Patient and provider experiences with CBT-I administered in-person or via telemedicine: A randomized non-inferiority trial

Cognitive behavioral therapy for insomnia (CBT-I) is an effective treatment in adults. However, access to care is limited. One potential solution is telemedicine. Though synchronous video-based telemedicine CBT-I has been shown to be non-inferior to in-person treatment, there is no study to date that evaluates patient and provider experiences with video-based treatment. Our study team evaluated patient and provider perceptions of CBT-I delivered via telemedicine versus an in-person format. As part of a larger randomized control trial, we interviewed patients and providers in both arms of the study (in-person and via telemedicine). 20 minute interviews were conducted over the phone and were transcribed and coded to identify themes. While patients shared initial concerns about telemedicine CBT-I, including privacy and technological issues, they were satisfied with the approach and had similar experiences as the patients receiving in-person treatment. Providers shared concerns about challenges establishing a strong therapeutic alliance, patient engagement, and accountability in CBT-I, but felt these did not interfere with their overall ability to deliver care. Patients and providers were satisfied with CBT-I treatment delivered via telemedicine when compared to those being treated in-person. Patients in both arms noted that virtual care could increase access and provide convenience

Genome-Wide Association Analyses in 128,266 Individuals Identifies New Morningness and Sleep Duration Loci

Disrupted circadian rhythms and reduced sleep duration are associated with several human diseases, particularly obesity and type 2 diabetes, but until recently, little was known about the genetic factors influencing these heritable traits. We performed genome-wide association studies of self-reported chronotype (morning/evening person) and self-reported sleep duration in 128,266 white British individuals from the UK Biobank study. Sixteen variants were associated with chronotype (P<5x10(-8)), including variants near the known circadian rhythm genes RGS16 (1.21 odds of morningness, 95% CI [1.15, 1.27], P = 3x10(-12)) and PER2 (1.09 odds of morningness, 95% CI [1.06, 1.12], P = 4x10(-10)). The PER2 signal has previously been associated with iris function. We sought replication using self-reported data from 89,283 23andMe participants;thirteen of the chronotype signals remained associated at P<5x10(-8) on meta-analysis and eleven of these reached P< 0.05 in the same direction in the 23andMe study. We also replicated 9 additional variants identified when the 23andMe study was used as a discovery GWAS of chronotype (all P<0.05 and meta-analysis P<5x10(-8)). For sleep duration, we replicated one known signal in PAX8 (2.6 minutes per allele, 95% CI [1.9, 3.2], P = 5.7x10(-16)) and identified and replicated two novel associations at VRK2 (2.0 minutes per allele, 95% CI [1.3, 2.7], P = 1.2x10(-9);and 1.6 minutes per allele, 95% CI [1.1, 2.2], P = 7.6x10(-9)). Although we found genetic correlation between chronotype and BMI (rG = 0.056, P = 0.05);undersleeping and BMI (rG = 0.147, P = 1x10(-5)) and over-sleeping and BMI (rG = 0.097, P = 0.04), Mendelian Randomisation analyses, with limited power, provided no consistent evidence of causal associations between BMI or type 2 diabetes and chronotype or sleep duration. Our study brings the total number of loci associated with chronotype to 22 and with sleep duration to three, and provides new insights into the biology of sleep and circadian rhythms in humans

Genetic variants in RBFOX3 are associated with sleep latency

Time to fall asleep (sleep latency) is a major determinant of sleep quality. Chronic, long sleep latency is a major characteristic of sleep-onset insomnia and/or delayed sleep phase syndrome. In this study we aimed to discover common polymorphisms that contribute to the genetics of sleep latency. We performed a meta-analysis of genome-wide association studies (GWAS) including 2 572 737 single nucleotide polymorphisms (SNPs) established in seven European cohorts including 4242 individuals. We found a cluster of three highly correlated variants (rs9900428, rs9907432 and rs7211029) in the RNA-binding protein fox-1 homolog 3 gene (RBFOX3) associated with sleep latency (P-values=5.77 × 10-08, 6.59 × 10- 08 and 9.17 × 10- 08). These SNPs were replicated in up to 12 independent populations including 30 377 individuals (P-values=1.5 × 10- 02, 7.0 × 10- 03 and 2.5 × 10- 03; combined meta-analysis P-values=5.5 × 10-07, 5.4 × 10-07 and 1.0 × 10-07). A functional prediction of RBFOX3 based on co-expression with other genes shows that this gene is predominantly expressed in brain (P-value=1.4 × 10-316) and the central nervous system (P-value=7.5 × 10- 321). The predicted function of RBFOX3 based on co-expression analysis with other genes shows that this gene is significantly involved in the release cycle of neurotransmitte

Genetic Pathways to Insomnia

This review summarizes current research on the genetics of insomnia, as genetic contributions are thought to be important for insomnia etiology. We begin by providing an overview of genetic methods (both quantitative and measured gene), followed by a discussion of the insomnia genetics literature with regard to each of the following common methodologies: twin and family studies, candidate gene studies, and genome-wide association studies (GWAS). Next, we summarize the most recent gene identification efforts (primarily GWAS results) and propose several potential mechanisms through which identified genes may contribute to the disorder. Finally, we discuss new genetic approaches and how these may prove useful for insomnia, proposing an agenda for future insomnia genetics research

