As characterized by the progressive decline of cognitive function, activities of daily living (ADL), and social function (Knopman et al., 2021), Alzheimer’s disease (AD) is an age-related neurodegenerative disorder, which accounts for about 60–80% of all dementias (Alzheimer’s Association, 2021). It is generally believed that the sporadic AD (which accounts for more than 99% of all cases) is comprehensively caused by age, genetics, metabolism, inflammation, and environmental and other factors (Livingston et al., 2020); however, the exact pathogenesis has not been fully elucidated and the treatment that can block or reverse the disease progress has not been developed so far (Levey, 2021). Thus, the significance of the early diagnosis of AD grows to be increasingly prominent.

In the past decades, the great progress of biomarkers has promoted an early diagnosis of AD to a large extent. The AD research framework proposed by NIA-AA in 2018 categorized AD biomarkers into A/T(N) system (Jack et al., 2018), in which the core biomarkers were mainly based on cerebrospinal fluid (CSF) test [e.g., CSF-amyloid β (Aβ) and CSF-phosphorylated-tau (p-tau)] or positron emission tomography (PET) test (e.g., ¹¹C-Pittsburgh compound B (PiB)-PET and tau-PET) (Jack et al., 2018). Nevertheless, the potential risk of invasive deep puncture in CSF collection and the high cost of PET test have hindered the applications of these biomarkers. Therefore, the development of blood-based biomarkers of AD is promising currently (Thijssen and Rabinovici, 2021).

Apolipoprotein M (ApoM) is a newly discovered apolipoprotein with a molecular weight of 26 kDa (Xu and Dahlbäck, 1999), which is mainly expressed in liver, kidney, adipose tissue, and cerebrovascular endothelial cells of human beings (Xu and Dahlbäck, 1999; Kober et al., 2017; Sramkova et al., 2019). To date, the studies of ApoM mainly focused on lipid metabolism (Wolfrum et al., 2005), cardiovascular disease (Versmissen et al., 2016), and diabetes (Kurano et al., 2020). Of note, a genome-wide association study (GWAS) found that the APOM gene could drive the association of lipid metabolism pathway with AD risk (Kunkle et al., 2019; Chernick et al., 2020). Besides, the CSF level of ApoM in the patients with AD was significantly lower than that in the cognitively normal (CN) controls (Khoonsari et al., 2016). But, the relationship between blood ApoM and AD has not been revealed so far.

In addition, there are often obviously individual differences in the absolute values of certain blood-based biomarkers in clinical practice, which limits their interpretation and applications. Thus, standardization or normalization by calculating with other related clinical indicators, such as the international normalized ratio (INR) generated from the prothrombin time (PT), may lead to better stability and comparability (Deitcher, 2002). Actually, the combination of biomarkers has also been a common strategy in AD research, such as Aβ42/Aβ40 ratio, p-tau/total-tau ratio, and total-tau/α-synuclein ratio (Shim et al., 2020), etc. Considering that ApoM is closely related to lipid metabolism and based on our previous research experience (Yang et al., 2021), the ratios of blood ApoM level to that of different blood lipids including total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), may be the more optimized indicators than ApoM itself (Yang et al., 2021).

Therefore, here, we reported a multicenter, cross-sectional pilot clinical study, in which AD group and CN control group were recruited. The demographic data, clinical characteristics, and some of the common indicators in clinical laboratories were collected. Then, we detected and compared the plasma ApoM levels of both groups. Further, we investigated the correlation between plasma ApoM with the presence, main clinical characteristics, and the representative biomarkers of AD, respectively. Finally, we explored the diagnostic power of plasma ApoM for AD. We expected that this study could provide new evidence for evaluating plasma ApoM as a new candidate biomarker of AD.

In this multicenter, cross-sectional study, we found for the first time that plasma level of ApoM and its derived indicators (i.e., ratios of ApoM/TC, ApoM/TG, ApoM/HDL-C, and ApoM/LDL-C) were significantly higher in AD group than those in CN group, respectively. Then, we confirmed that plasma ApoM and its derived indicators were remarkably associated with the presence of AD, respectively. Subsequently, the correlations between plasma ApoM and its derived indicators with clinical characteristics (i.e., cognitive impairment and ADL) and representative blood biomarkers (i.e., p-tau217 and NfL) of AD were analyzed, respectively. Finally, we assessed the diagnostic power of plasma ApoM for AD and revealed that the majority of the four derived indicators performed individually better than ApoM. Meanwhile, the plasma ApoM and all the derived indicators could significantly enhance the diagnostic efficiency of the basic model of combining age, sex, APOE4 carriage status, and BMI, respectively. To our knowledge, this is the first time to reveal the association between plasma ApoM with AD so far.

