Critical assessment of variant prioritization methods for rare disease diagnosis within the rare genomes project.

BACKGROUND: A major obstacle faced by families with rare diseases is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years and causal variants are identified in under 50%, even when capturing variants genome-wide. To aid in the interpretation and prioritization of the vast number of variants detected, computational methods are proliferating. Knowing which tools are most effective remains unclear. To evaluate the performance of computational methods, and to encourage innovation in method development, we designed a Critical Assessment of Genome Interpretation (CAGI) community challenge to place variant prioritization models head-to-head in a real-life clinical diagnostic setting. METHODS: We utilized genome sequencing (GS) data from families sequenced in the Rare Genomes Project (RGP), a direct-to-participant research study on the utility of GS for rare disease diagnosis and gene discovery. Challenge predictors were provided with a dataset of variant calls and phenotype terms from 175 RGP individuals (65 families), including 35 solved training set families with causal variants specified, and 30 unlabeled test set families (14 solved, 16 unsolved). We tasked teams to identify causal variants in as many families as possible. Predictors submitted variant predictions with estimated probability of causal relationship (EPCR) values. Model performance was determined by two metrics, a weighted score based on the rank position of causal variants, and the maximum F-measure, based on precision and recall of causal variants across all EPCR values. RESULTS: Sixteen teams submitted predictions from 52 models, some with manual review incorporated. Top performers recalled causal variants in up to 13 of 14 solved families within the top 5 ranked variants. Newly discovered diagnostic variants were returned to two previously unsolved families following confirmatory RNA sequencing, and two novel disease gene candidates were entered into Matchmaker Exchange. In one example, RNA sequencing demonstrated aberrant splicing due to a deep intronic indel in ASNS, identified in trans with a frameshift variant in an unsolved proband with phenotypes consistent with asparagine synthetase deficiency. CONCLUSIONS: Model methodology and performance was highly variable. Models weighing call quality, allele frequency, predicted deleteriousness, segregation, and phenotype were effective in identifying causal variants, and models open to phenotype expansion and non-coding variants were able to capture more difficult diagnoses and discover new diagnoses. Overall, computational models can significantly aid variant prioritization. For use in diagnostics, detailed review and conservative assessment of prioritized variants against established criteria is needed.

Maternal Periodontitis Prevalence and its Relationship with Preterm and Low-Birth Weight Infants: A Hospital-Based Research.

Introduction: Overall wellness depends on oral health. Epidemiological, clinical, and laboratory studies have linked periodontitis to some systemic diseases. Pregnancy labor, contractions, and delivery are controlled by prostaglandin (PGE 2) levels rise during pregnancy, and labor begins when a critical threshold is reached. These associations support the underlying cause of maternal periodontal disease. Materials and Methods: In the study, 3,885 pregnant women aged 18-40 had singleton babies. All mother participants were clinically evaluated by the primary investigator. The periodontal disease is defined using a few parameters. Based on that the prevalence rate will be evaluated. Result: The prevalence of preterm babies' mothers affected with periodontitis was 0.5% and low-birth weight babies' mothers affected with periodontitis was 1.6%. So, there was a significant result is there. Conclusion: Periodontal health and preterm LBW newborns are highly associated with periodontitis in research. It may modify preterm birth and LBW risk factors. Thus, dentists detect and treat this sickness early, preventing pregnancy difficulties in sensitive mothers.

A novel model to study mechanisms of cholestasis in human cholangiocytes reveals a role for the SIPR2 pathway.

