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the benefits of physical activity (PA) and sleep for health, accurate and objective population-based surveillance is important. Monitor-based surveillance has potential, but the main challenge is the need for replicable outcomes from different monitors. This study investigated the agreement of movement behavior outcomes assessed with four research-grade activity monitors (i.e., Movisens Move4, ActiGraph GT3X+, GENEActiv, and Axivity AX3) in adults. Twenty-three participants wore four monitors on the non-dominant wrist simultaneously for seven days. Open-source software (GGIR) was used to estimate the daily time in sedentary, light, moderate-to-vigorous PA (MVPA), and sleep (movement behaviors). The prevalence of participants meeting the PA and sleep recommendations were calculated from each monitor’s data. Outcomes were deemed equivalent between monitors if the absolute standardized difference and its 95% confidence intervals (CI95%) fell within ± 0.2 standard deviations (SD) of the mean of the differences. The participants were mostly men (n = 14, 61%) and aged 36 (SD = 14) years. Pairwise confusion matrices showed that 83–87% of the daily time was equally classified into the movement categories by the different pairs of monitors. The between-monitor difference in MVPA ranged from 1 (CI95%: − 6, 7) to 8 (CI95%: 1, 15) min/day. Most of the PA and sleep metrics could be considered equivalent. The prevalence of participants meeting the PA and the sleep guidelines was 100% consistent across monitors (22 and 5 participants out of the 23, respectively). Our findings indicate that the various research-grade activity monitors investigated show high inter-instrument reliability with respect to sedentary, PA and sleep-related estimates when their raw data are processed in an identical manner. These findings may have important implications for advancement towards monitor-based PA and sleep surveillance systems.
Attention-deficit hyperactivity disorder (ADHD) is a complex neurodevelopmental disorder characterized by hyperactivity, impulsivity, and/or inattention, which are symptoms also observed in many rare genetic disorders. We searched for genes involved in Mendelian disorders presenting with ADHD symptoms in the Online Mendelian Inheritance in Man (OMIM) database, to curate a list of new candidate risk genes for ADHD. We explored the enrichment of functions and pathways in this gene list, and tested whether rare or common variants in these genes are associated with ADHD or with its comorbidities. We identified 139 genes, causal for 137 rare disorders, mainly related to neurodevelopmental and brain function. Most of these Mendelian disorders also present with other psychiatric traits that are often comorbid with ADHD. Using whole exome sequencing (WES) data from 668 ADHD cases, we found rare variants associated with the dimension of the severity of inattention symptoms in three genes: KIF11, WAC, and CRBN. Then, we focused on common variants and identified six genes associated with ADHD (in 19,099 cases and 34,194 controls): MANBA, UQCC2, HIVEP2, FOPX1, KANSL1, and AUH. Furthermore, HIVEP2, FOXP1, and KANSL1 were nominally associated with autism spectrum disorder (ASD) (18,382 cases and 27,969 controls), as well as HIVEP2 with anxiety (7016 cases and 14,475 controls), and FOXP1 with aggression (18,988 individuals), which is in line with the symptomatology of the rare disorders they are responsible for. In conclusion, inspecting Mendelian disorders and the genes responsible for them constitutes a valuable approach for identifying new risk genes and the mechanisms of complex disorders.
Highligths
• Immune-inflammatory alterations might appear in subjects with ADHD.
• Blood levels of tumor necrosis factor-α might be reduced in individuals with ADHD.
• Individuals with ADHD might show elevated blood levels of interleukin-6.
