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Abstract Alzheimer’s disease (AD) is the most common neurodegenerative disease in the United States (US). Animal models, specifically mouse models have been developed to better elucidate disease mechanisms and test therapeutic strategies for AD. A large portion of effort in the field was focused on developing transgenic (Tg) mouse models through over-expression of genetic mutations associated with familial AD (FAD) patients. Newer generations of mouse models through knock-in (KI)/knock-out (KO) or CRISPR gene editing technologies, have been developed for both familial and sporadic AD risk genes with the hope to more accurately model proteinopathies without over-expression of human AD genes in mouse brains. In this review, we summarized the phenotypes of a few commonly used as well as newly developed mouse models in translational research laboratories including the presence or absence of key pathological features of AD such as amyloid and tau pathology, synaptic and neuronal degeneration as well as cognitive and behavior deficits. In addition, advantages and limitations of these AD mouse models have been elaborated along with discussions of any sex-specific features. More importantly, the omics data from available AD mouse models have been analyzed to categorize molecular signatures of each model reminiscent of human AD brain changes, with the hope to guide future selection of most suitable models for specific research questions to be addressed in the AD field.

Abstract Background Alzheimer’s disease (AD) is a progressive and age-associated neurodegenerative disorder that affects women disproportionally. However, the underlying mechanisms are poorly characterized. Moreover, while the interplay between sex and ApoE genotype in AD has been investigated, multi-omics studies to understand this interaction are limited. Therefore, we applied systems biology approaches to investigate sex-specific molecular networks of AD. Methods We integrated large-scale human postmortem brain transcriptomic data of AD from two cohorts (MSBB and ROSMAP) via multiscale network analysis and identified key drivers with sexually dimorphic expression patterns and/or different responses to APOE genotypes between sexes. The expression patterns and functional relevance of the top sex-specific network driver of AD were further investigated using postmortem human brain samples and gene perturbation experiments in AD mouse models. Results Gene expression changes in AD versus control were identified for each sex. Gene co-expression networks were constructed for each sex to identify AD-associated co-expressed gene modules shared by males and females or specific to each sex. Key network regulators were further identified as potential drivers of sex differences in AD development. LRP10 was identified as a top driver of the sex differences in AD pathogenesis and manifestation. Changes of LRP10 expression at the mRNA and protein levels were further validated in human AD brain samples. Gene perturbation experiments in EFAD mouse models demonstrated that LRP10 differentially affected cognitive function and AD pathology in sex- and APOE genotype-specific manners. A comprehensive mapping of brain cells in LRP10 over-expressed (OE) female E4FAD mice suggested neurons and microglia as the most affected cell populations. The female-specific targets of LRP10 identified from the single cell RNA-sequencing (scRNA-seq) data of the LRP10 OE E4FAD mouse brains were significantly enriched in the LRP10-centered subnetworks in female AD subjects, validating LRP10 as a key network regulator of AD in females. Eight LRP10 binding partners were identified by the yeast two-hybrid system screening, and LRP10 over-expression reduced the association of LRP10 with one binding partner CD34. Conclusions These findings provide insights into key mechanisms mediating sex differences in AD pathogenesis and will facilitate the development of sex- and APOE genotype-specific therapies for AD.

Lemos Duarte et al. describe a strategy to produce, validate, and utilize highly-specific recombinant antibodies. As a proof of principle, they demonstrate development and validation of a panel of antibodies against proteins relevant to signaling by opiates. Their antibody-based tool can be useful in understanding the spatio-temporal dynamics of opioid signaling.

It is well accepted that treatment of chronic pain with morphine leads to μ opioid receptor (MOR) desensitization and the development of morphine tolerance. MOR activation by the selective peptide agonist, D-Ala2, N-MePhe4, Gly-ol]-enkephalin(DAMGO), leads to robust G protein receptor kinase activation, β-arrestin recruitment, and subsequent receptor endocytosis, which does not occur in an activation by morphine. However, MOR activation by morphine induces receptor desensitization, in a Protein kinase C (PKC) dependent manner. PKC inhibitors have been reported to decrease receptor desensitization, reduce opiate tolerance, and increase analgesia. However, the exact role of PKC in these processes is not clearly delineated. The difficulties in establishing a particular role for PKC have been, in part, due to the lack of reagents that allow the selective identification of PKC targets. Recently, we generated a conformation state-specific anti-PKC antibody that preferentially recognizes the active state of this kinase. Using this antibody to selectively isolate PKC substrates and a proteomics strategy to establish the identity of the proteins, we examined the effect of morphine treatment on the PKC targets. We found an enhanced interaction of a number of proteins with active PKC, in the presence of morphine. In this article, we discuss the role of these proteins in PKC-mediated MOR desensitization and analgesia. In addition, we posit a role for some of these proteins in mediating pain by TrKA activation, via the activation of transient receptor potential cation channel subfamily V member 1 (TRPV1). Finally, we discuss how these new PKC interacting proteins and pathways could be targeted for the treatment of pain.