Cellular and Biophysical Applications of Genetic Code Expansion.

Despite their diverse functions, proteins are inherently constructed from a limited set of building blocks. These compositional constraints pose significant challenges to protein research and its practical applications. Strategically manipulating the cellular protein synthesis system to incorporate novel building blocks has emerged as a critical approach for overcoming these constraints in protein research and application. In the past two decades, the field of genetic code expansion (GCE) has achieved significant advancements, enabling the integration of numerous novel functionalities into proteins across a variety of organisms. This technological evolution has paved the way for the extensive application of genetic code expansion across multiple domains, including protein imaging, the introduction of probes for protein research, analysis of protein-protein interactions, spatiotemporal control of protein function, exploration of proteome changes induced by external stimuli, and the synthesis of proteins endowed with novel functions. In this comprehensive Review, we aim to provide an overview of cellular and biophysical applications that have employed GCE technology over the past two decades.

White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group.

White matter pathways, typically studied with diffusion tensor imaging (DTI), have been implicated in the neurobiology of obsessive-compulsive disorder (OCD). However, due to limited sample sizes and the predominance of single-site studies, the generalizability of OCD classification based on diffusion white matter estimates remains unclear. Here, we tested classification accuracy using the largest OCD DTI dataset to date, involving 1336 adult participants (690 OCD patients and 646 healthy controls) and 317 pediatric participants (175 OCD patients and 142 healthy controls) from 18 international sites within the ENIGMA OCD Working Group. We used an automatic machine learning pipeline (with feature engineering and selection, and model optimization) and examined the cross-site generalizability of the OCD classification models using leave-one-site-out cross-validation. Our models showed low-to-moderate accuracy in classifying (1) "OCD vs. healthy controls" (Adults, receiver operator characteristic-area under the curve = 57.19 ± 3.47 in the replication set; Children, 59.8 ± 7.39), (2) "unmedicated OCD vs. healthy controls" (Adults, 62.67 ± 3.84; Children, 48.51 ± 10.14), and (3) "medicated OCD vs. unmedicated OCD" (Adults, 76.72 ± 3.97; Children, 72.45 ± 8.87). There was significant site variability in model performance (cross-validated ROC AUC ranges 51.6-79.1 in adults; 35.9-63.2 in children). Machine learning interpretation showed that diffusivity measures of the corpus callosum, internal capsule, and posterior thalamic radiation contributed to the classification of OCD from HC. The classification performance appeared greater than the model trained on grey matter morphometry in the prior ENIGMA OCD study (our study includes subsamples from the morphometry study). Taken together, this study points to the meaningful multivariate patterns of white matter features relevant to the neurobiology of OCD, but with low-to-moderate classification accuracy. The OCD classification performance may be constrained by site variability and medication effects on the white matter integrity, indicating room for improvement for future research.

Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk.

Machine learning approaches using structural magnetic resonance imaging (sMRI) can be informative for disease classification, although their ability to predict psychosis is largely unknown. We created a model with individuals at CHR who developed psychosis later (CHR-PS+) from healthy controls (HCs) that can differentiate each other. We also evaluated whether we could distinguish CHR-PS+ individuals from those who did not develop psychosis later (CHR-PS-) and those with uncertain follow-up status (CHR-UNK). T1-weighted structural brain MRI scans from 1165 individuals at CHR (CHR-PS+, n = 144; CHR-PS-, n = 793; and CHR-UNK, n = 228), and 1029 HCs, were obtained from 21 sites. We used ComBat to harmonize measures of subcortical volume, cortical thickness and surface area data and corrected for non-linear effects of age and sex using a general additive model. CHR-PS+ (n = 120) and HC (n = 799) data from 20 sites served as a training dataset, which we used to build a classifier. The remaining samples were used external validation datasets to evaluate classifier performance (test, independent confirmatory, and independent group [CHR-PS- and CHR-UNK] datasets). The accuracy of the classifier on the training and independent confirmatory datasets was 85% and 73% respectively. Regional cortical surface area measures-including those from the right superior frontal, right superior temporal, and bilateral insular cortices strongly contributed to classifying CHR-PS+ from HC. CHR-PS- and CHR-UNK individuals were more likely to be classified as HC compared to CHR-PS+ (classification rate to HC: CHR-PS+, 30%; CHR-PS-, 73%; CHR-UNK, 80%). We used multisite sMRI to train a classifier to predict psychosis onset in CHR individuals, and it showed promise predicting CHR-PS+ in an independent sample. The results suggest that when considering adolescent brain development, baseline MRI scans for CHR individuals may be helpful to identify their prognosis. Future prospective studies are required about whether the classifier could be actually helpful in the clinical settings.

