scholarly journals Novel genetic variants associated with brain functional networks in 18,445 adults from the UK Biobank

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Heidi Foo ◽  
Anbupalam Thalamuthu ◽  
Jiyang Jiang ◽  
Forrest C. Koch ◽  
Karen A. Mather ◽  
...  
Keyword(s):  
Sleep Duration ◽  
Brain Network ◽  
Functional Network ◽  
Chromosome 2 ◽  
Uk Biobank ◽  
Network Graph ◽  
Network Measures ◽  
Functional Brain Network ◽  
Significant Locus ◽  
The Uk

AbstractHere, we investigated the genetics of weighted functional brain network graph theory measures from 18,445 participants of the UK Biobank (44–80 years). The eighteen measures studied showed low heritability (mean h2SNP = 0.12) and were highly genetically correlated. One genome-wide significant locus was associated with strength of somatomotor and limbic networks. These intergenic variants were located near the PAX8 gene on chromosome 2. Gene-based analyses identified five significantly associated genes for five of the network measures, which have been implicated in sleep duration, neuronal differentiation/development, cancer, and susceptibility to neurodegenerative diseases. Further analysis found that somatomotor network strength was phenotypically associated with sleep duration and insomnia. Single nucleotide polymorphism (SNP) and gene level associations with functional network measures were identified, which may help uncover novel biological pathways relevant to human brain functional network integrity and related disorders that affect it.

scholarly journals Novel genetic variants associated with brain functional networks in 18,445 adults from the UK Biobank

2020 ◽  
Author(s):  
Heidi Foo ◽  
Anbupalam Thalamuthu ◽  
Jiyang Jiang ◽  
Forrest C. Koch ◽  
Karen A. Mather ◽  
...  
Keyword(s):  
Sleep Duration ◽  
Psychiatric Symptoms ◽  
Association Studies ◽  
Genetic Correlations ◽  
Functional Network ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Network Measures ◽  
Functional Brain Network ◽  
The Uk

AbstractThis is the first study investigating the genetics of weighted functional brain network graph theory measures from 18,445 participants of the UK Biobank (44-80 years). The eighteen measures studied showed low heritability (mean h2SNP =0.12) and were highly genetically correlated. Genome-wide association studies for these measures observed 14 significant variants associated with strength of somatomotor and limbic networks. These intergenic variants were located near the PAX8 gene on chromosome 2. Gene-based analyses identified five significantly associated genes for five of the network measures, which have been implicated in sleep duration, neuronal differentiation/development, cancer, and susceptibility to neurodegenerative diseases. Genetic correlations with other traits were examined and significant correlations were observed with sleep measures and psychiatric symptoms. Further analysis found that somatomotor network strength was phenotypically associated with sleep duration and insomnia. Single nucleotide polymorphism (SNP) and gene level associations with functional network measures were identified, which may help uncover novel biological pathways relevant to human brain functional network integrity and diseases that affect it.

scholarly journals 699 Sleep Health Traits and COVID-19: Mortality Risk from the UK Biobank

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A273-A273
Author(s):  
Xi Zheng ◽  
Ma Cherrysse Ulsa ◽  
Peng Li ◽  
Lei Gao ◽  
Kun Hu
Keyword(s):  
Risk Factors ◽  
Sleep Apnea ◽  
Sleep Duration ◽  
Sex Education ◽  
Mortality Risk ◽  
Self Report ◽  
Severe Illness ◽  
Uk Biobank ◽  
Sleep Health ◽  
The Uk