Abstract
It has been observed that subclinical inflammation might be involved in the pathophysiology of attention deficit/hyperactivity disorder (ADHD). However, studies investigating peripheral blood levels of immune-inflammatory markers have provided mixed findings. We performed a systematic review and meta-analysis of studies comparing unstimulated serum or plasma levels of C-reactive protein (CRP) and cytokines in subjects with ADHD and healthy controls (the PROSPERO registration number: CRD 42021276869). Online searches covered the publication period until 30th Sep 2021 and random-effects meta-analyses were carried out. Out of 1844 publication records identified, 10 studies were included. The levels of interleukin (IL)-6 were significantly higher in studies of participants up to the age of 18 years (k = 10, g = 0.70, 95%CI: 0.10–1.30, p = 0.023) and after including those above the age of 18 years (k = 10, g = 0.71, 95%CI: 0.12–1.31, p = 0.019). In turn, the levels of tumor necrosis factor-α (TNF-α) were significantly lower in subjects with ADHD compared to healthy controls (k = 7, g = −0.16, 95%CI: −0.30 - -0.03, p = 0.020). Individual studies had a high contribution to the overall effect, since the overall effect was no longer significant after removing single studies. No significant differences were found with respect to the levels of CRP, IL-1β, IL-10 and interferon-γ. The present findings indicate that individuals with ADHD tend to show elevated levels of IL-6 and reduced levels of TNF-α. Larger and longitudinal studies recording potential confounding factors and comorbid psychopathology are needed to confirm our findings.
Introduction: Bipolar disorder (BD) is characterized by recurrent episodes of depression and mania and affects up to 2% of the population worldwide. Patients suffering from bipolar disorder have a reduced life expectancy of up to 10 years. The increased mortality might be due to a higher rate of somatic diseases, especially cardiovascular diseases. There is however also evidence for an increased rate of diabetes mellitus in BD, but the reported prevalence rates vary by large.
Material and Methods: 85 bipolar disorder patients were recruited in the framework of the BiDi study (Prevalence and clinical features of patients with Bipolar Disorder at High Risk for Type 2 Diabetes (T2D), at prediabetic state and with manifest T2D) in Dresden and Würzburg. T2D and prediabetes were diagnosed measuring HBA1c and an oral glucose tolerance test (oGTT), which at present is the gold standard in diagnosing T2D. The BD sample was compared to an age-, sex- and BMI-matched control population (n = 850) from the Study of Health in Pomerania cohort (SHIP Trend Cohort).
Results: Patients suffering from BD had a T2D prevalence of 7%, which was not significantly different from the control group (6%). Fasting glucose and impaired glucose tolerance were, contrary to our hypothesis, more often pathological in controls than in BD patients. Nondiabetic and diabetic bipolar patients significantly differed in age, BMI, number of depressive episodes, and disease duration.
Discussion: When controlled for BMI, in our study there was no significantly increased rate of T2D in BD. We thus suggest that overweight and obesity might be mediating the association between BD and diabetes. Underlying causes could be shared risk genes, medication effects, and lifestyle factors associated with depressive episodes. As the latter two can be modified, attention should be paid to weight changes in BD by monitoring and taking adequate measures to prevent the alarming loss of life years in BD patients.
Background: Bipolar disorder is associated with circadian disruption and a high risk of suicidal behavior. In a previous exploratory study of patients with bipolar I disorder, we found that a history of suicide attempts was associated with differences between winter and summer levels of solar insolation. The purpose of this study was to confirm this finding using international data from 42% more collection sites and 25% more countries. Methods: Data analyzed were from 71 prior and new collection sites in 40 countries at a wide range of latitudes. The analysis included 4876 patients with bipolar I disorder, 45% more data than previously analyzed. Of the patients, 1496 (30.7%) had a history of suicide attempt. Solar insolation data, the amount of the sun’s electromagnetic energy striking the surface of the earth, was obtained for each onset location (479 locations in 64 countries). Results: This analysis confirmed the results of the exploratory study with the same best model and slightly better statistical significance. There was a significant inverse association between a history of suicide attempts and the ratio of mean winter insolation to mean summer insolation (mean winter insolation/mean summer insolation). This ratio is largest near the equator which has little change in solar insolation over the year, and smallest near the poles where the winter insolation is very small compared to the summer insolation. Other variables in the model associated with an increased risk of suicide attempts were a history of alcohol or substance abuse, female gender, and younger birth cohort. The winter/summer insolation ratio was also replaced with the ratio of minimum mean monthly insolation to the maximum mean monthly insolation to accommodate insolation patterns in the tropics, and nearly identical results were found. All estimated coefficients were significant at p < 0.01. Conclusion: A large change in solar insolation, both between winter and summer and between the minimum and maximum monthly values, may increase the risk of suicide attempts in bipolar I disorder. With frequent circadian rhythm dysfunction and suicidal behavior in bipolar disorder, greater understanding of the optimal roles of daylight and electric lighting in circadian entrainment is needed.
