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Published in final edited form as: Psychoneuroendocrinology. 2020 Feb 20;116:104632. doi: 10.1016/j.psyneuen.2020.104632

Molecular Markers of Neuroendocrine Function and Mitochondrial Biogenesis Associated with Early Life Stress

Kathryn K Ridout 1,2,*, Jesse L Coe 4,5, Stephanie H Parade 4,5, Carmen J Marsit 6, Hung-Teh Kao 2, Barbara Porton 2, Linda L Carpenter 2,3, Lawrence H Price 2,3, Audrey R Tyrka 2,3
PMCID: PMC7887859  NIHMSID: NIHMS1635400  PMID: 32199200

Abstract

Objective:

Glucocorticoid receptor gene (NR3C1) promoter methylation influences cellular expression of the glucocorticoid receptor and is a proposed mechanism by which early life stress impacts neuroendocrine function. Mitochondria are sensitive and responsive to neuroendocrine stress signaling through the glucocorticoid receptor, and recent evidence with this sample and others shows that mitochondrial DNA copy number (mtDNAcn) is increased in adults with a history of early stress. No prior work has examined the role of NR3C1 methylation in the association between early life stress and mtDNAcn alterations.

Methods:

Adult participants (n=290) completed diagnostic interviews and questionnaires characterizing early stress and lifetime psychiatric symptoms. Medical conditions, active substance abuse, and prescription medications other than oral contraceptives were exclusionary. Subjects with a history of lifetime bipolar, obsessive-compulsive, or psychotic disorders were excluded; individuals with other forms of major psychopathology were included. Whole blood mtDNAcn was measured using qPCR; NR3C1 methylation was measured via pyrosequencing. Multiple regression and bootstrapping procedures tested NR3C1 methylation as a mediator of effects of early stress on mtDNAcn.

Results:

The positive association between early adversity and mtDNAcn (p=.02) was mediated by negative associations of early adversity with NR3C1 methylation (p=.02) and NR3C1 methylation with mtDNAcn (p<.001). The indirect effect involving early adversity, NR3C1 methylation, and mtDNAcn was significant (95% CI [.002, .030]).

Conclusions:

NR3C1 methylation significantly mediates the association between early stress and mtDNAcn, suggesting that glucocorticoid receptor signaling may be a mechanistic pathway underlying mtDNAcn alterations of interest for future longitudinal work.

Keywords: early life stress, mitochondrial DNA copy number: glucocorticoid receptor methylation, adversity: adverse childhood experiences, trauma

INTRODUCTION

An estimated 61% of adults in the United States experienced some form of early life stress defined as abuse, neglect, parental separation, or poverty (Merrick et al., 2018). Traumatic early life exposures are associated with an increased risk for many poor health outcomes, including diabetes, cardiovascular disease, and psychiatric conditions, including major depressive disorder (MDD), anxiety disorders, and post-traumatic stress disorder (PTSD) (Vachon et al., 2015). These conditions exact costs in excess of $124 billion through suffering, disability, treatment, and loss of productivity over the lifespan (Fang et al., 2012), making early stress exposures an important public health problem. Therefore, toward the goal of disorder prevention or treatment, there is great interest in understanding the molecular pathways impacted after exposure to early life stress.

Early life stress is linked to alterations in the neuroendocrine stress response system and changes to mitochondrial DNA and function (Picard et al., 2014; Ridout et al., 2016) Early life stress in the form of prolonged, repetitive, or severe adversity in the absence of a nurturing environment can result in hypothalamic-pituitary-adrenal (HPA) axis dysregulation (Danese and McEwen, 2012; Tyrka et al., 2016c). HPA hyper- or hyporeactivity after toxic stress can result in increased risk of stress-related psychiatric disorders (Syed and Nemeroff, 2017; Tyrka et al., 2016c).

