Comprehensive gene- and pathway-based analysis of depressive symptoms in older adults

Two polygenic mouse models of major depressive disorders identify TMEM161B as a potential biomarker of disease in humans

Treatments are only partially effective in major depressive disorders (MDD) but no biomarker exists to predict symptom improvement in patients. Animal models are essential tools in the development of antidepressant medications, but while recent genetic studies have demonstrated the polygenic contribution to MDD, current models are limited to either mimic the effect of a single gene or environmental factor. We developed in the past a model of depressive-like behaviors in mice (H/Rouen), using selective breeding based on behavioral reaction after an acute mild stress in the tail suspension test. Here, we propose a new mouse model of depression (H-TST) generated from a more complex genetic background and based on the same selection process. We first demonstrated that H/Rouen and H-TST mice had similar phenotypes and were more sensitive to glutamate-related antidepressant medications than selective serotonin reuptake inhibitors. We then conducted an exome sequencing on the two mouse models and showed that they had damaging variants in 174 identical genes, which have also been associated with MDD in humans. Among these genes, we showed a higher expression level of Tmem161b in brain and blood of our two mouse models. Changes in TMEM161B expression level was also observed in blood of MDD patients when compared with controls, and after 8-week treatment with duloxetine, mainly in good responders to treatment. Altogether, our results introduce H/Rouen and H-TST as the two first polygenic animal models of MDD and demonstrate their ability to identify biomarkers of the disease and to develop rapid and effective antidepressant medications.

Association between genetic variants of GRM7 (rs1396409 and rs9883258) and treatment outcomes in Schizophrenic Egyptian patients

BACKGROUND AND AIM

This study evaluated the association between rs1396409 and rs9883258 and the risk of schizophrenia (SCZ) and treatment outcomes in Egyptian patients.

METHODS

This study included 88 patients with SCZ and 88 healthy controls. Lipid profile was assayed. Genotyping of rs1396409 and rs9883258 polymorphisms was analyzed using real-time PCR.

RESULTS

The rs1396409 AG genotype frequency was significantly associated with SCZ risk (p = 0.002). Also, significant increased risk of SCZ was observed under allelic (p = 0.001), dominant (p = 0.001) and overdominant (p = 0.001) genetic model of rs1396409. However, rs9883258 AA genotype revealed nonsignificant association with SCZ. Cases with the rs1396409AG genotype exhibited hypertriglyceridemia (p < 0.001) and hypercholesterolemia (p = 0.001). In total, 72.3% and 74.5% of the cases presented with rs1396409 AG have negative symptoms (p = 0.022) and exhibited poor drug response (p = 0.023), respectively; all cases with rs1396409 GG genotype attempted suicide (p = 0.002) and are drug-free (p = 0.003). SCZ patients with negative symptoms had hypercholesterolemia (p = 0.008) mainly low-density lipoproteins (LDLc) (p = 0.016), and those with cognitive symptoms presented with low level of high-density lipoprotein (HDLc) (p = 0.023). Moreover, the multivariate regression analysis revealed that both rs1396409 G allele and HDLc were predictors of SCZ (p = 0.003 and 0.001, resp.).

CONCLUSION

The current study concluded that metabotropic glutamate receptor 7 (GRM7) rs1396409 AG could be a potential biomarker for SCZ diagnosis. It also revealed an independent association between the GRM7 rs1396409 G allele, HDLc and SCZ development.

LRFN5 and OLFM4 as novel potential biomarkers for major depressive disorder: a pilot study

Evidences have shown that both LRFN5 and OLFM4 can regulate neural development and synaptic function. Recent genome-wide association studies on major depressive disorder (MDD) have implicated LRFN5 and OLFM4, but their expressions and roles in MDD are still completely unclear. Here, we examined serum concentrations of LRFN5 and OLFM4 in 99 drug-naive MDD patients, 90 drug-treatment MDD patients, and 81 healthy controls (HCs) using ELISA methods. The results showed that both LRFN5 and OLFM4 levels were considerably higher in MDD patients compared to HCs, and were significantly lower in drug-treatment MDD patients than in drug-naive MDD patients. However, there were no significant differences between MDD patients who received a single antidepressant and a combination of antidepressants. Pearson correlation analysis showed that they were associated with the clinical data, including Hamilton Depression Scale score, age, duration of illness, fasting blood glucose, serum lipids, and hepatic, renal, or thyroid function. Moreover, these two molecules both yielded fairly excellent diagnostic performance in diagnosing MDD. In addition, a combination of LRFN5 and OLFM4 demonstrated a better diagnostic effectiveness, with an area under curve of 0.974 in the training set and 0.975 in the testing set. Taken together, our data suggest that LRFN5 and OLFM4 may be implicated in the pathophysiology of MDD and the combination of LRFN5 and OLFM4 may offer a diagnostic biomarker panel for MDD.

Correlation between variants of the CREB1 and GRM7 genes and risk of depression

The pathogenesis of depression involves cAMP-response element binding protein1 (CREB1) and metabotropic glutamate receptor 7 (GRM7), and their genetic polymorphisms may affect susceptibility to depression. The purpose of this study was to investigate whether the CREB1 polymorphisms rs2253206 and rs10932201 and the GRM7 polymorphism rs162209 are associated with the risk of depression. Using polymerase chain reaction-restriction fragment length polymorphism and DNA sequencing, we analyzed the rs2253206, rs10932201, and rs162209 frequencies in 479 patients with depression and 329 normal controls. The results showed that the rs2253206 and rs10932201 polymorphisms were significantly associated with an increased risk of depression. However, no association was found between rs162209 and depression risk. When the data were stratified for several disease-related variables, none of the three polymorphisms were found to be correlated to onset, disease severity, family history, or suicidal tendency. Thus, the present findings indicate that the CREB1 polymorphisms rs2253206 and rs10932201 may be related to the occurrence of depression.