BACKGROUND: Ductular reactivity is central to the pathophysiology of cholangiopathies. Mechanisms underlying the reactive phenotype activation by exogenous inflammatory mediators and bile acids are poorly understood. METHODS: Using human extrahepatic cholangiocyte organoids (ECOs) we developed an injury model emulating the cholestatic microenvironment with exposure to inflammatory mediators and various pathogenic bile acids. Moreover, we explored roles for the bile acid activated Sphingosine-1-phosphate receptor 2 (S1PR2) and potential beneficial effects of therapeutic bile acids UDCA and norUDCA. RESULTS: Synergistic exposure to bile acids (taurocholic acid, glycocholic acid, glycochenodeoxycholic acid) and TNF-α for 24 hours induced a reactive state as measured by ECO diameter, proliferation, lactate dehydrogenase activity and reactive phenotype markers. While NorUDCA and UDCA treatments given 8 hours after injury induction both suppressed reactive phenotype activation and most injury parameters, proliferation was improved by NorUDCA only. Extrahepatic cholangiocyte organoid stimulation with S1PR2 agonist sphingosine-1-phosphate reproduced the cholangiocyte reactive state and upregulated S1PR2 downstream mediators; these effects were suppressed by S1PR2 antagonist JET-013 (JET), downstream mediator extracellular signal-regulated kinase 1/2 inhibitor, and by norUDCA or UDCA treatments. JET also partially suppressed reactive phenotype after bile acid injury. CONCLUSIONS: We developed a novel model to study the reactive cholangiocyte state in response to pathological stimuli in cholestasis and demonstrated a contributory role of S1PR2 signaling in both injury and NorUDCA/UDCA treatments. This model is a valuable tool to further explore the pathophysiology of human cholangiopathies.

MTL neurons phase-lock to human hippocampal theta.

Memory formation depends on neural activity across a network of regions, including the hippocampus and broader medial temporal lobe (MTL). Interactions between these regions have been studied indirectly using functional MRI, but the bases for interregional communication at a cellular level remain poorly understood. Here, we evaluate the hypothesis that oscillatory currents in the hippocampus synchronize the firing of neurons both within and outside the hippocampus. We recorded extracellular spikes from 1854 single- and multi-units simultaneously with hippocampal local field potentials (LFPs) in 28 neurosurgical patients who completed virtual navigation experiments. A majority of hippocampal neurons phase-locked to oscillations in the slow (2-4 Hz) or fast (6-10 Hz) theta bands, with a significant subset exhibiting nested slow theta × beta frequency (13-20 Hz) phase-locking. Outside of the hippocampus, phase-locking to hippocampal oscillations occurred only at theta frequencies and primarily among neurons in the entorhinal cortex and amygdala. Moreover, extrahippocampal neurons phase-locked to hippocampal theta even when theta did not appear locally. These results indicate that spike-time synchronization with hippocampal theta is a defining feature of neuronal activity in the hippocampus and structurally connected MTL regions. Theta phase-locking could mediate flexible communication with the hippocampus to influence the content and quality of memories.

The Role of Natriuretic Peptides in Predicting Adverse Outcomes After Cardiac Surgery: An Updated Systematic Review.

The increasing global burden of cardiovascular disease, particularly, in the aging population, has led to an increase in high-risk cardiac surgical procedures. The current preoperative risk stratification scores, such as the European System for Cardiac Operative Risk Evaluation and the Society for Thoracic Surgeons score, have limitations in their predictive accuracy and tend to underestimate the mortality risk in higher-risk populations. This systematic review aimed to evaluate the utility of natriuretic peptides, brain natriuretic peptide (BNP) and its precursor prohormone (N-terminal prohormone BNP), as predictive biomarkers for adverse outcomes after cardiac surgery. A comprehensive search strategy was performed, and 63 studies involving 40,667 patients who underwent major cardiac operations were included for data extraction. Preoperative levels of BNP and N-terminal prohormone BNP seemed to be associated with an increased risk of short- and long-term mortality, postoperative heart failure, kidney injury, and length of intensive care unit stay. However, their predictive value for postoperative arrhythmias and myocardial infarction was less established. Our findings suggest that natriuretic peptides may play an important role in risk prediction in patients who underwent cardiac surgery. The addition of these biomarkers to the existing clinical risk stratification strategies may enhance their predictive accuracy. However, this needs to be endorsed by data derived from wide-scale clinical trials.

Treatment of Severe COVID-19 Infection With Remdesivir in Peritoneal Dialysis.

End-stage kidney disease (ESKD) has been shown to be correlated with an increased risk of COVID-19 infection and mortality. Remdesivir is an effective non-EUA U.S. Food and Drug Administration (FDA)-approved antiviral agent for the treatment of COVID-19 in hospitalized adult and pediatric patients, though a lack of data has prevented its use in patients with severe kidney disease including dialysis patients. Some observational studies report the use of remdesivir in hemodialysis patients, but there are no reports of patients treated with remdesivir on peritoneal dialysis. Dialysis modalities may affect drug pharmacokinetics, and safety and efficiency of remdesivir in peritoneal dialysis is unknown. We report the first case, to our knowledge, of using remdesivir in a patient treated with peritoneal dialysis with no significant adverse events. This case illustrates the potential for remdesivir to be considered in peritoneal dialysis patients with severe COVID infection. Proper risk analysis and careful monitoring should be done, given the unpredictable clearance of the drug.