Mounting evidence shows that a key mechanism linking early life experiences to changes in neuroendocrine function is epigenetic modification of genes central to the neuroendocrine stress response (Syed and Nemeroff, 2017; Tyrka et al., 2016c). Methylation at CpG nucleotides in gene promoter regions has been of particular interest given their important role in the dynamic regulation of gene expression (Suzuki and Bird, 2008). Epigenetic alterations of neuroendocrine genes have been detected after early life stress exposure (Tyrka et al., 2016c) and are associated with risk for psychiatric disorders (Klengel and Binder, 2015; Syed and Nemeroff, 2017; Tyrka et al., 2016c). Much of this work has focused on promoter methylation of the glucocorticoid receptor (GR) gene, NR3C1 (Tyrka et al., 2016c). The GR is responsible for intracellular responses to neuroendocrine signaling, and intracellular GR expression is reduced with promoter methylation of NR3C1 (Daskalakis and Yehuda, 2014; Turner et al., 2010; Tyrka et al., 2016c). This in turn results in reduced GR-mediated glucocorticoid negative feedback and increases in corticosterone responses (Francis et al., 1999; Liu et al., 1997). Most work also shows this positive association between NR3C1 methylation and measures of glucocorticoid activity (Palma-Gudiel et al., 2015; Stonawski et al., 2018; Tyrka, 2016).

A central target of intracellular glucocorticoid signaling critical to responding and adapting to stress is the mitochondrion (Picard et al., 2014; Ridout et al., 2016). Mitochondria are intracellular organelles that generate ATP, the main energy source in the cell, through the process of oxidative phosphorylation. Mitochondria, which supply the large energy requirements needed to mount the stress response, are particularly vital for highly metabolically active organs such as the brain (Manoli et al., 2007). Mitochondrial oxidative phosphorylation is controlled by a complex cascade of enzymes that is tightly regulated through nuclear and mitochondrial gene expression pathways (Lee et al., 2013; Manoli et al., 2007). In addition to providing the main source of cellular energy, mitochondria are integral to cellular signaling, differentiation, replication, inflammation, and apoptosis (Streck et al., 2014). Glucocorticoid signaling through the GR can modify mitochondrial activity by binding to and regulating mitochondrial and nuclear gene expression (Lee et al., 2013; Psarra and Sekeris, 2009, 2011), in addition to altering cellular processes that regulate mitochondrial genome replication leading to changes in mitochondrial DNA copy number (mtDNAcn) (Lee et al., 2013; Psarra and Sekeris, 2008, 2009) (Figure 1).

Figure 1.

Figure 1.

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Mechanisms by which the glucocorticoid receptor (GR) contributes to mitochondrial DNA copy number (mtDNAcn) regulation.

After intracellular cortisol binds the GR, the activated GR can impact mitochondrial DNA copy number via a variety of mechanisms: 1) GR can enter the mitochondrion, bind to glucocorticoid response elements (GREs) in the mtDNA and directly activate its replication; 2) GR can directly bind to GREs in the nuclear genome and increase transcription of genes that regulate mtDNAcn; and 3) GR-mediated increases in mtDNAcn or modification of intracellular oxidative stress and inflammation pathways can lead to further activation of nuclear genes that enhance mtDNA replication.

Recent evidence suggests that mitochondrial dysfunction may be involved in the development of depressive and anxiety disorders. In rodent models, pharmacological inhibition of mitochondrial function induces anxiety phenotypes (Hollis et al., 2015) and mitochondrial dysfunction is observed in rodent models of MDD (Rezin et al., 2008; Seibenhener et al., 2013; Yang et al., 2016) and PTSD (Garabadu et al., 2015; Zhang et al., 2015). In humans, preliminary evidence shows mitochondrial involvement in PTSD (Bersani et al., 2016; Su et al., 2008; Zhang et al., 2015), and MDD (Karabatsiakis et al., 2014; Moreno et al., 2013; Nicod et al., 2015) as well as transdiagnostic behaviors and symptoms, including anergia, psychomotor retardation, memory impairment, and fatigue (Karabatsiakis et al., 2014), as well as somatization (Gardner and Boles, 2008). Alterations in neuroendocrine signaling have been implicated in the link between psychiatric disorders and mitochondrial function (Cai et al., 2015; Liu and Zhou, 2012; Yang et al., 2016). In rodents, chronic stress or corticosterone exposure increases mitochondrial DNA replication (Cai et al., 2015), and repeated injection of corticosterone reduces brain mitochondrial activity while inducing depressive (Liu and Zhou, 2012; Yang et al., 2016) and anxiety phenotypes (Yang et al., 2016). Further, in adult mice with mitochondrial gene deletions, neuroendocrine function after restraint stress is altered and induces depressive phenotypes (Picard et al., 2015). Thus, changes in mitochondrial biogenesis may be an important downstream molecular target of NR3C1 gene expression changes after methylation and may impact risk for the development of psychiatric disorders.

