Dipeptidyl peptidase 10 (DPP10(789)): a voltage gated potassium channel associated protein is abnormally expressed in Alzheimer's and other neurodegenerative diseases

Transcriptional Heterogeneity and Differential Response of Rod Photoreceptor Pathway Uncovered by Single-Cell RNA Sequencing of the Aging Mouse Retina

Visual function deteriorates throughout the natural course of aging. Age-related structural and functional adaptations are observed in the retina, the light-sensitive neuronal tissue of the eye where visual perception begins. Molecular mechanisms underlying retinal aging are still poorly understood, highlighting the need to identify biomarkers for better prognosis and alleviation of aging-associated vision impairment. Here, we investigate dynamics of transcriptional dysregulation in the retina and identify affected pathways within distinct retinal cell types. Using an optimized protocol for single-cell RNA sequencing of mouse retinas at 3, 12, 18, and 24 months, we detect a progressive increase in the number of differentially expressed genes across all retinal cell types. The extent and direction of expression changes varies, with photoreceptor, bipolar, and Müller cells showing the maximum number of differentially expressed genes at all age groups. Furthermore, our analyses uncover transcriptionally distinct, heterogeneous subpopulations of rod photoreceptors and bipolar cells, distributed across distinct areas of the retina. Our findings provide a plausible molecular explanation for enhanced susceptibility of rod cells to aging and correlate with the observed loss of scotopic sensitivity in elderly individuals.

Stereo-seq of the prefrontal cortex in aging and Alzheimer's disease

Aging increases the risk for Alzheimer's disease (AD), driving pathological changes like amyloid-β (Aβ) buildup, inflammation, and oxidative stress, especially in the prefrontal cortex (PFC). We present the first subcellular-resolution spatial transcriptome atlas of the human prefrontal cortex (PFC), generated with Stereo-seq from six male AD cases at varying neuropathological stages and six age-matched male controls. Our analyses revealed distinct transcriptional alterations across PFC layers, highlighted disruptions in laminar structure, and exposed AD-related shifts in layer-to-layer and cell-cell interactions. Notably, we identified genes highly upregulated in stressed neurons and nearby glial cells, where AD diminished stress-response interactions that promote Aβ clearance. Further, cell-type-specific co-expression analysis highlighted three neuronal modules linked to neuroprotection, protein dephosphorylation, and Aβ regulation, with all modules downregulated as AD progresses. We identified ZNF460 as a transcription factor regulating these modules, offering a potential therapeutic target. In summary, this spatial transcriptome atlas provides valuable insight into AD's molecular mechanisms.

Systematic Analysis of Biological Processes Reveals Gene Co-expression Modules Driving Pathway Dysregulation in Alzheimer's Disease

Alzheimer's disease (AD) manifests as a complex systems pathology with intricate interplay among various genes and biological processes. Traditional differential gene expression (DEG) analysis, while commonly employed to characterize AD-driven perturbations, does not sufficiently capture the full spectrum of underlying biological processes. Utilizing single-nucleus RNA-sequencing data from postmortem brain samples across key regions-middle temporal gyrus, superior frontal gyrus, and entorhinal cortex-we provide a comprehensive systematic analysis of disrupted processes in AD. We go beyond the DEG-centric analysis by integrating pathway activity analysis with weighted gene co-expression patterns to comprehensively map gene interconnectivity, identifying region- and cell-type-specific drivers of biological processes associated with AD. Our analysis reveals profound modular heterogeneity in neurons and glia as well as extensive AD-related functional disruptions. Co-expression networks highlighted the extended involvement of astrocytes and microglia in biological processes beyond neuroinflammation, such as calcium homeostasis, glutamate regulation, lipid metabolism, vesicle-mediated transport, and TOR signaling. We find limited representation of DEGs within dysregulated pathways across neurons and glial cells, suggesting that differential gene expression alone may not adequately represent the disease complexity. Further dissection of inferred gene modules revealed distinct dynamics of hub DEGs in neurons versus glia, suggesting that DEGs exert more impact on neurons compared to glial cells in driving modular dysregulations underlying perturbed biological processes. Interestingly, we observe an overall downregulation of astrocyte and microglia modules across all brain regions in AD, indicating a prevailing trend of functional repression in glial cells across these regions. Notable genes from the CALM and HSP90 families emerged as hub genes across neuronal modules in all brain regions, suggesting conserved roles as drivers of synaptic dysfunction in AD. Our findings demonstrate the importance of an integrated, systems-oriented approach combining pathway and network analysis to comprehensively understand the cell-type-specific roles of genes in AD-related biological processes.

