Microheterogeneity in the Kinetics and Sex-Specific Response to Type I IFN.

The response to type I IFNs involves the rapid induction of prototypical IFN signature genes (ISGs). It is not known whether the tightly controlled ISG expression observed at the cell population level correctly represents the coherent responses of individual cells or whether it masks some heterogeneity in gene modules and/or responding cells. We performed a time-resolved single-cell analysis of the first 3 h after in vivo IFN stimulation in macrophages and CD4+ T and B lymphocytes from mice. All ISGs were generally induced in concert, with no clear cluster of faster- or slower-responding ISGs. Response kinetics differed between cell types: mostly homogeneous for macrophages, but with far more kinetic diversity among B and T lymphocytes, which included a distinct subset of nonresponsive cells. Velocity analysis confirmed the differences between macrophages in which the response progressed throughout the full 3 h, versus B and T lymphocytes in which it was rapidly curtailed by negative feedback and revealed differences in transcription rates between the lineages. In all cell types, female cells responded faster than their male counterparts. The ISG response thus seems to proceed as a homogeneous gene block, but with kinetics that vary between immune cell types and with sex differences that might underlie differential outcomes of viral infections.

Cell subtype-specific effects of genetic variation in the Alzheimer's disease brain.

The relationship between genetic variation and gene expression in brain cell types and subtypes remains understudied. Here, we generated single-nucleus RNA sequencing data from the neocortex of 424 individuals of advanced age; we assessed the effect of genetic variants on RNA expression in cis (cis-expression quantitative trait loci) for seven cell types and 64 cell subtypes using 1.5 million transcriptomes. This effort identified 10,004 eGenes at the cell type level and 8,099 eGenes at the cell subtype level. Many eGenes are only detected within cell subtypes. A new variant influences APOE expression only in microglia and is associated with greater cerebral amyloid angiopathy but not Alzheimer's disease pathology, after adjusting for APOEε4, providing mechanistic insights into both pathologies. Furthermore, only a TMEM106B variant affects the proportion of cell subtypes. Integration of these results with genome-wide association studies highlighted the targeted cell type and probable causal gene within Alzheimer's disease, schizophrenia, educational attainment and Parkinson's disease loci.

AIRE relies on Z-DNA to flag gene targets for thymic T cell tolerization.

AIRE is an unconventional transcription factor that enhances the expression of thousands of genes in medullary thymic epithelial cells and promotes clonal deletion or phenotypic diversion of self-reactive T cells1-4. The biological logic of AIRE's target specificity remains largely unclear as, in contrast to many transcription factors, it does not bind to a particular DNA sequence motif. Here we implemented two orthogonal approaches to investigate AIRE's cis-regulatory mechanisms: construction of a convolutional neural network and leveraging natural genetic variation through analysis of F1 hybrid mice5. Both approaches nominated Z-DNA and NFE2-MAF as putative positive influences on AIRE's target choices. Genome-wide mapping studies revealed that Z-DNA-forming and NFE2L2-binding motifs were positively associated with the inherent ability of a gene's promoter to generate DNA double-stranded breaks, and promoters showing strong double-stranded break generation were more likely to enter a poised state with accessible chromatin and already-assembled transcriptional machinery. Consequently, AIRE preferentially targets genes with poised promoters. We propose a model in which Z-DNA anchors the AIRE-mediated transcriptional program by enhancing double-stranded break generation and promoter poising. Beyond resolving a long-standing mechanistic conundrum, these findings suggest routes for manipulating T cell tolerance.

Sex-dependent placental methylation quantitative trait loci provide insight into the prenatal origins of childhood onset traits and conditions.

Molecular quantitative trait loci (QTLs) allow us to understand the biology captured in genome-wide association studies (GWASs). The placenta regulates fetal development and shows sex differences in DNA methylation. We therefore hypothesized that placental methylation QTL (mQTL) explain variation in genetic risk for childhood onset traits, and that effects differ by sex. We analyzed 411 term placentas from two studies and found 49,252 methylation (CpG) sites with mQTL and 2,489 CpG sites with sex-dependent mQTL. All mQTL were enriched in regions that typically affect gene expression in prenatal tissues. All mQTL were also enriched in GWAS results for growth- and immune-related traits, but male- and female-specific mQTL were more enriched than cross-sex mQTL. mQTL colocalized with trait loci at 777 CpG sites, with 216 (28%) specific to males or females. Overall, mQTL specific to male and female placenta capture otherwise overlooked variation in childhood traits.

