History of traumatic brain injury is associated with increased grey-matter loss in patients with mild cognitive impairment.

OBJECTIVES: To investigate whether a history of traumatic brain injury (TBI) is associated with greater long-term grey-matter loss in patients with mild cognitive impairment (MCI). METHODS: 85 patients with MCI were identified, including 26 with a previous history of traumatic brain injury (MCI[TBI-]) and 59 without (MCI[TBI+]). Cortical thickness was evaluated by segmenting T1-weighted MRI scans acquired longitudinally over a 2-year period. Bayesian multilevel modelling was used to evaluate group differences in baseline cortical thickness and longitudinal change, as well as group differences in neuropsychological measures of executive function. RESULTS: At baseline, the MCI[TBI+] group had less grey matter within right entorhinal, left medial orbitofrontal and inferior temporal cortex areas bilaterally. Longitudinally, the MCI[TBI+] group also exhibited greater longitudinal declines in left rostral middle frontal, the left caudal middle frontal and left lateral orbitofrontal areas sover the span of 2 years (median = 1-2%, 90%HDI [-0.01%: -0.001%], probability of direction (PD) = 90-99%). The MCI[TBI+] group also displayed greater longitudinal declines in Trail-Making-Test (TMT)-derived ratio (median: 0.737%, 90%HDI: [0.229%: 1.31%], PD = 98.8%) and differences scores (median: 20.6%, 90%HDI: [-5.17%: 43.2%], PD = 91.7%). CONCLUSIONS: Our findings support the notion that patients with MCI and a history of TBI are at risk of accelerated neurodegeneration, displaying greatest evidence for cortical atrophy within the left middle frontal and lateral orbitofrontal frontal cortex. Importantly, these results suggest that long-term TBI-mediated atrophy is more pronounced in areas vulnerable to TBI-related mechanical injury, highlighting their potential relevance for diagnostic forms of intervention in TBI.

Neuroanatomical correlates of distracted straight driving performance: a driving simulator MRI study across the lifespan.

Background: Driving is the preferred mode of transportation for adults across the healthy age span. However, motor vehicle crashes are among the leading causes of injury and death, especially for older adults, and under distracted driving conditions. Understanding the neuroanatomical basis of driving may inform interventions that minimize crashes. This exploratory study examined the neuroanatomical correlates of undistracted and distracted simulated straight driving. Methods: One-hundred-and-thirty-eight participants (40.6% female) aged 17-85 years old (mean and SD = 58.1 ± 19.9 years) performed a simulated driving task involving straight driving and turns at intersections in a city environment using a steering wheel and foot pedals. During some straight driving segments, participants responded to auditory questions to simulate distracted driving. Anatomical T1-weighted MRI was used to quantify grey matter volume and cortical thickness for five brain regions: the middle frontal gyrus (MFG), precentral gyrus (PG), superior temporal cortex (STC), posterior parietal cortex (PPC), and cerebellum. Partial correlations controlling for age and sex were used to explore relationships between neuroanatomical measures and straight driving behavior, including speed, acceleration, lane position, heading angle, and time speeding or off-center. Effects of interest were noted at an unadjusted p-value threshold of 0.05. Results: Distracted driving was associated with changes in most measures of straight driving performance. Greater volume and cortical thickness in the PPC and cerebellum were associated with reduced variability in lane position and heading angle during distracted straight driving. Cortical thickness of the MFG, PG, PPC, and STC were associated with speed and acceleration, often in an age-dependent manner. Conclusion: Posterior regions were correlated with lane maintenance whereas anterior and posterior regions were correlated with speed and acceleration, especially during distracted driving. The regions involved and their role in straight driving may change with age, particularly during distracted driving as observed in older adults. Further studies should investigate the relationship between distracted driving and the aging brain to inform driving interventions.

Assessing past suicidal behaviour in schizophrenia spectrum disorders using the Columbia-Suicide Severity Rating Scale and the Beck Scale for Suicide Ideation: Analysis across the life-span.

