Summary - Introduction and aims: Affective disorders, characterized by recurrent episodes of low and/or elevated mood, are among the most costly and burdensome chronic diseases. Diagnostic categories and episodespecific symptoms overlap, and prevention of illness progression is hampered by an inability to detect early signs of new episodes in due time. Psychiatry as a medical discipline is uniquely dependent on clinical observation of signs and symptoms with few objective markers of disease. In all states of affective disorders, there are variations in mood symptoms, sleep, circadian rhythms and motor activity. While mood is an ambiguous and subjective symptom, circadian rhythms and motor activity patterns are objectively assessable via the use of actigraphy. Actigraphs are convenient and non-invasive devices for monitoring wrist movement, and they are increasingly employed in psychiatric settings to record sleep-wake and motor activity rhythms. To date, analytical methods have focused on mean levels and simple variability measures. This thesis aimed to analyze motor activity patterns in inpatients and outpatients with affective disorders, using linear and non-linear mathematical methods, in order to compare groups of patients defined by phenotypes. Methods: In two studies, 24-hour actigraphically recorded motor activity patterns in acutely admitted inpatients with affective disorders and recordings from healthy controls were included. In the first study, 52 patients with unipolar depression were divided into groups with and without clinically assessed motor retardation. The second study included 30 patients with mania or bipolar depression. In a third study, 1-week actigraphy recordings in 43 outpatients with euthymic bipolar disorder and subjective sleep disturbance were compared between groups with actigraphically determined stable and unstable rest-activity cycles. Actigraphy recordings were compared to concurrent reports of mood and sleep. In all studies, motor activity patterns were analyzed by measures of variability (standard deviation (SD), root mean square successive difference (RMSSD), RMSSD/SD ratio). Studies I and II additionally employed other measures of variability (autocorrelation lag 1, Fourier analysis) and complexity (sample entropy, symbolic dynamics) and other non-linear methods for studying the distribution of active and inactive periods. Results: Within the unipolar depression sample, patients with motor retardation had reduced activity levels and higher intra-individual variability in activity compared to patients without motor retardation. Motor retardation implied being active in shorter bursts with fewer long bursts of activity. Patients without motor retardation displayed increased complexity in activity during an active morning sequence of approximately one hour. Bipolar depression was characterized by significantly lower mean activity and higher variability compared to healthy controls, similar to all depression groups relative to controls. Patients with mania showed higher minute-to-minute variability (higher RMSSD values) during 24 hours compared to healthy controls, and increased complexity (higher sample entropy) during the active morning sequence compared to patients with bipolar depression. In euthymic bipolar disorder and sleep disturbance, a subgroup of patients demonstrated unstable rest-activity cycles in combination with variability in mood and motor activity patterns. The unstable subgroup was younger and showed delayed sleep phases compared to the group with stable rest-activity cycles. Discussion: Patients with unipolar depression with and without motor retardation differed in 24-hour activity patterns, and the two phenotypes could be distinguished by complementary methods. Findings in unipolar depression without motor retardation resembled findings in the manic state, which further resembled findings from previous studies of schizophrenia and glutamate antagonism. Results from the euthymic bipolar group with unstable rest-activity cycles resembled variability findings in activity during affective episodes. Here, the activity findings could be associated to mood variability and/or circadian instability. In conclusion, activity characteristics are potentially important clinical signatures of affective disorders, and it may be possible to distinguish phenotypically different subgroups based on activity levels and patterns. Actigraphy recordings combined with a set of advanced analytical methods from linear and non-linear dynamics could provide a future diagnostic and prognostic tool in affective disorders, of importance to the accuracy of diagnostics, treatment response, prevention and classification of disease.

Norsk sammendrag - Norsk tittel: Aktigrafi ved stemningslidelser Det er i dag ingen objektive mål på symptomene ved psykiske lidelser. I dette doktorgradsarbeidet er det vist at mennesker med ulike former for depresjoner og manier har bevegelsesmønstre som skiller seg fra hverandre. Akuttinnlagte pasienter med stemningslidelser (bipolar lidelse og depresjon) har gått med en bevegelsesmåler (aktigraf) i 24 timer under innleggelse ved avdeling Østmarka, St Olavs Hospital. Ved bruk av avanserte matematiske metoder ble mengde bevegelse, grad av variasjon og stabilitet av aktivitet beregnet. Ved alle depresjonstyper var det lav gjennomsnittsaktivitet og høy variasjon av aktivitet sammenlignet med hos friske personer. Det var også objektive forskjeller i aktivitetsmønstre mellom de pasientene med depresjon som etter legenes vurdering hadde langsomme kroppsbevegelser (såkalt psykomotorisk retardasjon) og deprimerte som var motorisk urolige. De deprimerte pasientene som var mer urolige, hadde et uorganisert bevegelsesmønster som lignet mønsteret for pasienter med mani. I en annen studie av pasienter som var i stabil fase av bipolar lidelse og som samtidig hadde søvnvansker, fant vi at de som ikke hadde stabil døgnrytme, var yngre, og en større andel hadde forsinket søvnfase og hyppige dag-til-dag-forandringer i stemningsleie. Det var også forskjeller i bevegelsesmønstrene mellom gruppene. Analyser av bevegelsesmønstre målt ved hjelp av instrumenter på størrelse med et armbåndsur, kan trolig utvikles til å skille undergrupper med stemningslidelser fra hverandre og få betydning for klassifisering og behandling av depresjoner og manier både ved tilbakevendende depresjoner og ved bipolar lidelse.