Recurrent cannabis-induced catatonia: a case report and comprehensive systematic literature review.

Background: Catatonia presents itself as a complex neuropsychiatric syndrome, giving rise to various motor, speech, and behavioral challenges. It is noteworthy that approximately 10% of psychiatric hospital admissions can be attributed to this condition. It is imperative to note that cannabis-induced catatonia, while infrequent, has been linked to the use of marijuana. This connection has the potential to disrupt neurotransmitter systems, necessitating further research for a comprehensive understanding and effective treatment, particularly given the evolving trends in cannabis use. In this context, we shall delve into a unique case of recurrent cannabis-induced catatonia. Case presentation: A 23-year-old gentleman, who has previously struggled with substance use disorder, experienced the emergence of mutism, social isolation, and a fixed gaze subsequent to his use of cannabis. Remarkably, despite the absence of hallucinations, he exhibited recurrent episodes of catatonia. These episodes were effectively addressed through a combination of electroconvulsive therapy (ECT) and lorazepam administration. Notably, when the lorazepam dosage was gradually reduced to below 2 mg per day, the catatonic symptoms resurfaced; however, they promptly abated upon reinstating the medication. The diagnosis of cannabis-induced catatonia was established, and its management primarily involved a therapeutic approach encompassing ECT and lorazepam. It is pertinent to underscore that this catatonic condition can be directly linked to the individual's cannabis usage. Conclusion: The connection between cannabis and catatonia is intricate and not entirely comprehended. Although cannabis possesses therapeutic advantages, it can paradoxically trigger catatonia in certain individuals. Multiple factors, such as genetics, cannabinoids, and neurotransmitter systems, contribute to this intricacy, underscoring the necessity for additional research.

Maternal psychological stress during pregnancy and newborn telomere length: a systematic review and meta-analysis.

INTRODUCTION: Telomeres protect the ends of chromosomes, and shorter leukocyte telomeres are associated with major group diseases. Maternal psychological stress may be related to the shortening of telomeres in infants. This systematic review and meta-analysis set out to consolidate the varying effect sizes found in studies of maternal psychological stress and telomere length (TL) in newborns and identify moderators of the relationship between stress during pregnancy and newborn TL. METHODS: Our systematic review was registered in Prospero. Six databases (PubMed, Scopus, Embase, PsycINFO, Web of Science, and CINAHL Complete) were searched for records in English from inception to February 10, 2023. Observational studies were included that measured the relationship of psychological stress of the mother during pregnancy on the TL of the newborn. The Newcastle-Ottawa quality assessment scale was used to assess the quality of the included studies. A random-effect model was selected. Statistical analysis performed by Stata software version 17. RESULTS: Eight studies were included for qualitative and four for quantitative analysis. There was an inverse statistically significant relationship between maternal stress and newborn TL; A one score increase in maternal psychological stress resulted in a 0.04 decrease in the TL of the newborn (B = -0.04, 95% CI = [-0.08, 0.00], p = 0.05). Selectivity analysis showed that the pooled effect size was sensitive to one study; After removing this study, the pooled effect size remained significant (B = -0.06, 95% CI = [-0. 10, -0.02], p < 0.001). CONCLUSION: Physiological and environmental factors can significantly affect the TL of newborns. Our results support a significant impact of maternal psychological stress on the TL of a newborn. This association demonstrates the significance of stress in influencing the telomere length, which can be a contributing factor in the infant's future. Therefore, recognizing this association is crucial for understanding and addressing potential health risks and necessitates the need for additional future studies to validate our findings.

Benchmarking of deep neural networks for predicting personal gene expression from DNA sequence highlights shortcomings.

Deep learning methods have recently become the state of the art in a variety of regulatory genomic tasks1-6, including the prediction of gene expression from genomic DNA. As such, these methods promise to serve as important tools in interpreting the full spectrum of genetic variation observed in personal genomes. Previous evaluation strategies have assessed their predictions of gene expression across genomic regions; however, systematic benchmarking is lacking to assess their predictions across individuals, which would directly evaluate their utility as personal DNA interpreters. We used paired whole genome sequencing and gene expression from 839 individuals in the ROSMAP study7 to evaluate the ability of current methods to predict gene expression variation across individuals at varied loci. Our approach identifies a limitation of current methods to correctly predict the direction of variant effects. We show that this limitation stems from insufficiently learned sequence motif grammar and suggest new model training strategies to improve performance.