Assessing the number of past suicide attempts is vital in clinical and research settings, as it is a significant variable in assessing suicide risk. This study sought to compare the accuracy of the C-SSRS and the BSS in reporting past suicide attempts in schizophrenia spectrum disorders . Six hundred participants were recruited from the Centre for Addiction and Mental Health in Toronto, and completed the BSS and C-SSRS. A medical chart review was performed to determine the number of past suicide attempts. In addition, receiver operating characteristic curves were generated to compare the accuracy of both tests under various stratifications. Based on our findings, there were no significant differences (P = 0.8977) between the BSS and CSSRS in detecting a history of past suicide attempts. The BSS exhibited a sensitivity of 0.847 and a specificity of 0.841, while the C-SSRS had a slightly lower sensitivity of 0.795 and a slightly higher specificity of 0.889. Additionally, repeating the analysis to determine the accuracy of detecting multiple past suicide attempts, the BSS demonstrated a sensitivity of 0.704 and a specificity of 0.959, whereas the C-SSRS had a sensitivity of 0.787 and a specificity of 0.927. We further contrasted the two scales, stratified by different demographic variables such as age and sex. The accuracy of both tools, which is defined as the ability to identify true positive cases while minimizing false positives, increased as age increased, but these differences were not statistically significant. Therefore, both tools show a high level of accuracy in reporting past suicide attempt history and should be utilized to fit the specific needs of the research or clinical teams. These findings can inform clinical practice and future research, highlighting the importance of selecting assessment tools that fit the population's needs and context.

Cognitive function based on theta-gamma coupling vs. clinical diagnosis in older adults with mild cognitive impairment with or without major depressive disorder.

Whether individuals with mild cognitive impairment (MCI) and a history of major depressive disorder (MDD) are at a higher risk for cognitive decline than those with MCI alone is still not clear. Previous work suggests that a reduction in prefrontal cortical theta phase-gamma amplitude coupling (TGC) is an early marker of cognitive impairment. This study aimed to determine whether using a TGC cutoff is better at separating individuals with MCI or MCI with remitted MDD (MCI+rMDD) on cognitive performance than their clinical diagnosis. Our hypothesis was that global cognition would differ more between TGC-based groups than diagnostic groups. We analyzed data from 128 MCI (mean age: 71.8, SD: 7.3) and 85 MCI+rMDD (mean age: 70.9, SD: 4.7) participants. Participants completed a comprehensive neuropsychological battery; TGC was measured during the N-back task. An optimal TGC cutoff was determined during the performance of the 2-back. This TGC cutoff was used to classify participants into low vs. high-TGC groups. We then compared Cohen's d of the difference in global cognition between the high and low TGC groups to Cohen's d between the MCI and MCI+rMDD groups. We used bootstrapping to determine 95% confidence intervals for Cohen's d values using the whole sample. As hypothesized, Cohen's d for the difference in global cognition between the TGC groups was larger (0.64 [0.32, 0.88]) than between the diagnostic groups (0.10 [0.004, 0.37]) with a difference between these two Cohen's d's of 0.54 [0.10, 0.80]. Our findings suggest that TGC is a useful marker to identify individuals at high risk for cognitive decline, beyond clinical diagnosis. This could be due to TGC being a sensitive marker of prefrontal cortical dysfunction that would lead to an accelerated cognitive decline.

Neuropsychiatric symptoms and brain morphology in patients with mild cognitive impairment, cerebrovascular disease and Parkinson disease: A cross sectional and longitudinal study.

OBJECTIVES: Neuropsychiatric symptoms (NPS) increase risk of developing dementia and are linked to various neurodegenerative conditions, including mild cognitive impairment (MCI due to Alzheimer's disease [AD]), cerebrovascular disease (CVD), and Parkinson's disease (PD). We explored the structural neural correlates of NPS cross-sectionally and longitudinally across various neurodegenerative diagnoses. METHODS: The study included individuals with MCI due to AD, (n = 74), CVD (n = 143), and PD (n = 137) at baseline, and at 2-years follow-up (MCI due to AD, n = 37, CVD n = 103, and PD n = 84). We assessed the severity of NPS using the Neuropsychiatric Inventory Questionnaire. For brain structure we included cortical thickness and subcortical volume of predefined regions of interest associated with corticolimbic and frontal-executive circuits. RESULTS: Cross-sectional analysis revealed significant negative correlations between appetite with both circuits in the MCI and CVD groups, while apathy was associated with these circuits in both the MCI and PD groups. Longitudinally, changes in apathy scores in the MCI group were negatively linked to the changes of the frontal-executive circuit. In the CVD group, changes in agitation and nighttime behavior were negatively associated with the corticolimbic and frontal-executive circuits, respectively. In the PD group, changes in disinhibition and apathy were positively associated with the corticolimbic and frontal-executive circuits, respectively. CONCLUSIONS: The observed correlations suggest that underlying pathological changes in the brain may contribute to alterations in neural activity associated with MBI. Notably, the difference between cross-sectional and longitudinal results indicates the necessity of conducting longitudinal studies for reproducible findings and drawing robust inferences.

