McLean Hospital

Opioid dependence is defined by an aversive withdrawal syndrome upon drug cessation that can motivate continued drug-taking, development of opioid use disorder, and precipitate relapse. An understudied but common opioid withdrawal symptom is disrupted sleep, reported as both insomnia and daytime sleepiness. Despite the prevalence and severity of sleep disturbances during opioid withdrawal, there is a gap in our understanding of their interactions. The goal of this study was to establish an in-depth, temporal signature of spontaneous oxycodone withdrawal effects on the diurnal composition of discrete sleep stages and the dynamic spectral properties of the electroencephalogram (EEG) signal in male rats. We continuously recorded EEG and electromyography (EMG) signals for 8 d of spontaneous withdrawal after a 14-d escalating-dose oxycodone regimen (0.5–8.0 mg/kg, 2×d; SC). During withdrawal, there was a profound loss (peaking on days 2–3) and gradual return of diurnal structure in sleep, body temperature, and locomotor activity, as well as decreased sleep and wake bout durations dependent on lights on/off. Withdrawal was associated with significant alterations in the slope of the aperiodic 1/f component of the EEG power spectrum, an established biomarker of arousal level. Early in withdrawal, NREM exhibited an acute flattening and return to baseline of both low (1–4 Hz) and high (15–50 Hz) frequency components of the 1/f spectrum. These findings suggest temporally dependent withdrawal effects on sleep, reflecting the complex way in which the allostatic forces of opioid withdrawal impinge upon sleep and diurnal processes. These foundational data based on continuous tracking of vigilance state, sleep stage composition, and spectral EEG properties provide a detailed construct with which to form and test hypotheses on the mechanisms of opioid-sleep interactions.

Childhood cognitively stimulating activities have been associated with higher cognitive function in late life. Whether activities in early or late childhood are more salient, and whether activities are associated with specific cognitive domains is unknown. Participants retrospectively reported cognitively stimulating activities at ages 6, 12, and 18 years. 4,198 participants were aged 55 to 77 years at cognitive testing. Six tasks measured overall cognitive function, processing speed, visual short-term memory, attention, cognitive control, episodic memory, working memory, perception, vocabulary, and verbal reasoning. Cognitively stimulating activities across childhood were associated with higher cognitive scores (highest versus lowest quartile, beta = 0.18 SD, 95% CI = 0.12, 0.23). In models adjusted for activities at each age, only age 18 activities were associated with overall cognition. The association of activities with cognitive function was strongly positive at the lowest levels of activities, with little association at middle and high levels of activities. A test of crystalized intelligence was most strongly associated with activities; tests assessing processing speed, visual short-term memory, visual working memory, and sustained attention were least associated. If the associations we found are causal, increasing cognitively stimulating activities in the late teen years among those with very few activities may benefit late life cognitive health. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-024-79083-x.

In graph theory, “multilayer networks” represent systems involving several interconnected topological levels. One example in neuroscience is the stratification of connections between different cortical depths or “laminae”, which is becoming non-invasively accessible in humans using ultra-high-resolution functional MRI (fMRI). Here, we applied multilayer graph theory to examine functional connectivity across different cortical depths in humans, using 7T fMRI (1-mm³ voxels; 30 participants). Blood oxygenation level dependent (BOLD) signals were derived from five depths between the white matter and pial surface. We compared networks where the inter-regional connections were limited to a single cortical depth only (“layer-by-layer matrices”) to those considering all possible connections between areas and cortical depths (“multilayer matrix”). We utilized global and local graph theory features that quantitatively characterize network attributes including network composition, nodal centrality, path-based measures, and hub segregation. Detecting functional differences between cortical depths was improved using multilayer connectomics compared to the layer-by-layer versions. Superficial depths of the cortex dominated information transfer and deeper depths drove clustering. These differences were largest in frontotemporal and limbic regions. fMRI functional connectivity across different cortical depths may contain neurophysiologically relevant information; thus, multilayer connectomics could provide a methodological framework for studies on how information flows across this stratification.