The effects of transcranial direct-current stimulation (tDCS) on pain intensity of patients with fibromyalgia: a systematic review and meta-analysis.

INTRODUCTION: Fibromyalgia (FM) is a chronic pain condition that affects millions of people worldwide. Transcranial Direct Current Stimulation (tDCS) is a non-invasive brain stimulation technique that has shown promise as a potential treatment for FM by modulating pain perception and reducing symptoms, such as fatigue and depression. We aimed to systematically review studies that assess the effect of tDCS on pain reduction in FM patients. METHODS: Seven electronic databases (PubMed, Scopus, Embase, PsycINFO, Web of Science, Cochrane, and CINAHL Complete) were searched for records in English. Studies that measured the effect of tDCS on pain intensity in FM patients were included. The Cochrane Collaboration's tool was used to assess the quality of the included studies. A random-effect model was preferred, and statistical analysis was performed by Stata software version 17. RESULTS: Twenty studies were included for qualitative, and eleven for quantitative analysis. Out of 664 patients included in the study, 443 were in the stimulation group. The left M1 area was the most common stimulation target (n = 12), and 2 mA was the most common stimulation amplitude (n = 19). The analysis showed that active tDCS significantly reduced pain intensity in FM patients in comparison to the sham group (SMD= -1.55; 95% CI -2.10, -0.99); also, no publication bias was noted. CONCLUSION: Our systematic review highlights the potential effect of tDCS on the reduction of pain intensity in FM patients. Additionally, this current evidence could suggest that tDCS applied at an intensity of 2mA to the left M1 is the most effective strategy.

Impact on splicing in Saccharomyces cerevisiae of random 50-base sequences inserted into an intron.

Intron splicing is a key regulatory step in gene expression in eukaryotes. Three sequence elements required for splicing-5' and 3' splice sites and a branchpoint-are especially well-characterized in Saccharomyces cerevisiae, but our understanding of additional intron features that impact splicing in this organism is incomplete, due largely to its small number of introns. To overcome this limitation, we constructed a library in S. cerevisiae of random 50-nt (N50) elements individually inserted into the intron of a reporter gene and quantified canonical splicing and the use of cryptic splice sites by sequencing analysis. More than 70% of approximately 140,000 N50 elements reduced splicing by at least 20%. N50 features, including higher GC content, presence of GU repeats, and stronger predicted secondary structure of its pre-mRNA, correlated with reduced splicing efficiency. A likely basis for the reduced splicing of such a large proportion of variants is the formation of RNA structures that pair N50 bases-such as the GU repeats-with other bases specifically within the reporter pre-mRNA analyzed. However, multiple models were unable to explain more than a small fraction of the variance in splicing efficiency across the library, suggesting that complex nonlinear interactions in RNA structures are not accurately captured by RNA structure prediction methods. Our results imply that the specific context of a pre-mRNA may determine the bases allowable in an intron to prevent secondary structures that reduce splicing. This large data set can serve as a resource for further exploration of splicing mechanisms.

Sex and cell-specific gene expression in corticolimbic brain regions associated with psychiatric disorders revealed by bulk and single-nuclei RNA sequencing.

BACKGROUND: There are sex-specific differences in the prevalence, symptomology and course of psychiatric disorders. However, preclinical models have primarily used males, such that the molecular mechanisms underlying sex-specific differences in psychiatric disorders are not well established. METHODS: In this study, we compared transcriptome-wide gene expression profiles in male and female rats within the corticolimbic system, including the cingulate cortex, nucleus accumbens medial shell (NAcS), ventral dentate gyrus and the basolateral amygdala (n = 22-24 per group/region). FINDINGS: We found over 3000 differentially expressed genes (DEGs) in the NAcS between males and females. Of these DEGs in the NAcS, 303 showed sex-dependent conservation DEGs in humans and were significantly enriched for gene ontology terms related to blood vessel morphogenesis and regulation of cell migration. Single nuclei RNA sequencing in the NAcS of male and female rats identified widespread sex-dependent expression, with genes upregulated in females showing a notable enrichment for synaptic function. Female upregulated genes in astrocytes, Drd3+MSNs and oligodendrocyte were also enriched in several psychiatric genome-wide association studies (GWAS). INTERPRETATION: Our data provide comprehensive evidence of sex- and cell-specific molecular profiles in the NAcS. Importantly these differences associate with anxiety, bipolar disorder, schizophrenia, and cross-disorder, suggesting an intrinsic molecular basis for sex-based differences in psychiatric disorders that strongly implicates the NAcS. FUNDING: This work was supported by funding from the Hope for Depression Research Foundation (MJM).