In the past decades, the early diagnosis and the exploration of biomarkers have been the frontiers of AD research. The research framework proposed by NIA-AA in 2018 categorized the biomarkers of AD as A/T(N), where A represents Aβ deposition, T represents tau hyperphosphorylation and neurofibrillary tangle (NFT) formation, and N represents neuronal loss and neurodegeneration (Jack et al., 2018). This framework requires that the establishment of AD definitive diagnosis must be based on the evidence of brain Aβ aggregation (cerebrospinal fluid or PET test) (Jack et al., 2018). However, the high cost of invasive lumbar puncture and molecular imaging greatly limit their applications. Thus, blood-derived biomarkers are attracting increasing attention from clinicians and researchers (Thijssen and Rabinovici, 2021).

At present, both plasma p-tau217 and NfL are representative among all blood-based biomarkers of AD (Janelidze et al., 2021b). Additionally, a series of novel blood biomarkers and combinations of different biomarkers were also being developed and validated taking plasma p-tau217 and NfL as reference (Cullen et al., 2021; Palmqvist et al., 2021a). Thus, in this study, we measured the plasma levels of p-tau217 and NfL and further analyzed their correlations with ApoM and its derived indicators, respectively. All the results from total participants and subgroup analyses (sex and APOE4 carriage status) indicated that plasma ApoM had the potential to evaluate the severity of neurodegeneration of AD. The extensive studies on plasma p-tau217 have shown an excellent accuracy of p-tau217 in differentiating patients with AD and non-AD (Palmqvist et al., 2020; Palmqvist et al., 2021b; Thijssen et al., 2021). However, in this study, we found an overlap of plasma p-tau217 between the AD and CN groups. The previous studies have shown that biomarkers may vary with the stage and severity of AD, and the CSF p-tau as an early biomarker of downstream pathological changes was triggered by Aβ deposition (Sato et al., 2018). Research has shown different patterns of changes in CSF p-tau and tau-PET measures across the AD continuum. CSF levels of p-tau increased in the earliest disease stages (i.e., in asymptomatic individuals with CSF or PET evidence of abnormal Aβ accumulation) and appeared to reach a plateau or even decrease in later symptomatic stages of AD (Fagan et al., 2014; Mattsson-Carlgren et al., 2020a; Janelidze et al., 2021a). Considering the consistency of CSF and plasma p-tau (Barthélemy et al., 2020; Palmqvist et al., 2020; Janelidze et al., 2021a), it is speculated that the plasma p-tau217 may have a similar trajectory to CSF p-tau217. Most of the patients with AD in previous clinical studies involving plasma p-tau217 were at the stage of mild or moderate AD (Mattsson-Carlgren et al., 2020b,2021). However, many patients with AD in this study were moderate to severe AD (CDR scored 2–3), which indicates that the plasma p-tau217 might have entered a plateau or even declined, which could result in an overlap with CN group.

However, the role and related mechanism of ApoM in the pathogenesis of AD is uncovered. Reviewing the previously published literature, we proposed that ApoM might influence on Aβ metabolism and AD pathogenesis through the pathways as followings. First, sphingosine 1-phosphate (S1P), a metabolite of membrane sphingosine lipid, binds to the extracellular partners, is enriched in circulating fluid, and binds to G protein-coupled S1P receptors (S1PRs), which regulates the embryonic development and organ function (Cartier and Hla, 2019). It showed that immunoregulatory S1P had the potential as a biomarker for plasma diagnosis and differential diagnosis of AD (Chua et al., 2020). Postmortem study found that the level of brain S1P was reduced in patients with AD and significantly negatively correlated with the level of brain Aβ and hyperphosphorylated tau protein (He et al., 2010). Cell experiments showed that S1P was specifically bound to full-length BACE1 and increased its proteolytic activity. Reducing S1P generation in mouse neurons could reduce BACE1 activity level and Aβ production (Takasugi et al., 2011). It was also found that the accumulation of intracellular S1P disrupted the amyloid precursor protein (APP) metabolism. Inhibition of S1P lyase led to the accumulation of S1P, which impeded lysosomal degradation of APP, that leads to the accumulation of APP in cells and increase of APP amyloid fragment, and also reduced γ-secretase activity (Karaca et al., 2014). Nevertheless, in some neurodegenerative models, S1P has been shown to counteract the pro-apoptotic effect of neuramide by reducing oxidative stress and regulating the expression of pro-apoptotic and anti-apoptotic proteins in the Bcl-2 family (Czubowicz and Strosznajder, 2014). It was found that ApoM-bound S1P maintained the low level of permeability of paracellular blood–brain barrier (BBB) in all cerebral microvessels and low level of vesicle-mediated transport in the penetrating arterioles (Mathiesen Janiurek et al., 2019). In addition, S1P receptor 1 of cerebral endothelial cells maintained the BBB permeability in a size-selective manner by regulating the correct localization of tight junction protein (Yanagida et al., 2017). In addition, accumulation of S1P in neurons activated the microglia through S1P receptor 2, which leads to impaired autophagy and neuroinflammation (Karunakaran et al., 2019). The S1P axis in the nucleus might promote the transformation of microglia from M1 to M2 phenotype, thus regulating the neuroinflammation (Ji et al., 2019). Therefore, considering that ApoM is an important molecular chaperone of S1P, it stably binds and transports S1P in circulation and interstitial fluid, promoting the activation of receptor S1PRs and forming an important signal axis (Christoffersen et al., 2011), and ApoM is also involved in regulating the metabolism and transport of S1P (Christensen et al., 2017). These studies suggested that ApoM could regulate Aβ metabolism and AD pathogenesis through S1P and its receptors.

