The tip of the iceberg? The underestimated potential of non-canonical beta-amyloids for Alzheimer’s disease (2023)

Formation and deposition of amyloid-beta (Aβ) are considered one of the main drivers of Alzheimer’s disease (AD). For more than 30 years, Aβ has challenged researchers through its complex physicochemical properties and multiple peptide processing steps that involve several proteases (Andreasson et al., 2007), ultimately creating many Aβ variants that trigger various physiological effects in neurons, glia, and peripheral immune cells (Busch et al., 2022a). Recent research identified various additional naturally occurring Aβ species with different lengths and chemical modifications. Their impact on AD pathology is currently not well understood, although some of them occur at much higher abundance than Aβ1–42 and Aβ1–40. Here, we highlight new findings that challenge traditional views and summarize recent findings that argue for a significant contribution of previously neglected Aβ variants to the development and progression of AD. Next, we provide an overview on the technical challenges and open questions associated with their study and highlight how different Aβ variants such as Aβ11–40 and Aβ17–40 may use formyl peptide receptor signaling to trigger distinct cellular effects in neurons, glia, and immune cells. Over the years, more than 100 Aβ isoforms with different posttranslational modifications have been discovered (Figure 1) that arise from a single common precursor, the amyloid precursor protein (APP), which is expressed ubiquitously in many cell types but is most abundant in cerebral neurons (Andreasson et al., 2007). Traditionally, the conversion of APP to Aβ was thought to rely on two major processing pathways: an α secretase pathway that leads to supposedly non-toxic p3-fragments starting at position 17 of the Aβ domain (Aβ17–40/42) and a β secretase pathway that produces the neurotoxic variants starting at position 1 and ending at position 40 to 42 (Aβ1–40/42). New findings now challenge this simplistic dichotomy because more than 20 additional enzymes have been discovered to date that can affect APP processing, resulting in over 100 different peptides whose pathophysiological effects are only partially understood (Busch et al., 2022a). In addition to canonical secretase cleavage, non-canonical proteases such as insulysin, plasminogen, or matrix metallopeptidase 9 can contribute to the processing of a given Aβ peptide precursor (Andreasson et al., 2007). Subsequently, the resulting peptide isoforms can undergo further modifications such as pyroglutamylation, phoshphorylation, or oxidation (Wildburger et al., 2017; Busch et al., 2022a), leading to a variety of potentially patient- and brain-region specific Aβ-isoform combinations. The impact of these structural alterations in combination with chemical modifications on the onset, progression, and severity of disease has in most cases not been examined in detail. Of note, up to 70% of all Aβ peptides in the human brain have abridged N-termini (Wildburger et al., 2017). At the cellular level, N-shortened variants such as Aβ11–40/42, Aβ17–40/42, AβpE3–40/42, and AβpE11–40/42 can induce pro-inflammatory effects that sometimes surpass those of Aβ1–42 (Busch et al., 2022a). For example, they may induce a higher release of inflammatory cytokines from microglia and astrocytes, act as stronger chemoattractants for immune cells, and thus directly or indirectly contribute to the death of neurons (Busch et al., 2022a). In addition, serval well-known variations in the APP gene that are high-risk factors for familial forms of AD, such as the Swedish, French, or German mutations, directly affect the production of non-canonical Aβ variants. Remarkably, alterations in the levels of non-canonical peptides within the cerebrospinal fluid have been directly associated with the onset of AD (Busch et al., 2022a).Figure 1: The tip of the Iceberg? Occurrence, pathophysiology, and research-challenges of non-canonical amyloid-beta variants.Left: Frequency of different Aβ variants; center: deleterious effects of non-canonical Aβ variants; right: challenges that hinder the research on non-canonical Aβ isoforms. AD: Alzheimer’s disease; Aβ: amyloid-beta; cAMP: cyclic adenosine monophosphate; ERK1/2: extracellular signal-regulated kinase 1/2; MAPK: mitogen-activated protein kinase; p38: p38 mitogen-activated protein kinase; pE: pyro-glutamylation; ROS: reactive oxygen species. Created with BioRender.com.Challenges for the investigation of non-canonical Aβ variants in AD: Examination of non-canonical variants is hindered by several obstacles that have yet to be overcome (Figure 1). First, the most commonly used AD mouse models such as APP/PS1 and 5×FAD do not correctly reflect the variant composition of most patients (Armbrust et al., 2022). APP/PS1 mice encode the Swedish mutation K670N/M671L of the APP gene and a mutation in Presenilin-1 that both influence the processing of APP in the Aβ domain (Armbrust et al., 2022). 