Impact of COVID-19 Pandemic on Sleep Quality, Stress Level and Health-Related Quality of Life-A Large Prospective Cohort Study on Adult Danes

The everyday lives of Danish inhabitants have been affected by the COVID-19 pandemic, e.g., by social distancing, which was employed by the government in March 2020 to prevent the spread of SARS-CoV-2. Moreover, the pandemic has entailed economic consequences for many people. This study aims to assess changes in physical and mental health-related quality of life (MCS, PCS), in stress levels, and quality of sleep during the COVID-19 pandemic and to identify factors that impact such changes, using a prospective national cohort study including 26,453 participants from the Danish Blood Donor Study who answered a health questionnaire before the pandemic and during the pandemic. Descriptive statistics, multivariable linear and multinomial logistic regression analyses were applied. A worsening of MCS and quality of sleep was found, and an overall decrease in stress levels was observed. PCS was decreased in men and slightly increased in women. The extent of health changes was mainly affected by changes in job situation, type of job, previous use of anti-depressive medication and the participants’ level of personal stamina. Thus, living under the unusual circumstances that persisted during the COVID-19 pandemic has had a negative impact on the health of the general population. This may, in time, constitute a public health problem

Diagnostic stability among chronic patients with functional psychoses: an epidemiological and clinical study

<p>Abstract</p> <p>Background</p> <p>Diagnostic stability and illness course of chronic non-organic psychoses are complex phenomena and only few risk factors or predictors are known that can be used reliably. This study investigates the diagnostic stability during the entire course of illness in patients with non-organic psychoses and attempts to identify non-psychopathological risk factors or predictors.</p> <p>Method</p> <p>100 patients with functional psychosis were initially characterised using the Operational Criteria Checklist for Psychotic Illness and Affective Illness (OPCRIT), medical records and health registers. To study the stability of diagnoses (i.e. shifts per time), we used registry data to define four measures of diagnostic variation that were subsequently examined in relation to four possible measures of time (i.e. observation periods or hospitalisation events). Afterwards, we identified putative co-variables and predictors of the best measures of diagnostic stability.</p> <p>Results</p> <p>All four measures of diagnostic variation are very strongly associated with numbers-of-hospitalisations and less so with duration-of-illness, duration-of-hospitalisation and with year-of-first-admission. The four measures of diagnostic variation corrected for numbers-of-hospitalisations were therefore used to study the diagnostic stability. Conventional predictors of illness course – e.g. age-of-onset and premorbid-functioning – are not significantly associated with stability. Only somatic-comorbidity is significantly associated with two measures of stability, while family-history-of-psychiatric-illness and global-assessment-of-functioning (GAF) scale score show a trend. However, the traditional variables age-of-first-admission, civil-status, first-diagnosis-being-schizophrenia and somatic-comorbidity are able to explain two-fifth of the variation in numbers-of-hospitalisations.</p> <p>Conclusion</p> <p>Diagnostic stability is closely linked with the contact between patient and the healthcare system. This could very likely be due to fluctuation of disease manifestation over time or presence of co-morbid psychiatric illness in combination with rigid diagnostic criteria that are unable to capture the multiple psychopathologies of the functional psychoses that results in differential diagnoses and therefore diagnostic instability. Not surprisingly, somatic-comorbidity was found to be a predictor of diagnostic variation thereby being a non-psychiatric confounder.</p

A mouse model of the schizophrenia-associated 1q21.1 microdeletion syndrome exhibits altered mesolimbic dopamine transmission

Abstract 1q21.1 hemizygous microdeletion is a copy number variant leading to eightfold increased risk of schizophrenia. In order to investigate biological alterations induced by this microdeletion, we generated a novel mouse model (Df(h1q21)/+) and characterized it in a broad test battery focusing on schizophrenia-related assays. Df(h1q21)/+ mice displayed increased hyperactivity in response to amphetamine challenge and increased sensitivity to the disruptive effects of amphetamine and phencyclidine hydrochloride (PCP) on prepulse inhibition. Probing of the direct dopamine (DA) pathway using the DA D1 receptor agonist SKF-81297 revealed no differences in induced locomotor activity compared to wild-type mice, but Df(h1q21)/+ mice showed increased sensitivity to the DA D2 receptor agonist quinpirole and the D1/D2 agonist apomorphine. Electrophysiological characterization of DA neuron firing in the ventral tegmental area revealed more spontaneously active DA neurons and increased firing variability in Df(h1q21)/+ mice, and decreased feedback reduction of DA neuron firing in response to amphetamine. In a range of other assays, Df(h1q21)/+ mice showed no difference from wild-type mice: gross brain morphology and basic functions such as reflexes, ASR, thermal pain sensitivity, and motor performance were unaltered. Similarly, anxiety related measures, baseline prepulse inhibition, and seizure threshold were unaltered. In addition to the central nervous system-related phenotypes, Df(h1q21)/+ mice exhibited reduced head-to tail length, which is reminiscent of the short stature reported in humans with 1q21.1 deletion. With aspects of both construct and face validity, the Df(h1q21)/+ model may be used to gain insight into schizophrenia-relevant alterations in dopaminergic transmission

Restless legs syndrome is associated with major comorbidities in a population of Danish blood donors.