Insomnia in the older adult

KEY POINTS - The incidence of insomnia increases with aging. Insomnia can include difficulty falling asleep at the start of the sleep period, waking up during the night and having difficulty falling back asleep, and waking up early and being unable to get back to sleep. Difficulty staying asleep and early morning insomnia are common in older adults with insomnia disorder. - When diagnosing insomnia, health care providers need to collect a thorough health history and include questions about the older adult’s sleep, medical, and psychiatric history. - Cognitive-behavioral therapy for insomnia, which consists of stimulus control, sleep restriction, sleep hygiene, and cognitive therapy, is the recommended first-line therapy for treatment of insomnia in older adults. - Because of the higher risk for adverse effects in older patients, medications should be used sparingly and, when possible, be discontinued. - Cognitive-behavioral therapy for insomnia has been shown to be more efficacious than medications for the long-term management of insomnia in older adults

Insomnia in the older adult

Although insomnia is not a normal part of the aging process, its prevalence increases with age. Factors such as medications and medical and psychiatric disorders can increase the risk for insomnia. In order to diagnose insomnia, it is important for older adults to complete comprehensive sleep and health histories. Cognitive behavioral therapy for insomnia, which includes stimulus control, sleep restriction, sleep hygiene, and cognitive therapy, is the recommended first-line treatment of insomnia and is more effective that medications for the long-term management of insomnia. Medications such as benzodiazepines and antidepressants should be avoided for the treatment of insomnia in older adults

The Sigmoidally-transformed Cosine Curve: A Mathematical Model for Circadian Rhythms with Non-sinusoidal Shapes

We introduce a family of nonlinear transformations of the traditional cosine curve used in the modeling of biological rhythms. The nonlinear transformation is the sigmoidal family, represented here by three family members: the Hill function, the logistic function, and the arctangent function. These transforms add two additional parameters that must be estimated, in addition to the acrophase, MESOR, and amplitude (and period in some applications), but the estimated curves have shapes requiring many more than 2 additional harmonics to achive the same fit when modeled by harmonic regression. Particular values of the additional parameters can yield rectangular waves, narrow pulses, wide pulses, and for rectangular waves (representing alternating “on” and “off” states) the times of onset and offset. We illustrate the sigmoidally transformed cosine curves, and compare them to harmonic regression modeling, in a sample of 8 activity recordings made on patients in a nursing home. We introduce a family of nonlinear transformations of the traditional cosine curve used in the modeling of biological rhythms. The nonlinear transformation is the sigmoidal family, represented here by three family members: the Hill function, the logistic function, and the arctangent function. These transforms add two additional parameters that must be estimated, in addition to the acrophase, MESOR, and amplitude (and period in some applications), but the estimated curves have shapes requiring many more than 2 additional harmonics to achive the same fit when modeled by harmonic regression. Particular values of the additional parameters can yield rectangular waves, narrow pulses, wide pulses, and for rectangular waves (representing alternating “on” and “off” states) the times of onset and offset. We illustrate the sigmoidally transformed cosine curves, and compare them to harmonic regression modeling, in a sample of 8 activity recordings made on patients in a nursing home

Genetics of sleep disorders

Sleep disorders are, in part, attributable to genetic variability across individuals. There has been considerable progress in understanding the role of genes for some sleep disorders, such as the identification of a human leukocyte antigen gene for narcolepsy. For other sleep disorders, such as insomnia, little work has been done. Optimizing phenotyping strategies is critical, as is the case for sleep apnea, for which intermediate traits such as obesity and craniofacial features may prove to be more tractable for genetic studies. Rapid advances in genotyping and statistical genetics are likely to lead to greater discoveries in the near future

Sleep Deprivation as a Treatment for Depression: Comparison of mood ratings and improving prediction of treatment response

Major Depressive Disorder (MDD), a major contributor to disability and disease burden, is a critical public health issue. Typical treatments for MDD include pharmacotherapy and office-based therapy. However, fewer than 60% of those with MDD respond to a single course of these treatments, and the relapse rate is nearly 50%. In contrast, acute sleep deprivation therapy (SD) yields an antidepressant effect in \u3c 24 hours with comparable response rates. Clinical practice has not widely adopted the use of SD due in-part to its transient effects and inconvenience to patients. This study examined the utility self-administered baseline PANAS, POMS-SF, and VAS mood measures and baseline demographics to predict a participant’s response to SD. Depressed participants (N = 37) underwent ~36 hr of sleep deprivation. An antidepressant response was defined as a ≥ 30% decrease in HDRS-NOW score from baseline to post-sleep deprivation. Odds ratios of experiencing a response were calculated utilizing univariate binary logistic regression. 64% (n = 23) of participants responded to SD. Identifying as white OR = 5.14, p = .030, 95% CI [1.19, 22.48], being employed OR = 4.53, p = .042, 95% CI [1.06, 19.41], and greater scores on the baseline PANAS positive affect scale OR = 1.30, p = .010, 95% CI [ 1.07, 1.59], were significantly associated with the odds of experiencing an antidepressant response to SD. To our knowledge, the PANAS positive affect scale has not been previously identified as a predictor of response to SD. The results of this research may be utilized to inform and ease screening for this treatment modality in the clinical and research settings