The new obesity-associated protein, neuronal growth regulator 1 (NEGR1), is implicated in Niemann-Pick disease Type C (NPC2)-mediated cholesterol trafficking

Genomic insights into local adaptation and phenotypic diversity of Wenchang chickens

Wenchang chicken, a prized local breed in Hainan Province of China renowned for its exceptional adaptability to tropical environments and good meat quality, is deeply favored by the public. However, an insufficient understanding of its population architecture and the unclear genetic basis that governs its typical attributes have posed challenges in the protection and breeding of this precious breed. To address these gaps, we conducted whole-genome resequencing on 200 Wenchang chicken samples derived from 10 distinct strains, and we gathered data on an array of 21 phenotype traits. Population genomics analysis unveiled distinctive population structures in Wenchang chickens, primarily attributed to strong artificial selection for different feather colors. Selection sweep analysis identified a group of candidate genes, including PCDH9, DPF3, CDIN1, and SUGCT, closely linked to adaptations that enhance resilience in tropical island habitats. Genome-wide association studies (GWAS) highlighted potential candidate genes associated with diverse feather color traits, encompassing TYR, RAB38, TRPM1, GABARAPL2, CDH1, ZMIZ1, LYST, MC1R, and SASH1. Through the comprehensive analysis of high-quality genomic and phenotypic data across diverse Wenchang chicken resource groups, this study unveils the intricate genetic backgrounds and population structures of Wenchang chickens. Additionally, it identifies multiple candidate genes linked to environmental adaptation, feather color variations, and production traits. These insights not only provide genetic reference for the purification and breeding of Wenchang chickens but also broaden our understanding of the genetic basis of phenotypic diversity in chickens.

The Role of IgLON Cell Adhesion Molecules in Neurodegenerative Diseases

In the brain, cell adhesion molecules (CAMs) are critical for neurite outgrowth, axonal fasciculation, neuronal survival and migration, and synapse formation and maintenance. Among CAMs, the IgLON family comprises five members: Opioid Binding Protein/Cell Adhesion Molecule Like (OPCML or OBCAM), Limbic System Associated Membrane Protein (LSAMP), neurotrimin (NTM), Neuronal Growth Regulator 1 (NEGR1), and IgLON5. IgLONs exhibit three N-terminal C2 immunoglobulin domains; several glycosylation sites; and a glycosylphosphatidylinositol anchoring to the membrane. Interactions as homo- or heterodimers in cis and in trans, as well as binding to other molecules, appear critical for their functions. Shedding by metalloproteases generates soluble factors interacting with cellular receptors and activating signal transduction. The aim of this review was to analyse the available data implicating a role for IgLONs in neuropsychiatric disorders. Starting from the identification of a pathological role for antibodies against IgLON5 in an autoimmune neurodegenerative disease with a poorly understood mechanism of action, accumulating evidence links IgLONs to neuropsychiatric disorders, albeit with still undefined mechanisms which will require future thorough investigations.

Optimized cell type signatures revealed from single-cell data by combining principal feature analysis, mutual information, and machine learning

Machine learning techniques are excellent to analyze expression data from single cells. These techniques impact all fields ranging from cell annotation and clustering to signature identification. The presented framework evaluates gene selection sets how far they optimally separate defined phenotypes or cell groups. This innovation overcomes the present limitation to objectively and correctly identify a small gene set of high information content regarding separating phenotypes for which corresponding code scripts are provided. The small but meaningful subset of the original genes (or feature space) facilitates human interpretability of the differences of the phenotypes including those found by machine learning results and may even turn correlations between genes and phenotypes into a causal explanation. For the feature selection task, the principal feature analysis is utilized which reduces redundant information while selecting genes that carry the information for separating the phenotypes. In this context, the presented framework shows explainability of unsupervised learning as it reveals cell-type specific signatures. Apart from a Seurat preprocessing tool and the PFA script, the pipeline uses mutual information to balance accuracy and size of the gene set if desired. A validation part to evaluate the gene selection for their information content regarding the separation of the phenotypes is provided as well, binary and multiclass classification of 3 or 4 groups are studied. Results from different single-cell data are presented. In each, only about ten out of more than 30000 genes are identified as carrying the relevant information. The code is provided in a GitHub repository at https://github.com/AC-PHD/Seurat_PFA_pipeline.

Major depression-related factor NEGR1 controls salivary secretion in mouse submandibular glands

Salivary gland cells, which secrete water in response to neuronal stimulation, are closely connected to other neurons. Transcriptomic studies show that salivary glands also express some proteins responsible for neuronal function. However, the physiological functions of these common neuro-exocrine factors in salivary glands are largely unknown. Here, we studied the function of Neuronal growth regulator 1 (NEGR1) in the salivary gland cells. NEGR1 was also expressed in mouse and human salivary glands. The structure of salivary glands of Negr1 knockout (KO) mice was normal. Negr1 KO mice showed tempered carbachol- or thapsigargin-induced intracellular Ca²⁺ increases and store-operated Ca²⁺ entry. Of interest, the activity of the large-conductance Ca²⁺-activated K⁺ channel (BK channel) was increased, whereas Ca²⁺-activated Cl^- channel ANO1 channel activity was not altered in Negr1 KO mice. Pilocarpine- and carbachol-induced salivation was decreased in Negr1 KO mice. These results suggest that NEGR1 influence salivary secretion though the muscarinic Ca²⁺ signaling.

