Different heart rate variability profile during sleep in mid-later life adults with remitted early-onset versus late-onset depression.

BACKGROUND: In mid-later life adults, early-onset and late-onset (i.e., onset ≥50 years) depression appear to be underpinned by different pathophysiology yet have not been examined in relation to autonomic function. Sleep provides an opportunity to examine the autonomic nervous system as the physiology changes across the night. Hence, we aimed to explore if autonomic profile is altered in mid-later life adults with remitted early-onset, late-onset and no history of lifetime depression. METHODS: Participants aged 50-90 years (n = 188) from a specialised clinic underwent a comprehensive clinical assessment and completed an overnight polysomnography study. General Linear Models were used to examine the heart rate variability differences among the three groups for four distinct sleep stages and the wake after sleep onset. All analyses controlled for potential confounders - age, sex, current depressive symptoms and antidepressant usage. RESULTS: For the wake after sleep onset, mid-later life adults with remitted early-onset depression had reduced standard deviation of Normal to Normal intervals (SDNN; p = .014, d = -0.64) and Shannon Entropy (p = .004, d = -0.46,) than those with no history of lifetime depression. Further, the late-onset group showed a reduction in high-frequency heart rate variability (HFn.u.) during non-rapid eye movement sleep stage 2 (N2; p = .005, d = -0.53) and non-rapid eye movement sleep stage 3 (N3; p = .009, d = -0.55) when compared to those with no lifetime history. LIMITATIONS: Causality between heart rate variability and depression cannot be derived in this cross-sectional study. Longitudinal studies are needed to examine the effects remitted depressive episodes on autonomic function. CONCLUSION: The findings suggest differential autonomic profile for remitted early-onset and late-onset mid-later life adults during sleep stages and wake periods. The differences could potentially serve as peripheral biomarkers in conjunction with more disease-specific markers of depression to improve diagnosis and prognosis.

Sleep spindle architecture associated with distinct clinical phenotypes in older adults at risk for dementia.

Sleep spindles are a hallmark of non-REM sleep and play a fundamental role in memory consolidation. Alterations in these spindles are emerging as sensitive biomarkers for neurodegenerative diseases of ageing. Understanding the clinical presentations associated with spindle alterations may help to elucidate the functional role of these distinct electroencephalographic oscillations and the pathophysiology of sleep and neurodegenerative disorders. Here, we use a data-driven approach to examine the sleep, memory and default mode network connectivity phenotypes associated with sleep spindle architecture in older adults (mean age = 66 years). Participants were recruited from a specialist clinic for early diagnosis and intervention for cognitive decline, with a proportion showing mild cognitive deficits on neuropsychological testing. In a sample of 88 people who underwent memory assessment, overnight polysomnography and resting-state fMRI, a k-means cluster analysis was applied to spindle measures of interest: fast spindle density, spindle duration and spindle amplitude. This resulted in three clusters, characterised by preserved spindle architecture with higher fast spindle density and longer spindle duration (Cluster 1), and alterations in spindle architecture (Clusters 2 and 3). These clusters were further characterised by reduced memory (Clusters 2 and 3) and nocturnal hypoxemia, associated with sleep apnea (Cluster 3). Resting-state fMRI analysis confirmed that default mode connectivity was related to spindle architecture, although directionality of this relationship differed across the cluster groups. Together, these results confirm a diversity in spindle architecture in older adults, associated with clinically meaningful phenotypes, including memory function and sleep apnea. They suggest that resting-state default mode connectivity during the awake state can be associated with sleep spindle architecture; however, this is highly dependent on clinical phenotype. Establishing relationships between clinical and neuroimaging features and sleep spindle alterations will advance our understanding of the bidirectional relationships between sleep changes and neurodegenerative diseases of ageing.

Heart rate variability during slow wave sleep is linked to functional connectivity in the central autonomic network.