Abstract Introduction While there is emerging evidence for acute sleep disruption in the aftermath of coronavirus disease 2019 (COVID-19), it is unknown whether sleep traits contribute to mortality risk. In this study, we tested whether earlier-life sleep duration, chronotype, insomnia, napping or sleep apnea were associated with increased 30-day COVID-19 mortality. Methods We included 34,711 participants from the UK Biobank, who presented for COVID-19 testing between March and October 2020 (mean age at diagnosis: 69.4±8.3; range 50.2–84.6). Self-reported sleep duration (less than 6h/6-9h/more than 9h), chronotype (“morning”/”intermediate”/”evening”), daytime dozing (often/rarely), insomnia (often/rarely), napping (often/rarely) and presence of sleep apnea (ICD-10 or self-report) were obtained between 2006 and 2010. Multivariate logistic regression models were used to adjust for age, sex, education, socioeconomic status, and relevant risk factors (BMI, hypertension, diabetes, respiratory diseases, smoking, and alcohol). Results The mean time between sleep measures and COVID-19 testing was 11.6±0.9 years. Overall, 5,066 (14.6%) were positive. In those who were positive, 355 (7.0%) died within 30 days (median = 8) after diagnosis. Long sleepers (>9h vs. 6-9h) [20/103 (19.4%) vs. 300/4,573 (6.6%); OR 2.09, 95% 1.19–3.64, p=0.009), often daytime dozers (OR 1.68, 95% 1.04–2.72, p=0.03), and nappers (OR 1.52, 95% 1.04–2.23, p=0.03) were at greater odds of mortality. Prior diagnosis of sleep apnea also saw a two-fold increased odds (OR 2.07, 95% CI: 1.25–3.44 p=0.005). No associations were seen for short sleepers, chronotype or insomnia with COVID-19 mortality. Conclusion Data across all current waves of infection show that prior sleep traits/disturbances, in particular long sleep duration, daytime dozing, napping and sleep apnea, are associated with increased 30-day mortality after COVID-19, independent of health-related risk factors. While sleep health traits may reflect unmeasured poor health, further work is warranted to examine the exact underlying mechanisms, and to test whether sleep health optimization offers resilience to severe illness from COVID-19. Support (if any) NIH [T32GM007592 and R03AG067985 to L.G. RF1AG059867, RF1AG064312, to K.H.], the BrightFocus Foundation A2020886S to P.L. and the Foundation of Anesthesia Education and Research MRTG-02-15-2020 to L.G.

scholarly journals Association of accelerometer-derived sleep measures with lifetime psychiatric diagnoses: A cross-sectional study of 89,205 participants from the UK Biobank

PLoS Medicine ◽  
2021 ◽  
Vol 18 (10) ◽  
pp. e1003782
Author(s):  
Michael Wainberg ◽  
Samuel E. Jones ◽  
Lindsay Melhuish Beaupre ◽  
Sean L. Hill ◽  
Daniel Felsky ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Sleep Duration ◽  
Sleep Efficiency ◽  
Risk Scores ◽  
Psychiatric Diagnoses ◽  
Uk Biobank ◽  
Major Depressive ◽  
Cross Sectional ◽  
Polygenic Risk ◽  
The Uk

Background Sleep problems are both symptoms of and modifiable risk factors for many psychiatric disorders. Wrist-worn accelerometers enable objective measurement of sleep at scale. Here, we aimed to examine the association of accelerometer-derived sleep measures with psychiatric diagnoses and polygenic risk scores in a large community-based cohort. Methods and findings In this post hoc cross-sectional analysis of the UK Biobank cohort, 10 interpretable sleep measures—bedtime, wake-up time, sleep duration, wake after sleep onset, sleep efficiency, number of awakenings, duration of longest sleep bout, number of naps, and variability in bedtime and sleep duration—were derived from 7-day accelerometry recordings across 89,205 participants (aged 43 to 79, 56% female, 97% self-reported white) taken between 2013 and 2015. These measures were examined for association with lifetime inpatient diagnoses of major depressive disorder, anxiety disorders, bipolar disorder/mania, and schizophrenia spectrum disorders from any time before the date of accelerometry, as well as polygenic risk scores for major depression, bipolar disorder, and schizophrenia. Covariates consisted of age and season at the time of the accelerometry recording, sex, Townsend deprivation index (an indicator of socioeconomic status), and the top 10 genotype principal components. We found that sleep pattern differences were ubiquitous across diagnoses: each diagnosis was associated with a median of 8.5 of the 10 accelerometer-derived sleep measures, with measures of sleep quality (for instance, sleep efficiency) generally more affected than mere sleep duration. Effect sizes were generally small: for instance, the largest magnitude effect size across the 4 diagnoses was β = −0.11 (95% confidence interval −0.13 to −0.10, p = 3 × 10−56, FDR = 6 × 10−55) for the association between lifetime inpatient major depressive disorder diagnosis and sleep efficiency. Associations largely replicated across ancestries and sexes, and accelerometry-derived measures were concordant with self-reported sleep properties. Limitations include the use of accelerometer-based sleep measurement and the time lag between psychiatric diagnoses and accelerometry. Conclusions In this study, we observed that sleep pattern differences are a transdiagnostic feature of individuals with lifetime mental illness, suggesting that they should be considered regardless of diagnosis. Accelerometry provides a scalable way to objectively measure sleep properties in psychiatric clinical research and practice, even across tens of thousands of individuals.

scholarly journals A whole-brain and cross-diagnostic perspective on functional brain network dysfunction