Neuronal growth regulator 1 may modulate interleukin-6 signaling in adipocytes

Interleukin-6 (IL-6) is a pleiotropic cytokine that plays both anti- and pro-inflammatory roles. Due to the restricted expression of membrane IL-6 receptor (IL-6R), most pro-inflammatory functions of IL-6 are attributed to its association with soluble IL-6R (sIL-6R). Neuronal growth regulator 1 (NEGR1) is a brain-enriched membrane protein that has recently been recognized as a risk factor for many human diseases including obesity, depression, and autism. In the present study, we report that the expression levels of IL-6 and IL-6R, as well as the phosphorylation of signal transducer and activator of transcription (STAT) 3, were significantly elevated in white adipose tissues of Negr1 knockout mice. Elevated levels of circulating IL-6 and sIL-6R have also been observed in Negr1 ^-/- mice. Furthermore, NEGR1 interacted with IL-6R, which was supported by subcellular fractionation and an in situ proximity ligation assay. Importantly, NEGR1 expression attenuated the phosphorylation of STAT3 by sIL-6R, suggesting that NEGR1 negatively regulates IL-6 trans-signaling. Taken together, we propose that NEGR1 may play a regulatory role in IL-6 signaling by interacting with IL-6R, which may contribute to a molecular link underlying obesity, inflammation, and the depression cycle.

Reduced secretion of neuronal growth regulator 1 contributes to impaired adipose-neuronal crosstalk in obesity

While the endocrine function of white adipose tissue has been extensively explored, comparatively little is known about the secretory activity of less-investigated fat depots. Here, we use proteomics to compare the secretory profiles of male murine perivascular depots with those of canonical white and brown fat. Perivascular secretomes show enrichment for neuronal cell-adhesion molecules, reflecting a higher content of intra-parenchymal sympathetic projections compared to other adipose depots. The sympathetic innervation is reduced in the perivascular fat of obese (ob/ob) male mice, as well as in the epicardial fat of patients with obesity. Degeneration of sympathetic neurites is observed in presence of conditioned media of fat explants from ob/ob mice, that show reduced secretion of neuronal growth regulator 1. Supplementation of neuronal growth regulator 1 reverses this neurodegenerative effect, unveiling a neurotrophic role for this protein previously identified as a locus associated with human obesity. As sympathetic stimulation triggers energy-consuming processes in adipose tissue, an impaired adipose-neuronal crosstalk is likely to contribute to the disrupted metabolic homeostasis characterising obesity.

Shared genetics between classes of obesity and psychiatric disorders: A large-scale genome-wide cross-trait analysis

AIMS

Epidemiological studies demonstrate an association between classes of obesity and psychiatric disorders, although little is known about shared genetics and causality of association. Thus, we aimed to investigate shared genetics and causal link between different classes of obesity and psychiatric disorders.

METHODS

We used genome-wide association study (GWAS) summary data range from 9725 to 500,199 sample sizes of European descent, conducted a large-scale genome-wide cross-trait association study to investigate genetic overlap between the classes of obesity and anorexia nervosa, attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, obsessive-compulsive disorder, schizophrenia, anxiety disorders and Tourette syndrome. We conducted transcriptome-wide association study analysis (TWAS) to identified variants regulated gene expression in those related disorders. Finally, pathway enrichment analysis to identified major pathways.

RESULTS

In the combined analysis, we replicated 211 previously reported loci and discovered 58 novel independent loci that were associated with all three classes of obesity and related psychiatric disorders. Functional analysis revealed that the identified variants regulated gene expression in major tissues belonging to exocrine/endocrine, digestive, circulatory, adipose, digestive, respiratory, and nervous systems, such as DCC, NEGR1, INO80E. Mendelian randomization analyses suggested that there may be a two-way or one-way causal relationship between obesity and psychiatric disorders.

CONCLUSION

This large-scale genome-wide cross-trait analysis identified shared genetics and potential causal links between classes of obesity and psychiatric disorders (attention deficit hyperactivity disorder, autism spectrum disorder, anorexia nervosa, major depressive disorder, schizophrenia, and obsessive-compulsive disorder). Such shared genetics suggests potential new biological functions in common among them.

