Shared mechanisms across the major psychiatric and neurodegenerative diseases

A TrkB cleavage fragment in hippocampus promotes Depressive-Like behavior in mice

Decreased hippocampal tropomyosin receptor kinase B (TrkB) level is implicated in the pathophysiology of stress-induced mood disorder and cognitive decline. However, how TrkB is modified and mediates behavioral responses to chronic stress remains largely unknown. Here the effects and mechanisms of TrkB cleavage by asparagine endopeptidase (AEP) were examined on a preclinical murine model of chronic restraint stress (CRS)-induced depression. CRS activated IL-1β-C/EBPβ-AEP pathway in mice hippocampus, accompanied by elevated TrkB 1-486 fragment generated by AEP. Specifi.c overexpression or suppression of AEP-TrkB axis in hippocampal CaMKIIα-positive cells aggravated or relieved depressive-like behaviors, respectively. Mechanistically, in addition to facilitating AMPARs internalization, TrkB 1-486 interacted with peroxisome proliferator-activated receptor-δ (PPAR-δ) and sequestered it in cytoplasm, repressing PPAR-δ-mediated transactivation and mitochondrial function. Moreover, co-administration of 7,8-dihydroxyflavone and a peptide disrupting the binding of TrkB 1-486 with PPAR-δ attenuated depression-like symptoms not only in CRS animals, but also in Alzheimer's disease and aged mice. These findings reveal a novel role for TrkB cleavage in promoting depressive-like phenotype.

Major Psychiatric Disorders, Substance Use Behaviors, and Longevity

Importance

Observational studies suggest that major psychiatric disorders and substance use behaviors reduce longevity, making it difficult to disentangle their relationships with aging-related outcomes.

Objective

To evaluate the associations between the genetic liabilities for major psychiatric disorders, substance use behaviors (smoking and alcohol consumption), and longevity.

Design, Settings, and Participants

This 2-sample mendelian randomization (MR) study assessed associations between psychiatric disorders, substance use behaviors, and longevity using single-variable and multivariable models. Multiomics analyses were performed elucidating transcriptomic underpinnings of the MR associations and identifying potential proteomic therapeutic targets. This study sourced summary-level genome-wide association study (GWAS) data, gene expression, and proteomic data from cohorts of European ancestry. Analyses were performed from May 2022 to November 2023.

Exposures

Genetic susceptibility for major depression (n = 500 199), bipolar disorder (n = 413 466), schizophrenia (n = 127 906), problematic alcohol use (n = 435 563), weekly alcohol consumption (n = 666 978), and lifetime smoking index (n = 462 690).

Main Outcomes and Measures

The main outcome encompassed aspects of health span, lifespan, and exceptional longevity. Additional outcomes were epigenetic age acceleration (EAA) clocks.

Results

Findings from multivariable MR models simultaneously assessing psychiatric disorders and substance use behaviorsm suggest a negative association between smoking and longevity in cohorts of European ancestry (n = 709 709; 431 503 [60.8%] female; β, -0.33; 95% CI, -0.38 to -0.28; P = 4.59 × 10-34) and with increased EAA (n = 34 449; 18 017 [52.3%] female; eg, PhenoAge: β, 1.76; 95% CI, 0.72 to 2.79; P = 8.83 × 10-4). Transcriptomic imputation and colocalization identified 249 genes associated with smoking, including 36 novel genes not captured by the original smoking GWAS. Enriched pathways included chromatin remodeling and telomere assembly and maintenance. The transcriptome-wide signature of smoking was inversely associated with longevity, and estimates of individual smoking-associated genes, eg, XRCC3 and PRMT6, aligned with the smoking-longevity MR analyses, suggesting underlying transcriptomic mediators. Cis-instrument MR prioritized brain proteins associated with smoking behavior, including LY6H (β, 0.02; 95% CI, 0.01 to 0.03; P = 2.37 × 10-6) and RIT2 (β, 0.02; 95% CI, 0.01 to 0.03; P = 1.05 × 10-5), which had favorable adverse-effect profiles across 367 traits evaluated in phenome-wide MR.

Conclusions

The findings suggest that the genetic liability of smoking, but not of psychiatric disorders, is associated with longevity. Transcriptomic associations offer insights into smoking-related pathways, and identified proteomic targets may inform therapeutic development for smoking cessation strategies.

Emerging therapies for treatment of agitation, psychosis, or apathy in Alzheimer's disease

INTRODUCTION

Agitation, psychosis, and apathy are prevalent and highly distressing neuropsychiatric symptoms (NPS) of Alzheimer's disease (AD) that have been linked to numerous negative outcomes, including increased mortality, worsened cognitive decline, and caregiver burden. Current treatments for AD-associated agitation, namely atypical antipsychotics, provide some benefits but may increase the risk of serious adverse events and death. Meanwhile, no pharmacotherapies have been approved by regulatory agencies for the treatment of psychosis or apathy in AD. Over the past decade, many new and repurposed drugs have emerged as potential therapeutic options for managing these challenging NPS.

AREAS COVERED

This review aims to provide a comprehensive summary of pharmacotherapies that have recently been investigated in phase 2 and 3 clinical trials for the treatment of agitation, psychosis, or apathy in AD.

EXPERT OPINION

Novel atypical antipsychotics, serotonergic antidepressants, cannabinoids, and dextromethorphan combination drugs have shown promising results for alleviating agitation. Pimavanserin appears to be the most effective emerging therapy for psychosis, while methylphenidate has demonstrated good efficacy for apathy. Further research on biomarkers of NPS severity and treatment response, as well as continued improvements in methodological approaches are needed to advance the field.

Shared genetic links between hypothyroidism and psychiatric disorders: evidence from a comprehensive genetic analysis

Background

Epidemiologic studies have suggested co-morbidity between hypothyroidism and psychiatric disorders. However, the shared genetic etiology and causal relationship between them remain currently unclear.

Methods

We assessed the genetic correlations between hypothyroidism and psychiatric disorders [anxiety disorders (ANX), schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP)] using summary association statistics from genome-wide association studies (GWAS). Two disease-associated pleiotropic risk loci and genes were identified, and pathway enrichment, tissue enrichment, and other analyses were performed to determine their specific functions. Furthermore, we explored the causal relationship between them through Mendelian randomization (MR) analysis.

Results

We found significant genetic correlations between hypothyroidism with ANX, SCZ, and MDD, both in the Linkage disequilibrium score regression (LDSC) approach and the high-definition likelihood (HDL) approach. Meanwhile, the strongest correlation was observed between hypothyroidism and MDD (LDSC: rg=0.264, P=7.35×10-12; HDL: rg=0.304, P=4.14×10-17). We also determined a significant genetic correlation between MDD with free thyroxine (FT4) and thyroid-stimulating hormone (TSH) levels. A total of 30 pleiotropic risk loci were identified between hypothyroidism and psychiatric disorders, of which the 15q14 locus was identified in both ANX and SCZ (P values are 6.59×10-11 and 2.10×10-12, respectively) and the 6p22.1 locus was identified in both MDD and SCZ (P values are 1.05×10-8 and 5.75×10-14, respectively). Sixteen pleiotropic risk loci were identified between MDD and indicators of thyroid function, of which, four loci associated with MDD (1p32.3, 6p22.1, 10q21.1, 11q13.4) were identified in both FT4 normal level and Hypothyroidism. Further, 79 pleiotropic genes were identified using Magma gene analysis (P<0.05/18776 = 2.66×10-6). Tissue-specific enrichment analysis revealed that these genes were highly enriched into six brain-related tissues. The pathway analysis mainly involved nucleosome assembly and lipoprotein particles. Finally, our two-sample MR analysis showed a significant causal effect of MDD on the increased risk of hypothyroidism, and BIP may reduce TSH normal levels.

Conclusions

Our findings not only provided evidence of a shared genetic etiology between hypothyroidism and psychiatric disorders, but also provided insights into the causal relationships and biological mechanisms that underlie their relationship. These findings contribute to a better understanding of the pleiotropy between hypothyroidism and psychiatric disorders, while having important implications for intervention and treatment goals for these disorders.

Leveraging sex-genetic interactions to understand brain disorders: recent advances and current gaps

It is established that there are sex differences in terms of prevalence, age of onset, clinical manifestations, and response to treatment for a variety of brain disorders, including neurodevelopmental, psychiatric, and neurodegenerative disorders. Cohorts of increasing sample sizes with diverse data types collected, including genetic, transcriptomic and/or phenotypic data, are providing the building blocks to permit analytical designs to test for sex-biased genetic variant-trait associations, and for sex-biased transcriptional regulation. Such molecular assessments can contribute to our understanding of the manifested phenotypic differences between the sexes for brain disorders, offering the future possibility of delivering personalized therapy for females and males. With the intention of raising the profile of this field as a research priority, this review aims to shed light on the importance of investigating sex-genetic interactions for brain disorders, focusing on two areas: (i) variant-trait associations and (ii) transcriptomics (i.e. gene expression, transcript usage and regulation). We specifically discuss recent advances in the field, current gaps and provide considerations for future studies.