Critical assessment of variant prioritization methods for rare disease diagnosis within the Rare Genomes Project.

Background: A major obstacle faced by rare disease families is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years, and causal variants are identified in under 50%. The Rare Genomes Project (RGP) is a direct-to-participant research study on the utility of genome sequencing (GS) for diagnosis and gene discovery. Families are consented for sharing of sequence and phenotype data with researchers, allowing development of a Critical Assessment of Genome Interpretation (CAGI) community challenge, placing variant prioritization models head-to-head in a real-life clinical diagnostic setting. Methods: Predictors were provided a dataset of phenotype terms and variant calls from GS of 175 RGP individuals (65 families), including 35 solved training set families, with causal variants specified, and 30 test set families (14 solved, 16 unsolved). The challenge tasked teams with identifying the causal variants in as many test set families as possible. Ranked variant predictions were submitted with estimated probability of causal relationship (EPCR) values. Model performance was determined by two metrics, a weighted score based on rank position of true positive causal variants and maximum F-measure, based on precision and recall of causal variants across EPCR thresholds. Results: Sixteen teams submitted predictions from 52 models, some with manual review incorporated. Top performing teams recalled the causal variants in up to 13 of 14 solved families by prioritizing high quality variant calls that were rare, predicted deleterious, segregating correctly, and consistent with reported phenotype. In unsolved families, newly discovered diagnostic variants were returned to two families following confirmatory RNA sequencing, and two prioritized novel disease gene candidates were entered into Matchmaker Exchange. In one example, RNA sequencing demonstrated aberrant splicing due to a deep intronic indel in ASNS, identified in trans with a frameshift variant, in an unsolved proband with phenotype overlap with asparagine synthetase deficiency. Conclusions: By objective assessment of variant predictions, we provide insights into current state-of-the-art algorithms and platforms for genome sequencing analysis for rare disease diagnosis and explore areas for future optimization. Identification of diagnostic variants in unsolved families promotes synergy between researchers with clinical and computational expertise as a means of advancing the field of clinical genome interpretation.

Multimodality pictorial review of IgG4-related disease in the abdomen and pelvis.

BACKGROUND: Immunoglobulin G4-related disease (IgG4-RD) is a systemic, immune-mediated disease that can affect multiple organs, including the orbits, salivary glands, thyroid gland, lungs, aorta, pancreas, bile ducts, lymph nodes, and retroperitoneum. While timely diagnosis is particularly important given the efficacy of glucocorticoid treatment for IgG4-RD, accurate recognition can prove a challenge given the overlap between the imaging features of this disease and other entities. PURPOSE: After a review of the epidemiology, pathophysiology, and clinical considerations (including treatment) associated with IgG4-RD, this pictorial review will showcase the variable imaging manifestations of this disease in the abdomen and pelvis. Post-treatment imaging appearance of these entities will be reviewed and mimickers of this disease in the abdomen and pelvis will be presented. CONCLUSION: The presence of mass-like soft tissue with radiographic characteristics of fibrosis affecting multiple organs should raise suspicion for IgG4-RD, although definite diagnosis can only be made with appropriate clinical, serological, and pathologic data.

Transient 2D IR Spectroscopy and Multiscale Simulations Reveal Vibrational Couplings in the Cyanobacteriochrome Slr1393-g3.

Cyanobacteriochromes are bistable photoreceptor proteins with desirable photochemical properties for biotechnological applications, such as optogenetics or fluorescence microscopy. Here, we investigate Slr1393-g3, a cyanobacteriochrome that reversibly photoswitches between a red-absorbing (Pr) and green-absorbing (Pg) form. We applied advanced IR spectroscopic methods to track the sequence of intermediates during the photocycle over many orders of magnitude in time. In the conversion from Pg to Pr, we have revealed a new intermediate with distinct spectroscopic features in the IR, which precedes Pr formation using transient IR spectroscopy. In addition, stationary and transient 2D IR experiments measured the vibrational couplings between different groups of the chromophore and the protein in these intermediate states, as well as their structural disorder. Anharmonic QM/MM calculations predict spectra in good agreement with experimental 2D IR spectra of the initial and final states of the photocycle. They facilitate the assignment of the IR spectra that serve as a basis for the interpretation of the spectroscopic results and suggest structural changes of the intermediates along the photocycle.