Extended gene set analysis of human neuro-psychiatric traits shows enrichment in brain-expressed human accelerated regions across development

Human neuropsychiatric disorders are associated with genetic and environmental factors affecting the brain, which has been subjected to strong evolutionary pressures resulting in an enlarged cerebral cortex and improved cognitive performance. Thus, genes involved in human brain evolution may also play a role in neuropsychiatric disorders. We test whether genes associated with 7 neuropsychiatric phenotypes are enriched in genomic regions that have experienced rapid changes in human evolution (HARs) and importantly, whether HAR status interacts with developmental brain expression to predict associated genes. We used the most recent publicly available GWAS and gene expression data to test for enrichment of HARs, brain expression, and their interaction. These revealed significant interactions between HAR status and whole-brain expression across developmental stages, indicating that the relationship between brain expression and association with schizophrenia and intelligence is stronger among HAR than non-HAR genes. Follow-up regional analyses indicated that predicted HAR-expression interaction effects may vary substantially across regions and developmental stages. Although depression indicated significant enrichment of HAR genes, little support was found for HAR enrichment among bipolar, autism, ADHD, or Alzheimer's associated genes. Our results indicate that intelligence, schizophrenia, and depression-associated genes are enriched for those involved in the evolution of the human brain. These findings highlight promising candidates for follow-up study and considerations for novel drug development, but also caution careful assessment of the translational ability of animal models for studying neuropsychiatric traits in the context of HARs, and the importance of using humanized animal models or human-derived tissues when researching these traits.

The Role of N-Glycosylation in the Intracellular Trafficking and Functionality of Neuronal Growth Regulator 1

Neuronal growth regulator 1 (NEGR1) is a brain-enriched membrane protein that is involved in neural cell communication and synapse formation. Accumulating evidence indicates that NEGR1 is a generic risk factor for various psychiatric diseases including autism and depression. Endoglycosidase digestion of single NEGR1 mutants revealed that the wild type NEGR1 has six putative N-glycosylation sites partly organized in a Golgi-dependent manner. To understand the role of each putative N-glycan residue, we generated a series of multi-site mutants (2MT–6MT) with additive mutations. Cell surface staining and biotinylation revealed that NEGR1 mutants 1MT to 4MT were localized on the cell surface at different levels, whereas 5MT and 6MT were retained in the endoplasmic reticulum to form highly stable multimer complexes. This indicated 5MT and 6MT are less likely to fold correctly. Furthermore, the removal of two N-terminal sites N75 and N155 was sufficient to completely abrogate membrane targeting. An in vivo binding assay using the soluble NEGR1 protein demonstrated that glycans N286, N294 and N307 on the C-terminal immunoglobulin-like domain play important roles in homophilic interactions. Taken together, these results suggest that the N-glycan moieties of NEGR1 are closely involved in the folding, trafficking, and homodimer formation of NEGR1 protein in a site-specific manner.

High-Fat Diet Induces Pre-Diabetes and Distinct Sex-Specific Metabolic Alterations in Negr1-Deficient Mice

In the large GWAS studies, NEGR1 gene has been one of the most significant gene loci for body mass phenotype. The purpose of the current study was to clarify the role of NEGR1 in the maintenance of systemic metabolism, including glucose homeostasis, by using both male and female Negr1-/- mice receiving a standard or high fat diet (HFD). We found that 6 weeks of HFD leads to higher levels of blood glucose in Negr1-/- mice. In the glucose tolerance test, HFD induced phenotype difference only in male mice; Negr1-/- male mice displayed altered glucose tolerance, accompanied with upregulation of circulatory branched-chain amino acids (BCAA). The general metabolomic profile indicates that Negr1-/- mice are biased towards glyconeogenesis, fatty acid synthesis, and higher protein catabolism, all of which are amplified by HFD. Negr1 deficiency appears to induce alterations in the efficiency of energy storage; reduced food intake could be an attempt to compensate for the metabolic challenge present in the Negr1-/- males, particularly during the HFD exposure. Our results suggest that the presence of functional Negr1 allows male mice to consume more HFD and prevents the development of glucose intolerance, liver steatosis, and excessive weight gain.

Gene expression atlas of energy balance brain regions

Energy balance is controlled by interconnected brain regions in the hypothalamus, brainstem, cortex, and limbic system. Gene expression signatures of these regions can help elucidate the pathophysiology underlying obesity. RNA sequencing was conducted on P56 C57BL/6NTac male mice and E14.5 C57BL/6NTac embryo punch biopsies in 16 obesity-relevant brain regions. The expression of 190 known obesity-associated genes (monogenic, rare, and low-frequency coding variants; GWAS; syndromic) was analyzed in each anatomical region. Genes associated with these genetic categories of obesity had localized expression patterns across brain regions. Known monogenic obesity causal genes were highly enriched in the arcuate nucleus of the hypothalamus and developing hypothalamus. The obesity-associated genes clustered into distinct “modules” of similar expression profile, and these were distinct from expression modules formed by similar analysis with genes known to be associated with other disease phenotypes (type 1 and type 2 diabetes, autism, breast cancer) in the same energy balance–relevant brain regions.