We recently reported that adults with a history of early life stress or psychiatric disorders had increases in mtDNAcn (Tyrka et al., 2015; Tyrka et al., 2016a) and reduced methylation of NR3C1 (Tyrka, 2016). Given the evidence of neuroendocrine dysfunction after early life stress, these findings may be due to an impact on mtDNAcn through a neuroendocrine pathway. Since GR is an important regulator of mitochondria and mtDNAcn, in the present study we hypothesized that NR3C1 methylation may be a mechanism by which early life stress alters mtDNAcn.

METHODS AND MATERIALS

Subjects

Adults aged 18–65 (n = 290) were recruited using newspaper and internet advertisements directed toward healthy adults and individuals with psychiatric disorders and/or a history of early life stress. These participants were studied in our prior publication on associations of early stress and psychopathology with mtDNAcn (Tyrka et al., 2016a). Participants self-identified as white (n = 241), black (n = 26), Asian (n = 9), Hispanic (n = 4), and other (n = 10). Subjects free of current substance-use disorders (defined as meeting DSM-IV criteria in the past month) and without current or lifetime bipolar, obsessive-compulsive, or psychotic disorders were included. Medical conditions and prescription medications other than oral contraceptives were exclusionary. Prior to study enrollment, participants were informed about the study and voluntary written informed consent was obtained. The study was approved by the Butler Hospital Institutional Review Board.

Measures

Demographics.

Age, sex, race, and highest educational level were obtained by subject self-report. Height and weight were measured, and body mass index (BMI) was calculated using the formula (weight [kg]/height [m2]).

Early Life Stress Assessment.

Subjects were asked whether they experienced parental loss prior to age 18, defined as parental death and/or parental separation for at least 6 months with no attempts by the parent to contact or respond to the child. Maltreatment was assessed using the Childhood Trauma Questionnaire (CTQ) 28-item version, which evaluates physical, sexual, and emotional abuse and physical and emotional neglect (Bernstein et al., 2003). Participants were considered to have experienced early life adversity if they endorsed parental loss or had at least moderate levels of one or more of the five maltreatment types on the CTQ.

Psychiatric Disorders.

Psychiatric diagnoses were assessed using the Structured Clinical Interview for DSM-IV (First MB, 1997).

DNA Isolation and Measurement of mtDNAcn and NR3C1 Methylation

DNA Isolation.

Whole blood was drawn from participants and then stored at −80° C until processing. DNA was isolated from whole blood using standard techniques.

mtDNAcn Quantification.

Three parallel qPCRs reactions were performed to quantitate copy numbers for the mitochondrial genome and the beta-hemoglobin gene as a single-copy standard as previously described (O’Callaghan, 2011). Data acquisition was performed using the ABI Prism HT79000 DNA Sequence Detection System (Applied Biosystems, Grand Island, New York). qPCR was performed in 384-well plates with a reaction volume of 10 mL containing 25 ng of genomic DNA, 300 nmol/L of each primer, and Sybr Select Master Mix (Life Technologies Corporation, Grand Island, New York). Each reaction plate contained wells with serial dilutions of a cloned amplicon (containing a mtDNA and beta-hemoglobin amplicon) to generate standard curves and permit absolute quantitation of mitochondrial DNA and beta-hemoglobin copy number. Mitochondrial forward and reverse primer sequences were directed toward the D-loop region: CAT CTG GTT CCT ACT TCA GGG and TGA GTG GTT AAT AGG GTG ATA GA. Forward and reverse primers for the beta-hemoglobin gene were: GCT TCT GAC ACA ACT GTG TTC ACT AGC and CAC CAA CTTCAT CCA CGT (Bai and Wong, 2005). As previously described (Tyrka et al., 2015; Tyrka et al., 2016a), the initial heating step of 95 °C for 10 minutes was followed by 40 cycles of 95 °C for 15 seconds and 60 °C for 1 minute. PCR efficiency criteria were 99–104% for both measures. Coefficients of variation (CVs) were calculated within each triplicate and samples with CVs > 5% were repeated. MtDNA copy number was divided by the beta-hemoglobin gene copy number to obtain the final value of mtDNAcn per cell.