Neurocomputational model of compulsivity: deviating from an uncertain goal-directed system.

Despite a theory that an imbalance in goal-directed versus habitual systems serve as building blocks of compulsions, research has yet to delineate how this occurs during arbitration between the two systems in obsessive-compulsive disorder. Inspired by a brain model in which the inferior frontal cortex selectively gates the putamen to guide goal-directed or habitual actions, this study aimed to examine whether disruptions in the arbitration process via the fronto-striatal circuit would underlie imbalanced decision-making and compulsions in patients. Thirty patients with obsessive-compulsive disorder [mean (standard deviation) age = 26.93 (6.23) years, 12 females (40%)] and 30 healthy controls [mean (standard deviation) age = 24.97 (4.72) years, 17 females (57%)] underwent functional MRI scans while performing the two-step Markov decision task, which was designed to dissociate goal-directed behaviour from habitual behaviour. We employed a neurocomputational model to account for an uncertainty-based arbitration process, in which a prefrontal arbitrator (i.e. inferior frontal gyrus) allocates behavioural control to a more reliable strategy by selectively gating the putamen. We analysed group differences in the neural estimates of uncertainty of each strategy. We also compared the psychophysiological interaction effects of system preference (goal-directed versus habitual) on fronto-striatal coupling between groups. We examined the correlation between compulsivity score and the neural activity and connectivity involved in the arbitration process. The computational model captured the subjects' preferences between the strategies. Compared with healthy controls, patients had a stronger preference for the habitual system (t = -2.88, P = 0.006), which was attributed to a more uncertain goal-directed system (t = 2.72, P = 0.009). Before the allocation of controls, patients exhibited hypoactivity in the inferior frontal gyrus compared with healthy controls when this region tracked the inverse of uncertainty (i.e. reliability) of goal-directed behaviour (P = 0.001, family-wise error rate corrected). When reorienting behaviours to reach specific goals, patients exhibited weaker right ipsilateral ventrolateral prefronto-putamen coupling than healthy controls (P = 0.001, family-wise error rate corrected). This hypoconnectivity was correlated with more severe compulsivity (r = -0.57, P = 0.002). Our findings suggest that the attenuated top-down control of the putamen by the prefrontal arbitrator underlies compulsivity in obsessive-compulsive disorder. Enhancing fronto-striatal connectivity may be a potential neurotherapeutic approach for compulsivity and adaptive decision-making.

Magnetic resonance texture analysis reveals stagewise nonlinear alterations of the frontal gray matter in patients with early psychosis.

Although gray matter (GM) abnormalities are present from the early stages of psychosis, subtle/miniscule changes may not be detected by conventional volumetry. Texture analysis (TA), which permits quantification of the complex interrelationship between contrasts at the individual voxel level, may capture subtle GM changes with more sensitivity than does volume or cortical thickness (CTh). We performed three-dimensional TA in nine GM regions of interest (ROIs) using T1 magnetic resonance images from 101 patients with first-episode psychosis (FEP), 85 patients at clinical high risk (CHR) for psychosis, and 147 controls. Via principal component analysis, three features of gray-level cooccurrence matrix - informational measure of correlation 1 (IMC1), autocorrelation (AC), and inverse difference (ID) - were selected to analyze cortical texture in the ROIs that showed a significant change in volume or CTh in the study groups. Significant reductions in GM volume and CTh of various frontotemporal regions were found in the FEP compared with the controls. Increased frontal AC was found in the FEP group compared to the controls after adjusting for volume and CTh changes. While volume and CTh were preserved in the CHR group, a stagewise nonlinear increase in frontal IMC1 was found, which exceeded both the controls and FEP group. Increased frontal IMC1 was also associated with a lesser severity of attenuated positive symptoms in the CHR group, while neither volume nor CTh was. The results of the current study suggest that frontal IMC1 may reflect subtle, dynamic GM changes and the symptomatology of the CHR stage with greater sensitivity, even in the absence of gross GM abnormalities. Some structural mechanisms that may contribute to texture changes (e.g., macrostructural cortical lamina, neuropil/myelination, cortical reorganization) and their possible implications are explored and discussed. Texture may be a useful tool to investigate subtle and dynamic GM abnormalities, especially during the CHR period.

