So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

Human biochemical genetics

In summary, although actigraphy is not as accurate as PSG for determining some sleep measurements, studies are in general agreement that actigraphy, with its ability to record continuously for long time periods, is more reliable than sleep logs which rely on the patients' recall of how many times they woke up or how long they slept during the night and is more reliable than observations which only capture short time periods Actigraphy can provide information obtainable in no other practical way It can also have a role in the medical care of patients with sleep disorders However, it should not be held to the same expectations as polysomnography Actigraphy is one-dimensional, whereas polysomnography comprises at least 3 distinct types of data (EEG, EOG, EMG), which jointly determine whether a person is asleep or awake It is therefore doubtful whether actigraphic data will ever be informationally equivalent to the PSG, although progress on hardware and data processing software is continuously being made Although the 1995 practice parameters paper determined that actigraphy was not appropriate for the diagnosis of sleep disorders, more recent studies suggest that for some disorders, actigraphy may be more practical than PSG While actigraphy is still not appropriate for the diagnosis of sleep disordered breathing or of periodic limb movements in sleep, it is highly appropriate for examining the sleep variability (ie, night-to-night variability) in patients with insomnia Actigraphy is also appropriate for the assessment of and stability of treatment effects of anything from hypnotic drugs to light treatment to CPAP, particularly if assessments are done before and after the start of treatment A recent independent review of the actigraphy literature by Sadeh and Acebo reached many of these same conclusions Some of the research studies failed to find relationships between sleep measures and health-related symptoms The interpretation of these data is also not clear-cut Is it that the actigraph is not reliable enough to the access the relationship between sleep changes and quality of life measures, or, is it that, in fact, there is no relationship between sleep in that population and quality of life measures? Other studies of sleep disordered breathing, where actigraphy was not used and was not an outcome measure also failed to find any relationship with quality of life Is it then the actigraph that is not reliable or that the associations just do not exist? The one area where actigraphy can be used for clinical diagnosis is in the evaluation of circadian rhythm disorders Actigraphy has been shown to be very good for identifying rhythms Results of actigraphic recordings correlate well with measurements of melatonin and of core body temperature rhythms Activity records also show sleep disturbance when sleep is attempted at an unfavorable phase of the circadian cycle Actigraphy therefore would be particularly good for aiding in the diagnosis of delayed or advanced sleep phase syndrome, non-24-hour-sleep syndrome and in the evaluation of sleep disturbances in shift workers It must be remembered, however, that overt rest-activity rhythms are susceptible to various masking effects, so they may not always show the underlying rhythm of the endogenous circadian pacemaker In conclusion, the latest set of research articles suggest that in the clinical setting, actigraphy is reliable for evaluating sleep patterns in patients with insomnia, for studying the effect of treatments designed to improve sleep, in the diagnosis of circadian rhythm disorders (including shift work), and in evaluating sleep in individuals who are less likely to tolerate PSG, such as infants and demented elderly While actigraphy has been used in research studies for many years, up to now, methodological issues had not been systematically addressed in clinical research and practice Those issues have now been addressed and actigraphy may now be reaching the maturity needed for application in the clinical arena

The role of actigraphy in the study of sleep and circadian rhythms.

Over more than a century of research has established the fact that sleep benefits the retention of memory. In this review we aim to comprehensively cover the field of "sleep and memory" research by providing a historical perspective on concepts and a discussion of more recent key findings. Whereas initial theories posed a passive role for sleep enhancing memories by protecting them from interfering stimuli, current theories highlight an active role for sleep in which memories undergo a process of system consolidation during sleep. Whereas older research concentrated on the role of rapid-eye-movement (REM) sleep, recent work has revealed the importance of slow-wave sleep (SWS) for memory consolidation and also enlightened some of the underlying electrophysiological, neurochemical, and genetic mechanisms, as well as developmental aspects in these processes. Specifically, newer findings characterize sleep as a brain state optimizing memory consolidation, in opposition to the waking brain being optimized for encoding of memories. Consolidation originates from reactivation of recently encoded neuronal memory representations, which occur during SWS and transform respective representations for integration into long-term memory. Ensuing REM sleep may stabilize transformed memories. While elaborated with respect to hippocampus-dependent memories, the concept of an active redistribution of memory representations from networks serving as temporary store into long-term stores might hold also for non-hippocampus-dependent memory, and even for nonneuronal, i.e., immunological memories, giving rise to the idea that the offline consolidation of memory during sleep represents a principle of long-term memory formation established in quite different physiological systems.