Neuropsychiatric Symptoms of Alzheimer's Disease: An Anatomic-Genetic Framework for Treatment Development

BACKGROUND

Despite the burden on patients and caregivers, there are no approved therapies for the neuropsychiatric symptoms of Alzheimer's disease (NPS-AD). This is likely due to an incomplete understanding of the underlying mechanisms.

OBJECTIVE

To review the neurobiological mechanisms of NPS-AD, including depression, psychosis, and agitation.

METHODS

Understanding that genetic encoding gives rise to the function of neural circuits specific to behavior, we review the genetics and neuroimaging literature to better understand the biological underpinnings of depression, psychosis, and agitation.

RESULTS

We found that mechanisms involving monoaminergic biosynthesis and function are likely key elements of NPS-AD and while current treatment approaches are in line with this, the lack of effectiveness may be due to contributions from additional mechanisms including neurodegenerative, vascular, inflammatory, and immunologic pathways.

CONCLUSION

Within an anatomic-genetic framework, development of novel effective biological targets may engage targets within these pathways but will require a better understanding of the heterogeneity in NPS-AD.

Therapeutic Targets and Mechanism of Xingpi Jieyu Decoction in Depression: A Network Pharmacology Study

Background

Depression is a common mental disease that lacks effective therapeutic drugs with good curative effects and few adverse reactions. Traditional Chinese medicine (TCM) has the advantages of multiple components, multiple channels, and fewer adverse reactions in the treatment of depression. Although Xingpi Jieyu Decoction (XPJYD) demonstrates a good therapeutic effect on depression, the pharmacological mechanism underlying its antidepressant effect is still unclear.

Methods

We used a network pharmacology strategy, including the construction and analysis of a complex drug-disease network, to explore the complex mechanism of XPJYD treatment of depression. In addition, molecular docking technology was used to preliminarily study the binding ability of the potential active components and core therapeutic targets of XPJYD.

Results

The network pharmacology results showed 42 targets of XPJYD that are involved in depression. PPI network analysis demonstrated that the top 10 core targets were AKT1, VEGFA, MAPK8, FOS, ESR1, NR3C1, IL6, HIF1A, NOS3, and AR. The molecular docking results showed that the binding energies of beta sitosterol with AR, FOS, AKT1, VEGFA, NR3C1, and NOS3 were less than −7.0 kcal·mol⁻¹, indicating a good docking effect. The GO enrichment analysis results showed that the XPJYD antidepression mechanism mainly involves the following biological processes such as apoptotic signaling pathway, cellular response to lipid, inflammatory response, and others. The KEGG analysis results indicated that XPJYD may regulate 13 pathways such as PI3K-Akt signaling pathway and estrogen signaling pathway in the treatment of depression.

Conclusions

This study reflects the characteristics of the mechanism of action by which XPJYD treats depression, which includes multiple components, multiple targets, and multiple pathways, and provides a biological basis for further verification and a novel perspective for drug discovery in depression.

Bi-ancestral depression GWAS in the Million Veteran Program and meta-analysis in >1.2 million individuals highlight new therapeutic directions

Major depressive disorder is the most common neuropsychiatric disorder, affecting 11% of veterans. Here we report results of a large meta-analysis of depression using data from the Million Veteran Program, 23andMe, UK Biobank and FinnGen, including individuals of European ancestry (n = 1,154,267; 340,591 cases) and African ancestry (n = 59,600; 25,843 cases). Transcriptome-wide association study analyses revealed significant associations with expression of NEGR1 in the hypothalamus and DRD2 in the nucleus accumbens, among others. We fine-mapped 178 genomic risk loci, and we identified likely pathogenicity in these variants and overlapping gene expression for 17 genes from our transcriptome-wide association study, including TRAF3. Finally, we were able to show substantial replications of our findings in a large independent cohort (n = 1,342,778) provided by 23andMe. This study sheds light on the genetic architecture of depression and provides new insight into the interrelatedness of complex psychiatric traits.

In Silico Identification of miRNA-lncRNA Interactions in Male Reproductive Disorder Associated with COVID-19 Infection

Coronavirus disease 2019 (COVID-19), a global pandemic, is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Angiotensin-converting enzyme 2 (ACE2) is the receptor for SARS-CoV-2 and transmembrane serine protease 2 (TMPRSS2) facilitates ACE2-mediated virus entry. Moreover, the expression of ACE2 in the testes of infertile men is higher than normal, which indicates that infertile men may be susceptible to be infected and SARS-CoV-2 may cause reproductive disorder through the pathway induced by ACE2 and TMPRSS2. Little is known about the pathway regulation of ACE2 and TMPRSS2 expression in male reproductive disorder. Since the regulation of gene expression is mediated by microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) at the post-transcriptional level, the aim of this study was to analyze the dysregulated miRNA–lncRNA interactions of ACE2 and TMPRSS2 in male reproductive disorder. Using bioinformatics analysis, we speculate that the predicted miRNAs including miR-125a-5p, miR-125b-5p, miR-574-5p, and miR-936 as regulators of ACE2 and miR-204-5p as a modulator of TMPRSS2 are associated with male infertility. The lncRNAs with a tissue-specific expression for testis including GRM7-AS3, ARHGAP26-AS1, BSN-AS1, KRBOX1-AS1, CACNA1C-IT3, AC012361.1, FGF14-IT1, AC012494.1, and GS1-24F4.2 were predicted. The identified miRNAs and lncRNAs are proposed as potential biomarkers to study the possible association between COVID-19 and male infertility. This study encourages further studies of miRNA–lncRNA interactions to explain the molecular mechanisms of male infertility in COVID-19 patients.