Depression in Alzheimer's Disease: Epidemiology, Mechanisms, and Treatment

Depression and Alzheimer's disease (AD) are substantial public health concerns. In the past decades, a link between the 2 disease entities has received extensive acknowledgment, yet the complex nature of this relationship demands further clarification. Some evidence indicates that midlife depression may be an AD risk factor, while a chronic course of depression in late life may be a precursor to or symptom of dementia. Recently, multiple pathophysiological mechanisms have been proposed to underlie the bidirectional relationship between depression and AD, including genetic predisposition, immune dysregulation, accumulation of AD-related biomarkers (e.g., amyloid-β and tau), and alterations in brain structure. Accordingly, numerous therapeutic approaches, such as pharmacology treatments, psychotherapy, and lifestyle interventions, have been suggested as potential means of interfering with these pathways. However, the current literature on this topic remains fragmented and lacks a comprehensive review characterizing the association between depression and AD. In this review, we aim to address these gaps by providing an overview of the co-occurrence and temporal relationship between depression and AD, as well as exploring their underlying mechanisms. We also examine the current therapeutic regimens for depression and their implications for AD management and outline key challenges facing the field.

DTNPD: A comprehensive database of drugs and targets for neurological and psychiatric disorders

In response to the shortcomings in data quality and coverage for neurological and psychiatric disorders (NPDs) in existing comprehensive databases, this paper introduces the DTNPD database, specifically designed for NPDs. DTNPD contains detailed information on 30 NPDs types, 1847 drugs, 514 drug targets, 64 drug combinations, and 61 potential target combinations, forming a network with 2389 drug-target associations. The database is user-friendly, offering open access and downloadable data, which is crucial for network pharmacology studies. The key strength of DTNPD lies in its robust networks of drug and target combinations, as well as drug-target networks, facilitating research and development in the field of NPDs. The development of the DTNPD database marks a significant milestone in understanding and treating NPDs. For accessing the DTNPD database, the primary URL is http://dtnpd.cnsdrug.com, complemented by a mirror site available at http://dtnpd.lyhbio.com.

Beyond memory impairment: the complex phenotypic landscape of Alzheimer's disease

Neuropsychiatric symptoms (NPSs) in Alzheimer's disease (AD) constitute multifaceted behavioral manifestations that reflect processes of emotional regulation, thinking, and social behavior. They are as prevalent in AD as cognitive impairment and develop independently during the progression of neurodegeneration. As studying NPSs in AD is clinically challenging, most AD research to date has focused on cognitive decline. In this opinion article we summarize emerging literature on the prevalence, time course, and the underlying genetic, molecular, and pathological mechanisms related to NPSs in AD. Overall, we propose that NPSs constitute a cluster of core symptoms in AD, and understanding their neurobiology can lead to a more holistic approach to AD research, paving the way for more accurate diagnostic tests and personalized treatments embracing the goals of precision medicine.

Systems biology dissection of PTSD and MDD across brain regions, cell types, and blood

The molecular pathology of stress-related disorders remains elusive. Our brain multiregion, multiomic study of posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) included the central nucleus of the amygdala, hippocampal dentate gyrus, and medial prefrontal cortex (mPFC). Genes and exons within the mPFC carried most disease signals replicated across two independent cohorts. Pathways pointed to immune function, neuronal and synaptic regulation, and stress hormones. Multiomic factor and gene network analyses provided the underlying genomic structure. Single nucleus RNA sequencing in dorsolateral PFC revealed dysregulated (stress-related) signals in neuronal and non-neuronal cell types. Analyses of brain-blood intersections in >50,000 UK Biobank participants were conducted along with fine-mapping of the results of PTSD and MDD genome-wide association studies to distinguish risk from disease processes. Our data suggest shared and distinct molecular pathology in both disorders and propose potential therapeutic targets and biomarkers.

Plasma fatty acids and attention deficit hyperactivity disorder: a Mendelian randomization investigation

Background

Attention deficit hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder of childhood, and pathogenesis is not fully understood. Observational studies suggest an association between fatty acids abnormalities and ADHD, but there are contradictions and differences between these findings. To address this uncertainty, we employed a two-sample bidirectional Mendelian Randomization (MR) analysis to investigate the causal relationship between fatty acids and ADHD.

Methods

We conducted a two-sample Mendelian Randomization (MR) study, selecting single nucleotide polymorphisms (SNPs) highly correlated with fatty acid levels from the CHARGE Consortium as our instruments. The outcome data were sourced from the Psychiatric Genomics Consortium (PGC) dataset on ADHD, comprising 225,534 individuals, with 162,384 cases and 65,693 controls. Inverse variance weighting, MR-Egger, and weighted median methods were employed to estimate the causal relationship between fatty acids and ADHD. Cochran's Q-test was used to quantify heterogeneity of instrumental variables. Sensitivity analyses included MR-Egger intercept tests, leave-one-out analyses, and funnel plots.

Results

The MR analysis revealed no significant associations between genetically predicted levels of various saturated, monounsaturated, and polyunsaturated fatty acids (including omega-3 and omega-6) and ADHD risk in the CHARGE and PGC cohorts. Notably, an initial association with Dihomo-gamma-linolenic acid (DGLA) (OR = 1.009, p = 0.032 by IVW) did not persist after correction for multiple testing (adjusted p-value = 0.286). Sensitivity analysis supported our findings, indicating robustness. Moreover, there was a lack of evidence supporting a causal link from ADHD to fatty acids.

Conclusion

While our study on the basis of genetic data does not provide evidence to support the causal role of fatty acids in ADHD, it does not preclude their potential involvement in reducing the risk of ADHD. Further research is needed to explore this possibility.

Ketogenic Diet Intervention on Metabolic and Psychiatric Health in Bipolar and Schizophrenia: A Pilot Trial

The ketogenic diet (KD, also known as metabolic therapy) has been successful in the treatment of obesity, type 2 diabetes, and epilepsy. More recently, this treatment has shown promise in the treatment of psychiatric illness. We conducted a 4-month pilot study to investigate the effects of a KD on individuals with schizophrenia or bipolar disorder with existing metabolic abnormalities. Twenty-three participants were enrolled in a single-arm trial. Results showcased improvements in metabolic health, with no participants meeting metabolic syndrome criteria by study conclusion. Adherent individuals experienced significant reduction in weight (12 %), BMI (12 %), waist circumference (13 %), and visceral adipose tissue (36 %). Observed biomarker enhancements in this population include a 27 % decrease in HOMA-IR, and a 25 % drop in triglyceride levels. In psychiatric measurements, participants with schizophrenia showed a 32 % reduction in Brief Psychiatric Rating Scale scores. Overall Clinical Global Impression (CGI) severity improved by an average of 31 %, and the proportion of participants that started with elevated symptomatology improved at least 1-point on CGI (79 %). Psychiatric outcomes across the cohort encompassed increased life satisfaction (17 %) and enhanced sleep quality (19 %). This pilot trial underscores the potential advantages of adjunctive ketogenic dietary treatment in individuals grappling with serious mental illness.

Differentially Altered Metabolic Pathways in the Amygdala of Subjects with Schizophrenia, Bipolar Disorder and Major Depressive Disorder

Background and hypothesis

A growing number of studies implicate a key role for metabolic processes in psychiatric disorders. Recent studies suggest that ketogenic diet may be therapeutically effective for subgroups of people with schizophrenia (SCZ), bipolar disorder (BPD) and possibly major depressive disorder (MDD). Despite this promise, there is currently limited information regarding brain energy metabolism pathways across these disorders, limiting our understanding of how brain metabolic pathways are altered and who may benefit from ketogenic diets. We conducted gene expression profiling on the amygdala, a key region involved in in the regulation of mood and appetitive behaviors, to test the hypothesis that amygdala metabolic pathways are differentially altered between these disorders.

Study Design

We used a cohort of subjects diagnosed with SCZ, BPD or MDD, and non-psychiatrically ill control subjects (n=15/group), together with our bioinformatic 3-pod analysis consisting of full transcriptome pathway analysis, targeted pathway analysis, leading-edge gene analysis and iLINCS perturbagen analysis.

Study Results

We identified differential expression of metabolic pathways in each disorder. Subjects with SCZ displayed downregulation of mitochondrial respiration and nucleotide metabolism pathways. In comparison, we observed upregulation of mitochondrial respiration pathways in subjects with MDD, while subjects with BPD displayed enrichment of pathways involved in carbohydrate metabolism. Several pathways associated with brain metabolism including immune system processes and calcium ion transport were also differentially altered between diagnosis groups.

Conclusion

Our findings suggest metabolic pathways are differentially altered in the amygdala in these disorders, which may impact approaches for therapeutic strategies.