Heterogeneity of Cognition in Older Adults with Remitted Major Depressive Disorder: A Latent Profile Analysis.

OBJECTIVES: To identify data-driven cognitive profiles in older adults with remitted major depressive disorder (rMDD) with or without mild cognitive impairment (MCI) and examine how the profiles differ regarding demographic, clinical, and neuroimaging measures. DESIGN: Secondary cross-sectional analysis using latent profile analysis. SETTING: Multisite clinical trial in Toronto, Canada. PARTICIPANTS: One hundred seventy-eight participants who met DSM-5 criteria for rMDD without MCI (rMDD-MCI; n = 60) or with MCI (rMDD + MCI; n = 118). MEASUREMENTS: Demographic, clinical, neuroimaging measures, and domain scores from a neuropsychological battery assessing verbal memory, visuospatial memory, processing speed, working memory, language, and executive function. RESULTS: We identified three latent profiles: Profile 1 (poor cognition; n = 75, 42.1%), Profile 2 (intermediate cognition; n = 75, 42.1%), and Profile 3 (normal cognition; n = 28, 15.7%). Compared to participants with Profile 3, those with Profile 1 or 2 were older, had lower education, experienced a greater burden of medical comorbidities, and were more likely to have MCI. The profiles did not differ on the severity of residual symptoms, age of onset of rMDD, number of depressive episodes, psychotropic medication, cerebrovascular risk, ApoE4 carrier status, or family history of depression, dementia, or Alzheimer's disease. The profiles differed in cortical thickness of 15 regions, with the most prominent effects for left precentral and pars opercularis, and right inferior parietal and supramarginal. CONCLUSION: Older patients with rMDD can be grouped cross-sectionally based on data-driven cognitive profiles that differ from the absence or presence of a diagnosis of MCI. Future research should determine the differential risk for dementia of these data-driven subgroups.

Age-Related Alterations in Gray Matter Microstructure in Older People With Remitted Major Depression at Risk for Dementia.

Background: Major depressive disorder (MDD) in late life is a risk factor for mild cognitive impairment (MCI) and Alzheimer's disease. However, studies of gray matter changes have produced varied estimates of which structures are implicated in MDD and dementia. Changes in gray matter volume and cortical thickness are macrostructural measures for the microstructural processes of free water accumulation and dendritic spine loss. Methods: We conducted multishell diffusion imaging to assess gray matter microstructure in 244 older adults with remitted MDD (n = 44), MCI (n = 115), remitted MDD+MCI (n = 61), or without psychiatric disorders or cognitive impairment (healthy control participants; n = 24). We estimated measures related to neurite density, orientation dispersion, and free water (isotropic volume fraction) using a biophysically plausible model (neurite orientation dispersion and density imaging). Results: Results showed that increasing age was correlated with an increase in isotropic volume fraction and a decrease in orientation dispersion index, which is consistent with neuropathology dendritic loss. In addition, this relationship between age and increased isotropic volume fraction was more disrupted in the MCI group than in the remitted MDD or healthy control groups. However, the association between age and orientation dispersion index was similar for all 3 groups. Conclusions: The findings suggest that the neurite orientation dispersion and density imaging measures could be used to identify biological risk factors for Alzheimer's disease, signifying both conventional neurodegeneration observed with MCI and dendritic loss seen in MDD.

Interaction of Alzheimer Disease and Traumatic Brain Injury on Cortical Thickness.

INTRODUCTION: Traumatic brain injury (TBI) is associated with an accelerated course of dementia, although biological relationships are incompletely understood. METHODS: The study examined 1124 participants, including 343 with Alzheimer disease (AD), 127 with AD with TBI, 266 cognitively normal adults with TBI, and 388 cognitively normal adults without TBI. Cortical thickness was quantified from T1-weighted magnetic resonance imaging data. Multiple linear regression was used to determine the interaction between AD and TBI on cortical thickness. RESULTS: Among those with AD, TBI was associated with an earlier age of AD onset but, counterintuitively, less cortical thinning in frontotemporal regions relative to non-AD controls. DISCUSSION: AD with TBI represents a distinct group from AD, likely with distinct pathologic contributions beyond gray matter loss. This finding has important implications for the diagnosis and treatment of AD in the presence of TBI and indicates that models of AD, aging, and neural loss should account for TBI history.