Dissecting diagnostic heterogeneity in depression by integrating neuroimaging and genetics

Depression is a heterogeneous and etiologically complex psychiatric syndrome, not a unitary disease entity, encompassing a broad spectrum of psychopathology arising from distinct pathophysiological mechanisms. Motivated by a need to advance our understanding of these mechanisms and develop new treatment strategies, there is a renewed interest in investigating the neurobiological basis of heterogeneity in depression and rethinking our approach to diagnosis for research purposes. Large-scale genome-wide association studies have now identified multiple genetic risk variants implicating excitatory neurotransmission and synapse function and underscoring a highly polygenic inheritance pattern that may be another important contributor to heterogeneity in depression. Here, we review various sources of phenotypic heterogeneity and approaches to defining and studying depression subtypes, including symptom-based subtypes and biology-based approaches to decomposing the depression syndrome. We review "dimensional," "categorical," and "hybrid" approaches to parsing phenotypic heterogeneity in depression and defining subtypes using functional neuroimaging. Next, we review recent progress in neuroimaging genetics (correlating neuroimaging patterns of brain function with genetic data) and its potential utility for generating testable hypotheses concerning molecular and circuit-level mechanisms. We discuss how genetic variants and transcriptomic profiles may confer risk for depression by modulating brain structure and function. We conclude by highlighting several promising areas for future research into the neurobiological underpinnings of heterogeneity, including efforts to understand sexually dimorphic mechanisms, the longitudinal dynamics of depressive episodes, and strategies for developing personalized treatments and facilitating clinical decision-making.

Precision medicine for mood disorders: objective assessment, risk prediction, pharmacogenomics, and repurposed drugs

Mood disorders (depression, bipolar disorders) are prevalent and disabling. They are also highly co-morbid with other psychiatric disorders. Currently there are no objective measures, such as blood tests, used in clinical practice, and available treatments do not work in everybody. The development of blood tests, as well as matching of patients with existing and new treatments, in a precise, personalized and preventive fashion, would make a significant difference at an individual and societal level. Early pilot studies by us to discover blood biomarkers for mood state were promising [1], and validated by others [2]. Recent work by us has identified blood gene expression biomarkers that track suicidality, a tragic behavioral outcome of mood disorders, using powerful longitudinal within-subject designs, validated them in suicide completers, and tested them in independent cohorts for ability to assess state (suicidal ideation), and ability to predict trait (future hospitalizations for suicidality) [3-6]. These studies showed good reproducibility with subsequent independent genetic studies [7]. More recently, we have conducted such studies also for pain [8], for stress disorders [9], and for memory/Alzheimer's Disease [10]. We endeavored to use a similar comprehensive approach to identify more definitive biomarkers for mood disorders, that are transdiagnostic, by studying mood in psychiatric disorders patients. First, we used a longitudinal within-subject design and whole-genome gene expression approach to discover biomarkers which track mood state in subjects who had diametric changes in mood state from low to high, from visit to visit, as measured by a simple visual analog scale that we had previously developed (SMS-7). Second, we prioritized these biomarkers using a convergent functional genomics (CFG) approach encompassing in a comprehensive fashion prior published evidence in the field. Third, we validated the biomarkers in an independent cohort of subjects with clinically severe depression (as measured by Hamilton Depression Scale, (HAMD)) and with clinically severe mania (as measured by the Young Mania Rating Scale (YMRS)). Adding the scores from the first three steps into an overall convergent functional evidence (CFE) score, we ended up with 26 top candidate blood gene expression biomarkers that had a CFE score as good as or better than SLC6A4, an empirical finding which we used as a de facto positive control and cutoff. Notably, there was among them an enrichment in genes involved in circadian mechanisms. We further analyzed the biological pathways and networks for the top candidate biomarkers, showing that circadian, neurotrophic, and cell differentiation functions are involved, along with serotonergic and glutamatergic signaling, supporting a view of mood as reflecting energy, activity and growth. Fourth, we tested in independent cohorts of psychiatric patients the ability of each of these 26 top candidate biomarkers to assess state (mood (SMS-7), depression (HAMD), mania (YMRS)), and to predict clinical course (future hospitalizations for depression, future hospitalizations for mania). We conducted our analyses across all patients, as well as personalized by gender and diagnosis, showing increased accuracy with the personalized approach, particularly in women. Again, using SLC6A4 as the cutoff, twelve top biomarkers had the strongest overall evidence for tracking and predicting depression after all four steps: NRG1, DOCK10, GLS, PRPS1, TMEM161B, GLO1, FANCF, HNRNPDL, CD47, OLFM1, SMAD7, and SLC6A4. Of them, six had the strongest overall evidence for tracking and predicting both depression and mania, hence bipolar mood disorders. There were also two biomarkers (RLP3 and SLC6A4) with the strongest overall evidence for mania. These panels of biomarkers have practical implications for distinguishing between depression and bipolar disorder. Next, we evaluated the evidence for our top biomarkers being targets of existing psychiatric drugs, which permits matching patients to medications in a targeted fashion, and the measuring of response to treatment. We also used the biomarker signatures to bioinformatically identify new/repurposed candidate drugs. Top drugs of interest as potential new antidepressants were pindolol, ciprofibrate, pioglitazone and adiphenine, as well as the natural compounds asiaticoside and chlorogenic acid. The last 3 had also been identified by our previous suicidality studies. Finally, we provide an example of how a report to doctors would look for a patient with depression, based on the panel of top biomarkers (12 for depression and bipolar, one for mania), with an objective depression score, risk for future depression, and risk for bipolar switching, as well as personalized lists of targeted prioritized existing psychiatric medications and new potential medications. Overall, our studies provide objective assessments, targeted therapeutics, and monitoring of response to treatment, that enable precision medicine for mood disorders.