Brain ageing in schizophrenia: evidence from 26 international cohorts via the ENIGMA Schizophrenia consortium.

Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18-72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18-73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.55 years (95% CI: 2.91, 4.19; I2 = 57.53%) compared to controls, after adjusting for age, sex and site (Cohen's d = 0.48). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions.

The functional connectome in obsessive-compulsive disorder: resting-state mega-analysis and machine learning classification for the ENIGMA-OCD consortium.

Current knowledge about functional connectivity in obsessive-compulsive disorder (OCD) is based on small-scale studies, limiting the generalizability of results. Moreover, the majority of studies have focused only on predefined regions or functional networks rather than connectivity throughout the entire brain. Here, we investigated differences in resting-state functional connectivity between OCD patients and healthy controls (HC) using mega-analysis of data from 1024 OCD patients and 1028 HC from 28 independent samples of the ENIGMA-OCD consortium. We assessed group differences in whole-brain functional connectivity at both the regional and network level, and investigated whether functional connectivity could serve as biomarker to identify patient status at the individual level using machine learning analysis. The mega-analyses revealed widespread abnormalities in functional connectivity in OCD, with global hypo-connectivity (Cohen's d: -0.27 to -0.13) and few hyper-connections, mainly with the thalamus (Cohen's d: 0.19 to 0.22). Most hypo-connections were located within the sensorimotor network and no fronto-striatal abnormalities were found. Overall, classification performances were poor, with area-under-the-receiver-operating-characteristic curve (AUC) scores ranging between 0.567 and 0.673, with better classification for medicated (AUC = 0.702) than unmedicated (AUC = 0.608) patients versus healthy controls. These findings provide partial support for existing pathophysiological models of OCD and highlight the important role of the sensorimotor network in OCD. However, resting-state connectivity does not so far provide an accurate biomarker for identifying patients at the individual level.

Cortical gyrification differences between early- and late-onset obsessive-compulsive disorder: neurobiological evidence for neurodevelopmentally distinct subtypes.

BACKGROUND: Identifying more homogenous subtypes of patients with obsessive-compulsive disorder (OCD) using biological evidence is critical for understanding complexities of the disorder in this heterogeneous population. Age of onset serves as a useful subtyping scheme for distinguishing OCD into two subgroups that aligns with neurodevelopmental perspectives. The underlying neurobiological markers for these distinct neurodevelopmental differences can be identified by investigating gyrification changes to establish biological evidence-based homogeneous subtypes. METHODS: We compared whole-brain cortical gyrification in 84 patients with early-onset OCD, 84 patients with late-onset OCD, and 152 healthy controls (HCs) to identify potential markers for early neurodevelopmental deficits using the local gyrification index (lGI). Then, the relationships between lGI in clusters showing significant differences and performance in visuospatial memory and verbal fluency, which are considered trait-related neurocognitive impairments in OCD, were further examined in early-onset OCD patients. RESULTS: The early-onset OCD patients exhibited significantly greater gyrification than those with late-onset OCD patients and HCs in frontoparietal and cingulate regions, including the bilateral precentral, postcentral, precuneus, paracentral, posterior cingulate, superior frontal, and caudal anterior cingulate gyri. Moreover, impaired neurocognitive functions in early-onset OCD patients were correlated with increased gyrification. CONCLUSIONS: Our findings provide a neurobiological marker to distinguish the OCD population into more neurodevelopmentally homogeneous subtypes, which may contribute to the understanding of the neurodevelopmental underpinnings of an etiology in early-onset OCD consistent with the accumulated phenotypic evidence of greater neurodevelopmental deficits in early-onset OCD than in late-onset OCD.

Forecasting prognostic trajectories with mismatch negativity in early psychosis.