Spatial Dissection of the Distinct Cellular Responses to Normal Aging and Alzheimer's Disease in Human Prefrontal Cortex at Single-Nucleus Resolution

Aging significantly elevates the risk for Alzheimer's disease (AD), contributing to the accumulation of AD pathologies, such as amyloid-β (Aβ), inflammation, and oxidative stress. The human prefrontal cortex (PFC) is highly vulnerable to the impacts of both aging and AD. Unveiling and understanding the molecular alterations in PFC associated with normal aging (NA) and AD is essential for elucidating the mechanisms of AD progression and developing novel therapeutics for this devastating disease. In this study, for the first time, we employed a cutting-edge spatial transcriptome platform, STOmics® SpaTial Enhanced Resolution Omics-sequencing (Stereo-seq), to generate the first comprehensive, subcellular resolution spatial transcriptome atlas of the human PFC from six AD cases at various neuropathological stages and six age, sex, and ethnicity matched controls. Our analyses revealed distinct transcriptional alterations across six neocortex layers, highlighted the AD-associated disruptions in laminar architecture, and identified changes in layer-to-layer interactions as AD progresses. Further, throughout the progression from NA to various stages of AD, we discovered specific genes that were significantly upregulated in neurons experiencing high stress and in nearby non-neuronal cells, compared to cells distant from the source of stress. Notably, the cell-cell interactions between the neurons under the high stress and adjacent glial cells that promote Aβ clearance and neuroprotection were diminished in AD in response to stressors compared to NA. Through cell-type specific gene co-expression analysis, we identified three modules in excitatory and inhibitory neurons associated with neuronal protection, protein dephosphorylation, and negative regulation of Aβ plaque formation. These modules negatively correlated with AD progression, indicating a reduced capacity for toxic substance clearance in AD subject samples. Moreover, we have discovered a novel transcription factor, ZNF460, that regulates all three modules, establishing it as a potential new therapeutic target for AD. Overall, utilizing the latest spatial transcriptome platform, our study developed the first transcriptome-wide atlas with subcellular resolution for assessing the molecular alterations in the human PFC due to AD. This atlas sheds light on the potential mechanisms underlying the progression from NA to AD.

Systematic Analysis of Biological Processes Reveals Gene Co-expression Modules Driving Pathway Dysregulation in Alzheimer's Disease

Alzheimer's disease (AD) manifests as a complex systems pathology with intricate interplay among various genes and biological processes. Traditional differential gene expression (DEG) analysis, while commonly employed to characterize AD-driven perturbations, does not sufficiently capture the full spectrum of underlying biological processes. Utilizing single-nucleus RNA-sequencing data from postmortem brain samples across key regions-middle temporal gyrus, superior frontal gyrus, and entorhinal cortex-we provide a comprehensive systematic analysis of disrupted processes in AD. We go beyond the DEG-centric analysis by integrating pathway activity analysis with weighted gene co-expression patterns to comprehensively map gene interconnectivity, identifying region- and cell-type-specific drivers of biological processes associated with AD. Our analysis reveals profound modular heterogeneity in neurons and glia as well as extensive AD-related functional disruptions. Co-expression networks highlighted the extended involvement of astrocytes and microglia in biological processes beyond neuroinflammation, such as calcium homeostasis, glutamate regulation, lipid metabolism, vesicle-mediated transport, and TOR signaling. We find limited representation of DEGs within dysregulated pathways across neurons and glial cells, indicating that differential gene expression alone may not adequately represent the disease complexity. Further dissection of inferred gene modules revealed distinct dynamics of hub DEGs in neurons versus glia, highlighting the differential impact of DEGs on neurons compared to glial cells in driving modular dysregulations underlying perturbed biological processes. Interestingly, we note an overall downregulation of both astrocyte and microglia modules in AD across all brain regions, suggesting a prevailing trend of functional repression in glial cells across these regions. Notable genes, including those of the CALM and HSP90 family genes emerged as hub genes across neuronal modules in all brain regions, indicating conserved roles as drivers of synaptic dysfunction in AD. Our findings demonstrate the importance of an integrated, systems-oriented approach combining pathway and network analysis for a comprehensive understanding of the cell-type-specific roles of genes in AD-related biological processes.