Reduced heart rate variability can be an early sign of autonomic dysfunction in neurodegenerative diseases and may be related to brain dysfunction in the central autonomic network. As yet, such autonomic dysfunction has not been examined during sleep-which is an ideal physiological state to study brain-heart interaction as both the central and peripheral nervous systems behave differently compared to during wakefulness. Therefore, the primary aim of the current study was to examine whether heart rate variability during nocturnal sleep, specifically slow wave (deep) sleep, is associated with central autonomic network functional connectivity in older adults 'at-risk' of dementia. Older adults (n = 78; age range = 50-88 years; 64% female) attending a memory clinic for cognitive concerns underwent resting-state functional magnetic resonance imaging and an overnight polysomnography. From these, central autonomic network functional connectivity strength and heart rate variability data during sleep were derived, respectively. High-frequency heart rate variability was extracted to index parasympathetic activity during distinct periods of sleep, including slow wave sleep as well as secondary outcomes of non-rapid eye movement sleep, wake after sleep onset, and rapid eye movement sleep. General linear models were used to examine associations between central autonomic network functional connectivity and high-frequency heart rate variability. Analyses revealed that increased high-frequency heart rate variability during slow wave sleep was associated with stronger functional connectivity (F = 3.98, P = 0.022) in two core brain regions within the central autonomic network, the right anterior insular and posterior midcingulate cortex, as well as stronger functional connectivity (F = 6.21, P = 0.005) between broader central autonomic network brain regions-the right amygdala with three sub-nuclei of the thalamus. There were no significant associations between high-frequency heart rate variability and central autonomic network connectivity during wake after sleep onset or rapid eye movement sleep. These findings show that in older adults 'at-risk' of dementia, parasympathetic regulation during slow wave sleep is uniquely linked to differential functional connectivity within both core and broader central autonomic network brain regions. It is possible that dysfunctional brain-heart interactions manifest primarily during this specific period of sleep known for its role in memory and metabolic clearance. Further studies elucidating the pathophysiology and directionality of this relationship should be conducted to determine if heart rate variability drives neurodegeneration, or if brain degeneration within the central autonomic network promotes aberrant heart rate variability.

Altered heart rate variability during sleep in mild cognitive impairment.

STUDY OBJECTIVES: Cardiovascular autonomic dysfunction, as measured by short-term diurnal heart rate variability (HRV), has been reported in older adults with mild cognitive impairment (MCI). However, it is unclear whether this impairment also exists during sleep in this group. We, therefore, compared overnight HRV during sleep in older adults with MCI and those with subjective cognitive impairment (SCI). METHODS: Older adults (n = 210) underwent overnight polysomnography. Eligible participants were characterized as multi-domain MCI or SCI. The multi-domain MCI group was comprised of amnestic and non-amnestic subtypes. Power spectral analysis of HRV was conducted on the overnight electrocardiogram during non-rapid eye movement (NREM), rapid eye movement (REM), N1, N2, N3 sleep stages, and wake periods. High-frequency HRV (HF-HRV) was employed as the primary measure to estimate parasympathetic function. RESULTS: The MCI group showed reduced HF-HRV during NREM sleep (p = 0.018), but not during wake or REM sleep (p > 0.05) compared to the SCI group. Participants with aMCI compared to SCI had the most pronounced reduction in HF-HRV across all NREM sleep stages-N1, N2, and N3, but not during wake or REM sleep. The naMCI sub-group did not show any significant differences in HF-HRV during any sleep stage compared to SCI. CONCLUSIONS: Our study showed that amnestic MCI participants had greater reductions in HF-HRV during NREM sleep, relative to those with SCI, suggesting potential vulnerability to sleep-related parasympathetic dysfunction. HF-HRV, especially during NREM sleep, may be an early biomarker for dementia detection.

Validation of the social functioning scale: Comparison and evaluation in early psychosis, autism spectrum disorder and social anxiety disorder.

Social functioning is an important component of mental disorders for assessment and treatment. There is no recognised self-report instrument to measure social functioning across disorders where social impairment is significant. The Social Functioning Scale (SFS) has, however, been used to assess social functioning in psychotic disorders, including Schizophrenia and Early Psychosis. The current study investigated the reliability, validity and sensitivity of the SFS in Early Psychosis, Autism Spectrum Disorder (ASD), Social Anxiety Disorder (SAD) and neurotypical control populations. As expected, all clinical groups showed significant impairment on the total and sub-scale scores of the SFS. The SFS showed good internal consistency and concurrent validity for people diagnosed with SAD and Early Psychosis and a similar factors structure was found for these groups. Participants with ASD reported a relatively low internal consistency and poor concurrent validity, as well as a three-component solution. The SFS has also showed a good sensitivity to separate clinical populations and neurotypical controls. This study supports the use of the SFS for those with SAD and Early Psychosis. Lower internal consistency in ASD populations suggests further research in larger samples is required and that the relationship between its scales are likely different to other populations. Alternative scales or significant other reports may be required for adults with ASD.