Reduction and prevention of agitation in persons with neurocognitive disorders: an international psychogeriatric association consensus algorithm.

OBJECTIVES: To develop an agitation reduction and prevention algorithm is intended to guide implementation of the definition of agitation developed by the International Psychogeriatric Association (IPA). DESIGN: Review of literature on treatment guidelines and recommended algorithms; algorithm development through reiterative integration of research information and expert opinion. SETTING: IPA Agitation Workgroup. PARTICIPANTS: IPA panel of international experts on agitation. INTERVENTION: Integration of available information into a comprehensive algorithm. MEASUREMENTS: None. RESULTS: The IPA Agitation Work Group recommends the Investigate, Plan, and Act (IPA) approach to agitation reduction and prevention. A thorough investigation of the behavior is followed by planning and acting with an emphasis on shared decision-making; the success of the plan is evaluated and adjusted as needed. The process is repeated until agitation is reduced to an acceptable level and prevention of recurrence is optimized. Psychosocial interventions are part of every plan and are continued throughout the process. Pharmacologic interventions are organized into panels of choices for nocturnal/circadian agitation; mild-moderate agitation or agitation with prominent mood features; moderate-severe agitation; and severe agitation with threatened harm to the patient or others. Therapeutic alternatives are presented for each panel. The occurrence of agitation in a variety of venues-home, nursing home, emergency department, hospice-and adjustments to the therapeutic approach are presented. CONCLUSIONS: The IPA definition of agitation is operationalized into an agitation management algorithm that emphasizes the integration of psychosocial and pharmacologic interventions, reiterative assessment of response to treatment, adjustment of therapeutic approaches to reflect the clinical situation, and shared decision-making.

Agitation in cognitive disorders: Progress in the International Psychogeriatric Association consensus clinical and research definition.

BACKGROUND: The International Psychogeriatric Association (IPA) published a provisional consensus definition of agitation in cognitive disorders in 2015. As proposed by the original work group, we summarize the use and validation of criteria in order to remove "provisional" from the definition. METHODS: This report summarizes information from the academic literature, research resources, clinical guidelines, expert surveys, and patient and family advocates on the experience of use of the IPA definition. The information was reviewed by a working group of topic experts to create a finalized definition. RESULTS: We present a final definition which closely resembles the provisional definition with modifications to address special circumstances. We also summarize the development of tools for diagnosis and assessment of agitation and propose strategies for dissemination and integration into precision diagnosis and agitation interventions. CONCLUSION: The IPA definition of agitation captures a common and important entity that is recognized by many stakeholders. Dissemination of the definition will permit broader detection and can advance research and best practices for care of patients with agitation.

Association of plasma biomarkers with cognition, cognitive decline, and daily function across and within neurodegenerative diseases: Results from the Ontario Neurodegenerative Disease Research Initiative.

INTRODUCTION: We investigated whether novel plasma biomarkers are associated with cognition, cognitive decline, and functional independence in activities of daily living across and within neurodegenerative diseases. METHODS: Glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), phosphorylated tau (p-tau)181 and amyloid beta (Aß)42/40 were measured using ultra-sensitive Simoa immunoassays in 44 healthy controls and 480 participants diagnosed with Alzheimer's disease/mild cognitive impairment (AD/MCI), Parkinson's disease (PD), frontotemporal dementia (FTD) spectrum disorders, or cerebrovascular disease (CVD). RESULTS: GFAP, NfL, and/or p-tau181 were elevated among all diseases compared to controls, and were broadly associated with worse baseline cognitive performance, greater cognitive decline, and/or lower functional independence. While GFAP, NfL, and p-tau181 were highly predictive across diseases, p-tau181 was more specific to the AD/MCI cohort. Sparse associations were found in the FTD and CVD cohorts and for Aß42/40 . DISCUSSION: GFAP, NfL, and p-tau181 are valuable predictors of cognition and function across common neurodegenerative diseases, and may be useful in specialized clinics and clinical trials.