DeepCOMBI: explainable artificial intelligence for the analysis and discovery in genome-wide association studies

Deep learning has revolutionized data science in many fields by greatly improving prediction performances in comparison to conventional approaches. Recently, explainable artificial intelligence has emerged as an area of research that goes beyond pure prediction improvement by extracting knowledge from deep learning methodologies through the interpretation of their results. We investigate such explanations to explore the genetic architectures of phenotypes in genome-wide association studies. Instead of testing each position in the genome individually, the novel three-step algorithm, called DeepCOMBI, first trains a neural network for the classification of subjects into their respective phenotypes. Second, it explains the classifiers’ decisions by applying layer-wise relevance propagation as one example from the pool of explanation techniques. The resulting importance scores are eventually used to determine a subset of the most relevant locations for multiple hypothesis testing in the third step. The performance of DeepCOMBI in terms of power and precision is investigated on generated datasets and a 2007 study. Verification of the latter is achieved by validating all findings with independent studies published up until 2020. DeepCOMBI is shown to outperform ordinary raw P-value thresholding and other baseline methods. Two novel disease associations (rs10889923 for hypertension, rs4769283 for type 1 diabetes) were identified.

Effect of interaction between obesity-promoting genetic variants and behavioral factors on the risk of obese phenotypes

The studies investigating gene-gene and gene-environment (or gene-behavior) interactions provide valuable insight into the pathomechanisms underlying obese phenotypes. The Pakistani population due to its unique characteristics offers numerous advantages for conducting such studies. In this view, the current study was undertaken to examine the effects of gene-gene and gene-environment/behavior interactions on the risk of obesity in a sample of Pakistani population. A total of 578 adult participants including 290 overweight/obese cases and 288 normal-weight controls were involved. The five key obesity-associated genetic variants namely MC4R rs17782313, BDNF rs6265, FTO rs1421085, TMEM18 rs7561317, and NEGR1 rs2815752 were genotyped using the TaqMan allelic discrimination assays. The data related to behavioral factors, such as eating pattern, diet consciousness, the tendency toward fat-dense food (TFDF), sleep duration, sleep-wake cycle (SWC), shift work (SW), and physical activity levels were collected via a questionnaire. Gene-gene and gene-behavior interactions were analyzed by multifactor dimensionality reduction and linear regression, respectively. In our study, only TMEM18 rs7561317 was found to be significantly associated with anthropometric traits with no significant effect of gene-gene interactions were observed on obesity-related phenotypes. However, the genetic variants were found to interact with the behavioral factors to significantly influence various obesity-related anthropometric traits including BMI, waist circumference, hip circumference, waist-to-hip ratio, waist-to-height ratio, and percentage of body fat. In conclusion, the interaction between genetic architecture and behavior/environment determines the outcome of obesity-related anthropometric phenotypes. Thus, gene-environment/behavior interaction studies should be promoted to explore the risk of complex and multifactorial disorders, such as obesity.

Predicting anthropometric and metabolic traits with a genetic risk score for obesity in a sample of Pakistanis

Obesity is an outcome of multiple factors including environmental and genetic influences. Common obesity is a polygenic trait indicating that multiple genetic variants act synergistically to influence its expression. We constructed a genetic risk score (GRS) based on five genetic variants (MC4R rs17782313, BDNF rs6265, FTO rs1421085, TMEM18 rs7561317, and NEGR1 rs2815752) and examined its association with obesity-related traits in a sample of Pakistanis. The study involved 306 overweight/obese (OW/OB) and 300 normal-weight (NW) individuals. The age range of the study participants was 12-63 years. All anthropometric and metabolic parameters were measured for each participant via standard procedures and biochemical assays, respectively. The genetic variants were genotyped by allelic discrimination assays. The age- and gender-adjusted associations between the GRS and obesity-related anthropometric and metabolic measures were determined using linear regression analyses. The results showed that OW/OB individuals had significantly higher mean ranks of GRS than NW individuals. Moreover, a significant association of the GRS with obesity-related anthropometric traits was seen. However, the GRS did not appear to affect any obesity-related metabolic parameter. In conclusion, our findings indicate the combined effect of multiple genetic variants on the obesity-related anthropometric phenotypes in Pakistanis.

Na/K-ATPase beta1-subunit associates with neuronal growth regulator 1 (NEGR1) to participate in intercellular interactions

Neuronal growth regulator 1 (NEGR1) is a GPI-anchored membrane protein that is involved in neural cell adhesion and communication. Multiple genome wide association studies have found that NEGR1 is a generic risk factor for multiple human diseases, including obesity, autism, and depression. Recently, we reported that Negr1^−/− mice showed a highly increased fat mass and affective behavior. In the present study, we identified Na/K-ATPase, beta1-subunit (ATP1B1) as an NEGR1 binding partner by yeast two-hybrid screening. NEGR1 and ATP1B1 were found to form a relatively stable complex in cells, at least partially co-localizing in membrane lipid rafts. We found that NEGR1 binds with ATP1B1 at its C-terminus, away from the binding site for the alpha subunit, and may contribute to intercellular interactions. Collectively, we report ATP1B1 as a novel NEGR1-interacting protein, which may help deciphering molecular networks underlying NEGR1-associated human diseases.