BACKGROUND: Prognostic heterogeneity in early psychosis patients yields significant difficulties in determining the degree and duration of early intervention; this heterogeneity highlights the need for prognostic biomarkers. Although mismatch negativity (MMN) has been widely studied across early phases of psychotic disorders, its potential as a common prognostic biomarker in early periods, such as clinical high risk (CHR) for psychosis and first-episode psychosis (FEP), has not been fully studied. METHODS: A total of 104 FEP patients, 102 CHR individuals, and 107 healthy controls (HCs) participated in baseline MMN recording. Clinical outcomes were assessed; 17 FEP patients were treatment resistant, 73 FEP patients were nonresistant, 56 CHR individuals were nonremitters (15 transitioned to a psychotic disorder), and 22 CHR subjects were remitters. Baseline MMN amplitudes were compared across clinical outcome groups and tested for utility prognostic biomarkers using binary logistic regression. RESULTS: MMN amplitudes were greatest in HCs, intermediate in CHR subjects, and smallest in FEP patients. In the clinical outcome groups, MMN amplitudes were reduced from the baseline in both FEP and CHR patients with poor prognostic trajectories. Reduced baseline MMN amplitudes were a significant predictor of later treatment resistance in FEP patients [Exp(ß) = 2.100, 95% confidence interval (CI) 1.104-3.993, p = 0.024] and nonremission in CHR individuals [Exp(ß) = 1.898, 95% CI 1.065-3.374, p = 0.030]. CONCLUSIONS: These findings suggest that MMN could be used as a common prognostic biomarker across early psychosis periods, which will aid clinical decisions for early intervention.

Aberrant cortico-striatal white matter connectivity and associated subregional microstructure of the striatum in obsessive-compulsive disorder.

The striatum and its cortical circuits play central roles in the pathophysiology of obsessive-compulsive disorder (OCD). The striatum is subdivided by cortical connections and functions; however, the anatomical aberrations in different cortico-striatal connections and coexisting microstructural anomalies in striatal subregions of OCD patients are poorly understood. Thus, we aimed to elucidate the aberrations in cortico-striatal white matter (WM) connectivity and the associated subregional microstructure of the striatum in patients with OCD. From diffusion tensor/kurtosis imaging of 107 unmedicated OCD patients and 110 matched healthy controls (HCs), we calculated the cortico-striatal WM connectivity and segmented the striatum using probabilistic tractography. For the segmented striatal subregions, we measured average diffusion kurtosis values, which represent microstructural complexity. Connectivity and mean kurtosis values in each cortical target and associated striatal subregions were compared between groups. We identified significantly reduced orbitofrontal WM connectivity with its associated striatal subregion in patients with OCD compared to that in HCs. However, OCD patients exhibited significantly increased caudal-motor and parietal connectivity with the associated striatal subregions. The mean kurtosis values of the striatal subregions connected to the caudal-motor and parietal cortex were significantly decreased in OCD patients. Our results highlighted contrasting patterns of striatal WM connections with the orbitofrontal and caudal-motor/parietal cortices, thus supporting the cortico-striatal circuitry imbalance model of OCD. We suggest that aberrations in WM connections and the microstructure of their downstream regions in the caudal-motor-/parietal-striatal circuits may underlie OCD pathophysiology and further provide potential neuromodulation targets for the treatment of OCD.

Beyond verbal fluency in the verbal fluency task: semantic clustering as a predictor of remission in individuals at clinical high risk for psychosis.