Bayesian bi-level variable selection for genome-wide survival study

Mild cognitive impairment (MCI) is a clinical syndrome characterized by the onset and evolution of cognitive impairments, often considered a transitional stage to Alzheimer's disease (AD). The genetic traits of MCI patients who experience a rapid progression to AD can enhance early diagnosis capabilities and facilitate drug discovery for AD. While a genome-wide association study (GWAS) is a standard tool for identifying single nucleotide polymorphisms (SNPs) related to a disease, it fails to detect SNPs with small effect sizes due to stringent control for multiple testing. Additionally, the method does not consider the group structures of SNPs, such as genes or linkage disequilibrium blocks, which can provide valuable insights into the genetic architecture. To address the limitations, we propose a Bayesian bi-level variable selection method that detects SNPs associated with time of conversion from MCI to AD. Our approach integrates group inclusion indicators into an accelerated failure time model to identify important SNP groups. Additionally, we employ data augmentation techniques to impute censored time values using a predictive posterior. We adapt Dirichlet-Laplace shrinkage priors to incorporate the group structure for SNP-level variable selection. In the simulation study, our method outperformed other competing methods regarding variable selection. The analysis of Alzheimer's Disease Neuroimaging Initiative (ADNI) data revealed several genes directly or indirectly related to AD, whereas a classical GWAS did not identify any significant SNPs.

Neuronal Roles of the Multifunctional Protein Dipeptidyl Peptidase-like 6 (DPP6)

The concerted action of voltage-gated ion channels in the brain is fundamental in controlling neuronal physiology and circuit function. Ion channels often associate in multi-protein complexes together with auxiliary subunits, which can strongly influence channel expression and function and, therefore, neuronal computation. One such auxiliary subunit that displays prominent expression in multiple brain regions is the Dipeptidyl aminopeptidase-like protein 6 (DPP6). This protein associates with A-type K+ channels to control their cellular distribution and gating properties. Intriguingly, DPP6 has been found to be multifunctional with an additional, independent role in synapse formation and maintenance. Here, we feature the role of DPP6 in regulating neuronal function in the context of its modulation of A-type K+ channels as well as its independent involvement in synaptic development. The prevalence of DPP6 in these processes underscores its importance in brain function, and recent work has identified that its dysfunction is associated with host of neurological disorders. We provide a brief overview of these and discuss research directions currently underway to advance our understanding of the contribution of DPP6 to their etiology.

Differential Gene Expression in the Hippocampi of Nonhuman Primates Chronically Exposed to Methamphetamine, Cocaine, or Heroin

OBJECTIVE

Methamphetamine (MA), cocaine, and heroin cause severe public health problems as well as impairments in neural plasticity and cognitive function in the hippocampus. This study aimed to identify the genes differentially expressed in the hippocampi of cynomolgus monkeys in response to these drugs.

METHODS

After the monkeys were chronically exposed to MA, cocaine, and heroin, we performed large-scale gene expression profiling of the hippocampus using RNA-Seq technology and functional annotation of genes differentially expressed. Some genes selected from RNA-Seq analysis data were validated with reverse transcription-quantitative polymerase chain reaction (RT-qPCR). And the expression changes of ADAM10 protein were assessed using immunohistochemistry.

RESULTS

The changes in genes related to axonal guidance (PTPRP and KAL1), the cell cycle (TLK2), and the regulation of potassium ions (DPP10) in the drug-treated groups compared to the control group were confirmed using RT-qPCR. Comparative analysis of all groups showed that among genes related to synaptic long-term potentiation, CREBBP and GRIN3A were downregulated in both the MA- and heroin-treated groups compared to the control group. In particular, the mRNA and protein expression levels of ADAM10 were decreased in the MA-treated group but increased in the cocaine-treated group compared to the control group.

CONCLUSION

These results provide insights into the genes that are upregulated and downregulated in the hippocampus by the chronic administration of MA, cocaine, or heroin and basic information for developing novel drugs for the treatment of hippocampal impairments caused by drug abuse.

Convergence of independent DISC1 mutations on impaired neurite growth via decreased UNC5D expression

The identification of convergent phenotypes in different models of psychiatric illness highlights robust phenotypes that are more likely to be implicated in disease pathophysiology. Here, we utilize human iPSCs harboring distinct mutations in DISC1 that have been found in families with major mental illness. One mutation was engineered to mimic the consequences on DISC1 protein of a balanced translocation linked to mental illness in a Scottish pedigree; the other mutation was identified in an American pedigree with a high incidence of mental illness. Directed differentiation of these iPSCs using NGN2 expression shows rapid conversion to a homogenous population of mature excitatory neurons. Both DISC1 mutations result in reduced DISC1 protein expression, and show subtle effects on certain presynaptic proteins. In addition, RNA sequencing and qPCR showed decreased expression of UNC5D, DPP10, PCDHA6, and ZNF506 in neurons with both DISC1 mutations. Longitudinal analysis of neurite outgrowth revealed decreased neurite outgrowth in neurons with each DISC1 mutation, which was mimicked by UNC5D knockdown and rescued by transient upregulation of endogenous UNC5D. This study shows a narrow range of convergent phenotypes of two mutations found in families with major mental illness, and implicates dysregulated netrin signaling in DISC1 biology.