Highly Conserved Molecular Features in IgLONs Contrast Their Distinct Structural and Biological Outcomes

Neuronal growth regulator 1 (NEGR1) and neurotrimin (NTM) are abundant cell-surface proteins found in the brain and form part of the IgLON (Immunoglobulin LSAMP, OBCAM, Neurotrimin) family. In humans, NEGR1 is implicated in obesity and mental disorders, while NTM is linked to intelligence and cognitive function. IgLONs dimerize homophilically and heterophilically, and they are thought to shape synaptic connections and neural circuits by acting in trans (spanning cellular junctions) and/or in cis (at the same side of a junction). Here, we reveal homodimeric structures of NEGR1 and NTM. They assemble into V-shaped complexes via their Ig1 domains, and disruption of the Ig1-Ig1 interface abolishes dimerization in solution. A hydrophobic ridge from one Ig1 domain inserts into a hydrophobic pocket from the opposing Ig1 domain producing an interaction interface that is highly conserved among IgLONs but remarkably plastic structurally. Given the high degree of sequence conservation at the interaction interface, we tested whether different IgLONs could elicit the same biological effect in vivo. In a small-scale study administering different soluble IgLONs directly into the brain and monitoring feeding, only NEGR1 altered food intake significantly. Taking NEGR1 as a prototype, our studies thus indicate that while IgLONs share a conserved mode of interaction and are able to bind each other as homomers and heteromers, they are structurally plastic and can exert unique biological action.

Environment and Gene Association With Obesity and Their Impact on Neurodegenerative and Neurodevelopmental Diseases

Obesity is a multifactorial disease in which environmental conditions and several genes play an important role in the development of this disease. Obesity is associated with neurodegenerative diseases (Alzheimer, Parkinson, and Huntington diseases) and with neurodevelopmental diseases (autism disorder, schizophrenia, and fragile X syndrome). Some of the environmental conditions that lead to obesity are physical activity, alcohol consumption, socioeconomic status, parent feeding behavior, and diet. Interestingly, some of these environmental conditions are shared with neurodegenerative and neurodevelopmental diseases. Obesity impairs neurodevelopment abilities as memory and fine-motor skills. Moreover, maternal obesity affects the cognitive function and mental health of the offspring. The common biological mechanisms involved in obesity and neurodegenerative/neurodevelopmental diseases are insulin resistance, pro-inflammatory cytokines, and oxidative damage, among others, leading to impaired brain development or cell death. Obesogenic environmental conditions are not the only factors that influence neurodegenerative and neurodevelopmental diseases. In fact, several genes implicated in the leptin–melanocortin pathway (LEP, LEPR, POMC, BDNF, MC4R, PCSK1, SIM1, BDNF, TrkB, etc.) are associated with obesity and neurodegenerative and neurodevelopmental diseases. Moreover, in the last decades, the discovery of new genes associated with obesity (FTO, NRXN3, NPC1, NEGR1, MTCH2, GNPDA2, among others) and with neurodegenerative or neurodevelopmental diseases (APOE, CD38, SIRT1, TNFα, PAI-1, TREM2, SYT4, FMR1, TET3, among others) had opened new pathways to comprehend the common mechanisms involved in these diseases. In conclusion, the obesogenic environmental conditions, the genes, and the interaction gene–environment would lead to a better understanding of the etiology of these diseases.

Association of the NEGR1 rs2815752 with obesity and related traits in Pakistani females

Introduction: The variant NEGR1 rs2815752 has recently been linked with obesity in Caucasians. However, a very limited number of studies have examined the association of the NEGR1 rs2815752 with overweight/obesity in non-Caucasians with no such study ever performed in Pakistani population. Therefore, the present study was undertaken to seek the association of the rs2815752 with overweight, obesity, and related traits in Pakistanis.Subjects and methods: The study involved 112 overweight/control pairs (total 224) and 194 obese/control pairs (total 388). Anthropometric parameters were measured by employing standard procedures. Metabolic parameters were determined by biochemical assays. Behavioral information was collected through a questionnaire. The rs2815752 was genotyped via TaqMan allelic discrimination assay. Regression analyses were employed to analyze the data in SPSS software.Results: The study revealed significant gender-specific association of the rs2815752 with obesity (OR 3.03; CI 1.19-7.72, p = 0.020) and some obesity-related anomalous anthropometric traits (weight, BMI, waist circumference, hip circumference, and abdominal and supra-iliac skinfold thicknesses) in females according to dominant model (h = 0.023). However, no association of the rs2815752 with obesity-related behavioral and metabolic parameters was observed.Conclusion: The NEGR1 rs2815752 may be associated with obese phenotype and some of the related anthropometric traits in Pakistani females.