Dominant negative variants in IKZF2 cause ICHAD syndrome, a new disorder characterised by immunodysregulation, craniofacial anomalies, hearing impairment, athelia and developmental delay.

BACKGROUND: Helios (encoded by IKZF2), a member of the Ikaros family of transcription factors, is a zinc finger protein involved in embryogenesis and immune function. Although predominantly recognised for its role in the development and function of T lymphocytes, particularly the CD4+ regulatory T cells (Tregs), the expression and function of Helios extends beyond the immune system. During embryogenesis, Helios is expressed in a wide range of tissues, making genetic variants that disrupt the function of Helios strong candidates for causing widespread immune-related and developmental abnormalities in humans. METHODS: We performed detailed phenotypic, genomic and functional investigations on two unrelated individuals with a phenotype of immune dysregulation combined with syndromic features including craniofacial differences, sensorineural hearing loss and congenital abnormalities. RESULTS: Genome sequencing revealed de novo heterozygous variants that alter the critical DNA-binding zinc fingers (ZFs) of Helios. Proband 1 had a tandem duplication of ZFs 2 and 3 in the DNA-binding domain of Helios (p.Gly136_Ser191dup) and Proband 2 had a missense variant impacting one of the key residues for specific base recognition and DNA interaction in ZF2 of Helios (p.Gly153Arg). Functional studies confirmed that both these variant proteins are expressed and that they interfere with the ability of the wild-type Helios protein to perform its canonical function-repressing IL2 transcription activity-in a dominant negative manner. CONCLUSION: This study is the first to describe dominant negative IKZF2 variants. These variants cause a novel genetic syndrome characterised by immunodysregulation, craniofacial anomalies, hearing impairment, athelia and developmental delay.

Gemini: memory-efficient integration of hundreds of gene networks with high-order pooling.

MOTIVATION: The exponential growth of genomic sequencing data has created ever-expanding repositories of gene networks. Unsupervised network integration methods are critical to learn informative representations for each gene, which are later used as features for downstream applications. However, these network integration methods must be scalable to account for the increasing number of networks and robust to an uneven distribution of network types within hundreds of gene networks. RESULTS: To address these needs, we present Gemini, a novel network integration method that uses memory-efficient high-order pooling to represent and weight each network according to its uniqueness. Gemini then mitigates the uneven network distribution through mixing up existing networks to create many new networks. We find that Gemini leads to more than a 10% improvement in F1 score, 15% improvement in micro-AUPRC, and 63% improvement in macro-AUPRC for human protein function prediction by integrating hundreds of networks from BioGRID, and that Gemini's performance significantly improves when more networks are added to the input network collection, while Mashup and BIONIC embeddings' performance deteriorates. Gemini thereby enables memory-efficient and informative network integration for large gene networks and can be used to massively integrate and analyze networks in other domains. AVAILABILITY AND IMPLEMENTATION: Gemini can be accessed at: https://github.com/MinxZ/Gemini.

ExplaiNN: interpretable and transparent neural networks for genomics.

Deep learning models such as convolutional neural networks (CNNs) excel in genomic tasks but lack interpretability. We introduce ExplaiNN, which combines the expressiveness of CNNs with the interpretability of linear models. ExplaiNN can predict TF binding, chromatin accessibility, and de novo motifs, achieving performance comparable to state-of-the-art methods. Its predictions are transparent, providing global (cell state level) as well as local (individual sequence level) biological insights into the data. ExplaiNN can serve as a plug-and-play platform for pretrained models and annotated position weight matrices. ExplaiNN aims to accelerate the adoption of deep learning in genomic sequence analysis by domain experts.

Benchmarking of deep neural networks for predicting personal gene expression from DNA sequence highlights shortcomings.