Background Electroconvulsive therapy (ECT) is a safe and effective treatment for several major psychiatric conditions, including treatment-resistant depression, mania, and schizophrenia; nevertheless, its use remains controversial. Despite its availability in some European countries, ECT is still rarely used in others. This study aims to investigate the experiences and attitudes of early career psychiatrists (ECPs) across Europe towards ECT and to examine how their exposure to ECT influences their perceptions. Methods In Europe, a cross-sectional survey was conducted among ECPs, including psychiatric trainees and recently fully qualified psychiatrists. Results A total of 573 participants from 30 European countries were included in the study, of whom more than half ( N = 312; 54.5%) received ECT training. Overall, ECPs had a positive attitude towards ECT, with the vast majority agreeing or strongly agreeing that ECT is an effective ( N = 509; 88.8%) and safe ( N = 464; 81.0%) treatment and disagreeing or strongly disagreeing that ECT was used as a form of control or punishment ( N = 545; 95.1%). Those who had received ECT training during their psychiatry training were more likely to recommend ECT to their patients (p < 0.001, r = 0.34), and held more positive views on its safety (p < 0.001, r = 0.31) and effectiveness (p < 0.001, r = 0.33). Interest in further education about ECT was moderately high (modal rating on Likert scale: 4, agree), irrespective of prior training exposure. Conclusions ECT training is associated with more favorable perceptions of its safety and effectiveness among ECPs. There is a general willingness among ECPs to expand their knowledge and training on ECT, which could enhance patients’ access to this treatment.

Past research exploring gender differences in relation to emotion dysregulation has shown mixed results. This study explores the extent to which gender differences in emotion dysregulation exist among adolescents in residential or partial hospital treatment settings after controlling for known variables that have demonstrated significant gender differences and have been linked to emotion dysregulation. Participants were 412 adolescents at admission to residential or partial hospitalisation DBT treatment. Participants self-identified their gender as: 28% (n = 116) cisgender male, 50% (n = 206) cisgender female, and 22% (n = 90) transgender and gender diverse (TGD). One-way ANOVA indicated TGD individuals and cisgender females scored significantly higher on emotion dysregulation than cisgender males. Hierarchical regression results indicated that gender overall explained only an additional 1.6% of the variance in emotion dysregulation after controlling for interpersonal competence, psychological distress, and interpersonal needs. Present findings underscore the importance of considering a range of psychosocial factors and pathways that may contribute to emotion dysregulation, and how gender groups may be differentially impacted.

Xenon gas is considered to be a safe anesthetic and imaging agent. Research on its other potentially beneficial effects suggests that xenon may have broad efficacy for treating health disorders. A number of reviews on xenon applications have been published, but none have focused on substance use disorders. Accordingly, we review xenon effects and targets relevant to the treatment of substance use disorders, with a focus on opioid use disorder and alcohol use disorder. We report that xenon inhaled at subsedative concentrations inhibits conditioned memory reconsolidation and opioid withdrawal symptoms. We review work by others reporting on the antidepressant, anxiolytic, and analgesic properties of xenon, which could diminish negative affective states and pain. We discuss research supporting the possibility that xenon could prevent analgesic- or stress-induced opioid tolerance and, by so doing could reduce the risk of developing opioid use disorder. The rapid kinetics, favorable safety and side effect profiles, and multitargeting capability of xenon suggest that it could be used as an ambulatory on-demand treatment to rapidly attenuate maladaptive memory, physical and affective withdrawal symptoms, and pain drivers of substance use disorders when they occur. Xenon may also have human immunodeficiency virus and oncology applications because its effects relevant to substance use disorders could be exploited to target human immunodeficiency virus reservoirs, human immunodeficiency virus protein-induced abnormalities, and cancers. Although xenon is expensive, low concentrations exert beneficial effects, and gas separation, recovery, and recycling advancements will lower xenon costs, increasing the economic feasibility of its therapeutic use. More research is needed to better understand the remarkable repertoire of effects of xenon and its potential therapeutic applications.