A 10-gene prognostic methylation signature for stage I-III cervical cancer

PURPOSE

Cervical cancer (CC) patients usually have poor prognosis. The present study aims to find a DNA methylation signature for predicting survival of CC patients.

METHODS

We selected CC patients at pathological stage I-III with corresponding information on radiotherapy and overall survival (OS) from TCGA. Differential expression and methylation analysis was done between patients with and without radiotherapy. We selected feature genes using recursive feature elimination algorithm to build a support vector machine classifier. DNA methylation biomarkers predictive of prognosis were identified using a LASSO Cox-Proportional Hazards model to construct a prognostic scoring model. The classifier and the prognostic model were tested on the training set and the validation set. Nomogram combining risk score and prognostic clinical factors were used.

RESULTS

We obtained 497 differentially expressed genes (DEGs) and 865 differentially methylated genes (DMGs). Fifteen feature genes were selected from the 292 common genes between the DEGs and the DMGs to construct a classification model for radiotherapy. A DNA methylation signature including 10 genes was identified and used to establish a prognostic scoring model. The 10-gene methylation signature could effectively separate patients into two risk groups with markedly different OS time. Predictive capability of the methylation signature was successfully confirmed on the validation set. A nomogram comprised of risk score, radiotherapy, and recurrence was applied, with calibration plots displaying good concordance between predicted and actual OS. The DEGs were involved in 12 KEGG pathways most of which were correlated with metastasis and proliferation of various cancers, such as pathways in cancer, basal cell carcinoma, transcriptional misregulation in cancer and ECM-receptor interaction.

CONCLUSION

We Identified a 10-gene methylation signature for risk stratification of CC patients at pathological stages I-III, and ten methylation biomarkers might be novel therapeutic targets for CC.

1p31.1 microdeletion including only NEGR1 gene in two patients

Neuronal growth regulator 1 (NEGR1), a member of the immunoglobulin superfamily cell adhesion molecule subgroup IgLON, has been involved in neuronal growth and connectivity. Genetic variants, in or near the NEGR1 locus, have been associated with obesity and, more recently, with learning difficulties, intellectual disability, and psychiatric disorders. Here, we described the only second report of NEGR1 gene disruption in 1p31.1 microdeletion in two patients. Patient 1 is a 14-year-old female with neurological and psychiatric features present also in her family. Patient 2 is a 5-month-old infant showing global hypotonia as unique neurological features till now. This patient also carries 7p22.1 duplication, of paternal origin, that could be responsible for some malformations present in the child. We hypothesize a role of NEGR1 in producing the phenotype of our patients and compare them with other cases previously reported in the literature and DECIPHER database to better identify a possible genotype-phenotype correlation.

Negr1 controls adult hippocampal neurogenesis and affective behaviors

Recent genome-wide association studies on major depressive disorder have implicated neuronal growth regulator 1 (Negr1), a GPI-anchored cell adhesion molecule in the immunoglobulin LON family. Although Negr1 has been shown to regulate neurite outgrowth and synapse formation, the mechanism through which this protein affects mood disorders is still largely unknown. In this research, we characterized Negr1-deficient (negr1^-/-) mice to elucidate the function of Negr1 in anxiety and depression. We found that anxiety- and depression-like behaviors increased in negr1^-/- mice compared with wild-type mice. In addition, negr1^-/- mice had decreased adult hippocampal neurogenesis compared to wild-type mice. Concurrently, both LTP and mEPSC in the dentate gyrus (DG) region were severely compromised in negr1^-/- mice. In our effort to elucidate the underlying molecular mechanisms, we found that lipocalin-2 (Lcn2) expression was decreased in the hippocampus of negr1^-/- mice compared to wild-type mice. Heterologous Lcn2 expression in the hippocampal DG of negr1^-/- mice rescued anxiety- and depression-like behaviors and restored neurogenesis and mEPSC frequency to their normal levels in these mice. Furthermore, we discovered that Negr1 interacts with leukemia inhibitory factor receptor (LIFR) and modulates LIF-induced Lcn2 expression. Taken together, our data uncovered a novel mechanism of mood regulation by Negr1 involving an interaction between Negr1 and LIFR along with Lcn2 expression.

Neuronal growth regulator 1-deficient mice show increased adiposity and decreased muscle mass

BACKGROUND

Neuronal growth regulator 1 (NEGR1) is a glycosylphosphatidylinositol-anchored membrane protein that mediates neural cell communication and synapse formation. Multiple genome-wide association studies have reported that variations in NEGR1 are associated with human body weight control. Recently, we found that NEGR1 is involved in intracellular cholesterol trafficking, suggesting that it performs a non-central nervous system (CNS) function associated with human obesity.

