Integrating Electronic Health Records and Polygenic Risk to Identify Genetically Unrelated Comorbidities of Schizophrenia That May Be Modifiable.

Background: Patients with schizophrenia have substantial comorbidity that contributes to reduced life expectancy of 10 to 20 years. Identifying modifiable comorbidities could improve rates of premature mortality. Conditions that frequently co-occur but lack shared genetic risk with schizophrenia are more likely to be products of treatment, behavior, or environmental factors and therefore are enriched for potentially modifiable associations. Methods: Phenome-wide comorbidity was calculated from electronic health records of 250,000 patients across 2 independent health care institutions (Vanderbilt University Medical Center and Mass General Brigham); associations with schizophrenia polygenic risk scores were calculated across the same phenotypes in linked biobanks. Results: Schizophrenia comorbidity was significantly correlated across institutions (r = 0.85), and the 77 identified comorbidities were consistent with prior literature. Overall, comorbidity and polygenic risk score associations were significantly correlated (r = 0.55, p = 1.29 × 10-118). However, directly testing for the absence of genetic effects identified 36 comorbidities that had significantly equivalent schizophrenia polygenic risk score distributions between cases and controls. This set included phenotypes known to be consequences of antipsychotic medications (e.g., movement disorders) or of the disease such as reduced hygiene (e.g., diseases of the nail), thereby validating the approach. It also highlighted phenotypes with less clear causal relationships and minimal genetic effects such as tobacco use disorder and diabetes. Conclusions: This work demonstrates the consistency and robustness of electronic health record-based schizophrenia comorbidities across independent institutions and with the existing literature. It identifies known and novel comorbidities with an absence of shared genetic risk, indicating other causes that may be modifiable and where further study of causal pathways could improve outcomes for patients.

Patients with schizophrenia have many co-occurring diseases that contribute substantially to premature mortality of 10 to 20 years. Conditions that are comorbid but lack shared genetic risk with schizophrenia are likely to have causes that are more modifiable. Here, we calculated comorbidity from electronic health records from 2 independent health care institutions and associations with schizophrenia polygenic risk scores across the same phenotypes in linked biobanks. We identified known and novel diseases comorbid with schizophrenia, thereby validating our approach.

Multi-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes.

Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviours and although strides have been made using genome-wide association studies to identify risk variants, most variants identified have been for nicotine consumption, rather than TUD. Here we leveraged four US biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records) in 653,790 individuals (495,005 European, 114,420 African American and 44,365 Latin American) and data from UK Biobank (ncombined = 898,680). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviours in children and hundreds of medical outcomes, including HIV infection, heart disease and pain. This work furthers our biological understanding of TUD and establishes electronic health records as a source of phenotypic information for studying the genetics of TUD.

Identifying modifiable comorbidities of schizophrenia by integrating electronic health records and polygenic risk.

Patients with schizophrenia have substantial comorbidity contributing to reduced life expectancy of 10-20 years. Identifying which comorbidities might be modifiable could improve rates of premature mortality in this population. We hypothesize that conditions that frequently co-occur but lack shared genetic risk with schizophrenia are more likely to be products of treatment, behavior, or environmental factors and therefore potentially modifiable. To test this hypothesis, we calculated phenome-wide comorbidity from electronic health records (EHR) in 250,000 patients in each of two independent health care institutions (Vanderbilt University Medical Center and Mass General Brigham) and association with schizophrenia polygenic risk scores (PRS) across the same phenotypes (phecodes) in linked biobanks. Comorbidity with schizophrenia was significantly correlated across institutions (r = 0.85) and consistent with prior literature. After multiple test correction, there were 77 significant phecodes comorbid with schizophrenia. Overall, comorbidity and PRS association were highly correlated (r = 0.55, p = 1.29×10-118), however, 36 of the EHR identified comorbidities had significantly equivalent schizophrenia PRS distributions between cases and controls. Fifteen of these lacked any PRS association and were enriched for phenotypes known to be side effects of antipsychotic medications (e.g., "movement disorders", "convulsions", "tachycardia") or other schizophrenia related factors such as from smoking ("bronchitis") or reduced hygiene (e.g., "diseases of the nail") highlighting the validity of this approach. Other phenotypes implicated by this approach where the contribution from shared common genetic risk with schizophrenia was minimal included tobacco use disorder, diabetes, and dementia. This work demonstrates the consistency and robustness of EHR-based schizophrenia comorbidities across independent institutions and with the existing literature. It identifies comorbidities with an absence of shared genetic risk indicating other causes that might be more modifiable and where further study of causal pathways could improve outcomes for patients.

Multi-ancestry meta-analysis of tobacco use disorder prioritizes novel candidate risk genes and reveals associations with numerous health outcomes.

Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviors, and although strides have been made using genome-wide association studies (GWAS) to identify risk variants, the majority of variants identified have been for nicotine consumption, rather than TUD. We leveraged five biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records, EHR) in 898,680 individuals (739,895 European, 114,420 African American, 44,365 Latin American). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviors in children, and hundreds of medical outcomes, including HIV infection, heart disease, and pain. This work furthers our biological understanding of TUD and establishes EHR as a source of phenotypic information for studying the genetics of TUD.

Adaptive design clinical trials: current status by disease and trial phase in various perspectives.