Background Effect and Safety of Electroconvulsive Therapy plus Usual Care for the Acute Management of Severe Agitation in Dementia (ECT‐AD) is a multi‐site NIA‐funded FDA‐regulated pioneering clinical trial to investigate the effectiveness of electroconvulsive therapy (ECT) in treating severe and treatment‐refractory agitation and aggression among individuals with advanced dementia, a condition that has a profound negative impact on patient quality of life and caregiver burden. Here we present baseline demographics of the patient population in this ongoing trial. Method To date we have enrolled 18 participants, with a mean age of 74.1 years, where majority are male (61.1%). The racial composition is predominantly White (94.4%), with Asian representation (5.6%, 1/18), and with 11.1% (2/18) identifying as Hispanic or Latino. Dementia subtypes in our cohort include Alzheimer’s disease (AD, 77.8%), vascular dementia (VaD, 16.7%, 3/18), and frontotemporal dementia (FTD, 5.6%, 1/18). Result Baseline assessments reveal severe cognitive and functional impairment, as indicated by a mean Mini‐Mental State Examination (MMSE) score of 4.0, Barthel Index (BI) score of 52.2, and SIB‐8 score of 2.9, all consistent with advanced stages of dementia. High mean total scores on the Cohen‐Mansfield Agitation Inventory (CMAI, 75.8), Neuropsychiatric Inventory (NPI) agitation (15.1) and aggression (9.2) scales, and Pittsburgh Agitation Scale (PAS, 7.8), reflect the severe levels of agitation and aggression in our participants. Conclusion These baseline demographic and clinical data underscore the profound impact of advanced dementia, highlighting the need for innovative treatment approaches like ECT. The ECT‐AD trial offers a critical step towards understanding and improving the management of agitation in dementia, with implications that could enhance current clinical care practices.

Background Amyloid, Tau and neurodegeneration (ATN), the hallmark pathologies of Alzheimer’s Disease (AD) translating to measurable biomarkers are important for disease modifying therapeutics. Method AD Digital‐Twins were built using AITIA’s patented A.I. platform REFSTM [aitiabio.com], based on a Bayesian network model of ADNI data which reverse‐engineered the connectivity of ∼59K multi‐modal variables and AD‐related outcomes profiled from 317 subjects (Control: MCI: Dementia=97:191:29). The average causal effect of each upstream‐downstream variables was estimated through in‐silico counterfactual experiments to evaluate the temporal relationship between the ATN outcomes, to identify the causal gene‐drivers (at blood RNA‐expression level) of “ATN” outcomes, and to investigate the known AD genotypic variants strongly driving ATN gene‐drivers. Age‐gene interaction was additionally explored through “double‐intervention” experiments, to evaluate age‐specific effects of gene‐drivers on ATN outcomes. Result AD Digital‐Twins evaluated the ATN temporal relationship, and recapitulated some known relationships such that CSF‐abeta and Tau measures drive neurodegeneration measures, although it also showed CSF‐Tau measures to be upstream of amyloid PET, suggesting Tau changes may interact with other outcome changes more dynamically over the course of disease progression (Figure 1). Next, in‐silico experiments identified a total of 228 ATN gene‐drivers, including 8 common to all outcome‐categories, which affect cognitive outcomes as well (Figure 2) and are strongly related to immune‐response and inflammation pathways. Many of these genes were causally driven by multiple AD‐associated genotypic variants reported in GWAS, especially in the “NECTIN2” and “APOE” region. Furthermore, in‐silico experiments showed some Tau‐driving genes are likely to be causally driven by Amyloid and Neurodegeneration driving genes. Lastly, age‐specific effects were observed for a portion of each A‐, T‐ and N‐ gene‐drivers, especially with Tau‐driving genes having a stronger effect with opposite directionality for younger vs older age groups (Figure 3). Conclusion Tau related abnormalities are likely early events in AD progression and more strongly linked to disease pathophysiology. Aitia’s AI platform allows powerful and systematic evaluation of multiple modalities and outcomes, accelerating precision medicine efforts in AD.

