Schizophrenia (SZ) is a severe and poorly understood psychiatric disorder caused by complex genetic and environmental factors (van Os and Kapur, 2009). Several hypotheses have been proposed regarding the etiology and pathogenesis of SZ, including neurodevelopmental disturbance, mitochondrial dysfunction, oxidative-antioxidant imbalance and abnormal bioenergetic function (Bryll et al., 2020; Lang et al., 2007; Ni and Chung, 2020; Sullivan et al., 2018). However, due to the high heterogeneity of SZ patients, no hypothesis can fully explain this complex disorder, and the clinical diagnosis of SZ still lacks objective markers.

Cell-free DNA (cfDNA), which is released into body fluids through apoptosis or necrosis (Snyder et al., 2016), has been found to be elevated in SZ patients (Ershova et al., 2019; Jiang et al., 2018). Ershova et al. found increased cfDNA concentrations in the plasma of SZ patients (Ershova et al., 2019). Our previous study also found approximately twofold higher cfDNA levels in SZ patients than those in healthy controls, which mainly originated from cell apoptosis, while the levels in patients with mood disorder (MD) were not significantly different from those in healthy controls (Jiang et al., 2018). We proposed that cfDNA aberrations may be specific to SZ rather than common to all psychiatric diseases (Jiang et al., 2018). In addition to psychiatric diseases, increased cfDNA levels were also observed in many other conditions that share pathological processes with SZ, such as stroke, myocardial infarction, trauma and sepsis (Jackson Chornenki et al., 2019; O'Connell et al., 2017; Xie et al., 2018), suggesting its potential as an auxiliary diagnostic marker for SZ. However, limitations in detection methods, such as the cost, time required and sample consumption (Jiang and Lo, 2016), may hinder its clinical application.

Previously, we analyzed plasma cfDNA using fluorescence correlation spectroscopy (FCS) (Jiang et al., 2018), a relatively sensitive and rapid method that analyzes fluorescence fluctuations caused by Brownian motion of fluorescent molecules (Krieger et al., 2015). Due to the low concentration of cfDNA in plasma, DNA separation from 600 μL of plasma is required for quantitative analysis (Jiang et al., 2018). This process consumes much of the blood sample, and the detection steps are cumbersome, which greatly limits the clinical application of cfDNA as an auxiliary diagnostic marker. Previous study has successfully used FCS for an assay of DNA fragments in apoptotic cell lysates without DNA extraction, demonstrating that FCS has a good selectivity in complicated substances (Ruan et al., 2012). Thus, in this study, we intend to apply the FCS method without DNA extraction to further improve the cfDNA detection method, aiming to improve the efficiency of plasma cfDNA concentration determination.

We also aimed to determine whether cfDNA concentrations are associated with disease stages or antipsychotic medication use. Studies have revealed differences in brain structure, function, and molecular basis between early- and chronic-stage SZ patients (Lu et al., 2018; Narayan et al., 2008). Compared to those in first-episode patients, brain gray matter volume aberrations were increased in chronic patients (Lu et al., 2018), and inflammation, stimulus response and immune functions were more related to chronic disease (Narayan et al., 2008). Therefore, given the different physiological bases from the early to the chronic stage of the disease, it is necessary to explore whether cfDNA levels vary between these stages, which may help to determine whether cfDNA is a stable trait indicator or a state marker. Additionally, since long-term antipsychotic treatment may be associated with brain structure changes in SZ (Huhtaniska et al., 2017), we need to assess whether antipsychotic use has an association with cfDNA levels, particularly in chronic-stage SZ patients.

In addition to its potential value of clinical diagnosis, exploring the underlying mechanisms of elevated cfDNA concentrations will help to reveal the pathogenesis of SZ. First, different sources of cfDNA characterize different biological changes in cells. cfDNA is composed of cell-free nuclear DNA (cf-nDNA) and cell-free mitochondrial DNA (cf-mtDNA), derived from the nucleus and mitochondria, respectively. cf-nDNA may reflect the degree of cell apoptosis, which is implicated in the pathological process of SZ (Jarskog, 2006). cf-nDNA is generally tagged by the sequence of human ALU-interspersed repeats, a member of the short interspersed nuclear element (SINE) family of mammalian genomes that can be released from the nucleus of apoptotic cells. On the other hand, evidence suggests that mitochondria are damaged in SZ (Bergman and Ben-Shachar, 2016; Rosenfeld et al., 2011; Shivakumar et al., 2020). Damaged mitochondria release mtDNA fragments into body fluids, potentially reflecting the degree of mitochondrial damage. However, studies analyzing cf-nDNA and cf-mtDNA levels in mental diseases have produced inconsistent findings (Jeong et al., 2020; Kageyama et al., 2018; Lindqvist et al., 2018; Qi et al., 2019). For example, Lindqvist et al. (2018) found elevated cf-mtDNA, while Kageyama et al. (2018) found lower plasma mtDNA levels in major depressive disorder. Kageyama et al. found no significant differences in cf-mtDNA levels between SZ patients and healthy controls; however, only 17 SZ patients were included (Kageyama et al., 2018). Thus, to obtain a better understanding of the characteristics of cell damage and bioenergetic compromise, larger-scale studies are needed to determine the alterations in cf-nDNA and cf-mtDNA levels in SZ. Moreover, increased oxidative stress, which is linked to SZ pathogenesis (Koga et al., 2016), can directly damage both nuclear and mitochondrial DNA (Ermakov et al., 2013), leading to apoptosis and increased cfDNA levels. Therefore, we hypothesized that the increased cfDNA levels in SZ may be due to excessive apoptosis caused by increased oxidative stress. Besides, abnormal biochemical indexes, such as blood lipids and blood glucose, have been reported to induce oxidative stress and DNA damage (Ighodaro, 2018; Macut et al., 2013). Thus, to explore the possible mechanisms behind elevated cfDNA in SZ patients, we analyzed the cfDNA composition, oxidative stress levels and the biochemical indexes.

This study aimed to confirm and facilitate the clinical application of cfDNA in the auxiliary diagnosis of SZ by improving the detection method, using the MD group as disease controls and analyzing the effects of different SZ disease stages and the use of antipsychotic medication for SZ. Furthermore, we explored the possible mechanisms for the increased cfDNA concentrations by analyzing the cfDNA composition, the degree of oxidative stress and the relationship between cfDNA and biochemical indexes.