Blood biomarkers for memory: toward early detection of risk for Alzheimer disease, pharmacogenomics, and repurposed drugs

Short-term memory dysfunction is a key early feature of Alzheimer's disease (AD). Psychiatric patients may be at higher risk for memory dysfunction and subsequent AD due to the negative effects of stress and depression on the brain. We carried out longitudinal within-subject studies in male and female psychiatric patients to discover blood gene expression biomarkers that track short term memory as measured by the retention measure in the Hopkins Verbal Learning Test. These biomarkers were subsequently prioritized with a convergent functional genomics approach using previous evidence in the field implicating them in AD. The top candidate biomarkers were then tested in an independent cohort for ability to predict state short-term memory, and trait future positive neuropsychological testing for cognitive impairment. The best overall evidence was for a series of new, as well as some previously known genes, which are now newly shown to have functional evidence in humans as blood biomarkers: RAB7A, NPC2, TGFB1, GAP43, ARSB, PER1, GUSB, and MAPT. Additional top blood biomarkers include GSK3B, PTGS2, APOE, BACE1, PSEN1, and TREM2, well known genes implicated in AD by previous brain and genetic studies, in humans and animal models, which serve as reassuring de facto positive controls for our whole-genome gene expression discovery approach. Biological pathway analyses implicate LXR/RXR activation, neuroinflammation, atherosclerosis signaling, and amyloid processing. Co-directionality of expression data provide new mechanistic insights that are consistent with a compensatory/scarring scenario for brain pathological changes. A majority of top biomarkers also have evidence for involvement in other psychiatric disorders, particularly stress, providing a molecular basis for clinical co-morbidity and for stress as an early precipitant/risk factor. Some of them are modulated by existing drugs, such as antidepressants, lithium and omega-3 fatty acids. Other drug and nutraceutical leads were identified through bioinformatic drug repurposing analyses (such as pioglitazone, levonorgestrel, salsolidine, ginkgolide A, and icariin). Our work contributes to the overall pathophysiological understanding of memory disorders and AD. It also opens new avenues for precision medicine- diagnostics (assement of risk) as well as early treatment (pharmacogenomically informed, personalized, and preventive).

A telescope GWAS analysis strategy, based on SNPs-genes-pathways ensamble and on multivariate algorithms, to characterize late onset Alzheimer's disease

Genome–wide association studies (GWAS) have revealed a plethora of putative susceptibility genes for Alzheimer’s disease (AD), with the sole exception of APOE gene unequivocally validated in independent study. Considering that the etiology of complex diseases like AD could depend on functional multiple genes interaction network, here we proposed an alternative GWAS analysis strategy based on (i) multivariate methods and on a (ii) telescope approach, in order to guarantee the identification of correlated variables, and reveal their connections at three biological connected levels. Specifically as multivariate methods, we employed two machine learning algorithms and a genetic association test and we considered SNPs, Genes and Pathways features in the analysis of two public GWAS dataset (ADNI-1 and ADNI-2). For each dataset and for each feature we addressed two binary classifications tasks: cases vs. controls and the low vs. high risk of developing AD considering the allelic status of APOEe4. This complex strategy allowed the identification of SNPs, genes and pathways lists statistically robust and meaningful from the biological viewpoint. Among the results, we confirm the involvement of TOMM40 gene in AD and we propose GRM7 as a novel gene significantly associated with AD.

Morphological changes in subregions of hippocampus and amygdala in major depressive disorder patients

Despite many neuroimaging studies in the past years, the neuroanatomical substrates of major depressive disorder (MDD) subcortical structures are still not well understood. Since hippocampus and amygdala are the two vital subcortical structures that most susceptible to MDD, finding the evidence of morphological changes in their subregions may bring some new insights for MDD research. Combining structural magnetic resonance imaging (MRI) with novel morphometry analysis methods, we recruited 25 MDD patients and 28 healthy controls (HC), and investigated their volume and morphological differences in hippocampus and amygdala. Relative to volumetric method, our methods detected more significant global morphological atrophies (p<0.05). More precisely, subiculum and cornu ammonis (CA) 1 subregions of bilateral hippocampus, lateral (LA) and basolateral ventromedial (BLVM) of left amygdala and LA, BLVM, central (CE), amygdalostriatal transition area (ASTR), anterior cortical (ACO) and anterior amygdaloid area (AAA) of right amygdala were demonstrated prone to atrophy. Correlation analyses between each subject's surface eigenvalues and Hamilton Depression Scale (HAMD) were then performed. Correlation results showed that atrophy areas in hippocampus and amygdala have slight tendencies of expanding into other subregions with the development of MDD. Finally, we performed group morphometric analysis and drew the atrophy and expansion areas between MDD-Medicated group (only 19 medicated subjects in MDD group were included) and HC group, found some preliminary evidence about subregional morphological resilience of hippocampus and amygdala. These findings revealed new pathophysiologic patterns in the subregions of hippocampus and amygdala, which can help with subsequent smaller-scale MDD research.