Background Cognitive dysfunction is more common in individuals with type 1 diabetes (T1D) compared to the general population. Blood‐based biomarkers are accurate in identifying early signs of neurodegeneration. However, studies using these biomarkers in T1D are lacking. We examined the associations of plasma biomarkers and diabetes characteristics in adults with T1D. Methods This study included 114 adults with T1D from the Glycemic Variability and Fluctuations in Cognitive Status in Adults With Type 1 Diabetes (GluCog) study. Plasma biomarkers were: ratio of amyloid‐β (Aβ) 42/40, neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), phosphorylated Tau181 (pTau181) using Quanterix assays, and phosphorylated Tau 217 (pTau217) using ALZpath. The coefficient of variation (%) from continuous glucose monitor readings was used to define glycemic variability (GV). Relationships between biomarkers, demographics, and diabetes characteristics were evaluated using Spearman rank correlation, Mann‐Whitney U, and Kruskal‐Wallis tests, as appropriate. Linear regression models were used to examine the associations between plasma biomarkers (dependent variable) and diabetes characteristics (that were significant in bivariate analyses) as predictors in separate models adjusted for sex, age, and education. We added the adjustment for nephropathy in models in which the biomarker was associated with this variable. Results The sample [53% female, mean(SD) age of T1D diagnosis 20.3(12.7) years, 37% with hypertension, 11% with neuropathy, 8% with nephropathy)] had a baseline age of 49.0(14.5) years, HbA1c 7.6%(1.3), GV 36.6%(7.3). Adjusted linear regression models revealed significant associations with four biomarkers. Presence of nephropathy was associated with higher concentrations of NfL, pTau181, and pTau217 and was included in the models with these biomarkers. A lower Aβ42/40 ratio was associated with older age at diagnosis. A higher concentration of NfL was associated with higher HbA1c. A higher concentration of pTau181 was associated with higher GV. Lastly, higher pTau217 was associated with neuropathy. GFAP was not associated with any of the diabetes measures. Conclusion These data show that plasma biomarkers of neurodegeneration are associated with key diabetes characteristics in adults with T1D, particularly HbA1c, GV, neuropathy, and nephropathy. Further research is needed to understand whether T1D characteristics mediate biomarker associations with cognitive decline.

Background and Hypothesis Among individuals living with psychotic disorders, social impairment is common, debilitating, and challenging to treat. While the roots of this impairment are undoubtedly complex, converging lines of evidence suggest that social motivation and pleasure (MAP) deficits play a central role. Yet most neuroimaging studies have focused on monetary rewards, precluding decisive inferences. Study Design Here we leveraged parallel social and monetary incentive delay functional magnetic resonance imaging paradigms to test whether blunted reactivity to social incentives in the ventral striatum—a key component of the distributed neural circuit mediating appetitive motivation and hedonic pleasure—is associated with more severe MAP symptoms in a transdiagnostic adult sample enriched for psychosis. To maximize ecological validity and translational relevance, we capitalized on naturalistic audiovisual clips of an established social partner expressing positive feedback. Study Results Although both paradigms robustly engaged the ventral striatum, only reactivity to social incentives was associated with clinician-rated MAP deficits. This association remained significant when controlling for other symptoms, binary diagnostic status, or striatal reactivity to monetary incentives. Follow-up analyses suggested that this association predominantly reflects diminished activation during the presentation of social reward. Conclusions These observations provide a neurobiologically grounded framework for conceptualizing the social-anhedonia symptoms and social impairments that characterize many individuals living with psychotic disorders and underscore the need to develop targeted intervention strategies.