BACKGROUND: There have been conflicting reports on whether conventional verbal fluency measures can predict the prognosis of individuals at clinical high risk (CHR) for psychosis. We aimed to investigate whether verbal fluency task measures that represent semantic processing more directly than conventional measures could be more reliable predictors of later remission in CHR individuals. METHODS: We recruited CHR individuals and healthy controls to participate in a baseline verbal fluency assessment. We identified semantic clusters within the verbal fluency task responses based on cosine similarity between consecutive words, calculated from the word embedding model. Binomial logistic regression was performed to test whether average semantic cluster size and number of words produced could be predictors of remission in CHR individuals. RESULTS: Our study sample included 96 CHR individuals and 178 healthy controls. According to clinical assessment at the last follow-up, 23 CHR individuals were classified as remitters and 73 as nonremitters, including 29 individuals who converted to psychosis. The CHR remitters showed larger average and maximum semantic cluster sizes than CHR nonremitters and healthy controls. Average semantic cluster size, but not the number of words, was a significant predictor of later remission in CHR individuals. LIMITATIONS: Our sample included only native Korean speakers. CONCLUSION: A verbal fluency task measure that more specifically represents semantic processing may be a better neurocognitive predictive marker for remission in CHR individuals than conventional verbal fluency measures. Our results provide an explanation for heterogeneous reports on whether verbal fluency can predict prognosis in CHR individuals and suggest that semantic processing is a putative cognitive predictor of their prognosis.

Unbalanced fronto-pallidal neurocircuit underlying set shifting in obsessive-compulsive disorder.

Maladaptive habitual behaviours of obsessive-compulsive disorder are characterized by cognitive inflexibility, which hypothetically arises from dysfunctions of a certain cortico-basal ganglia-thalamo-cortical circuit including the ventrolateral prefrontal region. Inside this neurocircuit, an imbalance between distinct striatal projections to basal ganglia output nuclei, either directly or indirectly via the external globus pallidus, is suggested to be relevant for impaired arbitration between facilitation and inhibition of cortically initiated activity. However, current evidence of individually altered cortico-striatal or thalamo-cortical connectivities is insufficient to understand how cortical dysconnections are linked to the imbalanced basal ganglia system in patients. In this study, we aimed to identify aberrant ventrolateral prefronto-basal ganglia-thalamic subnetworks representing direct-indirect imbalance and its association with cognitive inflexibility in patients. To increase network detection sensitivity, we constructed a cortico-basal ganglia-thalamo-cortical network model incorporating striatal, pallidal and thalamic subregions defined by unsupervised clustering in 105 medication-free patients with obsessive-compulsive disorder (age = 25.05 ± 6.55 years, male/female = 70/35) and 99 healthy controls (age = 23.93 ± 5.80 years, male/female = 64/35). By using the network-based statistic method, we analysed group differences in subnetworks formed by suprathreshold dysconnectivities. Using linear regression models, we tested subnetwork dysconnectivity effects on symptom severity and set-shifting performance assessed by well-validated clinical and cognitive tests. Compared with the healthy controls, patients were slower to track the Part B sequence of the Trail Making Test when the effects of psychomotor and visuospatial functions were adjusted (t = 3.89, P < 0.001) and made more extradimensional shift errors (t = 4.09, P < 0.001). In addition to reduced fronto-striatal and striato-external pallidal connectivities and hypoconnected striato-thalamic subnetwork [P = 0.001, family-wise error rate (FWER) corrected], patients had hyperconnected fronto-external pallidal (P = 0.012, FWER corrected) and intra-thalamic (P = 0.015, FWER corrected) subnetworks compared with the healthy controls. Among the patients, the fronto-pallidal subnetwork alteration, especially ventrolateral prefronto-external globus pallidal hyperconnectivity, was associated with relatively fewer extradimensional shifting errors (ß = -0.30, P = 0.001). Our findings suggest that the hyperconnected fronto-external pallidal subnetwork may have an opposite effect to the imbalance caused by the reduced indirect pathway (fronto-striato-external pallidal) connectivities in patients. This ventrolateral prefrontal hyperconnectivity may help the external globus pallidus disinhibit basal ganglia output nuclei, which results in behavioural inhibition, so as to compensate for the impaired set shifting. We suggest the ventrolateral prefrontal and external globus pallidus as neuromodulatory targets for inflexible habitual behaviours in obsessive-compulsive disorder.

N-methyl-D-aspartate receptor regulates the circadian clock in megakaryocytic cells and impacts cell proliferation through BMAL1.