GRIK4 and GRM7 gene may be potential indicator of venlafaxine treatment reponses in Chinese of Han ethnicity

Venlafaxine is one of commonly prescribed antidepressants for major depressive disorder (MDD). Accumulated evidence implicates the involvement of glutamatergic receptors in the pathophysiology of MDD and antidepressant treatment.By using 193 MDD patients who have been taking venlafaxine for 6 weeks, we investigated whether single nucleotide polymorphisms (SNPs) in glutamate ionotropic receptor kainate type subunit 4 (GRIK4), glutamate ionotropic receptor AMPA type subunit 1 (GRIA1) and glutamate metabotropic receptor 7 (GRM7) were associated with treatment response. 14 SNPs were selected randomly depended on association studies. Efficacy of treatment was determined by 17-item of Hamilton Rating Scale. Allele and genotype frequencies were compared between responders and non-responders.After adjusting by the false discovery rate (FDR), rs6589847 and rs56275759 in GRIK4 and rs9870680 in GRM7 showed associating with venlafaxine treatment response at week 6. (FDR: P = .018, P = .042, and P = .040, respectively).Our results indicated that genetic variants in the GRIK4 and GRM7 may associate with the treatment response in MDD patients treated by venlafaxine.

Analysis of pleiotropic genetic effects on cognitive impairment, systemic inflammation, and plasma lipids in the Health and Retirement Study

Variants associated with modulation of c-reactive protein (CRP) and plasma lipids have been investigated for polygenic overlap with Alzheimer's disease risk variants. We examined pleiotropic genetic effects on cognitive impairment conditioned on genetic variants (SNPs) associated with systemic inflammation as measured by CRP and with plasma lipids using data from the Health and Retirement Study. SNP enrichment was observed for cognitive impairment conditioned on the secondary phenotypes of plasma CRP and lipids. Fold enrichment of 100%-800% was observed for increasingly stringent p-value thresholds for SNPs associated with cognitive impairment conditional on plasma CRP, 80%-800% for low-density lipoprotein, and 80%-600% for total cholesterol. Significant associations (false discovery rate Q ≤ 0.05) between cognitive impairment, conditional with either CRP, low-density lipoprotein, or total cholesterol, were found for the locus on chromosome 19 that contains the APOE, TOMM40, APOC1, and PVRL2 genes. Relative numbers of significant SNPs in each of the genes differed by the conditional associations with the secondary phenotypes. Biological interpretation of both the genetic pleiotropy results and the individual genome-wide association results showed that the variants and proximal genes identified are involved in multiple pathological processes including cholesterol metabolism, inflammation, and mitochondrial transport. These findings are potentially important for Alzheimer's disease risk prediction and development of novel therapeutic approaches.

Synaptic organizers: synaptic adhesion-like molecules (SALMs)

Synaptic adhesion-like molecules (SALMs), also known as leucine-rich repeat and fibronectin III domain-containing proteins (LRFNs), are a family of synaptic adhesion molecules that consist of five members. SALMs exhibit functions in regulating neurite outgrowth and branching, synapse formation, and synapse maturation. Recent clinical studies have shown an association of SALMs with diverse neurological disorders. In this review article, we summarize structural mechanisms of the interaction of SALMs with leukocyte common antigen (LAR) family receptor tyrosine phosphatases (LAR-RPTPs) for synaptic activity, based on recent advances in the structural biology of SALMs.

SALM/Lrfn Family Synaptic Adhesion Molecules

Synaptic adhesion-like molecules (SALMs) are a family of cell adhesion molecules involved in regulating neuronal and synapse development that have also been implicated in diverse brain dysfunctions, including autism spectrum disorders (ASDs). SALMs, also known as leucine-rich repeat (LRR) and fibronectin III domain-containing (LRFN) proteins, were originally identified as a group of novel adhesion-like molecules that contain LRRs in the extracellular region as well as a PDZ domain-binding tail that couples to PSD-95, an abundant excitatory postsynaptic scaffolding protein. While studies over the last decade have steadily explored the basic properties and synaptic and neuronal functions of SALMs, a number of recent studies have provided novel insights into molecular, structural, functional and clinical aspects of SALMs. Here we summarize these findings and discuss how SALMs act in concert with other synaptic proteins to regulate synapse development and function.

Stress, Depression, Resilience and Ageing: A Role for the LPA-LPA1 Pathway

BACKGROUND

Chronic stress affects health and the quality of life, with its effects being particularly relevant in ageing due to the psychobiological characteristics of this population. However, while some people develop psychiatric disorders, especially depression, others seem very capable of dealing with adversity. There is no doubt that along with the identification of neurobiological mechanisms involved in developing depression, discovering which factors are involved in positive adaptation under circumstances of extreme difficulty will be crucial for promoting resilience.

