patients with nonsevere AS. METHODS: The development cohort comprised 1,093 of 1,589 (69%) asymptomatic patients with mild-to-moderate AS who remained event-free one year after inclusion into the SEAS trial. Cox regression landmark analyses with a 2-year follow-up identified the model (ASGARD) with the lowest Akaike information criterion for association to AS-related composite outcome (heart failure hospitalization, aortic valve replacement, or cardiovascular death). Fine-Gray analyses provided cumulative event rates by ASGARD score quartiles. The ASGARD score was internally validated in the remaining 496 patients (31%) from the SEAS-cohort and externally in 71 asymptomatic outpatients with nonsevere AS from six Copenhagen hospitals. RESULTS: The ASGARD score comprises updated measurements of heart rate and age- and sex-adjusted N-terminal pro-brain natriuretic peptide upon transaortic maximal velocity (Vmax) from the previous year. The ASGARD score had high predictive accuracy across all cohorts (external validation: area under the curve: 0.74 [95% CI, 0.62-0.86]), and similar to an updated Vmax measurement. An ASGARD score ≤50% was associated with AS-related event rates ≤5% for a minimum of 15 months. CONCLUSION: The ASGARD score could provide a personalized and safe surveillance alternative to routinely planned echocardiograms, so physicians can prioritize echocardiograms for high-risk patients.

In this study, we developed and examined the potential of the novel ASGARD risk score to tailor personalized follow-up intervals for diagnostic heart scans, incorporating updated heart rate and blood marker measurements along with the heart scan data from the previous year. Patients with the ASGARD risk score within the lowest 50% had a low annual risk of aortic valve-related events (less than 5%) for a minimum of 15 months.In clinical settings, the ASGARD score could provide a personalized and safe monitoring alternative to routine heart scans, prioritizing the diagnostic heart scans for high-risk patients.

Quantitative MRI biomarker for classification of clinically significant prostate cancer: calibration for reproducibility across echo times.

Background: Restriction Spectrum Imaging restriction score (RSIrs) is a quantitative biomarker for detecting clinically significant prostate cancer (csPCa). However, the quantitative value of the RSIrs is affected by imaging parameters such as echo time (TE). Purpose: The purpose of the present study is to develop a calibration method to account for differences in echo times and facilitate use of RSIrs as a quantitative biomarker for the detection of csPCa. Methods: This study included 197 consecutive patients who underwent MRI and biopsy examination; 97 were diagnosed with csPCa (grade group ≥ 2). RSI data were acquired three times during the same session: twice at minimum TE∼75ms and once at TE=90ms (TEmin 1 , TEmin 2 , and TE90, respectively). A proposed calibration method, trained on patients without csPCa, estimated a linear scaling factor (f) for each of the four diffusion compartments (C) of the RSI signal model. A linear regression model was determined to match C-maps of TE90 to the reference C-maps of TEmin 1 within the interval ranging from 95 th to 99 th percentile of signal intensity within the prostate. RSIrs comparisons were made at 98 th percentile within each patient's prostate. We compared RSIrs from calibrated TE90 (RSIrs TE90corr ) and uncorrected TE90 (RSIrs TE90 ) to RSIrs from reference TEmin 1 (RSIrs TEmin1 ) and repeated TEmin 2 (RSIrs TEmin2 ). Calibration performance was evaluated with sensitivity, specificity, area under the ROC curve, positive predicted value, negative predicted value, and F1-score. Results: Scaling factors for C 1 , C 2 , C 3 , and C 4 were estimated as 1.70, 1.38, 1.03, and 1.19, respectively. In non-csPCa cases, the 98 th percentile of RSIrs TEmin2 and RSIrs TEmin1 differed by 0.27±0.86SI (mean±standard deviation), whereas RSIrs TE90 differed from RSIrs TEmin1 by 1.81±1.20SI. After calibration, this bias was reduced to -0.41±1.20SI, representing a 78% reduction in absolute error. For patients with csPCa, the difference was 0.54±1.98SI between RSIrs TEmin2 and RSIrs TEmin1 and 2.28±2.06SI between RSIrs TE90 and RSIrs TEmin1 . After calibration, the mean difference decreased to -0.86SI, a 38% reduction in absolute error. At the Youden index for patient-level classification of csPCa (8.94SI), RSIrs TEmin1 has a sensitivity of 66% and a specificity of 72%. Prior to calibration, RSIrs TE90 at the same threshold tended to over-diagnose benign cases (sensitivity 44%, specificity 88%). Post-calibration, RSIrs TE90corr performs more similarly to the reference (sensitivity 71%, specificity 62%). Conclusion: The proposed linear calibration method produces similar quantitative biomarker values for acquisitions with different TE, reducing TE-induced error by 78% and 38% for non-csPCa and csPCa, respectively.