Peripheral circadian clocks control cell proliferation and survival, but little is known about their role and regulation in megakaryocytic cells. N-methyl-D-aspartate receptor (NMDAR) regulates the central clock in the brain. The purpose of this study was to determine whether NMDAR regulates the megakaryocytic cell clock and whether the megakaryocytic clock regulates cell proliferation and cell death. We found that both the Meg-01 megakaryocytic cell line and native murine megakaryocytes expressed circadian clock genes. Megakaryocyte-directed deletion of Grin1 in mice caused significant disruption of the circadian rhythm pathway at the transcriptional level and increased expression of BMAL1 at the protein level. Similarly, both pharmacological (MK-801) and genetic (GRIN-/-) inhibition of NMDAR in Meg-01 cells in vitro resulted in widespread changes in clock gene expression including increased expression of BMAL1, the core clock transcription factor. BMAL1 overexpression reduced Meg-01 cell proliferation and altered the time-dependent expression of the cell cycle regulators MYC and WEE1, whereas BMAL1 knockdown led to increased cell death in Meg-01-GRIN1-/- cells. Our results demonstrate that NMDAR regulates the circadian clock in megakaryocytic cells and that the circadian clock component BMAL1 contributes to the control of Meg-01 cell proliferation and survival.

Why was the study done? Time of day impacts platelet function and production. Our bodies are informed about external time by the brain, but all other cells including platelet precursors megakaryocytes also have their own clock.Circadian disruption contributes to disorders such as thrombosis (e.g. stroke and heart attacks) and blood cancers (e.g. leukemia). However, the mechanism of circadian control in megakaryocytes remains poorly elucidated.N-methyl-D-aspartate receptor (NMDAR) regulates circadian clock in the brain and is expressed in megakaryocytes, thus we hypothesized that NMDAR also regulates circadian clock in megakaryocytic cells.What did the researchers do and find? We used Meg-01 cell line, its genetically modified version with deleted NMDAR, and data from murine megakaryocytes to determine the NMDAR impact on the clock in these cells.We found that megakaryocytic cells had all the machinery required to maintain their own circadian clock. NMDAR deletion disrupted circadian clock in megakaryocytic cells.Manipulation of circadian clock in Meg-01 cells (through BMAL1 overexpression) impacted proliferation and survival of cells.What do the results mean? Megakaryocytic cells have their own circadian clock regulated by NMDAR, and its disruption impacts cell proliferation.What is the objective influence on the wider field? It is possible that deregulated function of megakaryocytes that occurs in disease can be corrected through the modulation of NMDAR or other components of the cellular circadian clock, thus further studies to develop and test such strategies in disease models are warranted.

Rising of LOXHD1 as a signature causative gene of down-sloping hearing loss in people in their teens and 20s.

BACKGROUND: Down-sloping sensorineural hearing loss (SNHL) in people in their teens and 20s hampers efficient learning and communication and in-depth social interactions. Nonetheless, its aetiology remains largely unclear, with the exception of some potential causative genes, none of which stands out especially in people in their teens and 20s. Here, we examined the role and genotype-phenotype correlation of lipoxygenase homology domain 1 (LOXHD1) in down-sloping SNHL through a cohort study. METHODS: Based on the Seoul National University Bundang Hospital (SNUBH) genetic deafness cohort, in which the patients show varying degrees of deafness and different onset ages (n=1055), we have established the 'SNUBH Teenager-Young Adult Down-sloping SNHL' cohort (10-35 years old) (n=47), all of whom underwent exome sequencing. Three-dimensional molecular modelling, minigene splicing assay and short tandem repeat marker genotyping were performed, and medical records were reviewed. RESULTS: LOXHD1 accounted for 33.3% of all genetically diagnosed cases of down-sloping SNHL (n=18) and 12.8% of cases in the whole down-sloping SNHL cohort (n=47) of young adults. We identified a potential common founder allele, as well as an interesting genotype-phenotype correlation. We also showed that transcript 6 is necessary and probably sufficient for normal hearing. CONCLUSIONS: LOXHD1 exceeds other genes in its contribution to down-sloping SNHL in young adults, rising as a signature causative gene, and shows a potential but interesting genotype-phenotype correlation.

Risk of Kidney Failure in Patients With Cancer: A South Korean Population-Based Cohort Study.