Prenatal Alcohol Exposure Is Associated With Adverse Cognitive Effects and Distinct Whole-Genome DNA Methylation Patterns in Primary School Children

Prenatal alcohol exposure (PAE) is known to elicit a broad range of systemic effects, including neurophysiological alterations that result in adverse behavioral and cognitive outcomes. However, molecular pathways underlying these long-term intrauterine effects remain to be investigated. Here, we tested a hypothesis that PAE may lead to epigenetic alterations to the DNA resulting in attentional and cognitive alterations of the children. We report the results of the study that included 156 primary school children of the Franconian Cognition and Emotion Studies (FRANCES) cohort which were tested for an objective marker of PAE, ethyl glucuronide (EtG) in meconium at birth. Thirty-two newborns were found to be exposed to alcohol with EtG values above 30 ng/g (EtG+). Previously we described PAE being associated with lower IQ and smaller amplitude of the event-related potential component P3 in go trials (Go-P3), which indicates a reduced capacity of attentional resources. Whole-genome methylation analysis of the buccal cell DNA revealed 193 differentially methylated genes in children with positive meconium EtG, that were clustered into groups involved in epigenetic modifications, neurodegeneration, neurodevelopment, axon guidance and neuronal excitability. Furthermore, we detected mediation effects of the methylation changes in DPP10 and SLC16A9 genes on the EtG related cognitive and attention-related deficits. Our results suggest that system-wide epigenetic changes are involved in long-term effects of PAE. In particular, we show an epigenetic mediation of PAE effects on cognition and attention-related processes.

Manipulation of dipeptidylpeptidase 10 in mouse and human in vivo and in vitro models indicates a protective role in asthma

We previously identified dipeptidylpeptidase 10 (DPP10) on chromosome 2 as a human asthma susceptibility gene, through positional cloning. Initial association results were confirmed in many subsequent association studies but the functional role of DPP10 in asthma remains unclear. Using the MRC Harwell N-ethyl-N-nitrosourea (ENU) DNA archive, we identified a point mutation in Dpp10 that caused an amino acid change from valine to aspartic acid in the β-propeller region of the protein. Mice carrying this point mutation were recovered and a congenic line was established (Dpp10^145D). Macroscopic examination and lung histology revealed no significant differences between wild-type and Dpp10^145D/145D mice. However, after house dust mite (HDM) treatment, Dpp10 mutant mice showed significantly increased airway resistance in response to 100 mg/ml methacholine. Total serum IgE levels and bronchoalveolar lavage (BAL) eosinophil counts were significantly higher in homozygotes than in control mice after HDM treatment. DPP10 protein is present in airway epithelial cells and altered expression is observed in both tissue from asthmatic patients and in mice following HDM challenge. Moreover, knockdown of DPP10 in human airway epithelial cells results in altered cytokine responses. These results show that a Dpp10 point mutation leads to increased airway responsiveness following allergen challenge and provide biological evidence to support previous findings from human genetic studies.

This article has an associated First Person interview with the first author of the paper.

Summary: Here, we show a novel mouse model carrying a point mutation in dipeptidylpeptidase 10 (Dpp10). Our data provide evidence that DPP10 might play a protective role in asthma.

Large-scale identification of clinical and genetic predictors of motor progression in patients with newly diagnosed Parkinson's disease: a longitudinal cohort study and validation

Background

Better understanding and prediction of PD progression could improve disease management and clinical trial design. We aimed to use longitudinal clinical, molecular, and genetic data to develop predictive models, compare potential biomarkers, and identify novel predictors for motor progression in PD. We also sought to assess the use of these models in the design of treatment trials in PD.

Methods

A Bayesian multivariate predictive inference platform was applied to data from the Parkinson’s Progression Markers Initiative (PPMI) study (NCT01141023). We used genetic data and baseline molecular and clinical variables from PD patients and healthy controls to construct an ensemble of models to predict the annualised rate of the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale parts II and III combined. We tested our overall explanatory power, as assessed by the coefficient of determination (R²), and replicated novel findings in an independent clinical cohort of PD patients from the Longitudinal and Biomarker Study in PD (LABS-PD; NCT00605163). The potential utility of these models for clinical trial design was quantified by comparing simulated randomized placebo-controlled trials within the out-of sample LABS-PD cohort.