BACKGROUND: Restless Legs Syndrome (RLS) is characterized by uncomfortable nocturnal sensations in the legs making sedentary activities and sleep difficult, and is thus linked with psychosocial distress. Due to the symptomatology and neurobiology of RLS (disrupting brain iron and dopamine) it is likely that RLS associates with poorer health-related quality of life (HRQL) and depressive disorder. The objective of this study was to investigate the RLS-HRQL and the RLS-depressive disorder links in a generally healthy population that is not biased by medications. METHODS: Complete data, including the Cambridge-Hopkins RLS questionnaire, the 12-item short-form standardized health survey (SF-12), the Major Depression Inventory (MDI), body mass index, smoking status, alcohol consumption, and education were available for 24,707 participants enrolled in the Danish Blood Donor Study from May 1, 2015 to February 1, 2017. Information on quality of sleep was available for all RLS cases. T-tests and multivariable logistic regression models were applied to examine the associations of RLS and MDI scores, and the physical and mental component scores (PCS and MCS) of SF-12, respectively. Analyses were conducted separately for men and women. RESULTS: RLS associated with poorer MCS and poorer PCS. Moreover, Participants with RLS were more likely to classify with depressive disorder. Poor quality of sleep was associated with depressive disorder and poorer MCS among RLS cases, and with poorer PCS in female RLS cases. CONCLUSION: Thus, we demonstrated that RLS is associated with a significantly lower HRQL and a higher prevalence of depressive disorder among otherwise healthy individuals

Genome-wide association study of school grades identifies genetic overlap between language ability, psychopathology and creativity

Cognitive functions of individuals with psychiatric disorders differ from that of the general population. Such cognitive differences often manifest early in life as differential school performance and have a strong genetic basis. Here we measured genetic predictors of school performance in 30,982 individuals in English, Danish and mathematics via a genome-wide association study (GWAS) and studied their relationship with risk for six major psychiatric disorders. When decomposing the school performance into math and language-specific performances, we observed phenotypically and genetically a strong negative correlation between math performance and risk for most psychiatric disorders. But language performance correlated positively with risk for certain disorders, especially schizophrenia, which we replicate in an independent sample (n = 4547). We also found that the genetic variants relating to increased risk for schizophrenia and better language performance are overrepresented in individuals involved in creative professions (n = 2953) compared to the general population (n = 164,622). The findings together suggest that language ability, creativity and psychopathology might stem from overlapping genetic roots.Peer reviewe

Dose-Specific Adverse Drug Reaction Identification in Electronic Patient Records: Temporal Data Mining in an Inpatient Psychiatric Population

BACKGROUND: Data collected for medical, filing and administrative purposes in electronic patient records (EPRs) represent a rich source of individualised clinical data, which has great potential for improved detection of patients experiencing adverse drug reactions (ADRs), across all approved drugs and across all indication areas. OBJECTIVES: The aim of this study was to take advantage of techniques for temporal data mining of EPRs in order to detect ADRs in a patient- and dose-specific manner. METHODS: We used a psychiatric hospital’s EPR system to investigate undesired drug effects. Within one workflow the method identified patient-specific adverse events (AEs) and links these to specific drugs and dosages in a temporal manner, based on integration of text mining results and structured data. The structured data contained precise information on drug identity, dosage and strength. RESULTS: When applying the method to the 3,394 patients in the cohort, we identified AEs linked with a drug in 2,402 patients (70.8 %). Of the 43,528 patient-specific drug substances prescribed, 14,736 (33.9 %) were linked with AEs. From these links we identified multiple ADRs (p < 0.05) and found them to occur at similar frequencies, as stated by the manufacturer and in the literature. We showed that drugs displaying similar ADR profiles share targets, and we compared submitted spontaneous AE reports with our findings. For nine of the ten most prescribed antipsychotics in the patient population, larger doses were prescribed to sedated patients than non-sedated patients; five patients exhibited a significant difference (p < 0.05). Finally, we present two cases (p < 0.05) identified by the workflow. The method identified the potentially fatal AE QT prolongation caused by methadone, and a non-described likely ADR between levomepromazine and nightmares found among the hundreds of identified novel links between drugs and AEs (p < 0.05). CONCLUSIONS: The developed method can be used to extract dose-dependent ADR information from already collected EPR data. Large-scale AE extraction from EPRs may complement or even replace current drug safety monitoring methods in the future, reducing or eliminating manual reporting and enabling much faster ADR detection. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s40264-014-0145-z) contains supplementary material, which is available to authorised users

The population genomic legacy of the second plague pandemic

Human populations have been shaped by catastrophes that may have left long-lasting signatures in their genomes. One notable example is the second plague pandemic that entered Europe in ca. 1,347 CE and repeatedly returned for over 300 years, with typical village and town mortality estimated at 10%–40%.1 It is assumed that this high mortality affected the gene pools of these populations. First, local population crashes reduced genetic diversity. Second, a change in frequency is expected for sequence variants that may have affected survival or susceptibility to the etiologic agent (Yersinia pestis).2 Third, mass mortality might alter the local gene pools through its impact on subsequent migration patterns. We explored these factors using the Norwegian city of Trondheim as a model, by sequencing 54 genomes spanning three time periods: (1) prior to the plague striking Trondheim in 1,349 CE, (2) the 17th–19th century, and (3) the present. We find that the pandemic period shaped the gene pool by reducing long distance immigration, in particular from the British Isles, and inducing a bottleneck that reduced genetic diversity. Although we also observe an excess of large FST values at multiple loci in the genome, these are shaped by reference biases introduced by mapping our relatively low genome coverage degraded DNA to the reference genome. This implies that attempts to detect selection using ancient DNA (aDNA) datasets that vary by read length and depth of sequencing coverage may be particularly challenging until methods have been developed to account for the impact of differential reference bias on test statistics.publishedVersio