METHODS

Here, we review recent work in our laboratory, using an animal model lacking the LPA1 receptor, together with pharmacological studies and clinical evidence for the possible participation of the LPA1 receptor in mood and resilience to stress.

RESULTS

Substantial evidence has shown that the LPA1 receptor is involved in emotional regulation and in coping responses to chronic stress, which, if dysfunctional, may induce vulnerability to stress and predisposition to the development of depression. Given that there is commonality of mechanisms between those involved in negative consequences of stress and in ageing, this is not surprising, considering that the LPA1 receptor may be involved in coping with adversity during ageing.

CONCLUSION

Alterations in this receptor may be a susceptibility factor for the presence of depression and cognitive deficits in the elderly population. However, because this is only a promising hypothesis based on previous data, future studies should focus on the involvement of the LPA-LPA1 pathway in coping with stress and resilience in ageing.

Genome-wide association study of language performance in Alzheimer's disease

Language impairment is common in prodromal stages of Alzheimer's disease (AD) and progresses over time. However, the genetic architecture underlying language performance is poorly understood. To identify novel genetic variants associated with language performance, we analyzed brain MRI and performed a genome-wide association study (GWAS) using a composite measure of language performance from the Alzheimer's Disease Neuroimaging Initiative (ADNI; n=1560). The language composite score was associated with brain atrophy on MRI in language and semantic areas. GWAS identified GLI3 (GLI family zinc finger 3) as significantly associated with language performance (p<5×10^-8). Enrichment of GWAS association was identified in pathways related to nervous system development and glutamate receptor function and trafficking. Our results, which warrant further investigation in independent and larger cohorts, implicate GLI3, a developmental transcription factor involved in patterning brain structures, as a putative gene associated with language dysfunction in AD.

Genome-wide Regional Heritability Mapping Identifies a Locus Within the TOX2 Gene Associated With Major Depressive Disorder

BACKGROUND

Major depressive disorder (MDD) is the second largest cause of global disease burden. It has an estimated heritability of 37%, but published genome-wide association studies have so far identified few risk loci. Haplotype-block-based regional heritability mapping (HRHM) estimates the localized genetic variance explained by common variants within haplotype blocks, integrating the effects of multiple variants, and may be more powerful for identifying MDD-associated genomic regions.

METHODS

We applied HRHM to Generation Scotland: The Scottish Family Health Study, a large family- and population-based Scottish cohort (N = 19,896). Single-single nucleotide polymorphism (SNP) and haplotype-based association tests were used to localize the association signal within the regions identified by HRHM. Functional prediction was used to investigate the effect of MDD-associated SNPs within the regions.

RESULTS

A haplotype block across a 24-kb region within the TOX2 gene reached genome-wide significance in HRHM. Single-SNP- and haplotype-based association tests demonstrated that five of nine genotyped SNPs and two haplotypes within this block were significantly associated with MDD. The expression of TOX2 and a brain-specific long noncoding RNA RP1-269M15.3 in frontal cortex and nucleus accumbens basal ganglia, respectively, were significantly regulated by MDD-associated SNPs within this region. Both the regional heritability and single-SNP associations within this block were replicated in the UK-Ireland group of the most recent release of the Psychiatric Genomics Consortium (PGC), the PGC2-MDD (Major Depression Dataset). The SNP association was also replicated in a depressive symptom sample that shares some individuals with the PGC2-MDD.

CONCLUSIONS

This study highlights the value of HRHM for MDD and provides an important target within TOX2 for further functional studies.

From Gene to Behavior: L-Type Calcium Channel Mechanisms Underlying Neuropsychiatric Symptoms

The L-type calcium channels (LTCCs) Cav1.2 and Cav1.3, encoded by the CACNA1C and CACNA1D genes, respectively, are important regulators of calcium influx into cells and are critical for normal brain development and plasticity. In humans, CACNA1C has emerged as one of the most widely reproduced and prominent candidate risk genes for a range of neuropsychiatric disorders, including bipolar disorder (BD), schizophrenia (SCZ), major depressive disorder, autism spectrum disorder, and attention deficit hyperactivity disorder. Separately, CACNA1D has been found to be associated with BD and autism spectrum disorder, as well as cocaine dependence, a comorbid feature associated with psychiatric disorders. Despite growing evidence of a significant link between CACNA1C and CACNA1D and psychiatric disorders, our understanding of the biological mechanisms by which these LTCCs mediate neuropsychiatric-associated endophenotypes, many of which are shared across the different disorders, remains rudimentary. Clinical studies with LTCC blockers testing their efficacy to alleviate symptoms associated with BD, SCZ, and drug dependence have provided mixed results, underscoring the importance of further exploring the neurobiological consequences of dysregulated Cav1.2 and Cav1.3. Here, we provide a review of clinical studies that have evaluated LTCC blockers for BD, SCZ, and drug dependence-associated symptoms, as well as rodent studies that have identified Cav1.2- and Cav1.3-specific molecular and cellular cascades that underlie mood (anxiety, depression), social behavior, cognition, and addiction.