Findings

A total of 117 controls and 312 PD cases were available for analysis. Our model ensemble exhibited strong performance in-cohort (5-fold cross-validated R²=41%, 95% CI: 35% – 47%) and significant, though reduced, performance out-of-cohort (R²=9%, 95% CI: 4% – 16%). Individual predictive features identified from PPMI data were confirmed in the LABS-PD cohort of 317 PD patients. These included significant replication of higher baseline motor score, male sex, and increased age, as well as a novel PD-specific epistatic interaction all indicative of faster motor progression. Genetic variation was the most useful predictive marker of motor progression (2.9%, 95%CI: 1.5–4.3%). CSF biomarkers at baseline showed a more modest (0.3%; 95%CI: 0.1–0.5%), but still significant effect on motor progression prediction. The simulations (n=5000) showed that incorporating the predicted rates of motor progression into the final models of treatment effect reduced the variability in the study outcome allowing significant differences to be detected at sample sizes up to 20% smaller than in naïve trials.

Interpretation

Our model ensemble confirmed established and identified novel predictors of PD motor progression. Improving existing prognostic models through machine learning approaches should benefit trial design and evaluation, as well as clinical disease monitoring and treatment.

Funding

Michael J. Fox Foundation for Parkinson’s Research and National Institute of Neurological Disorders and Stroke (1P20NS092529-01).

A fast and powerful W-test for pairwise epistasis testing

Epistasis plays an essential role in the development of complex diseases. Interaction methods face common challenge of seeking a balance between persistent power, model complexity, computation efficiency, and validity of identified bio-markers. We introduce a novel W-test to identify pairwise epistasis effect, which measures the distributional difference between cases and controls through a combined log odds ratio. The test is model-free, fast, and inherits a Chi-squared distribution with data adaptive degrees of freedom. No permutation is needed to obtain the P-values. Simulation studies demonstrated that the W-test is more powerful in low frequency variants environment than alternative methods, which are the Chi-squared test, logistic regression and multifactor-dimensionality reduction (MDR). In two independent real bipolar disorder genome-wide associations (GWAS) datasets, the W-test identified significant interactions pairs that can be replicated, including SLIT3-CENPN, SLIT3-TMEM132D, CNTNAP2-NDST4 and CNTCAP2-RTN4R The genes in the pairs play central roles in neurotransmission and synapse formation. A majority of the identified loci are undiscoverable by main effect and are low frequency variants. The proposed method offers a powerful alternative tool for mapping the genetic puzzle underlying complex disorders.

Kv4.2 and accessory dipeptidyl peptidase-like protein 10 (DPP10) subunit preferentially form a 4:2 (Kv4.2:DPP10) channel complex

Kv4 is a member of the voltage-gated K(+) channel family and forms a complex with various accessory subunits. Dipeptidyl aminopeptidase-like protein (DPP) is one of the auxiliary subunits for the Kv4 channel. Although DPP has been well characterized and is known to increase the current amplitude and accelerate the inactivation and recovery from inactivation of Kv4 current, it remains to be determined how many DPPs bind to one Kv4 channel. To examine whether the expression level of DPP changes the biophysical properties of Kv4, we expressed Kv4.2 and DPP10 in different ratios in Xenopus oocytes and analyzed the currents under two-electrode voltage clamp. The current amplitude and the speed of recovery from inactivation of Kv4.2 changed depending on the co-expression level of DPP10. This raised the possibility that the stoichiometry of the Kv4.2-DPP10 complex is variable and affects the biophysical properties of Kv4.2. We next determined the stoichiometry of DPP10 alone by subunit counting using single-molecule imaging. Approximately 70% of the DPP10 formed dimers in the plasma membrane, and the rest existed as monomers in the absence of Kv4.2. We next determined the stoichiometry of the Kv4.2-DPP10 complex; Kv4.2-mCherry and mEGFP-DPP10 were co-expressed in different ratios and the stoichiometries of Kv4.2-DPP10 complexes were evaluated by the subunit counting method. The stoichiometry of the Kv4.2-DPP10 complex was variable depending on the relative expression level of each subunit, with a preference for 4:2 stoichiometry. This preference may come from the bulky dimeric structure of the extracellular domain of DPP10.