5×FAD mice express human APP with the mutations K670N/M671L (Swedish), I716V (Florida), and V717I (London) and presenilin-1 with the mutations M146L and L286V, which also leads to an altered processing (Armbrust et al., 2022). As the genetic mouse models have a strong bias in Aβ processing pattern, they do not reflect the patterns obtained in non-familial AD cases. Thus, they are not well suited to examine the effects of non-canonical isoforms because they do not reflect the pathology for the majority of clinical cases (Armbrust et al., 2022). Another issue arises from the antibodies that are routinely used to study Aβ species in tissue specimens derived from AD patients. Next, many antibodies do not recognize the p3 fragment Aβ17–40/42, although recent findings have shown that these peptides are present both in soluble heteromeric aggregates and in insoluble plaques of AD brains (Kuhn et al., 2020). This may distort results and might be a cause why the quantitative determination of Aβ isoform levels can vary strongly between different studies (Kuhn et al., 2020). In turn, for many non-canonical variants, the available concentrations in healthy brain tissue and different disease states are still unclear, making it difficult to judge their relevancy. Next, Aβ is infamous for its complex aggregation that is highly influenced by environmental factors such as pH value, salt concentration, temperature, and the presence of other molecules. This is further complicated through the fact, that different Aβ isoforms vary strongly in their aggregation kinetics (Chen et al., 2017). Different Aβ variants can cross-aggregate and form heteromeric complexes with altered biophysical properties. As a result, the reliability and reproducibility of aggregation studies remain a challenging task (Chen et al., 2017). Finally, a menagerie of Aβ interaction partners such as the triggering receptor expressed on myeloid cells 2 (TREM2), cluster of differentiation 36 (CD36), toll-like receptors (TLRs), formyl peptide receptors (FPRs), receptor for advanced glycation end products (RAGE), chemokine-like receptor 1, macrophage receptor with collagenous structure, transient receptor potential cation channel, subfamily M, member 2, and fragment crystallization receptors are known (Busch et al., 2022a). However, it is currently mostly unclear if and how truncations, elongations, and chemical modifications reshape the interactions of Aβ with these receptors (Figure 2A). This might be of high relevance, since this could influence the inflammatory potential of these variants.Figure 2: Known predisposition of different Aβ variants for a biased FPR signaling.(A) Functional bias in the response of glia cells towards Aβ11–40 and Aβ17–40. (B) Activation of FPRs by Aβ variants can induce multiple specific cellular responses through different signaling pathways. (C) Other FPR ligands may modulate Aβ signaling through induction of either anti- or pro-inflammatory responses through interactions with different FPR subtypes and/or biased agonism. AKT: Protein kinase B; Aβ: amyloid beta; BDNF: brain-derived neurotrophic factor; Ca2+: calcium; cAMP: cyclic adenosine monophosphate; CD36: cluster of differentiation 36; ERK1/2: extracellular signal-regulated kinase 1/2; FPR: formyl peptide receptor; MARCO: macrophage receptor with collagenous structure; MMP: metalloendoproteinase; p38: p38 mitogen-activated protein kinase; RAGE: receptor for advanced glycation endproducts; ROS: reactive oxygen species; TGFβ: transforming growth factor β; TLRs: toll-like receptors; TREM2: triggering receptor expressed on myeloid cells 2; TRPM2: transient receptor potential cation channel, subfamily M, member 2. Created with BioRender.com.Systematic studies on the variant-specific physiological response to non-canonical variants are scarce: While more than 3000 research articles examined the contribution of Aβ for AD, only a small subset investigated the effects of non-canonical Aβ. These studies demonstrated that unconventional Aβ’s can induce glial activation, chemokine and ROS release, cell migration and neuronal death. However, not much is known about the underlying molecular mechanisms. While more than 20 molecules on the cell surface interact with Aβ, to our knowledge, studies on pharmacological ligand-receptor interactions are confined to RAGE, TLR2, TLR4, and TREM2. Activation of TLR2 and TLR4 by N-abridged Aβ variants induces cytokine release, RAGE can interact with a wide range of Aβ peptides, and TREM2 can mediate the clearance of pyroglutamylated or phosphorylated variants. Together, these findings reveal a potential of non-canonical Aβ variants for the pathogenesis of AD but also highlight the need for a more systematic characterization. We recently started to systematically examine non-canonical Aβ on FPRs that comprise a small family of G-protein coupled pattern recognition receptors. FPRs are chemotactic receptors that are involved in the regulation of several important pro- and anti-inflammatory responses in most mammals (Ye et al., 2009). The family comprises three members in humans (hFPR1, hFPR2, hFPR3) and seven in mice (mFpr1, mFpr2, mFpr3, mFpr-rs4, mFpr-rs5, mFpr-rs6, mFpr-rs7) that are primarily expressed in the innate immune system. Inside the brain, they are most prevalent in astrocytes and microglia, where they contribute to regulatory immune functions. Our studies revealed a number of surprising observations with respect to their responses to non-canonical variants. First, we could show that the non-canonical variants Aβ11–40 and Aβ17–40 were 30-fold more potent in activating mouse and human FPR1 than the canonical Aβ1–42 and Aβ1–40 peptides (Busch et al., 2022b). Next, we could show that all human FPRs and murine mFpr1 and mFpr2 detect Aβ1–42 and Aβ1–40, which raises questions on the role of the individual FPR subtypes for Aβ detection (Figure 2B). Recent studies in other cell types suggest that an activation of hFPR1 may drive pro-inflammatory responses, while activation of hFPR2 may frequently help to resolve inflammatory processes (Wickstead et al., 2022). Since the progression of AD leads to steadily increasing levels of Aβ peptides in the brain, it is possible that FPR activation by Aβ triggers two opposing mechanisms. Due to a different sensitivity of the individual FPR subtypes for Aβ, they may first contribute to or even initiate pro-inflammatory responses via interaction with the more sensitive hFPR1 and later-on help to attenuate inflammation through activation of anti-inflammatory signaling at higher concentrations via the less sensitive hFPR2. Noteworthy, the precise interaction between FPRs and Aβ peptides might be even more complex because the receptors are not only confronted with different Aβ isoforms alone but are surrounded by a wide spectrum of other FPR interaction partners such as the neuroprotective lipoxin A4, resolvin D2, humanin, annexin A1 or formylated mitochondrial peptides released by necrotic cells and further endogenous inflammation markers such as serum amyloid A and LL-37 (Figure 2C; Ye et al., 2009). In vitro studies suggest that these factors can either potentiate or attenuate the inflammatory responses of FPRs (Zhang et al., 2020). To contextualize the role of FPRs, it is therefore important to keep these interactions in mind. Next, different Aβ variants may trigger distinct cellular responses. For example, a study reported that the detection of Aβ11–40 and Aβ17–40 by primary murine astrocytes lead in both cases to a pro-inflammatory activation but showed clear differences for the released types of interleukins and cytokines (Szczepanik et al., 2001). Next, we obtained evidence for a difference of distinct Aβ variants in the intracellular signaling and physiological responses (Figure 2C). In the glial cell line U87, activation of hFPR1 by Aβ11–40 or Aβ17–40 induced calcium signaling and ERK1/2 phosphorylation, but only Aβ11–40 initialized cell migration (Busch et al., 2022b). These observations raise the question how ligands that act on the same receptor can trigger different or even seemingly opposing effects. The answer might be based on the concept of biased agonism, where different ligands can trigger ligand-specific signal transduction events based on the activation of mutual-exclusive signaling pathways. In line with this idea, recent investigations demonstrated for hFPR1 and hFPR2 that ligands can show a bias in the induction of calcium and cAMP levels, MAPK phosphorylation, and β-arrestin translocation (Zhang et al., 2020). The investigation of FPR interactions with Aβ may provide valuable insights into the pathogenesis of Alzheimer’s disease: During the last 30 years, many facets of Aβ activity in the brain have been elucidated, however, it seems that constantly new questions appear that need to be solved. It might be too early to decide whether we are still just scratching the tip of the iceberg or if we are already looking deep below the surface to solve the central mysteries of Aβ (patho-)physiology. Further researches on the biological pathways and interaction partners are urgently needed to understand how the different Aβ variants contribute to the pathology of AD. Of note, FPRs respond to non-canonical peptides with markedly increased sensitivity compared to the canonical isoforms and are therefore excellent targets to examine variant-specific effects in AD’s chronic inflammatory events. Next, the dual function of FPRs in the initiation and resolution of inflammation might be helpful to exert a precise control over these processes. However, prior to this, three important questions need to be solved. First, which ligands trigger through which receptor interactions which signaling pathway (Figure 2A)? Second, which pathway or combination of pathways activates which cellular response (Figure 2B)? Third, how do other host endogenous FPR ligands such as the anti-inflammatory lipoxin A4, resolvin D2, cathelicidin LL-37, and annexin or pro-inflammatory ligands such as serum amyloid A and formylated mitochondrial peptides released from damaged cells (Ye et al., 2009) modulate the interplay between FPRs and the different Aβ isoforms (Figure 2C)? Answering these questions will help to predict the pathological consequences of neurodegenerative ligands and might help to target specific signaling pathways for future therapeutic approaches. Of note, a recent study showed that inhibition of FPRs in an AD mouse model ameliorated neuroinflammatory symptoms (Schröder et al., 2020). Thus, investigation of FPR interactions with Aβ not only provides valuable insights into the pathogenesis of AD, but might bring us one step further towards developing a treatment strategy for AD and related neurodegenerative diseases. We thank Kristina Endres (JGU Mainz) and Stefan Kins (TU Kaiserslautern) for providing valuable insights and thoughtful comments during the writing process that helped to improve this manuscript. This work was supported by Ministerium für Wissenschaft und Gesundheit (MWG), Rheinland Pfalz, NeurodegX Forschungskolleg (to BB). Open peer reviewers:Priyanka Joshi, University of California, USA; Amol Kaddoumi, Auburn University, USA. Additional file:Open peer review reports 1 and 2.P-Reviewers: Joshi P, Kaddoumi A; C-Editors: Zhao M, Liu WJ, Qiu Y; T-Editor: Jia Y