https://www.zora.uzh.ch/id/eprint/77770/1/physiol_rev_93.pdf

About sleep's role in memory

1.0 BACKGROUND ACTIGRAPHY HAS BEEN USED TO STUDY SLEEP/WAKE PATTERNS FOR OVER 20 YEARS. The advantage of actigraphy over traditional polysomnography (PSG) is that actigraphy can conveniently record continuously for 24-hours a day for days, weeks or even longer. In 1995, Sadeh et al.,1 under the auspices of the American Sleep Disorders Association (now called the American Academy of Sleep Medicine, AASM), reviewed the current knowledge about the role of actigraphy in the evaluation of sleep disorders. They concluded that actigraphy does provide useful information and that it may be a “cost-effective method for assessing specific sleep disorders...[but that] methodological issues have not been systematically addressed in clinical research and practice.” Based on that task force’s report, the AASM Standards of Practice Committee concluded that actigraphy was not indicated for routine diagnosis or for assessment of severity or management of sleep disorders, but might be a useful adjunct for diagnosing insomnia, circadian rhythm disorders or excessive sleepiness.2 Since that time, actigraph technology has improved, and many more studies have been conducted. Several review papers have concluded that wrist actigraphy can usefully approximate sleep versus wake state during 24 hours and have noted that actigraphy has been used for monitoring insomnia, circadian sleep/wake disturbances, and periodic limb movement disorder.3,4 This paper begins where the 1995 paper left off. Under the auspices of the AASM, a new task force was established to review the current state of the art of this technology.

The Role of Actigraphy in the Study of Sleep and Circadian Rhythms AMERICAN ACADEMY OF SLEEP MEDICINE REVIEW PAPER

Human behavior shows large interindividual variation in temporal organization. Extreme "larks" wake up when extreme "owls" fall asleep. These chronotypes are attributed to differences in the circadian clock, and in animals, the genetic basis of similar phenotypic differences is well established. To better understand the genetic basis of temporal organization in humans, the authors developed a questionnaire to document individual sleep times, self-reported light exposure, and self-assessed chronotype, considering work and free days separately. This report summarizes the results of 500 questionnaires completed inapilotstudy.Individualsleeptimesshowlargedifferencesbetweenworkand freedays,exceptforextremeearlytypes.Duringtheworkweek,latechronotypes

/pdf/life-between-clocks-daily-temporal-patterns-of-human-2i1rqfyvgw.pdf

Life between clocks: daily temporal patterns of human chronotypes.

A comparison of zolpidem and temazepam in psychophysiological insomniacs

Recently, Stickgold et al. (1999) demonstrated that subjects awakened from REM sleep showed a greater priming effect by weak primes than by strong primes, which is in contrast to the normal pattern of priming. Their interpretation was that REM sleep is involved in enhancing the strength of memory association. To replicate these findings a semantic priming experiment was designed. Subjects were exposed to prime-target pairs just before sleeping, just after awakening from slow wave sleep as well as from REM sleep, and after waking up in the morning. Reaction times on the target word were dependent on the level of association of the prime-target words, and on the sleep-wake state just before testing. In agreement with the literature was the finding that the stronger the association, the shorter the reaction time on the target was. Moreover, and in agreement with Stickgold et al.` findings, was the fact that reaction times after awakening from sleep and REM sleep were longer compared to those when wakefulness was preceding the test. This is in line with the phenomenon of ‘sleep inertia’. However, not in agreement with Stickgold et al.` results was that the priming effect after REM sleep was smaller than that after slow wave sleep. This effect was even comparable to the priming effect after waking. This finding jeopardises the interpretation and conclusions with respect to the positive function of REM sleep in memory consolidation.

Effects of sleep-wake states on reaction times and priming effects in a semantic priming paradigm

In order to assess age effects upon the daytime level of alertness, both subjective and objective measures of alertness were obtained in 19 healthy elderly males (mean age 65 years) and 19 healthy young males (mean age 21 years). Subjects were recorded during a Multiple Sleep Latency Test (MSLT), administered at 5 different times of day (9 a.m., 12 a.m., 3 p.m., 6 p.m., 9 p.m.). Before each test, subjects filled out an alertness questionnaire. During the entire 20 minutes of each test electroencephalographic (EEG) recordings were made and transformed into 40 averaged spectra, one for each 30 s epoch. For the delta, theta, alpha, sigma and beta bands of the EEG 6 consecutive values were averaged to obtain 1 value per 3 minutes. On the basis of the visually guided detection of the first spindle, sleep onset was determined. The elderly subjects obtained a higher overall level of subjective alertness than the young subjects. No age effect was observed for sleep latency, which followed a U-shaped diurnal trend...

Transitions from wakefulness to sleep at different times of day: old vs. young subjects

Simple Summary Sleep disorders negatively impact adolescent and young adult childhood cancer patients’ physical and psychosocial health. Early recognition might improve timely treatment. This national cohort study describes subjective sleep disorders (using a validated self-report questionnaire according to international diagnostic criteria) in childhood cancer patients after treatment, including all types of diagnoses. Sleep disorder prevalence rates ranged from 1.8–9.6%. Insomnia and circadian rhythm sleep disorders were most commonly reported and more prevalent than in the general population. Female sex, young adulthood (18–26 years old) and co-morbid health conditions were risk factors for having a sleep disorder, but cancer-related factors were not. The most commonly used sleep medication was melatonin, which exceeded use described in the general population. Patients with a sleep disorder expressed an unmet need for sleep treatment. Screening for sleep disorders after cancer might improve access to treatment and support childhood cancer patients to maintain optimal health and quality of life. Abstract Background: Sleep disorders negatively impact adolescent and young adult childhood cancer patients’ physical and psychosocial health. Early recognition improves timely treatment. We therefore studied the prevalence of subjective sleep disorders, risk factors and sleep treatment needs after completion of childhood cancer treatment. Methods: Childhood cancer patients (12–26 years old), ≥6 months after treatment, were invited to fill out the Holland Sleep Disorders Questionnaire, which distinguishes six sleep disorders in substantial agreement with the International Classification of Sleep Disorders, second edition (ICSD-2). They additionally indicated sleep treatment needs. Prevalence rates and needs were displayed in percentages. Logistic regression models were used for risk factors. Results: 576 patients participated (response rate 55.8%)—49.5% females, mean age 17.0 years, 44.4% hemato-oncology, 31.9% solid tumors, 23.6% neuro-oncology. Prevalence rates were: insomnia (9.6%), circadian rhythm sleep disorder (CRSD; 8.1%), restless legs syndrome (7.6%), parasomnia (3.5%), hypersomnia (3.5%) and sleep-related breathing disorders (1.8%). Female sex, comorbid health conditions and young adulthood seem to be risk factors for sleep disorders, but cancer-related factors were not. Differing per sleep disorder, 42–72% wanted help, but only 0–5.6% received sleep treatment. Conclusions: Insomnia and CRSD were most prevalent. An unmet need for sleep treatment was reported by childhood cancer patients during follow-up. Screening for sleep disorders after cancer might improve access to treatment and patient wellbeing.

/pdf/prevalence-of-sleep-disorders-risk-factors-and-sleep-2eiy5h8w.pdf

Prevalence of Sleep Disorders, Risk Factors and Sleep Treatment Needs of Adolescents and Young Adult Childhood Cancer Patients in Follow-Up after Treatment

Background Most individuals with mental disorders complain about the problems they experience with sleeping and waking. It is becoming evident that careful diagnosis of sleep-wake disorders is of great importance for the prevention and treatment of mental disorders. Since the introduction of the DSM-IV, clinical scientific research has provided important new insights in this field. Aim To find out whether the new classification of sleep-wake disorders in DSM-5 is likely to improve the diagnosis of disorders of this type. Method We discuss the main changes in the DSM-5 classification of sleep- wake disorders, comparing the new version with the version in DSM-IV. Results Because considerable attention is being given to the symptom-orientated and dimensional approach, the classification of sleep-wake disorders in the DSM-5 is closer to current psychiatric practice and it does justice to the current scientific insights into the dimensional nature of psychiatric disorders. Conclusion The DSM-5 classification takes recent scientific insights into account and might help to improve the diagnosis of sleep-wake disorders in psychiatry.

Gerard A. Kerkhof

Papers

A comparison of zolpidem and temazepam in psychophysiological insomniacs

Effects of sleep-wake states on reaction times and priming effects in a semantic priming paradigm

Transitions from wakefulness to sleep at different times of day: old vs. young subjects

Prevalence of Sleep Disorders, Risk Factors and Sleep Treatment Needs of Adolescents and Young Adult Childhood Cancer Patients in Follow-Up after Treatment

[Sleep-wake disorders and DSM-5].