RATIONALE & OBJECTIVE: Reduced kidney function is associated with an increased risk of cancer; however, it is unclear if cancer increases the risk of kidney failure with replacement therapy (KFRT). We assessed the risk of KFRT among patients with various types of cancer collectively and with specific types of cancer. STUDY DESIGN: Retrospective population-based cohort study. SETTING & PARTICIPANTS: A total of 2,473,095 participants with (n = 824,365) or without (n = 1,648,730) cancer registered in the Korean National Health Insurance Service database. PREDICTORS: Cancer and cancer subtypes defined using International Classification of Diseases, 10th Revision, Clinical Modification, codes. OUTCOMES: Primary outcome was KFRT defined as the initiation of hemodialysis or peritoneal dialysis or kidney transplantation. ANALYTICAL APPROACH: For each patient with cancer, 2 controls matched for age, sex, estimated glomerular filtration rate, diabetes, and hypertension were included. To address the competing risk of death, a competing risk survival analysis was conducted using the Fine and Gray method. RESULTS: Occurrence of KFRT was higher in patients with cancer than in controls without cancer (incidence rates of 1.07 vs 0.51 cases per 1,000 person-years). Competing risk analysis showed that cancer was significantly associated with an increased risk of KFRT after adjusting for other potential predictors (adjusted hazard ratio, 2.29 [95% CI, 2.20-2.39]). Multiple myeloma, leukemia, lymphoma, and kidney, ovarian, and liver cancer were most significantly associated with an increased KFRT risk, with multiple myeloma conferring the highest risk across age and sex groups. All subgroups of patients with cancer (based on age, sex, smoking, alcohol, exercise, obesity, and comorbid conditions) exhibited a higher risk of KFRT. LIMITATIONS: Causal association between cancer and kidney outcomes could not be confirmed. CONCLUSIONS: Patients with cancer, particularly those with multiple myeloma, exhibited an increased risk of KFRT after accounting for the competing risk of death.

Prediction of psychosis: model development and internal validation of a personalized risk calculator.

BACKGROUND: Over the past two decades, early detection and early intervention in psychosis have become essential goals of psychiatry. However, clinical impressions are insufficient for predicting psychosis outcomes in clinical high-risk (CHR) individuals; a more rigorous and objective model is needed. This study aims to develop and internally validate a model for predicting the transition to psychosis within 10 years. METHODS: Two hundred and eight help-seeking individuals who fulfilled the CHR criteria were enrolled from the prospective, naturalistic cohort program for CHR at the Seoul Youth Clinic (SYC). The least absolute shrinkage and selection operator (LASSO)-penalized Cox regression was used to develop a predictive model for a psychotic transition. We performed k-means clustering and survival analysis to stratify the risk of psychosis. RESULTS: The predictive model, which includes clinical and cognitive variables, identified the following six baseline variables as important predictors: 1-year percentage decrease in the Global Assessment of Functioning score, IQ, California Verbal Learning Test score, Strange Stories test score, and scores in two domains of the Social Functioning Scale. The predictive model showed a cross-validated Harrell's C-index of 0.78 and identified three subclusters with significantly different risk levels. CONCLUSIONS: Overall, our predictive model showed a predictive ability and could facilitate a personalized therapeutic approach to different risks in high-risk individuals.

Magnetic supercluster particles for highly sensitive magnetic biosensing of proteins.

A strategy is reported to improve the detection limits of current giant magnetoresistance (GMR) biosensors by augmenting the effective magnetic moment that the magnetic tags on the biosensors can exert. Magnetic supercluster particles (MSPs), each of which consists of ~ 1000 superparamagnetic cores, are prepared by a wet-chemical technique and are utilized to improve the limit of detection of GMR biosensors down to 17.6 zmol for biotin as a target molecule. This value is more than four orders of magnitude lower than that of the conventional colorimetric assay performed using the same set of reagents except for the signal transducer. The applicability of MSPs in immunoassay is further demonstrated by simultaneously detecting vascular endothelial growth factor (VEGF) and C-reactive protein (CRP) in a duplex assay format. MSPs outperform commercially available magnetic nanoparticles in terms of signal intensity and detection limit.

Distinct neural networks associated with obsession and delusion: a connectome-wide association study.