Gene expression profile analysis unravelled the systems level association of renal cell carcinoma with diabetic nephropathy and Matrix-metalloproteinase-9 as a potential therapeutic target.

Type 2 diabetes (T2D) and cancer share many common risk factors. However, the potential biological link that connects the two at the molecular level is still unclear. The experimental evidence suggests that several genes and their pathways may be involved in developing cancerous conditions associated with diabetes. In this study, we identified the protein-protein interaction (PPI) networks and the hub protein(s) that interlink T2D and cancer using genome-scale differential gene expression profiles. Further, the PPI network of AMP-activated protein kinase (AMPK) in cancer was analyzed to explore novel insights into the molecular association between the two conditions. The densely connected regions were analyzed by constructing the backbone and subnetworks with key nodes and shortest pathways, respectively. The PPI network studies identified Matrix-metalloproteinase-9 (MMP-9) as a hub protein playing a vital role in glomerulonephritis tubular diseases and some genetic kidney diseases. MMP-9 was also associated with different growth factors, like tumor necrosis factor (TNF-α), transforming growth factor 1 (TGF-1), and pathways like chemokine signaling, NOD-like receptor signaling, etc. Further, the molecular docking and molecular dynamic simulation studies supported the druggability of MMP-9, suggesting it as a potential therapeutic target in treating renal cell carcinoma linked with diabetic kidney disease.Communicated by Ramaswamy H. Sarma.

Systems Pharmacology and Pharmacokinetics Strategy to Decode Bioactive Ingredients and Molecular Mechanisms from Zingiber officinale as Phyto-therapeutics against Neurological Diseases.

BACKGROUND: The bioactive constituents from Zingiber officinale (Z. officinale) have shown a positive effect on neurodegenerative diseases like Alzheimer's disease (AD), which manifests as progressive memory loss and cognitive impairment. OBJECTIVE: This study investigates the binding ability and the pharmaco-therapeutic potential of Z. officinale with AD disease targets by molecular docking and molecular dynamic (MD) simulation approaches. METHODS: By coupling enormous available phytochemical data and advanced computational technologies, the possible molecular mechanism of action of these bioactive compounds was deciphered by evaluating phytochemicals, target fishing, and network biological analysis. RESULTS: As a result, 175 bioactive compounds and 264 human target proteins were identified. The gene ontology and Kyoto Encyclopaedia of Genes and Genomes pathway enrichment analysis and molecular docking were used to predict the basis of vital bioactive compounds and biomolecular mechanisms involved in the treatment of AD. Amongst selected bioactive compounds, 10- Gingerdione and 1-dehydro-[8]-gingerdione exhibited significant anti-neurological properties against AD targeting amyloid precursor protein with docking energy of -6.0 and -5.6, respectively. CONCLUSION: This study suggests that 10-Gingerdione and 1-dehydro-[8]-gingerdione strongly modulates the anti-neurological activity and are associated with pathological features like amyloid-ß plaques and hyperphosphorylated tau protein are found to be critically regulated by these two target proteins. This comprehensive analysis provides a clue for further investigation of these natural compounds' inhibitory activity in drug discovery for AD treatment.

Photoisomerization of phytochrome chromophore models: an XMS-CASPT2 study.

Phytochromes are a superfamily of photoreceptors that harbor linear tetrapyrroles as chromophores. Upon light illumination, the linear tetrapyrrole chromophore undergoes a double bond isomerization which starts a photocycle. In this work, we studied the photoisomerization of chromophore models designed based on the C- and D-rings of the phycocyanobilin (PCB) chromophore. In total, five different models with varying substitutions were investigated. Firstly, the vertical excitation energies were benchmarked using different computational methods to establish the relative order of the excited states. Based on these calculations, we computed the photoisomerization profiles using the extended multi-state (XMS) version of the CASPT2 method. The profiles were obtained for both the clockwise and counterclockwise rotations of the C15C16 bond in the Z and E isomers using a linear interpolation of internal coordinates between the Franck-Condon and MECI geometries. In the minimal chromophore model that lacks the substitutions at the pyrrole rings, the isomerization involves both C14-C15 and C15C16 bonds of the methine bridge between the C- and D-rings, resembling the hula-twist motion. The MECIs are characterized by a partial charge transfer between the two pyrrole rings pointing towards a twisted intramolecular charge transfer. Systematic introduction of substituents leads to an increase in the steric repulsion between the two pyrrole rings causing a pretwist of the dihedral around the C15C16 bond, which creates a preference for the counterclockwise isomerization. An introduction of the carbonyl group at the D-ring increases the extent of charge transfer which changes the isomerization mechanism from hula-twist to one-bond flip.