A novel multi-omics mendelian randomization method for gene set enrichment and its application to psychiatric disorders

Genome-wide association studies (GWAS) of psychiatric disorders (PD) yield numerous loci with significant signals, but often do not implicate specific genes. Because GWAS risk loci are enriched in expression/protein/methylation quantitative loci (e/p/mQTL, hereafter xQTL), transcriptome/proteome/methylome-wide association studies (T/P/MWAS, hereafter XWAS) that integrate xQTL and GWAS information, can link GWAS signals to effects on specific genes. To further increase detection power, gene signals are aggregated within relevant gene sets (GS) by performing gene set enrichment (GSE) analyses. Often GSE methods test for enrichment of "signal" genes in curated GS while overlooking their linkage disequilibrium (LD) structure, allowing for the possibility of increased false positive rates. Moreover, no GSE tool uses xQTL information to perform mendelian randomization (MR) analysis. To make causal inference on association between PD and GS, we develop a novel MR GSE (MR-GSE) procedure. First, we generate a "synthetic" GWAS for each MSigDB GS by aggregating summary statistics for x-level (mRNA, protein or DNA methylation (DNAm) levels) from the largest xQTL studies available) of genes in a GS. Second, we use synthetic GS GWAS as exposure in a generalized summary-data-based-MR analysis of complex trait outcomes. We applied MR-GSE to GWAS of nine important PD. When applied to the underpowered opioid use disorder GWAS, none of the four analyses yielded any signals, which suggests a good control of false positive rates. For other PD, MR-GSE greatly increased the detection of GO terms signals (2,594) when compared to the commonly used (non-MR) GSE method (286). Some of the findings might be easier to adapt for treatment, e.g., our analyses suggest modest positive effects for supplementation with certain vitamins and/or omega-3 for schizophrenia, bipolar and major depression disorder patients. Similar to other MR methods, when applying MR-GSE researchers should be mindful of the confounding effects of horizontal pleiotropy on statistical inference.

Unique transcriptional signatures correlate with behavioral and psychological symptom domains in Alzheimer's disease

Despite the significant burden, cost, and worse prognosis of Alzheimer's disease (AD) with behavioral and psychological symptoms of dementia (BPSD), little is known about the molecular causes of these symptoms. Using antemortem assessments of BPSD in AD, we demonstrate that individual BPSD can be grouped into 4 domain factors in our cohort: affective, apathy, agitation, and psychosis. Then, we performed a transcriptome-wide analysis for each domain utilizing bulk RNA-seq of post-mortem anterior cingulate cortex (ACC) tissues. Though all 4 domains are associated with a predominantly downregulated pattern of hundreds of differentially expressed genes (DEGs), most DEGs are unique to each domain, with only 22 DEGs being common to all BPSD domains, including TIMP1. Weighted gene co-expression network analysis (WGCNA) yielded multiple transcriptional modules that were shared between BPSD domains or unique to each domain, and NetDecoder was used to analyze context-dependent information flow through the biological network. For the agitation domain, we found that all DEGs and a highly associated transcriptional module were functionally enriched for ECM-related genes including TIMP1, TAGLN, and FLNA. Another unique transcriptional module also associated with the agitation domain was enriched with genes involved in post-synaptic signaling, including DRD1, PDE1B, CAMK4, and GABRA4. By comparing context-dependent changes in DEGs between cases and control networks, ESR1 and PARK2 were implicated as two high-impact genes associated with agitation that mediated significant information flow through the biological network. Overall, our work establishes unique targets for future study of the biological mechanisms of BPSD and resultant drug development.

A multi-ancestry genetic study of pain intensity in 598,339 veterans

Chronic pain is a common problem, with more than one-fifth of adult Americans reporting pain daily or on most days. It adversely affects the quality of life and imposes substantial personal and economic costs. Efforts to treat chronic pain using opioids had a central role in precipitating the opioid crisis. Despite an estimated heritability of 25-50%, the genetic architecture of chronic pain is not well-characterized, in part because studies have largely been limited to samples of European ancestry. To help address this knowledge gap, we conducted a cross-ancestry meta-analysis of pain intensity in 598,339 participants in the Million Veteran Program, which identified 126 independent genetic loci, 69 of which are new. Pain intensity was genetically correlated with other pain phenotypes, level of substance use and substance use disorders, other psychiatric traits, education level and cognitive traits. Integration of the genome-wide association studies findings with functional genomics data shows enrichment for putatively causal genes (n = 142) and proteins (n = 14) expressed in brain tissues, specifically in GABAergic neurons. Drug repurposing analysis identified anticonvulsants, β-blockers and calcium-channel blockers, among other drug groups, as having potential analgesic effects. Our results provide insights into key molecular contributors to the experience of pain and highlight attractive drug targets.

Distinctive whole-brain cell types predict tissue damage patterns in thirteen neurodegenerative conditions

For over a century, brain research narrative has mainly centered on neuron cells. Accordingly, most neurodegenerative studies focus on neuronal dysfunction and their selective vulnerability, while we lack comprehensive analyses of other major cell types' contribution. By unifying spatial gene expression, structural MRI, and cell deconvolution, here we describe how the human brain distribution of canonical cell types extensively predicts tissue damage in 13 neurodegenerative conditions, including early- and late-onset Alzheimer's disease, Parkinson's disease, dementia with Lewy bodies, amyotrophic lateral sclerosis, mutations in presenilin-1, and 3 clinical variants of frontotemporal lobar degeneration (behavioral variant, semantic and non-fluent primary progressive aphasia) along with associated three-repeat and four-repeat tauopathies and TDP43 proteinopathies types A and C. We reconstructed comprehensive whole-brain reference maps of cellular abundance for six major cell types and identified characteristic axes of spatial overlapping with atrophy. Our results support the strong mediating role of non-neuronal cells, primarily microglia and astrocytes, in spatial vulnerability to tissue loss in neurodegeneration, with distinct and shared across-disorder pathomechanisms. These observations provide critical insights into the multicellular pathophysiology underlying spatiotemporal advance in neurodegeneration. Notably, they also emphasize the need to exceed the current neuro-centric view of brain diseases, supporting the imperative for cell-specific therapeutic targets in neurodegeneration.

Therapeutic potential to target sialylation and SIGLECs in neurodegenerative and psychiatric diseases

Sialic acids, commonly found as the terminal carbohydrate on the glycocalyx of mammalian cells, are pivotal checkpoint inhibitors of the innate immune system, particularly within the central nervous system (CNS). Sialic acid-binding immunoglobulin-like lectins (SIGLECs) expressed on microglia are key players in maintaining microglial homeostasis by recognizing intact sialylation. The finely balanced sialic acid-SIGLEC system ensures the prevention of excessive and detrimental immune responses in the CNS. However, loss of sialylation and SIGLEC receptor dysfunctions contribute to several chronic CNS diseases. Genetic variants of SIGLEC3/CD33, SIGLEC11, and SIGLEC14 have been associated with neurodegenerative diseases such as Alzheimer's disease, while sialyltransferase ST8SIA2 and SIGLEC4/MAG have been linked to psychiatric diseases such as schizophrenia, bipolar disorders, and autism spectrum disorders. Consequently, immune-modulatory functions of polysialic acids and SIGLEC binding antibodies have been exploited experimentally in animal models of Alzheimer's disease and inflammation-induced CNS tissue damage, including retinal damage. While the potential of these therapeutic approaches is evident, only a few therapies to target either sialylation or SIGLEC receptors have been tested in patient clinical trials. Here, we provide an overview of the critical role played by the sialic acid-SIGLEC axis in shaping microglial activation and function within the context of neurodegeneration and synaptopathies and discuss the current landscape of therapies that target sialylation or SIGLECs.

Dissecting the genetic overlap between three complex phenotypes with trivariate MiXeR

Comorbidities are an increasing global health challenge. Accumulating evidence suggests overlapping genetic architectures underlying comorbid complex human traits and disorders. The bivariate causal mixture model (MiXeR) can quantify the polygenic overlap between complex phenotypes beyond global genetic correlation. Still, the pattern of genetic overlap between three distinct phenotypes, which is important to better characterize multimorbidities, has previously not been possible to quantify. Here, we present and validate the trivariate MiXeR tool, which disentangles the pattern of genetic overlap between three phenotypes using summary statistics from genome-wide association studies (GWAS). Our simulations show that the trivariate MiXeR can reliably reconstruct different patterns of genetic overlap. We further demonstrate how the tool can be used to estimate the proportions of genetic overlap between three phenotypes using real GWAS data, providing examples of complex patterns of genetic overlap between diverse human traits and diseases that could not be deduced from bivariate analyses. This contributes to a better understanding of the etiology of complex phenotypes and the nature of their relationship, which may aid in dissecting comorbidity patterns and their biological underpinnings.

Tremendous Fidelity of Vitamin D3 in Age-related Neurological Disorders

Vitamin D3 (VD) is a secosteroid hormone and shows a pleiotropic effect in brain-related disorders where it regulates redox imbalance, inflammation, apoptosis, energy production, and growth factor synthesis. Vitamin D3's active metabolic form, 1,25-dihydroxy Vitamin D3 (1,25(OH)2D3 or calcitriol), is a known regulator of several genes involved in neuroplasticity, neuroprotection, neurotropism, and neuroinflammation. Multiple studies suggest that VD deficiency can be proposed as a risk factor for the development of several age-related neurological disorders. The evidence for low serum levels of 25-hydroxy Vitamin D3 (25(OH)D3 or calcidiol), the major circulating form of VD, is associated with an increased risk of Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), dementia, and cognitive impairment. Despite decades of evidence on low VD association with neurological disorders, the precise molecular mechanism behind its beneficial effect remains controversial. Here, we will be delving into the neurobiological importance of VD and discuss its benefits in different neuropsychiatric disorders. The focus will be on AD, PD, and HD as they share some common clinical, pathological, and epidemiological features. The central focus will be on the different attributes of VD in the aspect of its anti-oxidative, anti-inflammatory, anti-apoptotic, anti-cholinesterase activity, and psychotropic effect in different neurodegenerative diseases.