2018 ◽  
Author(s):  
Marjolein Spronk ◽  
Kaustubh Kulkarni ◽  
Jie Lisa Ji ◽  
Brian P. Keane ◽  
Alan Anticevic ◽  
...  
Keyword(s):  
Mental Illness ◽  
Resting State ◽  
Brain Network ◽  
Functional Network ◽  
Graph Distance ◽  
Network Organization ◽  
Whole Brain ◽  
Functional Brain ◽  
Functional Brain Network ◽  
Mental Diseases

AbstractA wide variety of mental disorders have been associated with resting-state functional network alterations, which are thought to contribute to the cognitive changes underlying mental illness. These observations have seemed to support various theories postulating large-scale disruptions of brain systems in mental illness. However, existing approaches isolate differences in network organization without putting those differences in broad, whole-brain perspective. Using a graph distance measure – connectome-wide correlation – we found that whole-brain resting-state functional network organization in humans is highly similar across a variety of mental diseases and healthy controls. This similarity was observed across autism spectrum disorder, attention-deficit hyperactivity disorder, and schizophrenia. Nonetheless, subtle differences in network graph distance were predictive of diagnosis, suggesting that while functional connectomes differ little across health and disease those differences are informative. Such small network alterations may reflect the fact that most psychiatric patients maintain overall cognitive abilities similar to those of healthy individuals (relative to, e.g., the most severe schizophrenia cases), such that whole-brain functional network organization is expected to differ only subtly even for mental diseases with devastating effects on everyday life. These results suggest a need to reevaluate neurocognitive theories of mental illness, with a role for subtle functional brain network changes in the production of an array of mental diseases.

scholarly journals Association ofDAT1genetic variants with habitual sleep duration in the UK Biobank

SLEEP ◽  
2018 ◽  
Vol 42 (1) ◽  
Author(s):  
Jessica A Rhodes ◽  
Jacqueline M Lane ◽  
Irma M Vlasac ◽  
Martin K Rutter ◽  
Charles A Czeisler ◽  
...  
Keyword(s):  
Sleep Duration ◽  
Uk Biobank ◽  
The Uk

scholarly journals A genome-wide association study finds genetic variants associated with neck or shoulder pain in UK Biobank

2020 ◽  
Vol 29 (8) ◽  
pp. 1396-1404 ◽  
Author(s):  
Weihua Meng ◽  
Brian W Chan ◽  
Cameron Harris ◽  
Maxim B Freidin ◽  
Harry L Hebert ◽  
...  
Keyword(s):  
Association Study ◽  
Shoulder Pain ◽  
Genetic Variants ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Uk Biobank ◽  
Genome Wide ◽  
A Genome ◽  
Significant Locus ◽  
The Uk

Abstract Background Common types of musculoskeletal conditions include pain in the neck and shoulder areas. This study seeks to identify the genetic variants associated with neck or shoulder pain based on a genome-wide association approach using 203 309 subjects from the UK Biobank cohort and look for replication evidence from the Generation Scotland: Scottish Family Health Study (GS:SFHS) and TwinsUK. Methods A genome-wide association study was performed adjusting for age, sex, BMI and nine population principal components. Significant and independent genetic variants were then sent to GS:SFHS and TwinsUK for replication. Results We identified three genetic loci that were associated with neck or shoulder pain in the UK Biobank samples. The most significant locus was in an intergenic region in chromosome 17, rs12453010, having P = 1.66 × 10−11. The second most significant locus was located in the FOXP2 gene in chromosome 7 with P = 2.38 × 10−10 for rs34291892. The third locus was located in the LINC01572 gene in chromosome 16 with P = 4.50 × 10−8 for rs62053992. In the replication stage, among four significant and independent genetic variants, rs2049604 in the FOXP2 gene and rs62053992 in the LINC01572 gene were weakly replicated in GS:SFHS (P = 0.0240 and P = 0.0202, respectively). Conclusions We have identified three loci associated with neck or shoulder pain in the UK Biobank cohort, two of which were weakly supported in a replication cohort. Further evidence is needed to confirm their roles in neck or shoulder pain.

scholarly journals Oral Antidiabetics and Sleep Among Type 2 Diabetes Patients: Data From the UK Biobank

2021 ◽  
Vol 12 ◽  
Author(s):  
Pei Xue ◽  
Jiafei Wu ◽  
Xiangdong Tang ◽  
Xiao Tan ◽  
Christian Benedict
Keyword(s):  
Type 2 Diabetes ◽  
Sleep Duration ◽  
Small Scale ◽  
Uk Biobank ◽  
Metformin Therapy ◽  
Antidiabetic Therapy ◽  
Oral Antidiabetic ◽  
Metformin Monotherapy ◽  
The Uk