A robust host-response-based signature distinguishes bacterial and viral infections across diverse global populations.

Limited sensitivity and specificity of current diagnostics lead to the erroneous prescription of antibiotics. Host-response-based diagnostics could address these challenges. However, using 4,200 samples across 69 blood transcriptome datasets from 20 countries from patients with bacterial or viral infections representing a broad spectrum of biological, clinical, and technical heterogeneity, we show current host-response-based gene signatures have lower accuracy to distinguish intracellular bacterial infections from viral infections than extracellular bacterial infections. Using these 69 datasets, we identify an 8-gene signature to distinguish intracellular or extracellular bacterial infections from viral infections with an area under the receiver operating characteristic curve (AUROC) > 0.91 (85.9% specificity and 90.2% sensitivity). In prospective cohorts from Nepal and Laos, the 8-gene classifier distinguished bacterial infections from viral infections with an AUROC of 0.94 (87.9% specificity and 91% sensitivity). The 8-gene signature meets the target product profile proposed by the World Health Organization and others for distinguishing bacterial and viral infections.

Outcomes Analysis of Textured Versus Smooth Tissue Expanders in Breast Reconstruction.

INTRODUCTION: Because of concerns related to the correlation of breast implant-associated anaplastic large cell lymphoma (BIA-ALCL) and textured implants, the use of smooth devices in breast reconstruction has been increasing. Currently, there is a paucity of literature evaluating the safety of smooth tissue expanders (STEs), which are now being used more frequently in first-stage breast reconstruction. This study sought to compare the safety and outcomes associated with STEs compared with textured tissue expanders in prosthesis-based breast reconstruction. METHODS: A single-institution retrospective review of 394 patients undergoing tissue expander-based breast reconstruction (147 smooth and 247 textured) between 2015 and 2019 was conducted. Patient demographics, comorbidities, treatment characteristics, complications, and surgical outcomes were evaluated. Data analysis was performed using Fisher exact and t tests. RESULTS: No significant difference in demographics or complication rates were identified, including rates of hematoma, seroma, wound dehiscence, delayed wound healing, infection, tissue expander malposition, nipple necrosis, mastectomy flap necrosis, reoperation, readmission, and explantation. Average follow-up was 19 and 22 months for the smooth and textured groups, respectively. No cases of BIA-ALCL were identified in either group. CONCLUSIONS: With equivocal safety profiles and no demonstrated risk in BIA-ALCL associated with STEs, this study supports the safety of using STEs compared with textured tissue expanders in prosthesis-based breast reconstruction with the advantage in preventing BIA-ALCL and concludes that there is no role for textured breast expanders.

Host protease activity classifies pneumonia etiology.

Community-acquired pneumonia (CAP) has been brought to the forefront of global health priorities due to the COVID-19 pandemic. However, classification of viral versus bacterial pneumonia etiology remains a significant clinical challenge. To this end, we have engineered a panel of activity-based nanosensors that detect the dysregulated activity of pulmonary host proteases implicated in the response to pneumonia-causing pathogens and produce a urinary readout of disease. The nanosensor targets were selected based on a human protease transcriptomic signature for pneumonia etiology generated from 33 unique publicly available study cohorts. Five mouse models of bacterial or viral CAP were developed to assess the ability of the nanosensors to produce etiology-specific urinary signatures. Machine learning algorithms were used to train diagnostic classifiers that could distinguish infected mice from healthy controls and differentiate those with bacterial versus viral pneumonia with high accuracy. This proof-of-concept diagnostic approach demonstrates a way to distinguish pneumonia etiology based solely on the host proteolytic response to infection.

An 8-gene machine learning model improves clinical prediction of severe dengue progression.