Background Highly specific ATN plasma biomarker assays for neurodegenerative diseases have been developed, but their associations with cognition vary in different populations. Kidney disease, common in diabetes, may decrease the predictive precision of those biomarkers. The aim of this study was to characterize for the first time the relationships between plasma ATN biomarkers and cognitive function in adults with T1D. Method Adults with T1D mean age 49 years (range 19‐84), 53% female, mean HbA1c 7.6% who participated in the Glycemic Variability and Fluctuations in Cognitive Status in Adults with T1D study and had plasma β‐amyloid42/40, p‐tau181, neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) levels measured using Quanterix, and p‐tau217 using AlzPath assays, were included (N=114). Self‐administered online cognitive tests (TestMyBrain.org) were used: Digit Symbol Matching (processing speed), Gradual Onset Continuous Performance (cognitive control, attention), Multiple Object Tracking (visual working memory); Vocabulary (verbal reasoning), Matrix (non‐verbal reasoning), Simple Reaction Time (psychomotor speed), Letter‐Number Switching (cognitive flexibility), Visual Paired Associates (visual memory), Flicker (working memory), and Paced Serial Addition Test (PSAT, working memory, attention). Bivariate correlation analyses between cognitive function and biomarkers were performed. Significant correlations after false discovery rate were re‐analyzed using linear multiple regression with biomarker assigned as outcome and cognitive function as predictors in separate models, adjusting for age, sex and education. Result All biomarkers were correlated with cognitive function in bivariate analysis. Multivariate analyses revealed that higher concentrations of ptau181 and GFAP were associated with longer reaction time for correct responses, PSAT (β=0.002, p =0.011 and β=0.057, p =0.012, respectively), and higher β‐amyloid42/40 concentration was associated with better vocabulary performance (β=0.028, p =0.009). Associations remained significant after including kidney‐related disease or other diabetes features as adjustments. Conclusion PTau181, GFAP and β‐amyloid42/40 were associated with cognitive performance in adults with T1D. Working memory speed was related to ptau181 and GFAP, suggesting it may be an early indicator of neurodegeneration in this population. The positive association between β‐amyloid42/40 and Vocabulary, a measure of crystalized cognitive ability, suggests protective mechanisms related to cognitive reserve. Investigation on ATN biomarkers and longitudinal cognitive decline is crucial for disentangling their role in T1D.

Post-traumatic stress and major depressive disorders are associated with “overgeneral” autobiographical memory, or impaired recall of specific life events. Interpersonal trauma exposure, a risk factor for both conditions, may influence how symptomatic trauma-exposed (TE) individuals segment everyday events. The ability to parse experience into units (event segmentation) supports memory. Neural state transitions occur within a cortical hierarchy and play a key role in event segmentation, with regions like the occipital cortex, angular gyrus, and striatum involved in parsing event structure. We examined whether interpersonal trauma exposure was associated with alterations in the cortical hierarchy and striatal activity at neural state transitions in symptomatic TE versus healthy control (HC) individuals. Fifty older adolescents and young adults (29 TE, 21 HC) viewed the film “Partly Cloudy” during functional magnetic resonance imaging. A greedy-state boundary search algorithm assessed the optimal number of events, quality, and segmentation agreement of neural state transitions in the occipital cortex and angular gyrus. Striatal (nucleus accumbens, caudate, and putamen) activity was assessed at occipital and angular gyrus-evoked state transitions. Compared to HCs, TE participants displayed less occipital and greater angular gyrus-evoked optimal number of neural state transitions. TE participants also displayed lower quality of neural state segmentation solutions in occipital and angular cortices compared to HCs. Additionally, TE participants had less putamen activity at angular gyrus-evoked state transitions than HCs. This investigation provides neurobiological insights into aberrant event segmentation in symptomatic TE individuals, shedding light on mechanisms influencing overgeneral memory in trauma-related disorders.

Objective: Clients with relational trauma often face challenges in forming a therapeutic alliance, a primary predictor of psychotherapy outcomes. Unresolved traumatic stress can lead to a passive stance in therapy, manifested as a tendency to seek advice and approval from therapists in order to establish more predictable relational dynamics. This comes at the cost of adequately addressing their own therapeutic needs, which often leads to stagnation, treatment dropout, and frustration with the therapist. We postulated that neither relational nor nonrelational traumas could fully account for passive and maladaptive therapy role expectations, such as advice- and approval-seeking. Instead, we hypothesized that lingering effects of trauma, evident in trauma-related pathologies like dissociation, somatization, and borderline personality disorder, contribute more significantly to the tendency to adopt a passive interpersonal stance that can impede therapeutic progress. Method: Using a sample of 259 community mental health service users, we examined the link between histories of relational trauma (both in childhood and adulthood), trauma-related pathologies, and role expectations in the psychotherapeutic interaction. Results: Bivariate correlations revealed that history of relational trauma correlated with relationship-seeking expectation—an active way of approaching therapy. However, trauma-related pathologies were invariably related to maladaptive and passive role expectations. In subsequent hierarchical regressions, when multiple factors were entered into the model, dissociation emerged as the key factor that explains maladaptive role expectations. Conclusions: These findings suggest the importance of establishing clear role expectations and ensuring alignment with clients at the outset of therapy, particularly when indications of trauma-related pathologies are present.