Second, the scavenger receptor class B type I (SR-BI) has been found in astrocytes and vascular smooth muscle cells and has been shown to mediate the adhesion of microglia to fibrillary Aβ. Microglia can directly uptake the aggregates of Aβ via scavenger receptors (Paresce et al., 1996). It showed that the reduction of SR-BI enhanced the deposition of fibrillary Aβ and cerebral amyloid angiopathy, impaired the response of perivascular macrophages to Aβ, and exacerbated the deficits of learning and memory (Thanopoulou et al., 2010). SR-BI keeps Aβ in a soluble state by blocking the entry of Aβ into endothelial cells, thus mediating the inhibition of Aβ-mediated monocyte adhesion to cerebrovascular endothelial cells by HDL (Robert et al., 2017). In addition, synaptic plasticity (long-term potentiation) in the CA1 region of hippocampus was found to be defective in very old SR-BI knockout mice, which also showed selective impairment in recognition and spatial memory (Chang et al., 2009). Thus, considering that ApoM is highly bound to SR-BI (Yao et al., 2020), it suggested that ApoM might regulate Aβ metabolism and AD pathogenesis through SR-BI.

Third, ApoM is widely distributed in lipoprotein in plasma, and most of it (about 95%) mainly binds to HDL, which plays a crucial role in the formation of pre-β-HDL and cholesterol efflux (Wolfrum et al., 2005). Although it is currently considered that low-level dysfunction of HDL is both risk factors for AD, the relationship and mechanism between HDL with Aβ metabolism and AD pathogenesis are still not elucidated (Stukas et al., 2014). A recent GWAS study preliminarily found that APOM gene was the main regulation gene of intracellular cholesterol that drove lipid metabolism pathway and thus increased the risk of AD, which suggests that ApoM may play an important role in AD (Kunkle et al., 2019). These findings suggested that ApoM could be a key in unlocking the link between HDL and AD.

Currently, ApoM is not a clinical blood lipid indicator. To improve the application value of ApoM in the clinical practice, we adopted the ratio of ApoM to clinically common blood lipid indicators based on our previous experience (Yang et al., 2021) and sought the more optimized blood biomarkers related to ApoM. The results showed that some of the four ApoM-derived indicators could perform better in their correlation analysis with cognitive function, abilities of daily living, and the representative blood biomarkers and also performed better in the diagnosis of AD compared with ApoM itself.

This study still has the following limitations: (1) As a cross-sectional clinical study, it only revealed the association between plasma ApoM and AD, but could not determine the causal relationship between them. (2) Due to the fact that most patients with AD were hospitalized for a long time and their families were not willing to undergo lumbar puncture and PET examination, the inclusion criteria for AD group in this study were based on the clinical criteria of NINCDS-ADRDA rather than the most popular biomarker-based criteria of NIA-AA. (3) The Eighth People’s Hospital of Chengdu is a chronic disease hospital and municipal sanatorium for cadres. Many patients with AD are long-term hospitalized, and a majority of them had only underwent the head CT scanning. In addition, the brain MRI data often lacked the coronal images to assess hippocampal atrophy. Thus, we did not determine the association between ApoM and neuroimaging. (4) Considering the sample size of this study, we did not carry out the external validation after diagnostic power evaluation.

Taken together, this study preliminarily uncovered that the plasma ApoM is correlated with the presence, clinical characteristics, and representative blood biomarkers of AD and has certain diagnostic power of AD. The role and related mechanism of ApoM on the pathogenesis of AD is worthy of further study in the future.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving human participants were reviewed and approved by the Ethics Review Committee of Sichuan Provincial People’s Hospital. The patients/participants provided their written informed consent to participate in this study.

W-dL, S-JY, and YX carried out the study conception and design. J-YX, XH, YS, H-SJ, JF, N-wY, F-QG, FY, and JX performed the material preparation, data collection, and analysis. J-YX and YX wrote the first draft of the manuscript. All authors commented on the previous versions of the manuscript and read and approved the final manuscript.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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