How Real-World Data Can Facilitate the Development of Precision Medicine Treatment in Psychiatry.

Precision medicine has the ambition to improve treatment response and clinical outcomes through patient stratification and holds great potential for the treatment of mental disorders. However, several important factors are needed to transform current practice into a precision psychiatry framework. Most important are 1) the generation of accessible large real-world training and test data including genomic data integrated from multiple sources, 2) the development and validation of advanced analytical tools for stratification and prediction, and 3) the development of clinically useful management platforms for patient monitoring that can be integrated into health care systems in real-life settings. This narrative review summarizes strategies for obtaining the key elements-well-powered samples from large biobanks integrated with electronic health records and health registry data using novel artificial intelligence algorithms-to predict outcomes in severe mental disorders and translate these models into clinical management and treatment approaches. Key elements are massive mental health data and novel artificial intelligence algorithms. For the clinical translation of these strategies, we discuss a precision medicine platform for improved management of mental disorders. We use cases to illustrate how precision medicine interventions could be brought into psychiatry to improve the clinical outcomes of mental disorders.

First experiences of a hospital-based 3D printing facility - an analytical observational study.

PURPOSE: To identify the clinical impact and potential benefits of in-house 3D-printed objects through a questionnaire, focusing on three principal areas: patient education; interdisciplinary cooperation; preoperative planning and perioperative execution. MATERIALS AND METHODS: Questionnaires were sent from January 2021 to August 2022. Participants were directed to rate on a scale from 1 to 10. RESULTS: The response rate was 43%. The results of the rated questions are averages. 84% reported using 3D-printed objects in informing the patient about their condition/procedure. Clinician-reported improvement in patient understanding of their procedure/disease was 8.1. The importance of in-house placement was rated 9.2. 96% reported using the 3D model to confer with colleagues. Delay in treatment due to 3D printing lead-time was 1.8. The degree with which preoperative planning was altered was 6.9. The improvement in clinician perceived preoperative confidence was 8.3. The degree with which the scope of the procedure was affected, in regard to invasiveness, was 5.6, wherein a score of 5 is taken to mean unchanged. Reduction in surgical duration was rated 5.7. CONCLUSION: Clinicians report the utilization of 3D printing in surgical specialties improves procedures pre- and intraoperatively, has a potential for increasing patient engagement and insight, and in-house location of a 3D printing center results in improved interdisciplinary cooperation and allows broader access with only minimal delay in treatment due to lead-time.

Genome-wide analyses reveal shared genetic architecture and novel risk loci between opioid use disorder and general cognitive ability.

BACKGROUND: Opioid use disorder (OUD), a serious health burden worldwide, is associated with lower cognitive function. Recent studies have demonstrated a negative genetic correlation between OUD and general cognitive ability (COG), indicating a shared genetic basis. However, the specific genetic variants involved, and the underlying molecular mechanisms remain poorly understood. Here, we aimed to quantify and identify the genetic basis underlying OUD and COG. METHODS: We quantified the extent of genetic overlap between OUD and COG using a bivariate causal mixture model (MiXeR) and identified specific genetic loci applying conditional/conjunctional FDR. Finally, we investigated biological function and expression of implicated genes using available resources. RESULTS: We estimated that ~94% of OUD variants (4.8k out of 5.1k variants) also influence COG. We identified three novel OUD risk loci and one locus shared between OUD and COG. Loci identified implicated biological substrates in the basal ganglia. CONCLUSION: We provide new insights into the complex genetic risk architecture of OUD and its genetic relationship with COG.