Juvenile myoclonic epilepsy (JME) is a common epilepsy syndrome characterized by bilateral myoclonic and tonic-clonic seizures typically starting in adolescence and responding well to medication. Misdiagnosis of a more severe progressive myoclonus epilepsy (PME) as JME has been suggested as a cause of drug-resistance. Medical records of the Epilepsy Center Hessen-Marburg between 2005 and 2014 were automatically selected using keywords and manually reviewed regarding the presence of a JME diagnosis at any timepoint. The identified patients were evaluated regarding seizure outcome and drug resistance according to ILAE criteria. 87/168 identified JME patients were seizure-free at last follow-up including 61 drug-responsive patients (group NDR). Seventy-eight patients were not seizure-free including 26 drug-resistant patients (group DR). Valproate was the most efficacious AED. The JME diagnosis was revised in 7 patients of group DR including 6 in whom the diagnosis had already been questioned or revised during clinical follow-up. One of these was finally diagnosed with PME (genetically confirmed Lafora disease) based on genetic testing. She was initially reviewed at age 29 yrs and considered to be inconsistent with PME. Intellectual disability (p = 0.025), cognitive impairment (p < 0.001), febrile seizures in first-degree relatives (p = 0.023) and prominent dialeptic seizures (p = 0.009) where significantly more frequent in group DR. Individuals with PME are rarely found among drug-resistant alleged JME patients in a tertiary epilepsy center. Even a very detailed review by experienced epileptologists may not identify the presence of PME before the typical features evolve underpinning the need for early genetic testing in drug-resistant JME patients.
Attention-Deficit/Hyperactivity Disorder (ADHD) and obesity are frequently comorbid, genetically correlated, and share brain substrates. The biological mechanisms driving this association are unclear, but candidate systems, like dopaminergic neurotransmission and circadian rhythm, have been suggested. Our aim was to identify the biological mechanisms underpinning the genetic link between ADHD and obesity measures and investigate associations of overlapping genes with brain volumes. We tested the association of dopaminergic and circadian rhythm gene sets with ADHD, body mass index (BMI), and obesity (using GWAS data of N=53,293, N=681,275, and N=98,697, respectively). We then conducted genome-wide ADHD-BMI and ADHD-obesity gene-based meta-analyses, followed by pathway enrichment analyses. Finally, we tested the association of ADHD-BMI overlapping genes with brain volumes (primary GWAS data N=10,720–10,928; replication data N=9,428). The dopaminergic gene set was associated with both ADHD (P=5.81×10−3) and BMI (P=1.63×10−5), the circadian rhythm was associated with BMI (P=1.28×10−3). The genome-wide approach also implicated the dopaminergic system, as the Dopamine-DARPP32 Feedback in cAMP Signaling pathway was enriched in both ADHD-BMI and ADHD-obesity results. The ADHD-BMI overlapping genes were associated with putamen volume (P=7.7×10−3; replication data P=3.9×10−2) – a brain region with volumetric reductions in ADHD and BMI and linked to inhibitory control. Our findings suggest that dopaminergic neurotransmission, partially through DARPP-32-dependent signaling and involving the putamen, is a key player underlying the genetic overlap between ADHD and obesity measures. Uncovering shared etiological factors underlying the frequently observed ADHD-obesity comorbidity may have important implications in terms of prevention and/or efficient treatment of these conditions.