NR3C1 Promoter Methylation.

In this study, the NR3C1 exon 1F promoter region containing 13 CpGs, the human homologue of the rat exon 17, was examined. Using 500 ng of DNA and the EZ DNA Methylation Kit (Zymo Research, Orange, CA), sodium bisulfite modification was performed. NR3C1 promoter methylation was determined using the EpiTect methylation-specific PCR (Qiagen, Valencia CA) and quantitative pyrosequencing methods previously described (Oberlander et al., 2008); samples were run in triplicate. Sodium bisulfate-modified, fully methylated referent positive control and fully unmethylated whole genome amplified negative control DNA (Qiagen, Valencia CA) was examined with each batch. Peripheral blood derived DNA that was not sodium bisulfite-modified was included in each pyrosequencing run to control for non-specific amplification. PCR products were visualized and sized on an agarose gel after the run for quality control (FlashGel – Lonza). Pyromark Software (Qiagen) was used to quantify methylation. Our prior work showed high levels of intercorrelation across CpG sites in this region (Tyrka, 2016; Tyrka et al., 2012); for the current paper, we examined mean methylation across the entire region in statistical analyses.

Statistical Analysis

Analyses were conducted with SPSS version 25 (IBM, Armonk, NY, USA) and Mplus Version 7.4 (Muthen & Muthen, 1998–2012). To normalize the distribution of skewed or kurtotic variables, mtDNAcn and mean NR3C1 methylation were log10-transformed. Individuals were categorized according to presence or absence of early adversity (ncase=138; ncontrol=152). In order to maximize the size of the sample, full-information maximum likelihood estimation (FIML; (Enders, 2001)) was used to accommodate missing NR3C1 methylation data for two participants. Little’s Missing Completely at Random test (Little, 1988) demonstrated that these data were missing completely at random, χ2(6) = 11.06, p = .09.

Primary hypotheses were tested using regression and path analysis. In our prior work with this sample, early adversity was independently related to higher mtDNAcn (Tyrka et al., 2016a) and lower NR3C1 methylation (Tyrka, 2016). In the present study we therefore tested a mediation model in which the presence or absence of early adversity, predicted mean NR3C1 methylation, which in turn predicted mtDNAcn. Age, sex, and BMI were included as covariates based on prior literature showing effects with adversity, DNA methylation and/or mtDNAcn (Horvath and Raj, 2018; Inoshita et al., 2015; Mendelson et al., 2017). Because study aims were tested using fully saturated models (i.e., 0 degrees of freedom), models provided perfect fit to the data, so fit indices were not examined. To test for hypothesized mediation, we assessed all models using 10,000 bootstrap replicates to obtain bias-corrected bootstrap confidence intervals for the indirect effects (Mackinnon et al., 2004; Preacher and Hayes, 2008; Shrout and Bolger, 2002).

RESULTS

Subject characteristics are described in Table 1. Demographic characteristics were found to be largely unrelated to mtDNAcn and mean NR3C1 methylation, with the exception that BMI was related to mean NR3C1 methylation (r = −.13, p = .02).

Table 1.

Participant Characteristics

Total N=290. Depressive disorders include MDD, dysthymia, and depression not otherwise specified. Anxiety disorders include PTSD, generalized anxiety disorder, social phobia, panic disorder, and anxiety disorder not otherwise specified.

Demographics
Age, M (SD) 31.01 (10.75)
Sex, N (%) female 177 (61.0)
Race, N (%) white 241 (83.1)
BMI, M (SD) 26.17 (5.01)
College degree, N (%) 161 (55.5)
Oral contraceptive use, N (%) 39 (13.4)
Smokers, N (%) 29 (10.0)
Adversity
Emotional abuse, N (%) 51 (17.6)
Physical abuse, N (%) 37 (12.8)
Sexual abuse, N (%) 45 (15.5)
Emotional neglect, N (%) 52 (17.9)
Physical neglect, N (%) 32 (11.0)
Parental death, N (%) 36 (12.4)
Parental desertion, N (%) 43 (14.8)
Sum adversities, M (SD) 1.03 (1.43)
Psychiatric Disorders
Current Disorders
MDD, N (%) 13 (4.5)
Depressive, N (%) 25 (8.6)
PTSD, N (%) 3 (1.0)
Anxiety, N (%) 13 (4.5)
Past Disorders
MDD, N (%) 45 (15.5)
Depressive, N (%) 50 (17.2)
PTSD, N (%) 10 (3.4)
Anxiety, N (%) 21 (7.2)
Alcohol/Substance, N (%) 55 (19.0)
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Associations of Early Life Stress, NR3C1 Methylation, and mtDNAcn