The psychosis spectrum in Parkinson disease

In 2007, the clinical and research profile of illusions, hallucinations, delusions and related symptoms in Parkinson disease (PD) was raised with the publication of a consensus definition of PD psychosis. Symptoms that were previously deemed benign and clinically insignificant were incorporated into a continuum of severity, leading to the rapid expansion of literature focusing on clinical aspects, mechanisms and treatment. Here, we review this literature and the evolving view of PD psychosis. Key topics include the prospective risk of dementia in individuals with PD psychosis, and the causal and modifying effects of PD medication. We discuss recent developments, including recognition of an increase in the prevalence of psychosis with disease duration, addition of new visual symptoms to the psychosis continuum, and identification of frontal executive, visual perceptual and memory dysfunction at different disease stages. In addition, we highlight novel risk factors - for example, autonomic dysfunction - that have emerged from prospective studies, structural MRI evidence of frontal, parietal, occipital and hippocampal involvement, and approval of pimavanserin for the treatment of PD psychosis. The accumulating evidence raises novel questions and directions for future research to explore the clinical management and biomarker potential of PD psychosis.

Mood, stress and longevity: convergence on ANK3

Antidepressants have been shown to improve longevity in C. elegans. It is plausible that orthologs of genes involved in mood regulation and stress response are involved in such an effect. We sought to understand the underlying biology. First, we analyzed the transcriptome from worms treated with the antidepressant mianserin, previously identified in a large-scale unbiased drug screen as promoting increased lifespan in worms. We identified the most robust treatment-related changes in gene expression, and identified the corresponding human orthologs. Our analysis uncovered a series of genes and biological pathways that may be at the interface between antidepressant effects and longevity, notably pathways involved in drug metabolism/degradation (nicotine and melatonin). Second, we examined which of these genes overlap with genes which may be involved in depressive symptoms in an aging non-psychiatric human population (n=3577), discovered using a genome-wide association study (GWAS) approach in a design with extremes of distribution of phenotype. Third, we used a convergent functional genomics (CFG) approach to prioritize these genes for relevance to mood disorders and stress. The top gene identified was ANK3. To validate our findings, we conducted genetic and gene-expression studies, in C. elegans and in humans. We studied C. elegans inactivating mutants for ANK3/unc-44, and show that they survive longer than wild-type, particularly in older worms, independently of mianserin treatment. We also show that some ANK3/unc-44 expression is necessary for the effects of mianserin on prolonging lifespan and survival in the face of oxidative stress, particularly in younger worms. Wild-type ANK3/unc-44 increases in expression with age in C. elegans, and is maintained at lower youthful levels by mianserin treatment. These lower levels may be optimal in terms of longevity, offering a favorable balance between sufficient oxidative stress resistance in younger worms and survival effects in older worms. Thus, ANK3/unc-44 may represent an example of antagonistic pleiotropy, in which low-expression level in young animals are beneficial, but the age-associated increase becomes detrimental. Inactivating mutations in ANK3/unc-44 reverse this effect and cause detrimental effects in young animals (sensitivity to oxidative stress) and beneficial effect in old animals (increased survival). In humans, we studied if the most significant single nucleotide polymorphism (SNP) for depressive symptoms in ANK3 from our GWAS has a relationship to lifespan, and show a trend towards longer lifespan in individuals with the risk allele for depressive symptoms in men (odds ratio (OR) 1.41, P=0.031) but not in women (OR 1.08, P=0.33). We also examined whether ANK3, by itself or in a panel with other top CFG-prioritized genes, acts as a blood gene-expression biomarker for biological age, in two independent cohorts, one of live psychiatric patients (n=737), and one of suicide completers from the coroner's office (n=45). We show significantly lower levels of ANK3 expression in chronologically younger individuals than in middle age individuals, with a diminution of that effect in suicide completers, who presumably have been exposed to more severe and acute negative mood and stress. Of note, ANK3 was previously reported to be overexpressed in fibroblasts from patients with Hutchinson-Gilford progeria syndrome, a form of accelerated aging. Taken together, these studies uncover ANK3 and other genes in our dataset as biological links between mood, stress and longevity/aging, that may be biomarkers as well as targets for preventive or therapeutic interventions. Drug repurposing bioinformatics analyses identified the relatively innocuous omega-3 fatty acid DHA (docosahexaenoic acid), piracetam, quercetin, vitamin D and resveratrol as potential longevity promoting compounds, along with a series of existing drugs, such as estrogen-like compounds, antidiabetics and sirolimus/rapamycin. Intriguingly, some of our top candidate genes for mood and stress-modulated longevity were changed in expression in opposite direction in previous studies in the Alzheimer disease. Additionally, a whole series of others were changed in expression in opposite direction in our previous studies on suicide, suggesting the possibility of a "life switch" actively controlled by mood and stress.

Practical Strategies and Concepts in GPCR Allosteric Modulator Discovery: Recent Advances with Metabotropic Glutamate Receptors

Allosteric modulation of GPCRs has initiated a new era of basic and translational discovery, filled with therapeutic promise yet fraught with caveats. Allosteric ligands stabilize unique conformations of the GPCR that afford fundamentally new receptors, capable of novel pharmacology, unprecedented subtype selectivity, and unique signal bias. This review provides a comprehensive overview of the basics of GPCR allosteric pharmacology, medicinal chemistry, drug metabolism, and validated approaches to address each of the major challenges and caveats. Then, the review narrows focus to highlight recent advances in the discovery of allosteric ligands for metabotropic glutamate receptor subtypes 1-5 and 7 (mGlu1-5,7) highlighting key concepts ("molecular switches", signal bias, heterodimers) and practical solutions to enable the development of tool compounds and clinical candidates. The review closes with a section on late-breaking new advances with allosteric ligands for other GPCRs and emerging data for endogenous allosteric modulators.