Metabolic dysfunction has been long associated with severe mental illness (SMI), often viewed as a comorbidity to be managed. However, emerging evidence suggests that metabolic dysfunction, particularly at the mitochondrial level, may be a foundational element in the pathophysiology of neuropsychiatric disorders. This commentary expands on the current understanding by exploring the brain energy theory of mental illness, which posits that mitochondrial dysfunction is central to both metabolic and psychiatric conditions. The roles of insulin resistance, chronic stress and environmental factors are highlighted as shared biopsychosocial determinants that contribute to deterioration in both metabolic and mental health. The therapeutic potential of the ketogenic diet is discussed, particularly its ability to improve mitochondrial function and alleviate psychiatric symptoms. This shift in perspective, from viewing metabolic dysfunction as a secondary concern to recognising it as a root cause of SMI, has significant implications for clinical practice and research. By focusing on bioenergetic deficits and mitochondrial health, psychiatry may advance towards more effective, integrated treatment approaches that target the underlying cellular dysfunctions driving both metabolic and mental illnesses.

The relationship between cannabis use and mental health is complex, as studies often report seemingly contradictory findings regarding whether cannabis use results in more positive or negative treatment outcomes. With an increasing number of individuals using cannabis for both recreational (i.e., non-medical) and medical purposes, it is critical to gain a deeper understanding of the ways in which cannabis may be helpful or harmful for those diagnosed with psychiatric disorders. Although cannabis is composed of hundreds of compounds, studies assessing the effects of “cannabis” most often report the impact of delta-9-tetrahydrocannabinol (d9-THC), the primary intoxicating constituent of the plant. While d9-THC has documented therapeutic properties, negative clinical outcomes commonly associated with cannabis are generally related to d9-THC exposure. In contrast, non-intoxicating cannabinoids such as cannabidiol (CBD) show promise as potential treatment options for psychiatric symptoms. In this article, findings from studies and reviews examining the relationship between mental health conditions (mood, anxiety, psychosis, and post-traumatic stress disorder [PTSD]) and cannabis use are summarized to highlight critical variables that are often overlooked, including those associated with cannabis use patterns (e.g., frequency of use, amount used, cannabinoid exposure, product choice, and route of administration). Further, this article explores individual factors (e.g., age, sex, genetics/family history) that likely impact cannabis-related outcomes. Research to date suggests that youth and those with a family history or genetic liability for psychiatric disorders are at higher risk for negative outcomes, while more research is needed to fully understand unique effects related to sex and older age.

There is growing recognition of the importance of changes in behavior as an early clinical marker of the onset of Alzheimer’s disease. Behavior symptoms may precede the onset of cognitive symptoms by as many as three years. However, these symptoms are often confused for primary psychiatric pathology and there is an urgent need for markers that can help quantify behaviors with the eventual goal of helping distinguish behavior changes related to psychiatric pathology from behavior changes related to the onset of dementia. This talk will summarize the state of knowledge on mild behavioral impairment, and present data from three studies demonstrating how a range of sensor‐derived biomarkers can quantify subtle changes in behavior with precision. The talk will include case presentations around detection of apathy, agitation, pacing. It will also demonstrate how these markers can identify response to medications, which may be one way of distinguishing the presence of psychiatric versus neurodegenerative pathology. Finally, the talk will present data from ongoing clinical trials around how these biomarkers may translate into research and eventually practice.