As expected based on our prior report (Tyrka et al., 2016a), regression analyses revealed that early life stress was positively associated with mtDNAcn (B = .06, SE = .03, p = .02). Figure 2 provides the results of the mediation model testing associations of early life stress, NR3C1 methylation, and mtDNAcn, controlling for age, sex, and BMI. Early stress was negatively associated with mean NR3C1 methylation (B = −.08, SE = .04, p = .02), and mean NR3C1 methylation was negatively associated with mtDNAcn (B = −.18, SE = .04, p < .001). Supporting mediation, the indirect path involving early stress, mean NR3C1 methylation, and mtDNAcn was significantly different from zero (95% CI [.002, .030]). In addition to the primary analyses with a priori control for age, sex, and BMI, we also conducted sensitivity analyses to determine whether the inclusion of any of the other demographic characteristics (Table 1) altered the pattern of results, and findings were virtually identical with and without inclusion of additional covariates.

Figure 2.

Figure 2.

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Path model in which mean NR3C1 methylation is specified as a mediator of the association between early adversity and mtDNAcn.

Note t p < .10, * p < .05, ** p < .01, *** p < .001. Path coefficients are presented in B (SE) format. Dashed line indicates a non-significant association. The indirect effect involving early adversity, mean NR3C1 methylation, and mtDNAcn was statistically significant.

Exploratory Follow-up Analyses: Potential Implications for Psychiatric Disorders

Although the cross-sectional design precludes reliable testing of a four-step indirect effects model including prediction of psychiatric disorder outcomes (Cole and Maxwell, 2003), bivariate associations confirm significant relationships between these variables. History of early life stress was significantly associated with the lifetime presence of a psychiatric disorder (r = .27, p <.001), and in line with our prior work with this sample (Tyrka et al., 2015; Tyrka et al., 2016a; Tyrka et al., 2016b; Tyrka et al., 2012), both NR3C1 methylation and mtDNAcn were significantly associated with lifetime psychiatric disorders (r = −.22, p < .001; r = .17, p = .003, respectively).

DISCUSSION

To our knowledge this study is the first to examine the pathways between early stress, NR3C1 methylation, and mtDNAcn. The results indicate that NR3C1 promoter methylation mediates the effect of early adversity on mtDNAcn. These results are consistent with data from basic and cellular models showing dynamic regulation of mitochondrial function by the glucocorticoid receptor. In addition, these findings extend previous results by suggesting these mechanisms are relevant to allostatic changes in mtDNAcn observed after early adversity. Exposure to prolonged, severe, or multiple stressors early in life can result in alterations of HPA axis functioning (Bunea et al., 2017; Burke et al., 2005), and epigenetic modification of genes important to HPA axis regulation may be a critical mechanism by which these early exposures can impart physiologic changes (Argentieri et al., 2017; Tyrka et al., 2016c). NR3C1 methylation has been positively correlated with cortisol concentrations (Tyrka et al., 2016b; Yehuda et al., 2015), suggesting an important role of NR3C1 gene methylation in HPA axis regulation.

In this study, we found that lower levels of NR3C1 methylation were associated with higher mtDNAcn. Lower NR3C1 methylation of the 1F promoter region has been associated with increased GR gene expression. The GR can bind to mitochondrial DNA and promote mtDNA replication, increasing mtDNAcn (Clay Montier et al., 2009). The results presented here suggest that increased GR expression after early adversity might be a mechanism by which mtDNAcn increases (Clay Montier et al., 2009; Psarra and Sekeris, 2009); however, further research would be needed to confirm this model. Additionally, activated GR may also increase mtDNAcn by enhancing expression of nuclear genes that regulate mtDNAcn directly or indirectly by modifying oxidative stress pathways (Clay Montier et al., 2009; Lee et al., 2013; Psarra and Sekeris, 2009).