Heparan sulfate modified proteins affect cellular processes central to neurodegeneration and modulate presenilin function

Mutations in presenilin-1 (PSEN1) are the most common cause of familial, early-onset Alzheimer's disease (AD), typically producing cognitive deficits in the fourth decade. A variant of APOE, APOE3 Christchurch (APOE3ch) , was found associated with protection from both cognitive decline and Tau accumulation in a 70-year-old bearing the disease-causing PSEN1-E280A mutation. The amino acid change in ApoE3ch is within the heparan sulfate (HS) binding domain of APOE, and purified APOEch showed dramatically reduced affinity for heparin, a highly sulfated form of HS. The physiological significance of ApoE3ch is supported by studies of a mouse bearing a knock-in of this human variant and its effects on microglia reactivity and Aβ-induced Tau deposition. The studies reported here examine the function of heparan sulfate-modified proteoglycans (HSPGs) in cellular and molecular pathways affecting AD-related cell pathology in human cell lines and mouse astrocytes. The mechanisms of HSPG influences on presenilin- dependent cell loss and pathology were evaluated in Drosophila using knockdown of the presenilin homolog, Psn , together with partial loss of function of sulfateless (sfl) , a homolog of NDST1 , a gene specifically affecting HS sulfation. HSPG modulation of autophagy, mitochondrial function, and lipid metabolism were shown to be conserved in cultured human cell lines, Drosophila , and mouse astrocytes. RNAi of Ndst1 reduced intracellular lipid levels in wild-type mouse astrocytes or those expressing humanized variants of APOE, APOE3 , and APOE4 . RNA-sequence analysis of human cells deficient in HS synthesis demonstrated effects on the transcriptome governing lipid metabolism, autophagy, and mitochondrial biogenesis and showed significant enrichment in AD susceptibility genes identified by GWAS. Neuron-directed knockdown of Psn in Drosophila produced cell loss in the brain and behavioral phenotypes, both suppressed by simultaneous reductions in sfl mRNA levels. Abnormalities in mitochondria, liposome morphology, and autophagosome-derived structures in animals with Psn knockdown were also rescued by simultaneous reduction of sfl. sfl knockdown reversed Psn- dependent transcript changes in genes affecting lipid transport, metabolism, and monocarboxylate carriers. These findings support the direct involvement of HSPGs in AD pathogenesis.

Network Proteomics of the Lewy Body Dementia Brain Reveals Presynaptic Signatures Distinct from Alzheimer's Disease

Lewy body dementia (LBD), a class of disorders comprising Parkinson's disease dementia (PDD) and dementia with Lewy bodies (DLB), features substantial clinical and pathological overlap with Alzheimer's disease (AD). The identification of biomarkers unique to LBD pathophysiology could meaningfully advance its diagnosis, monitoring, and treatment. Using quantitative mass spectrometry (MS), we measured over 9,000 proteins across 138 dorsolateral prefrontal cortex (DLPFC) tissues from a University of Pennsylvania autopsy collection comprising control, Parkinson's disease (PD), PDD, and DLB diagnoses. We then analyzed co-expression network protein alterations in those with LBD, validated these disease signatures in two independent LBD datasets, and compared these findings to those observed in network analyses of AD cases. The LBD network revealed numerous groups or "modules" of co-expressed proteins significantly altered in PDD and DLB, representing synaptic, metabolic, and inflammatory pathophysiology. A comparison of validated LBD signatures to those of AD identified distinct differences between the two diseases. Notably, synuclein-associated presynaptic modules were elevated in LBD but decreased in AD relative to controls. We also found that glial-associated matrisome signatures consistently elevated in AD were more variably altered in LBD, ultimately stratifying those LBD cases with low versus high burdens of concurrent beta-amyloid deposition. In conclusion, unbiased network proteomic analysis revealed diverse pathophysiological changes in the LBD frontal cortex distinct from alterations in AD. These results highlight the LBD brain network proteome as a promising source of biomarkers that could enhance clinical recognition and management.

A genome-wide investigation into the underlying genetic architecture of personality traits and overlap with psychopathology

Personality is influenced by both genetic and environmental factors and is associated with other psychiatric traits such as anxiety and depression. The "Big Five" personality traits, which include neuroticism, extraversion, agreeableness, conscientiousness, and openness, are a widely accepted and influential framework for understanding and describing human personality. Of the big five personality traits, neuroticism has most often been the focus of genetic studies and is linked to various mental illnesses including depression, anxiety, and schizophrenia. Our knowledge of the genetic architecture of the other four personality traits is more limited. Utilizing the Million Veteran Program (MVP) cohort we conducted a genome-wide association study (GWAS) in individuals of European and African ancestry. Adding other published data, we performed GWAS meta-analysis for each of the five personality traits with sample sizes ranging from 237,390 to 682,688. We identified 158, 14, 3, 2, and 7 independent genome-wide significant (GWS) loci associated with neuroticism, extraversion, agreeableness, conscientiousness, and openness, respectively. These findings represent 55 novel loci for neuroticism, as well as the first GWS loci discovered for extraversion and agreeableness. Gene-based association testing revealed 254 genes showing significant association with at least one of the five personality traits. Transcriptome-wide and proteome-wide analysis identified altered expression of genes and proteins such as CRHR1, SLC12A5, MAPT, and STX4. Pathway enrichment and drug perturbation analyses identified complex biology underlying human personality traits. We also studied the inter-relationship of personality traits with 1,437 other traits in a phenome-wide genetic correlation analysis, identifying new associations. Mendelian randomization showed positive bidirectional effects between neuroticism and depression and anxiety while a negative bidirectional effect was observed for agreeableness and these psychiatric traits. This study improves our comprehensive understanding of the genetic architecture underlying personality traits and their relationship to other complex human traits.

Determining Commonalities in the Experiences of Patients with Rare Diseases: A Qualitative Analysis of US Food and Drug Administration Patient Engagement Sessions

BACKGROUND

Rare diseases are estimated to affect more than one in ten Americans. However, most patients with a rare disease face significant emotional, physical, and social challenges. To better understand the burden of disease and unmet needs, the US Food and Drug Administration (FDA) conducts and supports multiple patient engagement platforms. We analyzed summaries from these discussions to identify commonalities among patients with disparate rare diseases, the results of which could inform priorities for cross-disease policies and medical product development.

METHODS

We conducted a qualitative analysis of patient engagement session summaries to investigate shared experiences across rare diseases. Cross-disease similarities were identified within four dimensions: product development/regulatory, clinical/physical, social/psychological, and economic/financial. Summaries from 29 rare diseases were included in our analyses.

RESULTS

Within the product development/regulatory dimension, we observed that patients and caregivers across rare diseases shared the desire for development of medical products that cured their disease or improved their overall quality of life. In the clinical/physical dimension, we found that patients had numerous common symptoms, including pain and fatigue. In the social/psychological dimension, we observed significant negative impact on mental health. Within the economic/financial dimension, patients and caregivers shared that disease burden caused significant financial hardships.

CONCLUSION

We found remarkable similarities among patients with rare diseases across all four dimensions. Our results indicate that, even among rare diseases with diverse etiologies, patients share numerous commonalties due to their diseases: a lack of effective treatment options, certain physical symptoms, mental health challenges, and financial concerns.

Genomic variation in neurons

Neurons born during the fetal period have extreme longevity and survive until the death of the individual because the human brain has highly limited tissue regeneration. The brain is comprised of an enormous variety of neurons each exhibiting different morphological and physiological characteristics and recent studies have further reported variations in their genome including chromosomal abnormalities, copy number variations, and single nucleotide mutations. During the early stages of brain development, the increasing number of neurons generated at high speeds has been proposed to lead to chromosomal instability. Additionally, mutations in the neuronal genome can occur in the mature brain. This observed genomic mosaicism in the brain can be produced by multiple endogenous and environmental factors and careful analyses of these observed variations in the neuronal genome remain central for our understanding of the genetic basis of neurological disorders.

Stress-related cellular pathophysiology as a crosstalk risk factor for neurocognitive and psychiatric disorders

In this narrative review, we examine biological processes linking psychological stress and cognition, with a focus on how psychological stress can activate multiple neurobiological mechanisms that drive cognitive decline and behavioral change. First, we describe the general neurobiology of the stress response to define neurocognitive stress reactivity. Second, we review aspects of epigenetic regulation, synaptic transmission, sex hormones, photoperiodic plasticity, and psychoneuroimmunological processes that can contribute to cognitive decline and neuropsychiatric conditions. Third, we explain mechanistic processes linking the stress response and neuropathology. Fourth, we discuss molecular nuances such as an interplay between kinases and proteins, as well as differential role of sex hormones, that can increase vulnerability to cognitive and emotional dysregulation following stress. Finally, we explicate several testable hypotheses for stress, neurocognitive, and neuropsychiatric research. Together, this work highlights how stress processes alter neurophysiology on multiple levels to increase individuals' risk for neurocognitive and psychiatric disorders, and points toward novel therapeutic targets for mitigating these effects. The resulting models can thus advance dementia and mental health research, and translational neuroscience, with an eye toward clinical application in cognitive and behavioral neurology, and psychiatry.