BACKGROUND: Each year 3-6 million people develop life-threatening severe dengue (SD). Clinical warning signs for SD manifest late in the disease course and are nonspecific, leading to missed cases and excess hospital burden. Better SD prognostics are urgently needed. METHODS: We integrated 11 public datasets profiling the blood transcriptome of 365 dengue patients of all ages and from seven countries, encompassing biological, clinical, and technical heterogeneity. We performed an iterative multi-cohort analysis to identify differentially expressed genes (DEGs) between non-severe patients and SD progressors. Using only these DEGs, we trained an XGBoost machine learning model on public data to predict progression to SD. All model parameters were "locked" prior to validation in an independent, prospectively enrolled cohort of 377 dengue patients in Colombia. We measured expression of the DEGs in whole blood samples collected upon presentation, prior to SD progression. We then compared the accuracy of the locked XGBoost model and clinical warning signs in predicting SD. RESULTS: We identified eight SD-associated DEGs in the public datasets and built an 8-gene XGBoost model that accurately predicted SD progression in the independent validation cohort with 86.4% (95% CI 68.2-100) sensitivity and 79.7% (95% CI 75.5-83.9) specificity. Given the 5.8% proportion of SD cases in this cohort, the 8-gene model had a positive and negative predictive value (PPV and NPV) of 20.9% (95% CI 16.7-25.6) and 99.0% (95% CI 97.7-100.0), respectively. Compared to clinical warning signs at presentation, which had 77.3% (95% CI 58.3-94.1) sensitivity and 39.7% (95% CI 34.7-44.9) specificity, the 8-gene model led to an 80% reduction in the number needed to predict (NNP) from 25.4 to 5.0. Importantly, the 8-gene model accurately predicted subsequent SD in the first three days post-fever onset and up to three days prior to SD progression. CONCLUSIONS: The 8-gene XGBoost model, trained on heterogeneous public datasets, accurately predicted progression to SD in a large, independent, prospective cohort, including during the early febrile stage when SD prediction remains clinically difficult. The model has potential to be translated to a point-of-care prognostic assay to reduce dengue morbidity and mortality without overwhelming limited healthcare resources.

A 6-mRNA host response classifier in whole blood predicts outcomes in COVID-19 and other acute viral infections.

Predicting the severity of COVID-19 remains an unmet medical need. Our objective was to develop a blood-based host-gene-expression classifier for the severity of viral infections and validate it in independent data, including COVID-19. We developed a logistic regression-based classifier for the severity of viral infections and validated it in multiple viral infection settings including COVID-19. We used training data (N = 705) from 21 retrospective transcriptomic clinical studies of influenza and other viral illnesses looking at a preselected panel of host immune response messenger RNAs. We selected 6 host RNAs and trained logistic regression classifier with a cross-validation area under curve of 0.90 for predicting 30-day mortality in viral illnesses. Next, in 1417 samples across 21 independent retrospective cohorts the locked 6-RNA classifier had an area under curve of 0.94 for discriminating patients with severe vs. non-severe infection. Next, in independent cohorts of prospectively (N = 97) and retrospectively (N = 100) enrolled patients with confirmed COVID-19, the classifier had an area under curve of 0.89 and 0.87, respectively, for identifying patients with severe respiratory failure or 30-day mortality. Finally, we developed a loop-mediated isothermal gene expression assay for the 6-messenger-RNA panel to facilitate implementation as a rapid assay. With further study, the classifier could assist in the risk assessment of COVID-19 and other acute viral infections patients to determine severity and level of care, thereby improving patient management and reducing healthcare burden.

Rates and risk factors associated with 30- and 90-day readmissions and reoperations after spinal fusions for adult lumbar degenerative pathology and spinal deformity.