Background Alzheimer’s disease (AD) is a progressive neurodegenerative disease and the most prevalent type of senile dementia affecting more than 6 million Americans in 2023. Most of these AD cases are sporadic or late‐onset AD with unclear etiology. Recent clinical trials on antibody drug clearing Ab plagues in brain show modest benefits of slowing down cognitive decline. This indicates that a deeper and more comprehensive understanding of AD mechanism is needed for better therapeutic developments. Method Using Aitia’s proprietary REFSTM platform, Bayesian network models were built on clinical, demographic, and multi‐omic data from 287 postmortem brain samples of ROSMAP project. In silico perturbations were performed to assess causal effects among the variables. Hierarchical clustering was conducted to identify RNA‐ and protein‐ modules and to summarize a module‐level causal network, where a module‐level causal effect was computed as summated causal effects normalized to module sizes. For each module, gene ontology (GO) terms were annotated using Metascape. Result A total of 119 RNA‐ and 33 protein‐ modules were identified, of which 22 RNA‐ and 8 protein‐ modules were enriched with top genes driving AD outcomes identified through in silico perturbations. These modules were significantly over‐presented with various GO terms. Notably, three out of eight protein‐ modules are strongly related to mitochondria functions. Moreover, three pairs of RNA‐ and protein‐ modules identified for their similar enrichment patterns are related to synaptic signaling & neuron development, mitochondria translation, and complex I assembly. The module‐level causal network highlighted that the paths from AD risk factors (e.g. age, sex, APOE4) to AD outcomes (e.g. MMSE, Braak, Cerad) were strongly connected through three protein modules annotated for mitochondria function and three RNA modules annotated for nervous system development, while the paths to the cognitive outcome only (e.g. MMSE) included two immune response related and one cytoskeleton related modules as well. Conclusion Clustering analysis based on in silico causal relationships of clinical and multi‐omic data revealed a strong connection of genes involved in mitochondria functions with cognition and AD pathology, reminiscing “mitochondria cascade hypothesis” of AD first proposed two decades ago.

Background Latinos represent the fastest‐growing subpopulation of U.S. older adults and are 1.5 times more likely than non‐Latino Whites to be diagnosed with Alzheimer’s disease and related dementias. Mild Behavioral Impairment (MBI) describes emergence of new neuropsychiatric symptoms in individuals over 50, and is associated with late‐life depression, cognitive decline, and dementia. Despite its clinical relevance, the relationship between MBI and dementia risk is poorly understood in diverse populations. Here, we assessed MBI symptoms in older, community‐dwelling Latinos and examined the relationship of these symptoms to objective and subjective cognition. Method 53 participants from the Boston Latino Aging Study were included, ages 55 years and older, 71% female, mean age 64.13 ± 6.79 years, mean education 12.30 ± 5.12 years, 49 cognitively unimpaired, and 4 with mild cognitive impairment. Objective cognition was measured using the Preclinical Alzheimer’s Cognitive Composite‐5 (PACC5). Neuropsychiatric symptoms were measured with the Mild Behavioral Impairment Checklist (MBI‐C; self‐report) domains of interest motivation and drive (IMD) and mood anxiety (MA). Subjective cognitive decline was assessed with the Cognitive Function Instrument (CFI; self‐report). Associations among MBI‐C domains, CFI, and cognition were examined using Spearman’s correlation, controlling for age, sex, and education. Result Mean total MBI‐C IMD domain score was 2.37 ± 3.59, mean total MBI‐C MA domain score was 2.45 ± 3.79 and mean total CFI score was 3.60 ± 3.51. Higher scores on the MBI‐C IMD were associated with higher CFI (r = .606, p < .001) and lower PACC scores (r = ‐.333, p = .015). Higher scores on the MBI‐C MA were associated with higher CFI (r = .384, p = .005). There were no other significant associations. Conclusion Community dwelling older Latinos endorsed MBI symptoms of IMD and MA captured using the MBI‐checklist self‐report. MBI IMD symptoms were associated with greater subjective decline and worse objective cognition. Findings underscore the need for screening and management of neuropsychiatric symptomatology in Latino/a/e/x adults, and that such symptoms can be captured using the MBI‐checklist. Future longitudinal studies with larger samples are needed to further understand cognitive effects of neuropsychiatric functioning in Latino/a/e/x and other minoritized groups.