Brain Age Estimation on a Dementia Cohort Using FLAIR MRI Biomarkers.

BACKGROUND AND PURPOSE: The prodromal stage of Alzheimer's disease presents an imperative intervention window. This work focuses on using brain age prediction models and biomarkers from FLAIR MR imaging to identify subjects who progress to Alzheimer's disease (converting mild cognitive impairment) or those who remain stable (stable mild cognitive impairment). MATERIALS AND METHODS: A machine learning model was trained to predict the age of normal control subjects on the basis of volume, intensity, and texture features from 3239 FLAIR MRI volumes. The brain age gap estimation (BrainAGE) was computed as the difference between the predicted and true age, and it was used as a biomarker for both cross-sectional and longitudinal analyses. Differences in biomarker means, slopes, and intercepts were investigated using ANOVA and Tukey post hoc test. Correlation analysis was performed between brain age gap estimation and established Alzheimer's disease indicators. RESULTS: The brain age prediction model showed accurate results (mean absolute error = 2.46 years) when testing on held out normal control data. The computed BrainAGE metric showed significant differences between the stable mild cognitive impairment and converting mild cognitive impairment groups in cross-sectional and longitudinal analyses, most notably showing significant differences up to 4 years before conversion to Alzheimer's disease. A significant correlation was found between BrainAGE and previously established Alzheimer's disease conversion biomarkers. CONCLUSIONS: The BrainAGE metric can allow clinicians to consider a single explainable value that summarizes all the biomarkers because it considers many dimensions of disease and can determine whether the subject has normal aging patterns or if he or she is trending into a high-risk category using a single value.

Detecting conversion from mild cognitive impairment to Alzheimer's disease using FLAIR MRI biomarkers.

Mild cognitive impairment (MCI) is the prodromal phase of Alzheimer's disease (AD) and while it presents as an imperative intervention window, it is difficult to detect which subjects convert to AD (cMCI) and which ones remain stable (sMCI). The objective of this work was to investigate fluid-attenuated inversion recovery (FLAIR) MRI biomarkers and their ability to differentiate between sMCI and cMCI subjects in cross-sectional and longitudinal data. Three types of biomarkers were investigated: volume, intensity and texture. Volume biomarkers included total brain volume, cerebrospinal fluid volume (CSF), lateral ventricular volume, white matter lesion volume, subarachnoid CSF, and grey matter (GM) and white matter (WM), all normalized to intracranial volume. The mean intensity, kurtosis, and skewness of the GM and WM made up the intensity features. Texture features quantified homogeneity and microstructural tissue changes of GM and WM regions. Composite indices were also considered, which are biomarkers that represent an aggregate sum (z-score normalization and summation) of all biomarkers. The FLAIR MRI biomarkers successfully identified high-risk subjects as significant differences (p < 0.05) were found between the means of the sMCI and cMCI groups and the rate of change over time for several individual biomarkers as well as the composite indices for both cross-sectional and longitudinal analyses. Classification accuracy and feature importance analysis showed volume biomarkers to be most predictive, however, best performance was obtained when complimenting the volume biomarkers with the intensity and texture features. Using all the biomarkers, accuracy of 86.2 % and 69.2 % was achieved for normal control-AD and sMCI-cMCI classification respectively. Survival analysis demonstrated that the majority of the biomarkers showed a noticeable impact on the AD conversion probability 4 years prior to conversion. Composite indices were the top performers for all analyses including feature importance, classification, and survival analysis. This demonstrated their ability to summarize various dimensions of disease into single-valued metrics. Significant correlation (p < 0.05) with phosphorylated-tau and amyloid-beta CSF biomarkers was found with all the FLAIR biomarkers. The proposed biomarker system is easily attained as FLAIR is routinely acquired, models are not computationally intensive and the results are explainable, thus making this pipeline easily integrated into clinical workflow.

Copy Number Variation Analysis of Aggressive Behaviour in Schizophrenia.