PURPOSE: Analyze state databases to determine variables associated with of short-term readmissions and reoperations following thoracolumbar spine fusions for degenerative pathology and spinal deformity. METHODS: Retrospective study of State Inpatient Database (2005-13, CA, NE, NY, FL, NC, UT). INCLUSION CRITERIA: age > 45 years, diagnosis of degenerative spinal deformity, ≥ 3 level posterolateral lumbar spine fusion. EXCLUSION CRITERIA: revision surgery, cervical fusions, trauma, and cancer. Univariate and step-wise multivariate logistic regression analyses were performed to identify independent variables associated with of 30- and 90-day readmissions and reoperations. RESULTS: 12,641 patients were included. All-cause 30- and 90-day readmission rates were 14.6% and 21.1%, respectively. 90-day readmissions were associated with: age > 80 (OR: 1.42), 8 + level fusions (OR: 1.19), hospital length of stay (LOS) > 7 days (OR: 1.43), obesity (OR: 1.29), morbid obesity (OR: 1.66), academic hospital (OR: 1.13), cancer history (OR:1.21), drug abuse (OR: 1.31), increased Charlson Comorbidity index (OR: 1.12), and depression (OR: 1.20). Private insurance (OR: 0.64) and lumbar-only fusions (OR: 0.87) were not associated with 90-day readmissions. All-cause 30- and 90-day reoperation rates were 1.8% and 4.2%, respectively. Variables associated with 90-day reoperations were 8 + level fusions (OR: 1.28), LOS > 7 days (OR: 1.43), drug abuse (OR: 1.68), osteoporosis (OR: 1.26), and depression (OR: 1.23). Circumferential fusion (OR: 0.58) and lumbar-only fusions (OR: 0.68) were not associated with 90-day reoperations. CONCLUSIONS: 30- and 90-day readmission and reoperation rates in thoracolumbar fusions for adult degenerative pathology and spinal deformity may have been underreported in previously published smaller studies. Identification of modifiable risk factors is important for improving quality of care through preoperative optimization.

Inherited L1 Retrotransposon Insertions Associated With Risk for Schizophrenia and Bipolar Disorder.

Studies of the genetic heritability of schizophrenia and bipolar disorder examining single nucleotide polymorphisms (SNPs) and copy number variations have failed to explain a large portion of the genetic liability, resulting in substantial missing heritability. Long interspersed element 1 (L1) retrotransposons are a type of inherited polymorphic variant that may be associated with risk for schizophrenia and bipolar disorder. We performed REBELseq, a genome wide assay for L1 sequences, on DNA from male and female persons with schizophrenia and controls (n = 63 each) to identify inherited L1 insertions and validated priority insertions. L1 insertions of interest were genotyped in DNA from a replication cohort of persons with schizophrenia, bipolar disorder, and controls (n = 2268 each) to examine differences in carrier frequencies. We identified an inherited L1 insertion in ARHGAP24 and a quadallelic SNP (rs74169643) inside an L1 insertion in SNTG2 that are associated with risk for developing schizophrenia and bipolar disorder (all odds ratios ~1.2). Pathway analysis identified 15 gene ontologies that were differentially affected by L1 burden, including multiple ontologies related to glutamatergic signaling and immune function, which have been previously associated with schizophrenia. These findings provide further evidence supporting the role of inherited repetitive genetic elements in the heritability of psychiatric disorders.

Intraocular iron injection induces oxidative stress followed by elements of geographic atrophy and sympathetic ophthalmia.

Iron has been implicated in the pathogenesis of age-related retinal diseases, including age-related macular degeneration (AMD). Previous work showed that intravitreal (IVT) injection of iron induces acute photoreceptor death, lipid peroxidation, and autofluorescence (AF). Herein, we extend this work, finding surprising chronic features of the model: geographic atrophy and sympathetic ophthalmia. We provide new mechanistic insights derived from focal AF in the photoreceptors, quantification of bisretinoids, and localization of carboxyethyl pyrrole, an oxidized adduct of docosahexaenoic acid associated with AMD. In mice given IVT ferric ammonium citrate (FAC), RPE died in patches that slowly expanded at their borders, like human geographic atrophy. There was green AF in the photoreceptor ellipsoid, a mitochondria-rich region, 4 h after injection, followed later by gold AF in rod outer segments, RPE and subretinal myeloid cells. The green AF signature is consistent with flavin adenine dinucleotide, while measured increases in the bisretinoid all-trans-retinal dimer are consistent with the gold AF. FAC induced formation carboxyethyl pyrrole accumulation first in photoreceptors, then in RPE and myeloid cells. Quantitative PCR on neural retina and RPE indicated antioxidant upregulation and inflammation. Unexpectedly, reminiscent of sympathetic ophthalmia, autofluorescent myeloid cells containing abundant iron infiltrated the saline-injected fellow eyes only if the contralateral eye had received IVT FAC. These findings provide mechanistic insights into the potential toxicity caused by AMD-associated retinal iron accumulation. The mouse model will be useful for testing antioxidants, iron chelators, ferroptosis inhibitors, anti-inflammatory medications, and choroidal neovascularization inhibitors.