Familial α-synucleinopathy spectrum features in patients with psychiatric REM sleep behaviour disorder

BACKGROUND

Rapid eye movement (REM) sleep behaviour disorder (RBD) is one of the earliest and most specific prodromes of the α-synucleinopathies including Parkinson's disease (PD). It remains uncertain whether RBD occurring in the context of psychiatric disorders (psy-RBD), although very common, is merely a benign epiphenomenon of antidepressant treatment, or whether it harbours an underlying α-synucleinopathy. We hypothesised that patients with psy-RBD demonstrate a familial predisposition to an α-synucleinopathy.

METHODS

In this case-control-family study, a combination of family history and family study method was used to measure the α-synucleinopathy spectrum features, which included RBD, neurodegenerative prodromal markers and clinical diagnoses of neurodegenerative disorders. We compared the risk of α-synucleinopathy spectrum features in the first-degree relatives (FDRs) of patients with psy-RBD, psychiatric controls and healthy controls.

RESULTS

There was an increase of α-synucleinopathy spectrum features in the psy-RBD-FDRs, including possible and provisional RBD (adjusted HR (aHR)=2.02 and 6.05, respectively), definite RBD (adjusted OR=11.53) and REM-related phasic electromyographic activities, prodromal markers including depression (aHR=4.74) and probable subtle parkinsonism, risk of prodromal PD and clinical diagnosis of PD/dementia (aHR=5.50), as compared with healthy-control-FDRs. When compared with psychiatric-control-FDRs, psy-RBD-FDRs consistently presented with a higher risk for the diagnosis and electromyographic features of RBD, diagnosis of PD/dementia (aHR=3.91) and risk of prodromal PD. In contrast, psychiatric controls only presented with a familial aggregation of depression.

CONCLUSION

Patients with psy-RBD are familially predisposed to α-synucleinopathy. The occurrence of RBD with major depression may signify a subtype of major depressive disorders with underlying α-synucleinopathy neurodegeneration.

TRIAL REGISTRATION NUMBER

NCT03595475.

TSPO PET brain inflammation imaging: A transdiagnostic systematic review and meta-analysis of 156 case-control studies

INTRODUCTION

The 18-kDa translocator protein (TSPO) is increasingly recognized as a molecular target for PET imaging of inflammatory responses in various central nervous system (CNS) disorders. However, the reported sensitivity and specificity of TSPO PET to identify brain inflammatory processes appears to vary greatly across disorders, disease stages, and applied quantification methods. To advance TSPO PET as a potential biomarker to evaluate brain inflammation and anti-inflammatory therapies, a better understanding of its applicability across disorders is needed. We conducted a transdiagnostic systematic review and meta-analysis of all in vivo human TSPO PET imaging case-control studies in the CNS. Specifically, we investigated the direction, strength, and heterogeneity associated with the TSPO PET signal across disorders in pre-specified brain regions, and explored the demographic and methodological sources of heterogeneity.

METHODS

We searched for English peer-reviewed articles that reported in vivo human case-control TSPO PET differences. We extracted the demographic details, TSPO PET outcomes, and technical variables of the PET procedure. A random-effects meta-analysis was applied to estimate case-control standardized mean differences (SMD) of the TSPO PET signal in the lobar/whole-brain cortical grey matter (cGM), thalamus, and cortico-limbic circuitry between different illness categories. Heterogeneity was evaluated with the I2 statistic and explored using subgroup and meta-regression analyses for radioligand generation, PET quantification method, age, sex, and publication year. Significance was set at the False Discovery Rate (FDR)-corrected P < 0.05.

RESULTS

156 individual case-control studies were included in the systematic review, incorporating data for 2381 healthy controls and 2626 patients. 139 studies documented meta-analysable data and were grouped into 11 illness categories. Across all the illness categories, we observed a significantly higher TSPO PET signal in cases compared to controls for the cGM (n = 121 studies, SMD = 0.358, PFDR < 0.001, I2 = 68%), with a significant difference between the illness categories (P = 0.004). cGM increases were only significant for Alzheimer's disease (SMD = 0.693, PFDR < 0.001, I2 = 64%) and other neurodegenerative disorders (SMD = 0.929, PFDR < 0.001, I2 = 73%). Cortico-limbic increases (n = 97 studies, SMD = 0.541, P < 0.001, I2 = 67%) were most prominent for Alzheimer's disease, mild cognitive impairment, other neurodegenerative disorders, mood disorders and multiple sclerosis. Thalamic involvement (n = 79 studies, SMD = 0.393, P < 0.001, I2 = 71%) was observed for Alzheimer's disease, other neurodegenerative disorders, multiple sclerosis, and chronic pain and functional disorders (all PFDR < 0.05). Main outcomes for systemic immunological disorders, viral infections, substance use disorders, schizophrenia and traumatic brain injury were not significant. We identified multiple sources of between-study variance to the TSPO PET signal including a strong transdiagnostic effect of the quantification method (explaining 25% of between-study variance; VT-based SMD = 0.000 versus reference tissue-based studies SMD = 0.630; F = 20.49, df = 1;103, P < 0.001), patient age (9% of variance), and radioligand generation (5% of variance).

CONCLUSION

This study is the first overarching transdiagnostic meta-analysis of case-control TSPO PET findings in humans across several brain regions. We observed robust increases in the TSPO signal for specific types of disorders, which were widespread or focal depending on illness category. We also found a large and transdiagnostic horizontal (positive) shift of the effect estimates of reference tissue-based compared to VT-based studies. Our results can support future studies to optimize experimental design and power calculations, by taking into account the type of disorder, brain region-of-interest, radioligand, and quantification method.

The shared genetic risk architecture of neurological and psychiatric disorders: a genome-wide analysis

While neurological and psychiatric disorders have historically been considered to reflect distinct pathogenic entities, recent findings suggest shared pathobiological mechanisms. However, the extent to which these heritable disorders share genetic influences remains unclear. Here, we performed a comprehensive analysis of GWAS data, involving nearly 1 million cases across ten neurological diseases and ten psychiatric disorders, to compare their common genetic risk and biological underpinnings. Using complementary statistical tools, we demonstrate widespread genetic overlap across the disorders, even in the absence of genetic correlations. This indicates that a large set of common variants impact risk of multiple neurological and psychiatric disorders, but with divergent effect sizes. Furthermore, biological interrogation revealed a range of biological processes associated with neurological diseases, while psychiatric disorders consistently implicated neuronal biology. Altogether, the study indicates that neurological and psychiatric disorders share key etiological aspects, which has important implications for disease classification, precision medicine, and clinical practice.

Sex differences in brain protein expression and disease

Most complex human traits differ by sex, but we have limited insight into the underlying mechanisms. Here, we investigated the influence of biological sex on protein expression and its genetic regulation in 1,277 human brain proteomes. We found that 13.2% (1,354) of brain proteins had sex-differentiated abundance and 1.5% (150) of proteins had sex-biased protein quantitative trait loci (sb-pQTLs). Among genes with sex-biased expression, we found 67% concordance between sex-differentiated protein and transcript levels; however, sex effects on the genetic regulation of expression were more evident at the protein level. Considering 24 psychiatric, neurologic and brain morphologic traits, we found that an average of 25% of their putatively causal genes had sex-differentiated protein abundance and 12 putatively causal proteins had sb-pQTLs. Furthermore, integrating sex-specific pQTLs with sex-stratified genome-wide association studies of six psychiatric and neurologic conditions, we uncovered another 23 proteins contributing to these traits in one sex but not the other. Together, these findings begin to provide insights into mechanisms underlying sex differences in brain protein expression and disease.

Neuroimaging-AI Endophenotypes of Brain Diseases in the General Population: Towards a Dimensional System of Vulnerability

Disease heterogeneity poses a significant challenge for precision diagnostics in both clinical and sub-clinical stages. Recent work leveraging artificial intelligence (AI) has offered promise to dissect this heterogeneity by identifying complex intermediate phenotypes - herein called dimensional neuroimaging endophenotypes (DNEs) - which subtype various neurologic and neuropsychiatric diseases. We investigate the presence of nine such DNEs derived from independent yet harmonized studies on Alzheimer's disease (AD1-2)1, autism spectrum disorder (ASD1-3)2, late-life depression (LLD1-2)3, and schizophrenia (SCZ1-2)4, in the general population of 39,178 participants in the UK Biobank study. Phenome-wide associations revealed prominent associations between the nine DNEs and phenotypes related to the brain and other human organ systems. This phenotypic landscape aligns with the SNP-phenotype genome-wide associations, revealing 31 genomic loci associated with the nine DNEs (Bonferroni corrected P-value < 5×10-8/9). The DNEs exhibited significant genetic correlations, colocalization, and causal relationships with multiple human organ systems and chronic diseases. A causal effect (odds ratio=1.25 [1.11, 1.40], P-value=8.72×1-4) was established from AD2, characterized by focal medial temporal lobe atrophy, to AD. The nine DNEs and their polygenic risk scores significantly improved the prediction accuracy for 14 systemic disease categories and mortality. These findings underscore the potential of the nine DNEs to identify individuals at a high risk of developing the four brain diseases during preclinical stages for precision diagnostics. All results are publicly available at: http://labs.loni.usc.edu/medicine/.

