Genome-wide association analysis of composite sleep health scores in 413,904 individuals

Distinct Convergent Brain Alterations in Sleep Disorders and Sleep Deprivation: A Meta-Analysis

Importance

Sleep disorders have different etiologies yet share some nocturnal and daytime symptoms, suggesting common neurobiological substrates; healthy individuals undergoing experimental sleep deprivation also report analogous daytime symptoms. However, brain similarities and differences between long-term sleep disorders and short-term sleep deprivation are unclear.

Objective

To investigate the shared and specific neural correlates across sleep disorders and sleep deprivation.

Data Sources

PubMed, Web of Science, Embase, Scopus, and BrainMap were searched up to January 2024 to identify relevant structural and functional neuroimaging articles.

Study Selection

Whole-brain neuroimaging articles reporting voxel-based group differences between patients with different sleep disorders and healthy control participants or between total or partial sleep-deprived and well-rested individuals were included.

Data Extraction and Synthesis

Significant coordinates of group comparisons, their contrast direction (eg, patients < controls), and imaging modality were extracted. For each article, 2 raters independently evaluated eligibility and extracted data. Subsequently, several meta-analyses were performed with the revised activation likelihood estimation algorithm using P < .05 cluster-level familywise error correction.

Main Outcomes and Measures

Transdiagnostic regional brain alterations were identified across sleep disorders and among articles reporting sleep deprivation. Their associated behavioral functions and task-based or task-free connectivity patterns were explored using 2 independent datasets (BrainMap and the enhanced Nathan Kline Institute-Rockland Sample).

Results

A total of 231 articles (140 unique experiments, 3380 unique participants) were retrieved. The analysis across sleep disorders (n = 95 experiments) identified the subgenual anterior cingulate cortex (176 voxels, z score = 4.86), associated with reward, reasoning, and gustation, and the amygdala and hippocampus (130 voxels, z score = 4.00), associated with negative emotion processing, memory, and olfaction. Both clusters had positive functional connectivity with the default mode network. The right thalamus (153 voxels, z score = 5.21) emerged as a consistent regional alteration following sleep deprivation (n = 45 experiments). This cluster was associated with thermoregulation, action, and pain perception and showed positive functional connectivity with subcortical and (pre)motor regions. Subanalyses regarding the direction of alterations demonstrated that the subgenual anterior cingulate cortex exhibited decreased activation, connectivity, and/or volume, while the amygdala and hippocampus cluster and the thalamus cluster demonstrated increased activation, connectivity, and/or volume.

Conclusions and Relevance

Distinct convergent brain abnormalities were observed between long-term sleep disorders (probably reflecting shared symptoms) and short-term sleep deprivation.

Genetic factors and symptom dimensions associated with antidepressant treatment outcomes: clues for new potential therapeutic targets?

Treatment response and resistance in major depressive disorder (MDD) show a significant genetic component, but previous studies had limited power also due to MDD heterogeneity. This literature review focuses on the genetic factors associated with treatment outcomes in MDD, exploring their overlap with those associated with clinically relevant symptom dimensions. We searched PubMed for: (1) genome-wide association studies (GWASs) or whole exome sequencing studies (WESs) that investigated efficacy outcomes in MDD; (2) studies examining the association between MDD treatment outcomes and specific depressive symptom dimensions; and (3) GWASs of the identified symptom dimensions. We identified 13 GWASs and one WES of treatment outcomes in MDD, reporting several significant loci, genes, and gene sets involved in gene expression, immune system regulation, synaptic transmission and plasticity, neurogenesis and differentiation. Nine symptom dimensions were associated with poor treatment outcomes and studied by previous GWASs (anxiety, neuroticism, anhedonia, cognitive functioning, melancholia, suicide attempt, psychosis, sleep, sociability). Four genes were associated with both treatment outcomes and these symptom dimensions: CGREF1 (anxiety); MCHR1 (neuroticism); FTO and NRXN3 (sleep). Other overlapping signals were found when considering genes suggestively associated with treatment outcomes. Genetic studies of treatment outcomes showed convergence at the level of biological processes, despite no replication at gene or variant level. The genetic signals overlapping with symptom dimensions of interest may point to shared biological mechanisms and potential targets for new treatments tailored to the individual patient's clinical profile.

Associations of a multidimensional polygenic sleep health score and a sleep lifestyle index on health outcomes and their interaction in a clinical biobank

Sleep is a complex behavior regulated by genetic and environmental factors, and is known to influence health outcomes. However, the effect of multidimensional sleep encompassing several sleep dimensions on diseases has yet to be fully elucidated. Using the Mass General Brigham Biobank, we aimed to examine the association of multidimensional sleep with health outcomes and investigate whether sleep behaviors modulate genetic predisposition to unfavorable sleep on mental health outcomes. First, we generated a Polygenic Sleep Health Score using previously identified single nucleotide polymorphisms for sleep health and constructed a Sleep Lifestyle Index using data from self-reported sleep questions and electronic health records; second, we performed phenome-wide association analyses between these indexes and clinical phenotypes; and third, we analyzed the interaction between the indexes on prevalent mental health outcomes. Fifteen thousand eight hundred and eighty-four participants were included in the analysis (mean age 54.4; 58.6% female). The Polygenic Sleep Health Score was associated with the Sleep Lifestyle Index (β=0.050, 95%CI=0.032, 0.068) and with 114 disease outcomes spanning 12 disease groups, including obesity, sleep, and substance use disease outcomes (p<3.3×10-5). The Sleep Lifestyle Index was associated with 458 disease outcomes spanning 17 groups, including sleep, mood, and anxiety disease outcomes (p<5.1×10-5). No interactions were found between the indexes on prevalent mental health outcomes. These findings suggest that favorable sleep behaviors and genetic predisposition to healthy sleep may independently be protective of disease outcomes. This work provides novel insights into the role of multidimensional sleep on population health and highlights the need to develop prevention strategies focused on healthy sleep habits.