Genes encoding endocannabinoid and sphingolipid metabolism pathways were suggested to contribute to the genetic risk towards attention deficit hyperactivity disorder (ADHD). The present pilot study assessed plasma concentrations of candidate endocannabinoids, sphingolipids and ceramides in individuals with adult ADHD in comparison with healthy controls and patients with affective disorders. Targeted lipid analyses of 23 different lipid species were performed in 71 mental disorder patients and 98 healthy controls (HC). The patients were diagnosed with adult ADHD (n = 12), affective disorder (major depression, MD n = 16 or bipolar disorder, BD n = 6) or adult ADHD with comorbid affective disorders (n = 37). Canonical discriminant analysis and CHAID analyses were used to identify major components that predicted the diagnostic group. ADHD patients had increased plasma concentrations of sphingosine-1-phosphate (S1P d18:1) and sphinganine-1-phosphate (S1P d18:0). In addition, the endocannabinoids, anandamide (AEA) and arachidonoylglycerol were increased. MD/BD patients had increased long chain ceramides, most prominently Cer22:0, but low endocannabinoids in contrast to ADHD patients. Patients with ADHD and comorbid affective disorders displayed increased S1P d18:1 and increased Cer22:0, but the individual lipid levels were lower than in the non-comorbid disorders. Sphingolipid profiles differ between patients suffering from ADHD and affective disorders, with overlapping patterns in comorbid patients. The S1P d18:1 to Cer22:0 ratio may constitute a diagnostic or prognostic tool.
Introduction: Affective disorders are a major global burden, with approximately 15% of people worldwide suffering from some form of affective disorder. In patients experiencing their first depressive episode, in most cases it cannot be distinguished whether this is due to bipolar disorder (BD) or major depressive disorder (MDD). Valid fluid biomarkers able to discriminate between the two disorders in a clinical setting are not yet available.
Material and Methods: Seventy depressed patients suffering from BD (bipolar I and II subtypes) and 42 patients with major MDD were recruited and blood samples were taken for proteomic analyses after 8 h fasting. Proteomic profiles were analyzed using the Multiplex Immunoassay platform from Myriad Rules Based Medicine (Myriad RBM; Austin, Texas, USA). Human DiscoveryMAPTM was used to measure the concentration of various proteins, peptides, and small molecules. A multivariate predictive model was consequently constructed to differentiate between BD and MDD.
Results: Based on the various proteomic profiles, the algorithm could discriminate depressed BD patients from MDD patients with an accuracy of 67%.
Discussion: The results of this preliminary study suggest that future discrimination between bipolar and unipolar depression in a single case could be possible, using predictive biomarker models based on blood proteomic profiling.
Neurometabolic diseases (NMDs) are typically caused by genetic abnormalities affecting enzyme functions, which in turn interfere with normal development and activity of the nervous system. Although the individual disorders are rare, NMDs are collectively relatively common and often lead to lifelong difficulties and high societal costs. Neuropsychiatric manifestations, including ADHD symptoms, are prominent in many NMDs, also when the primary biochemical defect originates in cells and tissues outside the nervous system. ADHD symptoms have been described in phenylketonuria, tyrosinemias, alkaptonuria, succinic semialdehyde dehydrogenase deficiency, X-linked ichthyosis, maple syrup urine disease, and several mitochondrial disorders, but are probably present in many other NMDs and may pose diagnostic and therapeutic challenges. Here we review current literature linking NMDs with ADHD symptoms. We cite emerging evidence that many NMDs converge on common neurochemical mechanisms that interfere with monoamine neurotransmitter synthesis, transport, metabolism, or receptor functions, mechanisms that are also considered central in ADHD pathophysiology and treatment. Finally, we discuss the therapeutic implications of these findings and propose a path forward to increase our understanding of these relationships.