Toward a new nosology of neurodegenerative diseases

New "omic" technologies are revealing shared and distinct biological pathways within and across neurodegenerative diseases (NDDs), allowing a better understanding of endophenotypes that exceeds the boundaries of the current diagnostic criteria. Moreover, a diagnostic framework is needed that can accommodate the co-pathology and the clinical overlap and heterogeneity of NDDs. Apart from dissecting the reasons for a revolution in how we conceive NDD, this article aims to prompt a change in how we diagnose and classify NDD, drafting a general scheme for a new nosology. As identifying a cause is the key to using the term "disease" properly, we propose using a tridimensional classification based on three axes: (1) etiology or pathogenic mechanism, (2) pathology markers and molecular biomarkers, (3) anatomic-clinical; and three hierarchical levels of etiology: (1) genetic/sporadic (2) cellular pathways and processes, and function of fluidic brain systems, and (3) risk factors.

Artificial Intelligence: Deciphering the Links between Psychiatric Disorders and Neurodegenerative Disease

Artificial Intelligence (AI), which is the general term used to describe technology that simulates human cognition [...].

The use of environmental scenarios to project future health effects: a scoping review

Environmental risks are a substantial factor in the current burden of disease, and their role is likely to increase in the future. Model-based scenario analysis is used extensively in environmental sciences to explore the potential effects of human activities on the environment. In this Review, we examine the literature on scenarios modelling environmental effects on health to identify the most relevant findings, common methods used, and important research gaps. Health outcomes and measures related to climate change (n=106) and air pollution (n=30) were most frequently studied. Studies examining future disease burden due to changes or policies related to dietary risks were much less common (n=10). Only a few studies assessed more than two environmental risks (n=3), even though risks can accumulate and interact with each other. Studies predominantly covered high-income countries and Asia. Sociodemographic, vulnerability, and health-system changes were rarely accounted for; thus, assessing the full effect of future environmental changes in an integrative way is not yet possible. We recommend that future models incorporate a broader set of determinants of health to more adequately capture their effect, as well as the effect of mitigation and adaptation efforts.

Integrating -omics approaches into population-based studies of endocrine disrupting chemicals: A scoping review

Health effects of endocrine disrupting chemicals (EDCs) are challenging to detect in the general population. Omics technologies become increasingly common to identify early biological changes before the apparition of clinical symptoms, to explore toxic mechanisms and to increase biological plausibility of epidemiological associations. This scoping review systematically summarises the application of omics in epidemiological studies assessing EDCs-associated biological effects to identify potential gaps and priorities for future research. Ninety-eight human studies (2004-2021) were identified through database searches (PubMed, Scopus) and citation chaining and focused on phthalates (34 studies), phenols (19) and PFASs (17), while PAHs (12) and recently-used pesticides (3) were less studied. The sample sizes ranged from 10 to 12,476 (median = 159), involving non-pregnant adults (38), pregnant women (11), children/adolescents (15) or both latter populations studied together (23). Several studies included occupational workers (10) and/or highly exposed groups (11) focusing on PAHs, PFASs and pesticides, while studies on phenols and phthalates were performed in the general population only. Analysed omics layers included metabolic profiles (30, including 14 targeted analyses), miRNA (13), gene expression (11), DNA methylation (8), microbiome (5) and proteins (3). Twenty-one studies implemented targeted multi-assays focusing on clinical routine blood lipid traits, oxidative stress or hormones. Overall, DNA methylation and gene expression associations with EDCs did not overlap across studies, while some EDC-associated metabolite groups, such as carnitines, nucleotides and amino acids in untargeted metabolomic studies, and oxidative stress markers in targeted studies, were consistent across studies. Studies had common limitations such as small sample sizes, cross-sectional designs and single sampling for exposure biomonitoring. In conclusion, there is a growing body of evidence evaluating the early biological responses to exposure to EDCs. This review points to a need for larger longitudinal studies, wider coverage of exposures and biomarkers, replication studies and standardisation of research methods and reporting.

Identifying potential risk genes and pathways for neuropsychiatric and substance use disorders using intermediate molecular mediator information

Neuropsychiatric and substance use disorders (NPSUDs) have a complex etiology that includes environmental and polygenic risk factors with significant cross-trait genetic correlations. Genome-wide association studies (GWAS) of NPSUDs yield numerous association signals. However, for most of these regions, we do not yet have a firm understanding of either the specific risk variants or the effects of these variants. Post-GWAS methods allow researchers to use GWAS summary statistics and molecular mediators (transcript, protein, and methylation abundances) infer the effect of these mediators on risk for disorders. One group of post-GWAS approaches is commonly referred to as transcriptome/proteome/methylome-wide association studies, which are abbreviated as T/P/MWAS (or collectively as XWAS). Since these approaches use biological mediators, the multiple testing burden is reduced to the number of genes (∼20,000) instead of millions of GWAS SNPs, which leads to increased signal detection. In this work, our aim is to uncover likely risk genes for NPSUDs by performing XWAS analyses in two tissues-blood and brain. First, to identify putative causal risk genes, we performed an XWAS using the Summary-data-based Mendelian randomization, which uses GWAS summary statistics, reference xQTL data, and a reference LD panel. Second, given the large comorbidities among NPSUDs and the shared cis-xQTLs between blood and the brain, we improved XWAS signal detection for underpowered analyses by performing joint concordance analyses between XWAS results i) across the two tissues and ii) across NPSUDs. All XWAS signals i) were adjusted for heterogeneity in dependent instruments (HEIDI) (non-causality) p-values and ii) used to test for pathway enrichment. The results suggest that there were widely shared gene/protein signals within the major histocompatibility complex region on chromosome 6 (BTN3A2 and C4A) and elsewhere in the genome (FURIN, NEK4, RERE, and ZDHHC5). The identification of putative molecular genes and pathways underlying risk may offer new targets for therapeutic development. Our study revealed an enrichment of XWAS signals in vitamin D and omega-3 gene sets. So, including vitamin D and omega-3 in treatment plans may have a modest but beneficial effect on patients with bipolar disorder.

Shared genetic risk loci between Alzheimer's disease and related dementias, Parkinson's disease, and amyotrophic lateral sclerosis

BACKGROUND

Genome-wide association studies (GWAS) have indicated moderate genetic overlap between Alzheimer's disease (AD) and related dementias (ADRD), Parkinson's disease (PD) and amyotrophic lateral sclerosis (ALS), neurodegenerative disorders traditionally considered etiologically distinct. However, the specific genetic variants and loci underlying this overlap remain almost entirely unknown.

METHODS

We leveraged state-of-the-art GWAS for ADRD, PD, and ALS. For each pair of disorders, we examined each of the GWAS hits for one disorder and tested whether they were also significant for the other disorder, applying Bonferroni correction for the number of variants tested. This approach rigorously controls the family-wise error rate for both disorders, analogously to genome-wide significance.

RESULTS

Eleven loci with GWAS hits for one disorder were also associated with one or both of the other disorders: one with all three disorders (the MAPT/KANSL1 locus), five with ADRD and PD (near LCORL, CLU, SETD1A/KAT8, WWOX, and GRN), three with ADRD and ALS (near GPX3, HS3ST5/HDAC2/MARCKS, and TSPOAP1), and two with PD and ALS (near GAK/TMEM175 and NEK1). Two of these loci (LCORL and NEK1) were associated with an increased risk of one disorder but decreased risk of another. Colocalization analysis supported a shared causal variant between ADRD and PD at the CLU, WWOX, and LCORL loci, between ADRD and ALS at the TSPOAP1 locus, and between PD and ALS at the NEK1 and GAK/TMEM175 loci. To address the concern that ADRD is an imperfect proxy for AD and that the ADRD and PD GWAS have overlapping participants (nearly all of which are from the UK Biobank), we confirmed that all our ADRD associations had nearly identical odds ratios in an AD GWAS that excluded the UK Biobank, and all but one remained nominally significant (p < 0.05) for AD.

CONCLUSIONS

In one of the most comprehensive investigations to date of pleiotropy between neurodegenerative disorders, we identify eleven genetic risk loci shared among ADRD, PD, and ALS. These loci support lysosomal/autophagic dysfunction (GAK/TMEM175, GRN, KANSL1), neuroinflammation/immunity (TSPOAP1), oxidative stress (GPX3, KANSL1), and the DNA damage response (NEK1) as transdiagnostic processes underlying multiple neurodegenerative disorders.

Characterization of apathy-like behaviors in the 5xFAD mouse model of Alzheimer's disease

Most patients with Alzheimer's disease (AD) develop neuropsychiatric symptoms (NPS) alongside cognitive decline, and apathy is one of the most common symptoms. Few preclinical studies have investigated the biological substrates underlying NPS in AD. In this study, we used a cross-sectional design to characterize apathy-like behaviors and assess memory in 5xFAD and wildtype control mice at 6, 12, and 16 months of age. Nest building, burrowing, and marble burying were used to test representative behaviors of apathy, and a composite score of apathy-like behavior was generated from these assays. Soluble Aβ42 and plaques were quantified in the prefrontal cortex and hippocampus of the 5xFAD mice with the highest and lowest composite scores using ELISA and histology. Results suggest that 5xFAD mice develop significant apathy-like behaviors starting at 6 months of age that worsen with aging and are positively correlated with soluble Aβ42 and plaques in the prefrontal cortex and hippocampus. Our findings highlight the utility of studying NPS in mouse models of AD to uncover important relationships with underlying neuropathology.