Deep learning methods have recently become the state-of-the-art in a variety of regulatory genomic tasks1-6 including the prediction of gene expression from genomic DNA. As such, these methods promise to serve as important tools in interpreting the full spectrum of genetic variation observed in personal genomes. Previous evaluation strategies have assessed their predictions of gene expression across genomic regions, however, systematic benchmarking is lacking to assess their predictions across individuals, which would directly evaluates their utility as personal DNA interpreters. We used paired Whole Genome Sequencing and gene expression from 839 individuals in the ROSMAP study7 to evaluate the ability of current methods to predict gene expression variation across individuals at varied loci. Our approach identifies a limitation of current methods to correctly predict the direction of variant effects. We show that this limitation stems from insufficiently learnt sequence motif grammar, and suggest new model training strategies to improve performance.

In silico discovery of small molecules for efficient stem cell differentiation into definitive endoderm.

Improving methods for human embryonic stem cell differentiation represents a challenge in modern regenerative medicine research. Using drug repurposing approaches, we discover small molecules that regulate the formation of definitive endoderm. Among them are inhibitors of known processes involved in endoderm differentiation (mTOR, PI3K, and JNK pathways) and a new compound, with an unknown mechanism of action, capable of inducing endoderm formation in the absence of growth factors in the media. Optimization of the classical protocol by inclusion of this compound achieves the same differentiation efficiency with a 90% cost reduction. The presented in silico procedure for candidate molecule selection has broad potential for improving stem cell differentiation protocols.

AAV5-miHTT-mediated huntingtin lowering improves brain health in a Huntington's disease mouse model.

Huntingtin (HTT)-lowering therapies show great promise in treating Huntington's disease. We have developed a microRNA targeting human HTT that is delivered in an adeno-associated serotype 5 viral vector (AAV5-miHTT), and here use animal behaviour, MRI, non-invasive proton magnetic resonance spectroscopy and striatal RNA sequencing as outcome measures in preclinical mouse studies of AAV5-miHTT. The effects of AAV5-miHTT treatment were evaluated in homozygous Q175FDN mice, a mouse model of Huntington's disease with severe neuropathological and behavioural phenotypes. Homozygous mice were used instead of the more commonly used heterozygous strain, which exhibit milder phenotypes. Three-month-old homozygous Q175FDN mice, which had developed acute phenotypes by the time of treatment, were injected bilaterally into the striatum with either formulation buffer (phosphate-buffered saline + 5% sucrose), low dose (5.2 × 109 genome copies/mouse) or high dose (1.3 × 1011 genome copies/mouse) AAV5-miHTT. Wild-type mice injected with formulation buffer served as controls. Behavioural assessments of cognition, T1-weighted structural MRI and striatal proton magnetic resonance spectroscopy were performed 3 months after injection, and shortly afterwards the animals were sacrificed to collect brain tissue for protein and RNA analysis. Motor coordination was assessed at 1-month intervals beginning at 2 months of age until sacrifice. Dose-dependent changes in AAV5 vector DNA level, miHTT expression and mutant HTT were observed in striatum and cortex of AAV5-miHTT-treated Huntington's disease model mice. This pattern of microRNA expression and mutant HTT lowering rescued weight loss in homozygous Q175FDN mice but did not affect motor or cognitive phenotypes. MRI volumetric analysis detected atrophy in four brain regions in homozygous Q175FDN mice, and treatment with high dose AAV5-miHTT rescued this effect in the hippocampus. Like previous magnetic resonance spectroscopy studies in Huntington's disease patients, decreased total N-acetyl aspartate and increased myo-inositol levels were found in the striatum of homozygous Q175FDN mice. These neurochemical findings were partially reversed with AAV5-miHTT treatment. Striatal transcriptional analysis using RNA sequencing revealed mutant HTT-induced changes that were partially reversed by HTT lowering with AAV5-miHTT. Striatal proton magnetic resonance spectroscopy analysis suggests a restoration of neuronal function, and striatal RNA sequencing analysis shows a reversal of transcriptional dysregulation following AAV5-miHTT in a homozygous Huntington's disease mouse model with severe pathology. The results of this study support the use of magnetic resonance spectroscopy in HTT-lowering clinical trials and strengthen the therapeutic potential of AAV5-miHTT in reversing severe striatal dysfunction in Huntington's disease.