Depression as a risk factor for Alzheimer's disease: Genes, steroids, cytokines and neurogenesis - What do we need to know?

Depression (MDD) is prodromal to, and a component of, Alzheimer's disease (AD): it may also be a trigger for incipient AD. MDD is not a unitary disorder, so there may be particular subtypes of early life MDD that pose independent high risks for later AD, though the identification of these subtypes is problematical. There may either be a common pathological event underlying both MDD and AD, or MDD may sensitize the brain to a second event ('hit') that precipitates AD. MDD may also accelerate brain ageing, including altered DNA methylation, increased cortisol but decreasing DHEA and thus the risk for AD. So far, genes predicting AD (e.g. APOEε4) are not risk factors for MDD, and those implicated in MDD (e.g. SLC6A4) are not risks for AD, so a common genetic predisposition looks unlikely. There is as yet no strong indication that an epigenetic event occurs during some forms of MDD that predisposes to later AD, though the evidence is limited. Glucocorticoids (GCs) are disturbed in some cases of MDD and in AD. GCs have marked degenerative actions on the hippocampus, a site of early β-amyloid deposition, and rare genetic variants of GC-regulating enzymes (e.g. 11β-HSD) predispose to AD. GCs also inhibit hippocampal neurogenesis and plasticity, and thus episodic memory, a core symptom of AD. Disordered GCs in MDD may inhibit neurogenesis, but the contribution of diminished neurogenesis to the onset or progression of AD is still debated. GCs and cytokines also reduce BDNF, implicated in both MDD and AD and hippocampal neurogenesis, reinforcing the notion that those cases of MDD with disordered GCs may be a risk for AD. Cytokines, including IL1β, IL6 and TNFα, are increased in the blood in some cases of MDD. They also reduce hippocampal neurogenesis, and increased cytokines are a known risk for later AD. Inflammatory changes occur in both MDD and AD (e.g. raised CRP, TNFα). Both cytokines and GCs can have pro-inflammatory actions in the brain. Inflammation (e.g. microglial activation) may be a common link, but this has not been systematically investigated. We lack substantial, rigorous and comprehensive follow-up studies to better identify possible subtypes of MDD that may represent a major predictor for later AD. This would enable specific interventions during critical episodes of these subtypes of MDD that should reduce this substantial risk.

Mitogen-activated protein kinase signaling pathway and invasion and metastasis of gastric cancer

The mortality rate of gastric cancer worldwide is as high as 70%, despite the development of novel therapeutic strategies. One reason for the high mortality is the rapid and uninhibited spread of the disease, such that the majority of patients are diagnosed at a stage when efficient therapeutic treatment is not available. Therefore, in-depth research is needed to investigate the mechanism of gastric cancer metastasis and invasion to improve outcomes and provide biomarkers for early diagnosis. The mitogen-activated protein kinase (MAPK) signaling pathway is widely expressed in multicellular organisms, with critical roles in multiple biological processes, such as cell proliferation, death, differentiation, migration, and invasion. The MAPK pathway typically responds to extracellular stimulation. However, the MAPK pathway is often involved in the occurrence and progression of cancer when abnormally regulated. Many studies have researched the relationship between the MAPK signaling pathway and cancer metastasis and invasion, but little is known about the important roles that the MAPK signaling pathway plays in gastric cancer. Based on an analysis of published data, this review aims to summarize the important role that the MAP kinases play in the invasion and metastasis of gastric cancer and attempts to provide potential directions for further research and clinical treatment.

Genetic studies of quantitative MCI and AD phenotypes in ADNI: Progress, opportunities, and plans

INTRODUCTION

Genetic data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) have been crucial in advancing the understanding of Alzheimer's disease (AD) pathophysiology. Here, we provide an update on sample collection, scientific progress and opportunities, conceptual issues, and future plans.

METHODS

Lymphoblastoid cell lines and DNA and RNA samples from blood have been collected and banked, and data and biosamples have been widely disseminated. To date, APOE genotyping, genome-wide association study (GWAS), and whole exome and whole genome sequencing data have been obtained and disseminated.

RESULTS

ADNI genetic data have been downloaded thousands of times, and >300 publications have resulted, including reports of large-scale GWAS by consortia to which ADNI contributed. Many of the first applications of quantitative endophenotype association studies used ADNI data, including some of the earliest GWAS and pathway-based studies of biospecimen and imaging biomarkers, as well as memory and other clinical/cognitive variables. Other contributions include some of the first whole exome and whole genome sequencing data sets and reports in healthy controls, mild cognitive impairment, and AD.

DISCUSSION

Numerous genetic susceptibility and protective markers for AD and disease biomarkers have been identified and replicated using ADNI data and have heavily implicated immune, mitochondrial, cell cycle/fate, and other biological processes. Early sequencing studies suggest that rare and structural variants are likely to account for significant additional phenotypic variation. Longitudinal analyses of transcriptomic, proteomic, metabolomic, and epigenomic changes will also further elucidate dynamic processes underlying preclinical and prodromal stages of disease. Integration of this unique collection of multiomics data within a systems biology framework will help to separate truly informative markers of early disease mechanisms and potential novel therapeutic targets from the vast background of less relevant biological processes. Fortunately, a broad swath of the scientific community has accepted this grand challenge.