The relationship of history of psychiatric and substance use disorders on risk of dementia among racial and ethnic groups in the United States

Introduction

Dementia is characterized by significant declines in cognitive, physical, social, and behavioral functioning, and includes multiple subtypes that differ in etiology. There is limited evidence of the influence of psychiatric and substance use history on the risk of dementia subtypes among older underrepresented racial/ethnic minorities in the United States. Our study explored the role of psychiatric and substance use history on the risk of etiology-specific dementias: Alzheimer's disease (AD) and vascular dementia (VaD), in the context of a racially and ethnically diverse sample based on national data.

Methods

We conducted secondary data analyses based on the National Alzheimer's Coordinating Center Uniform Data Set (N = 17,592) which is comprised a large, racially, and ethnically diverse cohort of adult research participants in the network of US Alzheimer Disease Research Centers (ADRCs). From 2005 to 2019, participants were assessed for history of five psychiatric and substance use disorders (depression, traumatic brain injury, other psychiatric disorders, alcohol use, and other substance use). Cox proportional hazard models were used to examine the influence of psychiatric and substance use history on the risk of AD and VaD subtypes, and the interactions between psychiatric and substance use history and race/ethnicity with adjustment for demographic and health-related factors.

Results

In addition to other substance use, having any one type of psychiatric and substance use history increased the risk of developing AD by 22-51% and VaD by 22-53%. The risk of other psychiatric disorders on AD and VaD risk varied by race/ethnicity. For non-Hispanic White people, history of other psychiatric disorders increased AD risk by 27%, and VaD risk by 116%. For African Americans, AD risk increased by 28% and VaD risk increased by 108% when other psychiatric disorder history was present.

Conclusion

The findings indicate that having psychiatric and substance use history increases the risk of developing AD and VaD in later life. Preventing the onset and recurrence of such disorders may prevent or delay the onset of AD and VaD dementia subtypes. Prevention efforts should pay particular attention to non-Hispanic White and African American older adults who have history of other psychiatric disorders.Future research should address diagnostic shortcomings in the measurement of such disorders in ADRCs, especially with regard to diverse racial and ethnic groups.

Migratory Response of Cells in Neurogenic Niches to Neuronal Death: The Onset of Harmonic Repair?

Harmonic mechanisms orchestrate neurogenesis in the healthy brain within specific neurogenic niches, which generate neurons from neural stem cells as a homeostatic mechanism. These newly generated neurons integrate into existing neuronal circuits to participate in different brain tasks. Despite the mechanisms that protect the mammalian brain, this organ is susceptible to many different types of damage that result in the loss of neuronal tissue and therefore in alterations in the functionality of the affected regions. Nevertheless, the mammalian brain has developed mechanisms to respond to these injuries, potentiating its capacity to generate new neurons from neural stem cells and altering the homeostatic processes that occur in neurogenic niches. These alterations may lead to the generation of new neurons within the damaged brain regions. Notwithstanding, the activation of these repair mechanisms, regeneration of neuronal tissue within brain injuries does not naturally occur. In this review, we discuss how the different neurogenic niches respond to different types of brain injuries, focusing on the capacity of the progenitors generated in these niches to migrate to the injured regions and activate repair mechanisms. We conclude that the search for pharmacological drugs that stimulate the migration of newly generated neurons to brain injuries may result in the development of therapies to repair the damaged brain tissue.

A single-nucleus transcriptome-wide association study implicates novel genes in depression pathogenesis

Background

Depression is a common psychiatric illness and global public health problem. However, our limited understanding of the biological basis of depression has hindered the development of novel treatments and interventions.

Methods

To identify new candidate genes for therapeutic development, we examined single-nucleus RNA sequencing (snucRNAseq) data from the dorsolateral prefrontal cortex (N=424) in relation to ante-mortem depressive symptoms. To complement these direct analyses, we also used genome-wide association study (GWAS) results for depression (N=500,199) along with genetic tools for inferring the expression of 22,159 genes in 7 cell types and 55 cell subtypes to perform transcriptome-wide association studies (TWAS) of depression followed by Mendelian randomization (MR).

Results

Our single-nucleus TWAS analysis identified 71 causal genes in depression that have a role in specific neocortical cell subtypes; 59 of 71 genes were novel compared to previous studies. Depression TWAS genes showed a cell type specific pattern, with the greatest enrichment being in both excitatory and inhibitory neurons as well as astrocytes. Gene expression in different neuron subtypes have different directions of effect on depression risk. Compared to lower genetically correlated traits (e.g. body mass index) with depression, higher correlated traits (e.g., neuroticism) have more common TWAS genes with depression. In parallel, we performed differential gene expression analysis in relation to depression in 55 cortical cell subtypes, and we found that genes such as ANKRD36, MADD, TAOK3, SCAI and CHUK are associated with depression in specific cell subtypes.

Conclusions

These two sets of analyses illustrate the utility of large snucRNAseq data to uncover both genes whose expression is altered in specific cell subtypes in the context of depression and to enhance the interpretation of well-powered GWAS so that we can prioritize specific susceptibility genes for further analysis and therapeutic development.

Antidepressant and Neuroprotective Effects of 3-Hydroxy Paroxetine, an Analog of Paroxetine in Rats

BACKGROUND

Paroxetine (PX) is a widely used antidepressant with side effects such as weakness, dizziness, and trouble sleeping. In search of novel compounds with better efficacy and fewer side effects, we synthesized 3HPX, a hydroxylated analog of PX, and compared the 2 in silico for their pharmacokinetic and binding properties and in vivo for their antidepressant and potential neuroprotective effects.

METHODS

In silico studies compared pharmacological properties as well as interactions of PX and 3HPX with the serotonin transporter. In vivo studies utilized an animal model of comorbid depression-Parkinson disease. Adult male Wistar rats were injected (sterotaxically) with lipopolysaccharide in the striatum (unilaterally), followed by 14 days of once-daily injections (i.p.) of 10 mg/kg PX or 3HPX. Animals were tested for motor asymmetry and locomotor activity as well as indices of anhedonia and helplessness using sucrose preference and forced swim tests, respectively. Brains of these animals were collected after the last test, and tyrosine hydroxylase-positive neurons in substantia nigra pars compacta and Iba-1-positive stained microglia in ipsilateral striatum were measured.

RESULTS

In silico findings indicated that 3HPX could bind stronger to serotonin transporter and also have a better clearance and hence less toxicity compared with PX. In vivo results revealed a more effective reversal of immobility in the swim test, substantial increase in tyrosine hydroxylase-positive cells in the substantia nigra pars compacta, and more ramified Iba-1+ cells by 3HPX compared with PX.

CONCLUSION

The findings suggest superior effectiveness of 3HPX as an antidepressant and neuroprotectant compared with PX and hence potential utility in Parkinson disease depression co-morbidity.

The genetic architecture of pain intensity in a sample of 598,339 U.S. veterans

Chronic pain is a common problem, with more than one-fifth of adult Americans reporting pain daily or on most days. It adversely affects quality of life and imposes substantial personal and economic costs. Efforts to treat chronic pain using opioids played a central role in precipitating the opioid crisis. Despite an estimated heritability of 25-50%, the genetic architecture of chronic pain is not well characterized, in part because studies have largely been limited to samples of European ancestry. To help address this knowledge gap, we conducted a cross-ancestry meta-analysis of pain intensity in 598,339 participants in the Million Veteran Program, which identified 125 independent genetic loci, 82 of which are novel. Pain intensity was genetically correlated with other pain phenotypes, level of substance use and substance use disorders, other psychiatric traits, education level, and cognitive traits. Integration of the GWAS findings with functional genomics data shows enrichment for putatively causal genes (n = 142) and proteins (n = 14) expressed in brain tissues, specifically in GABAergic neurons. Drug repurposing analysis identified anticonvulsants, beta-blockers, and calcium-channel blockers, among other drug groups, as having potential analgesic effects. Our results provide insights into key molecular contributors to the experience of pain and highlight attractive drug targets.

Neurodegeneration, Mitochondria, and Antibiotics

Neurodegenerative diseases are characterized by the progressive loss of neurons, synapses, dendrites, and myelin in the central and/or peripheral nervous system. Actual therapeutic options for patients are scarce and merely palliative. Although they affect millions of patients worldwide, the molecular mechanisms underlying these conditions remain unclear. Mitochondrial dysfunction is generally found in neurodegenerative diseases and is believed to be involved in the pathomechanisms of these disorders. Therefore, therapies aiming to improve mitochondrial function are promising approaches for neurodegeneration. Although mitochondrial-targeted treatments are limited, new research findings have unraveled the therapeutic potential of several groups of antibiotics. These drugs possess pleiotropic effects beyond their anti-microbial activity, such as anti-inflammatory or mitochondrial enhancer function. In this review, we will discuss the controversial use of antibiotics as potential therapies in neurodegenerative diseases.