These data build on early evidence supporting relationships between early life stress, psychiatric disorders, the neuroendocrine stress response, and mtDNAcn. Previously, we reported greater mtDNAcn in adults with a history of either early stress or psychiatric disorders (Tyrka et al., 2015; Tyrka et al., 2016a). Individuals with a history of both early stress and psychiatric disorders were observed to have the highest mtDNAcn (Tyrka et al., 2016a). Changes in NR3C1 methylation have been reported after early life stress and with psychiatric disorders as well (Tyrka, 2016; Tyrka et al., 2012; Tyrka et al., 2016c), and the results of the present study implicate NR3C1 methylation as a potential mechanism of mtDNAcn increases which may be involved in the development of psychiatric conditions. Our cross-sectional design limits the reliable testing of multiple-effects mediation models; future longitudinal research is needed to test causal models regarding these mechanisms of risk for psychiatric outcomes.

These data are consistent with emerging evidence of mitochondrial dysfunction as a potential biomarker of early stress exposure (Picard et al., 2018; Ridout et al., 2018). Increases in mtDNAcn have been reported after early stress exposure (Cai et al., 2015; Ridout et al., 2018; Tyrka et al., 2016a). Intracellular mtDNAcn is a proxy indicator of mitochondrial biogenesis and a measure of mitochondrial content (Picard et al., 2014) that is dynamically regulated based on the energy demands on the cell (Sun et al., 2016). Consistent with evidence that mtDNAcn is regulated by the inflammatory and oxidative state of the cell to meet energy requirements (Clay Montier et al., 2009), it may be that mtDNAcn dynamically changes depending on stress chronicity and severity. The results of our study add to the evidence that changes in mtDNAcn may reflect allostatic adaptations to stress and be a good marker of allostatic load (Picard et al., 2014; Ridout et al., 2016; Ridout et al., 2018). Such adaptations could impart greater energetic flexibility after stress exposure, but it is unclear if such adaptations are markers of resilience or psychiatric disorder risk; further research in this area is required to clarify this distinction.

While these results suggest a shared mechanistic relationship between early life stress, neuroendocrine function, and mtDNAcn, there are limitations to our study. We do not have measures of GR cellular expression and are using NR3C1 methylation as a proxy for GR protein expression. There are many steps regulating gene expression to protein content, and intracellular regulation of GR availability for cortisol binding is tightly controlled by a number of proteins, including HSP90 and FKBP5 (Binder, 2009); it is possible that the relationships detected here reflect other intracellular processes for which NR3C1 methylation is a proxy. We examined mtDNAcn in this study, which is positively associated with mitochondrial mass and respiratory capacity in healthy tissues (D’Erchia et al., 2015), but it is unclear how variation in mtDNAcn relates to mitochondrial function in our sample. These results were obtained from whole blood, which is a heterogeneous sample, limiting our ability to determine the exact cellular determinants of the changes detected. These limitations provide suggestions for future work to confirm these results.

These data provide preliminary evidence of a mechanistic relationship between NR3C1 methylation, the exposure of early adversity, and mtDNAcn. Future studies focusing on these complex and dynamic processes in regulating the relationship between mtDNAcn, mitochondrial function, and GR are needed to elucidate the role of this pathway in psychiatric disorder risk and development. Such studies may identify new treatment targets for stress-related psychiatric disorders or provide insight to facilitate the development of interventions to prevent the onset of psychiatric disorders after adverse exposures.

Acknowledgments:

This research was supported by NIMH grants MH091508 and MH101107 (ART) and MH068767 (LLC). Dr. Ridout received support from R25 MH101076 and The Physician Researcher Program, Kaiser Permanente Northern California. Dr. Coe received support from T32 MH019927. The study sponsor had no role in this study.

This research was supported by NIMH grants MH091508 and MH101107 (ART) and MH068767 (LLC). Dr. Ridout received support from R25 MH101076. Dr. Coe received support from T32 MH019927.

Disclosures: Dr. Carpenter received clinical trial support from Janssen, Neosync, and Feelmore Labs and consulting income from Janssen and Neuronix. Dr. Price discloses grant/research support from the NIH, is on the data safety and monitoring boards for Baylor University, Cleveland Clinic, Clexio Biosciences, Worldwide Clinical Trials, is a consultant to Wiley, Springer, U Texas (Austin), and Fordham University. All other authors have nothing to disclose. All authors report no conflicts of interest.

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