BACKGROUND: Obsession and delusion are theoretically distinct from each other in terms of reality testing. Despite such phenomenological distinction, no extant studies have examined the identification of common and distinct neural correlates of obsession and delusion by employing biologically grounded methods. Here, we investigated dimensional effects of obsession and delusion spanning across the traditional diagnostic boundaries reflected upon the resting-state functional connectivity (RSFC) using connectome-wide association studies (CWAS). METHODS: Our study sample comprised of 96 patients with obsessive-compulsive disorder, 75 patients with schizophrenia, and 65 healthy controls. A connectome-wide analysis was conducted to examine the relationship between obsession and delusion severity and RFSC using multivariate distance-based matrix regression. RESULTS: Obsession was associated with the supplementary motor area, precentral gyrus, and superior parietal lobule, while delusion was associated with the precuneus. Follow-up seed-based RSFC and modularity analyses revealed that obsession was related to aberrant inter-network connectivity strength. Additional inter-network analyses demonstrated the association between obsession severity and inter-network connectivity between the frontoparietal control network and the dorsal attention network. CONCLUSIONS: Our CWAS study based on the Research Domain Criteria (RDoC) provides novel evidence for the circuit-level functional dysconnectivity associated with obsession and delusion severity across diagnostic boundaries. Further refinement and accumulation of biomarkers from studies embedded within the RDoC framework would provide useful information in treating individuals who have some obsession or delusion symptoms but cannot be identified by the category of clinical symptoms alone.

Hot snare polypectomy versus endoscopic mucosal resection for small colorectal polyps: a randomized controlled trial.

BACKGROUND AND AIMS: This study was performed to compare endoscopic mucosal resection (EMR) with hot snare polypectomy (HSP) in terms of the complete resection rate and the incidence of adverse events for resecting small (5-10 mm) colorectal polyps. METHODS: Small colorectal polyps (5-10 mm) with neoplastic features were randomly allocated to either the HSP or EMR group. A submucosal injection was performed prior to hot snaring in the EMR group only. Complete resection was defined as the absence of neoplastic tissue from two additional biopsies of the polypectomy site. R0 resection was defined as the absence of neoplastic tissue at the margin of the resected specimen. RESULTS: A total of 362 colon polyps from 272 patients were included, and 167 polyps in the HSP group and 155 polyps in the EMR group were analyzed. Between the polypectomy techniques, there was no significant difference in the complete resection rates, which were 96.4% (161/167) in the HSP group and 95.5% (148/155) in the EMR group (P = 0.67). The R0 resection rate in the HSP and EMR groups was significantly different, with 49.7% (83/167) and 74.8% (116/155), respectively (P < 0.001). There was no significant difference in the incidence of adverse events between the two groups. CONCLUSIONS: The complete resection rates for small (5-10 mm) polyps were not different between HSP and EMR. TRIAL REGISTRY: ClincialTrials.gov number NCT02239536.

In vivo gamma-aminobutyric acid-A/benzodiazepine receptor availability and genetic liability in asymptomatic individuals with high genetic loading of schizophrenia: A [11C]flumazenil positron emission tomography study.

OBJECTIVES: Whilst reduced signalling and gene expression related to gamma-aminobutyric acid (GABA) play a role in the presumed pathophysiology of schizophrenia, its origin is unclear. Studying asymptomatic individuals with high genetic liability to schizophrenia (AIs) would provide insights. Therefore, this study aimed to investigate the role of genetic liability in GABAergic dysfunction of schizophrenia by exploring in vivo GABA-A/benzodiazepine receptor (GABAR) availability in AIs. METHODS: A total of 10 AIs with multiple relatives diagnosed as schizophrenia and 11 healthy controls underwent [11C]flumazenil positron emission tomography and neurocognitive function tests. RESULTS: There was no significant difference in [11C]flumazenil availability based on the groups. GABAR availability in caudate nuclei had positive correlations with genetic liability of AIs. GABAR availability in caudate nuclei and verbal memory measures of AIs revealed positive correlations. Only the correlation between right caudate and short-term verbal memory survived multiple-comparison correction (p = 0.030). CONCLUSIONS: This study, for the first time, reports correlations between the genetic liability of schizophrenia and GABAR availability. Correlations between [11C]flumazenil binding in caudate of individuals with high genetic liability to schizophrenia suggests that the GABAergic dysfunction may arise from shared genetic factors and also that it may be responsible for cognitive impairment of AIs.