INTRODUCTION: An increased proclivity towards violence is often associated with those diagnosed with schizophrenia (SCZ), despite contradictory findings from prior studies exploring the association between violence and SCZ. Evidence has shown that certain comorbidities, specifically the presence of a substance use disorders, can result in increased aggression in those with SCZ. Copy number variation (CNV) load has also previously been implicated in the genetic vulnerability of individuals with SCZ. For this study, we aimed to determine whether CNV load correlates with increased violence in SCZ. METHODS: Community-dwelling patients diagnosed with SCZ spectrum disorders (n = 203) were recruited from a non-forensic population. The assessment for aggression was completed using a cross-sectional and retrospective design, and CNV analysis was conducted analysing genomic DNA using the Illumina Omni 2.5 array. RESULTS: No correlation between the number of CNV events (either deletion or duplication) and the severity of the physical violence episode index was found. However, there was a significant association between larger deletion events across the violent behaviours under investigation. DISCUSSION: These results need to be confirmed in more extensive studies using standardized tools developed for non-forensic populations, such as the Brown-Goodwin Scale of Aggression.

Perivascular spaces mediate a relationship between diabetes and other cerebral small vessel disease markers in cerebrovascular and neurodegenerative diseases.

Type 2 diabetes mellitus (T2DM) and hypertension are risk factors for cerebral small vessel disease (SVD); however, few studies have characterised their relationships with MRI-visible perivascular spaces (PVS). MRI was used to quantify deep (d) and periventricular (p) white matter hyperintensities (WMH), lacunes, PVS in the white matter (wmPVS) or basal ganglia (bgPVS), and diffusion metrics in white matter. Patients with T2DM had greater wmPVS volume and there were greater wmPVS volumes in patients with T2DM and hypertension together. Counterfactual moderated mediation models found indirect effects of T2DM on volumes of other SVD and diffusion markers that were mediated by wmPVS: pWMH, dWMH, periventricular lacunes, and deep lacunes, and progression of deep lacunes over 1 year, in patients with hypertension, but not in patients without hypertension. Studying the regulation of cortical perivascular fluid dynamics may reveal mechanisms that mediate the impact of T2DM on cerebral small vessels.

Dynamic change in genome-wide methylation in response to increased suicidal ideation in schizophrenia spectrum disorders.

Suicide is a significant public health crisis, with 800,000 people dying annually. Most people completing suicide have previous psychiatric conditions, and those with psychotic and mood disorders are particularly vulnerable. Unfortunately, there are currently no biomarkers available for accurately detecting suicidal ideation. Given the genetic and environmental factors that play a role in suicidal ideation, we attempted to determine epigenetic modifications, specifically DNA methylation, in response to changes in suicidal ideation. Using a longitudinal study design, 31 participants with schizophrenia spectrum disorders were interviewed at a baseline visit and again at a follow-up visit 3-12 months later. Current suicidal ideation was recorded at both visits with the Columbia Suicide Severity Rating Scale and the Beck Scale for Suicide Ideation, and whole blood was collected for methylation analysis. Our analysis shows a significant negative correlation between cg26910920 methylation and increasing Columbia Suicide Severity Rating Scale scores and a positive correlation between cg13673029 methylation and increasing Beck Scale for Suicide Ideation scores. This pilot study indicates that there is  the possibility  that DNA methylation can respond to changes in suicidal ideation over time and potentially be used as a biomarker of suicidal ideation in the future.

Beta to theta power ratio in EEG periodic components as a potential biomarker in mild cognitive impairment and Alzheimer's dementia.

BACKGROUND: Alzheimer's dementia (AD) is associated with electroencephalography (EEG) abnormalities including in the power ratio of beta to theta frequencies. EEG studies in mild cognitive impairment (MCI) have been less consistent in identifying such abnormalities. One potential reason is not excluding the EEG aperiodic components, which are less associated with cognition than the periodic components. Here, we investigate whether aperiodic and periodic EEG components are disrupted differently in AD or MCI vs. healthy control (HC) individuals and whether a periodic based beta/theta ratio differentiates better MCI from AD and HC groups than a ratio based on the full spectrum. METHODS: Data were collected from 44 HC (mean age (SD) = 69.1 (5.3)), 114 MCI (mean age (SD) = 72.2 (7.5)), and 41 AD (mean age (SD) = 75.7 (6.5)) participants. Aperiodic and periodic components and full spectrum EEG were compared among the three groups. Receiver operating characteristic curves obtained via logistic regression classifications were used to distinguish the groups. Last, we explored the relationships between cognitive performance and the beta/theta ratios based on the full or periodic spectrum. RESULTS: Aperiodic EEG components did not differ among the three groups. In contrast, AD participants showed an increase in full spectrum and periodic relative powers for delta, theta, and gamma and a decrease for beta when compared to HC or MCI participants. As predicted, MCI group differed from HC participants on the periodic based beta/theta ratio (Bonferroni corrected p-value = 0.036) measured over the occipital region. Classifiers based on beta/theta power ratio in EEG periodic components distinguished AD from HC and MCI participants, and outperformed classifiers based on beta/theta power ratio in full spectrum EEG. Beta/theta ratios were comparable in their association with cognition. CONCLUSIONS: In contrast to a full spectrum EEG analysis, a periodic-based analysis shows that MCI individuals are different on beta/theta ratio when compared to healthy individuals. Focusing on periodic components in EEG studies with or without other biological markers of neurodegenerative diseases could result in more reliable findings to separate MCI from healthy aging, which would be valuable for designing preventative interventions.