Previous small-scale studies have found that oral antidiabetic therapy is associated with sleep difficulties among patients with type 2 diabetes (T2D). Here, we used data from 11 806 T2D patients from the UK Biobank baseline investigation to examine the association of oral antidiabetic therapy with self-reported difficulty falling and staying asleep and daily sleep duration. As shown by logistic regression adjusted for, e.g., age, T2D duration, and HbA1c, patients on non-metformin therapy (N=815; 86% were treated with sulphonylureas) had a 1.24-fold higher odds ratio of reporting regular difficulty falling and staying asleep at night compared to those without antidiabetic medication use (N=5 366, P<0.05) or those on metformin monotherapy (N=5 625, P<0.05). Non-metformin patients reported about 8 to 10 minutes longer daily sleep duration than the other groups (P<0.05). We did not find significant differences in sleep outcomes between untreated and metformin patients. Our findings suggest that non-metformin therapy may result in sleep initiation and maintenance difficulties, accompanied by a small but significant sleep extension. The results of the present study must be replicated in future studies using objective measures of sleep duration and validated questionnaires for insomnia. Considering that most T2D patients utilize multiple therapies to manage their glycemic control in the long term, it may also be worth investigating possible interactions of antidiabetic drugs on sleep.

scholarly journals Age- and sex-related topological organisation of human brain functional networks and their relationship to cognition

2021 ◽  
Author(s):  
Heidi Foo ◽  
Anbupalam Thalamuthu ◽  
Jiyang Jiang ◽  
Forrest C Koch ◽  
Karen Mather ◽  
...  
Keyword(s):  
Cognitive Performance ◽  
Resting State ◽  
Brain Regions ◽  
Brain Network ◽  
Functional Networks ◽  
State Graph ◽  
Uk Biobank ◽  
Age Related ◽  
Functional Brain Network ◽  
Age And Sex

Age and sex have been associated with changes in functional brain network topology, which may in turn affect cognition in older adults. We explored this question further by examining differences in 11 resting-state graph theory measures with respect to age, sex, and their relationships with cognitive performance in 17,127 UK Biobank participants. Age was associated with an overall decrease in the effectiveness of network communication (i.e. integration) and loss of functional specialisation (i.e. segregation) of specific brain regions. Sex differences were also observed, with women showing more efficient networks which were less segregated than in men. Age-related changes were also more apparent in men than women, which suggests that men may be more vulnerable to cognitive decline with age. Interestingly, while network segregation and strength of limbic network were only nominally associated with cognitive performance, the network measures collectively were significantly associated with cognition. This may imply that individual measures may be inadequate to capture much of the variance in neural activity or its output and need further refinement.

Associations of sleep phenotypes with severe intentional self-harm: a prospective analysis of the UK Biobank cohort

SLEEP ◽  
2021 ◽  
Author(s):  
Binbin Lei ◽  
Jihui Zhang ◽  
Sijing Chen ◽  
Jie Chen ◽  
Lulu Yang ◽  
...  
Keyword(s):  
Older Adults ◽  
Mental Disorders ◽  
Sleep Duration ◽  
Uk Biobank ◽  
Middle Aged ◽  
Long Sleep ◽  
Self Harm ◽  
Future Risk ◽  
The Uk

Abstract Study objectives We aimed to investigate the prospective associations of sleep phenotypes with severe intentional self-harm (ISH) in middle-aged and older adults. Methods A total of 499,159 participants (mean age: 56.55 ± 8.09 years; female: 54.4%) were recruited from the UK Biobank between 2006 and 2010 with follow-up until February 2016 in this population-based prospective study. Severe ISH was based on hospital inpatient records or a death cause of ICD-10 codes X60-X84. Patients with hospitalized diagnosis of severe ISH before the initial assessment were excluded. Sleep phenotypes, including sleep duration, chronotype, insomnia, sleepiness, and napping, were assessed at the initial assessments. Cox regression analysis was used to estimate temporal associations between sleep phenotypes and future risk of severe ISH. Results During a follow-up period of 7.04 years (SD: 0.88), 1,219 participants experienced the first hospitalization or death related to severe ISH. After adjusting for demographics, substance use, medical diseases, mental disorders, and other sleep phenotypes, short sleep duration (HR: 1.50, 95% CI: 1.23-1.83, P < .001), long sleep duration (HR: 1.56, 95% CI: 1.15-2.12, P = .004), and insomnia (usually: HR: 1.57, 95% CI: 1.31-1.89, P < .001) were significantly associated with severe ISH. Sensitivity analyses excluding participants with mental disorders preceding severe ISH yielded similar results. Conclusion The current study provides the empirical evidence of the independent prediction of sleep phenotypes, mainly insomnia, short and long sleep duration, for the future risk of severe ISH among middle-aged and older adults.

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