METHODS

We compared peripheral tissues such as the adipose, liver, and skeletal muscle tissues of Negr1^-/- and Negr1^+/+ (wild-type [WT]) C57BL/6 mice (n = 5-14). Intracellular lipid content was measured, and lipid accumulation was visualized by staining tissue cross-sections with lipid-specific stains. Muscle capacity of the WT and Negr1^-/- mice was determined by performing a treadmill endurance test, and muscle fiber size was examined. Plasma glucose and insulin levels were measured, and glucose and insulin tolerance tests were performed.

RESULTS

The Negr1^-/- mice showed a significant increase in fat mass (~1.5-fold increase in the epididymal white adipose tissue, p = 0.000002), with abnormally enlarged adipose cells, compared with the WT mice. Primary adipocytes of the Negr1^-/- mice contained enlarged cytosolic lipid droplets (p = 0.049). Moreover, these mice showed significant hepatic lipid accumulation (~2.3-fold increase, p = 0.043). Although the Negr1^-/- mice did not show a significant change in plasma lipoprotein level, they showed a >1.3-fold increase in a serum glucose (p = 0.0002) and insulin (p = 0.016) levels. Moreover, the Negr1^-/- mice showed decreased muscle capacity, as indicated by a decrease in muscle mass (p = 0.000003).

CONCLUSION

These results indicate that NEGR1 deficiency induces abnormal fat deposition in various peripheral cells, especially fat and liver tissue cells, and suggest that NEGR1 is a potential molecular target for designing anti-obesity drugs to regulate body weight both centrally and peripherally.

Neural cell adhesion molecule Negr1 deficiency in mouse results in structural brain endophenotypes and behavioral deviations related to psychiatric disorders

Neuronal growth regulator 1 (NEGR1) belongs to the immunoglobulin (IgLON) superfamily of cell adhesion molecules involved in cortical layering. Recent functional and genomic studies implicate the role of NEGR1 in a wide spectrum of psychiatric disorders, such as major depression, schizophrenia and autism. Here, we investigated the impact of Negr1 deficiency on brain morphology, neuronal properties and social behavior of mice. In situ hybridization shows Negr1 expression in the brain nuclei which are central modulators of cortical-subcortical connectivity such as the island of Calleja and the reticular nucleus of thalamus. Brain morphological analysis revealed neuroanatomical abnormalities in Negr1^−/− mice, including enlargement of ventricles and decrease in the volume of the whole brain, corpus callosum, globus pallidus and hippocampus. Furthermore, decreased number of parvalbumin-positive inhibitory interneurons was evident in Negr1^−/− hippocampi. Behaviorally, Negr1^−/− mice displayed hyperactivity in social interactions and impairments in social hierarchy. Finally, Negr1 deficiency resulted in disrupted neurite sprouting during neuritogenesis. Our results provide evidence that NEGR1 is required for balancing the ratio of excitatory/inhibitory neurons and proper formation of brain structures, which is prerequisite for adaptive behavioral profiles. Therefore, Negr1^−/− mice have a high potential to provide new insights into the neural mechanisms of neuropsychiatric disorders.

The association of obesity and coronary artery disease genes with response to SSRIs treatment in major depression

Selective serotonin reuptake inhibitors (SSRIs) are first-line antidepressants for the treatment of major depressive disorder (MDD). However, treatment response during an initial therapeutic trial is often poor and is difficult to predict. Heterogeneity of response to SSRIs in depressed patients is partly driven by co-occurring somatic disorders such as coronary artery disease (CAD) and obesity. CAD and obesity may also be associated with metabolic side effects of SSRIs. In this study, we assessed the association of CAD and obesity with treatment response to SSRIs in patients with MDD using a polygenic score (PGS) approach. Additionally, we performed cross-trait meta-analyses to pinpoint genetic variants underpinnings the relationship of CAD and obesity with SSRIs treatment response. First, PGSs were calculated at different p value thresholds (P_T) for obesity and CAD. Next, binary logistic regression was applied to evaluate the association of the PGSs to SSRIs treatment response in a discovery sample (ISPC, N = 865), and in a replication cohort (STAR*D, N = 1,878). Finally, a cross-trait GWAS meta-analysis was performed by combining summary statistics. We show that the PGSs for CAD and obesity were inversely associated with SSRIs treatment response. At the most significant thresholds, the PGS for CAD and body mass index accounted 1.3%, and 0.8% of the observed variability in treatment response to SSRIs, respectively. In the cross-trait meta-analyses, we identified (1) 14 genetic loci (including NEGR1, CADM2, PMAIP1, PARK2) that are associated with both obesity and SSRIs treatment response; (2) five genetic loci (LINC01412, PHACTR1, CDKN2B, ATXN2, KCNE2) with effects on CAD and SSRIs treatment response. Our findings implicate that the genetic variants of CAD and obesity are linked to SSRIs treatment response in MDD. A better SSRIs treatment response might be achieved through a stratified allocation of treatment for MDD patients with a genetic risk for obesity or CAD.