Relationships between neuropsychiatric symptoms and cognitive profiles in Alzheimer's disease and related syndromes.

OBJECTIVES: To investigate the rate of occurrence of neuropsychiatric symptoms (NPS) and their relationship with age, sex and cognitive performance in subjects with Alzheimer's disease and related dementias (Alzheimer's disease and related dementias [ADRD]). METHODS: This is a retrospective matched case-control study. Data from memory clinic patients included demographic information presence of NPS, and cognitive testing of Orientation, Immediate and Delayed Memory, Visuospatial Function, Working Memory, Attention, Executive Control and Language. Participants were Individuals with subjective cognitive impairment (n = 352), mild cognitive impairment (MCI) (n = 369), vascular MCI (n = 80), Alzheimer's disease (n = 147), vascular dementia (n = 41), mixed dementia (n = 33), and healthy controls (n = 305). Logistic regression was used to investigate the relationship between the presence of NPS, age and sex. A generalised additive model was used to investigate the relationship between presence of NPS, age and cognitive impairment. Analysis of variance was used to investigate differences in cognition between younger and older groups with and without NPS. RESULTS: We found an increased likelihood of occurrence of NPS in younger individuals and females across cohorts. Anxiety, depression, agitation, and apathy were associated with higher overall rate of NPS. We also found that individuals under 65 years of age with NPS had worse cognitive scores than their counterpart without NPS. CONCLUSION: The younger group with ADRD and NPS had lower cognitive scores, probably reflecting more aggressive neurodegenerative disease. Further work will be needed to elicit the degree to which imaging or mechanistic abnormalities distinguish this group.

GWAS of biological aging to find longevity genes in schizophrenia.

Schizophrenia (SCZ) is a severe psychotic disorder associated with premature mortality and aging. Moreover, the symptoms and progression of psychiatric disorders in general are associated with decreased lifespan, biological aging, and poorer medical outcomes. In this study, we investigated the relationship between several epigenetic clocks and scanned the entire genome for association in a cohort of SCZ individuals (n = 107). Biological age was computed from blood DNA methylation (DNAm) and tested for association against  common  variants across the genome using general linear models. Genes affecting epigenetic age acceleration in our cohort were found mainly when using the telomeric length clock rather than the other biological clocks. These findings pair with existing evidence that there are some genes associated with longevity and suggest further investigations of  putative biological mechanisms for morbidity and premature mortality, not only in patients with SCZ but also in the general population.

Rare neurovascular genetic and imaging markers across neurodegenerative diseases.

INTRODUCTION: Cerebral small vessel disease (SVD) is common in patients with cognitive impairment and neurodegenerative diseases such as Alzheimer's and Parkinson's. This study investigated the burden of magnetic resonance imaging (MRI)-based markers of SVD in patients with neurodegenerative diseases as a function of rare genetic variant carrier status. METHODS: The Ontario Neurodegenerative Disease Research Initiative study included 520 participants, recruited from 14 tertiary care centers, diagnosed with various neurodegenerative diseases and determined the carrier status of rare non-synonymous variants in five genes (ABCC6, COL4A1/COL4A2, NOTCH3/HTRA1). RESULTS: NOTCH3/HTRA1 were found to significantly influence SVD neuroimaging outcomes; however, the mechanisms by which these variants contribute to disease progression or worsen clinical correlates are not yet understood. DISCUSSION: Further studies are needed to develop genetic and imaging neurovascular markers to enhance our understanding of their potential contribution to neurodegenerative diseases.