Modern Methods of Diagnostics and Treatment of Neurodegenerative Diseases and Depression

This paper discusses the promising areas of research into machine learning applications for the prevention and correction of neurodegenerative and depressive disorders. These two groups of disorders are among the leading causes of decline in the quality of life in the world when estimated using disability-adjusted years. Despite decades of research, the development of new approaches for the assessment (especially pre-clinical) and correction of neurodegenerative diseases and depressive disorders remains among the priority areas of research in neurophysiology, psychology, genetics, and interdisciplinary medicine. Contemporary machine learning technologies and medical data infrastructure create new research opportunities. However, reaching a consensus on the application of new machine learning methods and their integration with the existing standards of care and assessment is still a challenge to overcome before the innovations could be widely introduced to clinics. The research on the development of clinical predictions and classification algorithms contributes towards creating a unified approach to the use of growing clinical data. This unified approach should integrate the requirements of medical professionals, researchers, and governmental regulators. In the current paper, the current state of research into neurodegenerative and depressive disorders is presented.

Unique Transcriptional Signatures Correlate with Behavioral and Psychological Symptom Domains in Alzheimer's Disease

Despite the significant burden, cost, and worse prognosis of Alzheimer's disease (AD) with behavioral and psychological symptoms of dementia (BPSD), little is known about the molecular causes of these symptoms. Using antemortem assessments of BPSD in AD, we demonstrate that individual BPSD can be grouped into 4 domain factors in our sample: affective, apathy, agitation, and psychosis. Then, we performed a transcriptome-wide analysis for each domain utilizing bulk RNA-seq of post-mortem anterior cingulate cortex (ACC) tissue. Though all 4 domains are associated with a predominantly downregulated pattern of hundreds of differentially expressed genes (DEGs), most DEGs are unique to each domain, with only 22 DEGs being common to all BPSD domains, including TIMP1. Weighted gene co-expression network analysis (WGCNA) yielded multiple transcriptional modules that were shared between BPSD domains or unique to each domain, and NetDecoder was used to analyze context-dependent information flow through the biological network. For the agitation domain, we found that all DEGs and a highly correlated transcriptional module were functionally enriched for ECM-related genes including TIMP1, TAGLN, and FLNA. Another unique transcriptional module also associated with the agitation domain was enriched with genes involved in post-synaptic signaling, including DRD1, PDE1B, CAMK4, and GABRA4. By comparing context-dependent changes in DEGs between cases and control networks, ESR1 and PARK2 were implicated as two high impact genes associated with agitation that mediated significant information flow through the biological network. Overall, our work establishes unique targets for future study of the biological mechanisms of BPSD and resultant drug development.

Machine learning for predicting neurodegenerative diseases in the general older population: a cohort study

BACKGROUND

In the older general population, neurodegenerative diseases (NDs) are associated with increased disability, decreased physical and cognitive function. Detecting risk factors can help implement prevention measures. Using deep neural networks (DNNs), a machine-learning algorithm could be an alternative to Cox regression in tabular datasets with many predictive features. We aimed to compare the performance of different types of DNNs with regularized Cox proportional hazards models to predict NDs in the older general population.

METHODS

We performed a longitudinal analysis with participants of the English Longitudinal Study of Ageing. We included men and women with no NDs at baseline, aged 60 years and older, assessed every 2 years from 2004 to 2005 (wave2) to 2016-2017 (wave 8). The features were a set of 91 epidemiological and clinical baseline variables. The outcome was new events of Parkinson's, Alzheimer or dementia. After applying multiple imputations, we trained three DNN algorithms: Feedforward, TabTransformer, and Dense Convolutional (Densenet). In addition, we trained two algorithms based on Cox models: Elastic Net regularization (CoxEn) and selected features (CoxSf).

RESULTS

5433 participants were included in wave 2. During follow-up, 12.7% participants developed NDs. Although the five models predicted NDs events, the discriminative ability was superior using TabTransformer (Uno's C-statistic (coefficient (95% confidence intervals)) 0.757 (0.702, 0.805). TabTransformer showed superior time-dependent balanced accuracy (0.834 (0.779, 0.889)) and specificity (0.855 (0.0.773, 0.909)) than the other models. With the CoxSf (hazard ratio (95% confidence intervals)), age (10.0 (6.9, 14.7)), poor hearing (1.3 (1.1, 1.5)) and weight loss 1.3 (1.1, 1.6)) were associated with a higher DNN risk. In contrast, executive function (0.3 (0.2, 0.6)), memory (0, 0, 0.1)), increased gait speed (0.2, (0.1, 0.4)), vigorous physical activity (0.7, 0.6, 0.9)) and higher BMI (0.4 (0.2, 0.8)) were associated with a lower DNN risk.

CONCLUSION

TabTransformer is promising for prediction of NDs with heterogeneous tabular datasets with numerous features. Moreover, it can handle censored data. However, Cox models perform well and are easier to interpret than DNNs. Therefore, they are still a good choice for NDs.

Integrative Post-Genome-Wide Association Study Analyses Relevant to Psychiatric Disorders: Imputing Transcriptome and Proteome Signals

Background

The genome-wide association study (GWAS) is a common tool to identify genetic variants associated with complex traits, including psychiatric disorders (PDs). However, post-GWAS analyses are needed to extend the statistical inference to biologically relevant entities, e.g., genes, proteins, and pathways. To achieve this goal, researchers developed methods that incorporate biologically relevant intermediate molecular phenotypes, such as gene expression and protein abundance, which are posited to mediate the variant-trait association. Transcriptome-wide association study (TWAS) and proteome-wide association study (PWAS) are commonly used methods to test the association between these molecular mediators and the trait.

Summary

In this review, we discuss the most recent developments in TWAS and PWAS. These methods integrate existing "omic" information with the GWAS summary statistics for trait(s) of interest. Specifically, they impute transcript/protein data and test the association between imputed gene expression/protein level with phenotype of interest by using (i) GWAS summary statistics and (ii) reference transcriptomic/proteomic/genomic datasets. TWAS and PWAS are suitable as analysis tools for (i) primary association scan and (ii) fine-mapping to identify potentially causal genes for PDs.

Key Messages

As post-GWAS analyses, TWAS and PWAS have the potential to highlight causal genes for PDs. These prioritized genes could indicate targets for the development of novel drug therapies. For researchers attempting such analyses, we recommend Mendelian randomization tools that use GWAS statistics for both trait and reference datasets, e.g., summary Mendelian randomization (SMR). We base our recommendation on (i) being able to use the same tool for both TWAS and PWAS, (ii) not requiring the pre-computed weights (and thus easier to update for larger reference datasets), and (iii) most larger transcriptome reference datasets are publicly available and easy to transform into a compatible format for SMR analysis.

Spatiotemporal Characteristics of Regional Brain Perfusion Associated with Neuropsychiatric Symptoms in Patients with Alzheimer's Disease

BACKGROUND

Current technology for exploring neuroimaging markers and neural circuits of neuropsychiatric symptoms (NPS) in patients with Alzheimer's disease (AD) is expensive and usually invasive, limiting its use in clinical practice.

OBJECTIVE

To investigate the cerebral morphology and perfusion characteristics of NPS and identify the spatiotemporal perfusion circuits of NPS sub-symptoms.

METHODS

This nested case-control study included 102 AD patients with NPS and 51 age- and sex-matched AD patients without NPS. Gray matter volume, cerebral blood flow (CBF), and arterial transit time (ATT) were measured and generated using time-encoded 7-delay pseudo-continuous arterial spin labeling (pCASL). Multiple conditional logistic regression analysis was used to identify neuroimaging markers of NPS. The associations between the CBF or ATT of affected brain areas and NPS sub-symptoms were evaluated after adjusting for confounding factors. The neural circuits of sub-symptoms were identified based on spatiotemporal perfusion sequencing.

RESULTS

Lower Mini-Mental State Examination scores (p < 0.001), higher Caregiver Burden Inventory scores (p < 0.001), and higher CBF (p = 0.001) and ATT values (p < 0.003) of the right anteroventral thalamic nucleus (ATN) were risk factors for NPS in patients with AD. Six spatiotemporal perfusion circuits were found from 12 sub-symptoms, including the anterior cingulate gyri-temporal pole/subcortical thalamus-cerebellum circuit, insula-limbic-cortex circuit, subcortical thalamus-temporal pole-cortex circuit, subcortical thalamus-cerebellum circuit, frontal cortex-cerebellum-occipital cortex circuit, and subcortical thalamus-hippocampus-dorsal raphe nucleus circuit.

CONCLUSIONS

Prolonged ATT and increased CBF of the right ATN may be neuroimaging markers for detecting NPS in patients with AD. Time-encoded pCASL could be a reliable technique to explore the neural perfusional circuits of NPS.

Modeling of Neurodegenerative Diseases: 'Step by Step' and 'Network' Organization of the Complexes of Model Systems

Neurodegenerative diseases have acquired the status of one of the leading causes of death in developed countries, which requires creating new model systems capable of accurately reproducing the mechanisms underlying these pathologies. Here we analyzed modern model systems and their contribution to the solution of unexplored manifestations of neuropathological processes. Each model has unique properties that make it the optimal tool for modeling certain aspects of neurodegenerative disorders. We concluded that to optimize research, it is necessary to combine models into complexes that include organisms and artificial systems of different organizational levels. Such complexes can be organized in two ways. The first method can be described as "step by step", where each model for studying a certain characteristic is a separate step that allows using the information obtained in the modeling process for the gradual study of increasingly complex processes in subsequent models. The second way is a 'network' approach. Studies are carried out with several types of models simultaneously, and experiments with each specific type are adjusted in conformity with the data obtained from other models. In our opinion, the 'network' approach to combining individual model systems seems more promising for fundamental biology as well as diagnostics and therapy.