In silico approach to identify non-synonymous SNPs with highest predicted deleterious effect on protein function in human obesity related gene, neuronal growth regulator 1 (NEGR1)

Neuronal growth regulator 1 (NEGR1) is a candidate gene for human obesity, which encodes the neural cell adhesion and growth molecule. The aim of the current study was to recognize the non-synonymous SNPs (nsSNPs) with the highest predicted deleterious effect on protein function of the NEGR1 gene. We have used five computational tools, namely, PolyPhen, SIFT, PROVEAN, MutPred and M-CAP, to predict the deleterious and pathogenic nsSNPs of the NEGR1 gene. Homology modeling approach was used to model the native and mutant NEGR1 protein models. Furthermore, structural validation was performed by the PROCHECK server to interpret the stability of the predicted models. We have predicted four potential deleterious nsSNPs, i.e., rs145524630 (Ala70Thr), rs267598710 (Pro168Leu), rs373419972 (Arg239Cys) and rs375352213 (Leu158Phe), which might be involved in causing obesity phenotypes. The predicted mutant models showed higher root mean square deviation and free energy values under the PyMoL and SWISS-PDB viewer, respectively. Additionally, the FTSite server predicted one nsSNP, i.e., rs145524630 (Ala70Thr) out of four identified nsSNPs found in the NEGR1 protein-binding site. There were four potential deleterious and pathogenic nsSNPs, i.e., rs145524630, rs267598710, rs373419972 and rs375352213, identified from the above-mentioned tools. In future, further functional in vitro and in vivo analysis could lead to better knowledge about these nsSNPs on the influence of the NEGR1 gene in causing human obesity. Hence, the present computational examination suggest that predicated nsSNPs may feasibly be a drug target and play an important role in contributing to human obesity.

Do GWAS and studies of heterozygotes for NPC1 and/or NPC2 explain why NPC disease cases are so rare?

Early onset Niemann-Pick C diseases are extremely rare, especially Niemann-Pick C2. Perhaps unusually for autosomal recessive diseases, heterozygotes for mutations in NPC1 manifest many biological variations. NPC2 deficiency has large effects on fertility. These features of NPC1 and NPC2 are reviewed in regard to possible negative selection for heterozygotes carrying null and hypomorphic alleles.

Time-of-Day Dependent Neuronal Injury After Ischemic Stroke: Implication of Circadian Clock Transcriptional Factor Bmal1 and Survival Kinase AKT

Occurrence of stroke cases displays a time-of-day variation in human. However, the mechanism linking circadian rhythm to the internal response mechanisms against pathophysiological events after ischemic stroke remained largely unknown. To this end, temporal changes in the susceptibility to ischemia/reperfusion (I/R) injury were investigated in mice in which the ischemic stroke induced at four different Zeitgeber time points with 6-h intervals (ZT0, ZT6, ZT12, and ZT18). Besides infarct volume and brain swelling, neuronal survival, apoptosis, ischemia, and circadian rhythm related proteins were examined using immunohistochemistry, Western blot, planar surface immune assay, and liquid chromatography-mass spectrometry tools. Here, we present evidence that midnight (ZT18; 24:00) I/R injury in mice resulted in significantly improved infarct volume, brain swelling, neurological deficit score, neuronal survival, and decreased apoptotic cell death compared with ischemia induced at other time points, which were associated with increased expressions of circadian proteins Bmal1, PerI, and Clock proteins and survival kinases AKT and Erk-1/2. Moreover, ribosomal protein S6, mTOR, and Bad were also significantly increased, while the levels of PRAS40, negative regulator of AKT and mTOR, and phosphorylated p53 were decreased at this time point compared to ZT0 (06:00). Furthermore, detailed proteomic analysis revealed significantly decreased CSKP, HBB-1/2, and HBA levels, while increased GNAZ, NEGR1, IMPCT, and PDE1B at midnight as compared with early morning. Our results indicate that nighttime I/R injury results in less severe neuronal damage, with increased neuronal survival, increased levels of survival kinases and circadian clock proteins, and also alters the circadian-related proteins.

Glycosylphosphatidylinositol-Anchored Immunoglobulin Superfamily Cell Adhesion Molecules and Their Role in Neuronal Development and Synapse Regulation

Immunoglobulin superfamily (IgSF) cell adhesion molecules (CAMs) are cell surface glycoproteins that not only mediate interactions between neurons but also between neurons and other cells in the nervous system. While typical IgSF CAMs are transmembrane molecules, this superfamily also includes CAMs, which do not possess transmembrane and intracellular domains and are instead attached to the plasma membrane via a glycosylphosphatidylinositol (GPI) anchor. In this review, we focus on the role GPI-anchored IgSF CAMs have as signal transducers and ligands in neurons, and discuss their functions in regulation of neuronal development, synapse formation, synaptic plasticity, learning, and behavior. We also review the links between GPI-anchored IgSF CAMs and brain disorders.