Obtaining genetics insights from deep learning via explainable artificial intelligence.

Artificial intelligence (AI) models based on deep learning now represent the state of the art for making functional predictions in genomics research. However, the underlying basis on which predictive models make such predictions is often unknown. For genomics researchers, this missing explanatory information would frequently be of greater value than the predictions themselves, as it can enable new insights into genetic processes. We review progress in the emerging area of explainable AI (xAI), a field with the potential to empower life science researchers to gain mechanistic insights into complex deep learning models. We discuss and categorize approaches for model interpretation, including an intuitive understanding of how each approach works and their underlying assumptions and limitations in the context of typical high-throughput biological datasets.

Human JAK1 gain of function causes dysregulated myelopoeisis and severe allergic inflammation.

Primary atopic disorders are a group of inborn errors of immunity that skew the immune system toward severe allergic disease. Defining the biology underlying these extreme monogenic phenotypes reveals shared mechanisms underlying common polygenic allergic disease and identifies potential drug targets. Germline gain-of-function (GOF) variants in JAK1 are a cause of severe atopy and eosinophilia. Modeling the JAK1GOF (p.A634D) variant in both zebrafish and human induced pluripotent stem cells (iPSCs) revealed enhanced myelopoiesis. RNA-Seq of JAK1GOF human whole blood, iPSCs, and transgenic zebrafish revealed a shared core set of dysregulated genes involved in IL-4, IL-13, and IFN signaling. Immunophenotypic and transcriptomic analysis of patients carrying a JAK1GOF variant revealed marked Th cell skewing. Moreover, long-term ruxolitinib treatment of 2 children carrying the JAK1GOF (p.A634D) variant remarkably improved their growth, eosinophilia, and clinical features of allergic inflammation. This work highlights the role of JAK1 signaling in atopic immune dysregulation and the clinical impact of JAK1/2 inhibition in treating eosinophilic and allergic disease.

Quantitative serum determination of CD3, CD4, CD8, CD16, and CD56 in women with primary infertility: The role of cell-mediated immunity.

Objective: Cellular adaptive immunity plays an essential role in the etiology of primary infertility. This study aimed to measure the T-lymphocyte subpopulations and natural killer (NK) cells in infertile women compared with healthy ones. Materials and Methods: From January to September 2021, we conducted this cross-sectional study among women with primary infertility, and healthy women were referred to Isfahan Fertility and Infertility Center affiliated with Najafabad University of medical sciences in Isfahan, Iran for immunological investigations. For each person, we determined quantitative serum measurements of CD3, CD4, CD8, CD4/CD8, CD16, CD56, and CD56+16. Results: This study included one hundred and fifty-one infertile women with a mean age of 31.4±4.7 years and 46 healthy women with a mean age of 31.5±3.4 years. Compared to the controls, immunophenotyping findings in infertile patients revealed a significant drop in CD8 T cells [p=0.01, 95% confidence interval (CI) 0.53 to 4.57] and the percentage of CD 56 NK cells (p=0.005, 95% CI 0.74 to 4.03) in infertile patients. Conclusion: Despite having a normal quantity of CD3 T cells, infertile women had lower CD8 T cells and CD56 NK cells than the controls. More studies are needed to confirm the role of cell-mediated assessments as a screening test in patients with primary infertility.

Mosaic loss of Chromosome Y in aged human microglia.

Mosaic loss of Chromosome Y (LOY) is a common acquired structural mutation in the leukocytes of aging men that is correlated with several age-related diseases, including Alzheimer's disease (AD). The molecular basis of LOY in brain cells has not been systematically investigated. Here, we present a large-scale analysis of single-cell and single-nuclei RNA brain data sets, yielding 851,674 cells, to investigate the cell type-specific burden of LOY. LOY frequencies differed widely between donors and CNS cell types. Among five well-represented neural cell types, LOY was enriched in microglia and rare in neurons, astrocytes, and oligodendrocytes. In microglia, LOY was significantly enriched in AD subjects. Differential gene expression (DE) analysis in microglia found 172 autosomal genes, three X-linked genes, and 10 pseudoautosomal genes associated with LOY. To our knowledge, we provide the first evidence of LOY in the microglia and highlight its potential roles in aging and the pathogenesis of neurodegenerative disorders such as AD.