An adaptive design is a clinical trial design that allows for modification of a structured plan in a clinical trial based on data accumulated during pre-planned interim analyses. This flexible approach to clinical trial design improves the success rate of clinical trials while reducing time, cost, and sample size compared to conventional methods. The purpose of this study is to identify the current status of adaptive design and present key considerations for planning an appropriate adaptive design based on specific circumstances. We searched for clinical trials conducted between January 2006 to July 2021 in the Clinical Trials Registry (ClinicalTrials.gov) using keywords specified in the Food and Drug Administration Adaptive Design Clinical Trial Guidelines. In order to analyze the adaptive designs used in selected cases, we classified the results according to the phase of the clinical trial, type of indication, and the specific adaptation method employed. A total of 267 clinical trials were identified on ClinicalTrials.gov. Among them, 236 clinical trials actually applied adaptive designs and were classified according to phase, indication types, and adaptation methods. Adaptive designs were most frequently used in phase 2 clinical trials and oncology research. The most commonly used adaptation method was the adaptive treatment selection design. In the case of coronavirus disease 2019, the most frequently used designs were adaptive platform design and seamless design. Through this study, we expect to provide valuable insights and considerations for the implementation of adaptive design clinical trials in different diseases and stages.

Relationship between Preoperative Lower Back Pain and Severe Postoperative Pain after Gynecologic Laparoscopy: A Prospective Observational Study.

We hypothesized that preoperative lower back pain (LBP) may be associated with the severity of postoperative pain after gynecologic laparoscopy. This prospective observational study aimed to investigate the association between preoperative LBP and postoperative pain. We assessed the intensity of LBP before surgery and the postoperative pain after surgery. The abilities of preoperative LBP intensity, age, body mass index, and anesthetic duration time to predict moderate-to-severe postoperative pain were measured using receiver operating characteristic analysis. The data of 148 patients were analyzed. Only preoperative LBP intensity showed a significant association with moderate-to-severe postoperative pain (area under the curve, 0.71; 95% confidence interval, 0.63−0.79; p < 0.001). Preoperative LBP rated three on a numeric rating scale (NRS) had the highest combined sensitivity (75.3%) and specificity (58.3%). Patients with LBP above NRS 3 had more severe postoperative pain than those who did not (pain score 5.3 ± 2.2 vs. 3.9 ± 1.9, p < 0.001), leading to more opioid requirement in the recovery room (48.5% vs. 27.5%, p = 0.014). Preoperative LBP intensity is a useful factor for identifying patients at risk for pain after gynecologic laparoscopy.

Psychological Stress, Smoking, and Hazardous Drinking Behaviors among South Korean Adults: Findings from the Korean National Health and Nutrition Examination Survey.

INTRODUCTION: There is growing attention to mental health as a contributor to behavioral health in South Korea. We investigated the prevalence of psychological stress and its associations with cigarette smoking and drinking behaviors among a nationally representative sample of South Korean adults. METHODS: Using data from 14,855 adults aged ≥19 years who participated in the 2013 to 2016 Korea National Health and Nutrition Examination Survey (KNHANES), we performed weighted logistic regression to examine the associations between stress and three binary outcome variables: cigarette smoking, heavy episodic drinking and frequent drinking. RESULTS: 27.2% of participants reported high stress. Controlling for sociodemographic covariates, high stress was associated with 1.54 times the odds (p<0.001) of being a smoker, 1.25 times the odds (p<0.001) of being a heavy episodic drinker, and 1.23 times the odds (p<0.001) of being a frequent drinker. There was evidence of effect modification by gender and occupation, such that the effects of stress on these behaviors were particularly stronger among women and pink-collar (service industry) workers (compared to men and white-collar workers). CONCLUSIONS: Future policies that aim to address smoking and drinking behaviors in South Korea should consider stress reduction and coping strategies, especially among women and pink-collar workers.

Dual-Functional Electrocatalyst Derived from Iron-Porphyrin-Encapsulated Metal-Organic Frameworks.

Active, stable electrocatalysts based on non-precious metals for the oxygen reduction reaction (ORR) and hydrogen evolution reaction (HER) are critical for the development of cost-effective, efficient renewable energy technologies. Here, Fe/Fe3C-embedded nitrogen-doped carbon was fabricated via pyrolysis of iron-porphyrin-encapsulated mesoporous metal-organic frameworks [PCN-333 (Fe), where "PCN" stands for "porous coordination network"] at 700 °C. The various characterization techniques confirmed that Fe- and Fe3C-containing Fe-N-C material (FeP-P333-700) was successfully prepared by pyrolysis of porphyrin-encapsulated PCN-333 (Fe). FeP-P333-700 exhibited superior electrocatalytic performance for the ORR and HER owing to the synergistic effect of Fe/Fe3C and Fe-N-C active sites.

A facile synthetic strategy for iron, aniline-based non-precious metal catalysts for polymer electrolyte membrane fuel cells.

The development of a low cost and highly active alternative to the commercial Pt/C catalysts used in the oxygen reduction reaction (ORR) requires a facile and environmentally-friendly synthesis process to facilitate large-scale production and provide an effective replacement. Transition metals, in conjunction with nitrogen-doped carbon, are among the most promising substitute catalysts because of their high activity, inexpensive composition, and high carbon monoxide tolerance. We prepared a polyaniline-derived Fe-N-C catalyst for oxygen reduction using a facile one-pot process with no additional reagents. This process was carried out by ultrasonicating a mixture containing an iron precursor, an aniline monomer, and carbon black. The half-wave potential of the synthesized Fe-N-C catalyst for the ORR was only 10 mV less than that of a commercial Pt/C catalyst. The optimized Fe-N-C catalyst showed outstanding performance in a practical anion exchange membrane fuel cell (AEMFC), suggesting its potential as an alternative to commercial Pt/C catalysts for the ORR.