-
NeuroImage Aug 2024The perspective of personalized medicine for brain disorders requires efficient learning models for anatomical neuroimaging-based prediction of clinical conditions....
The perspective of personalized medicine for brain disorders requires efficient learning models for anatomical neuroimaging-based prediction of clinical conditions. There is now a consensus on the benefit of deep learning (DL) in addressing many medical imaging tasks, such as image segmentation. However, for single-subject prediction problems, recent studies yielded contradictory results when comparing DL with Standard Machine Learning (SML) on top of classical feature extraction. Most existing comparative studies were limited in predicting phenotypes of little clinical interest, such as sex and age, and using a single dataset. Moreover, they conducted a limited analysis of the employed image pre-processing and feature selection strategies. This paper extensively compares DL and SML prediction capacity on five multi-site problems, including three increasingly complex clinical applications in psychiatry namely schizophrenia, bipolar disorder, and Autism Spectrum Disorder (ASD) diagnosis. To compensate for the relative scarcity of neuroimaging data on these clinical datasets, we also evaluate three pre-training strategies for transfer learning from brain imaging of the general healthy population: self-supervised learning, generative modeling and supervised learning with age. Overall, we find similar performance between randomly initialized DL and SML for the three clinical tasks and a similar scaling trend for sex prediction. This was replicated on an external dataset. We also show highly correlated discriminative brain regions between DL and linear ML models in all problems. Nonetheless, we demonstrate that self-supervised pre-training on large-scale healthy population imaging datasets (N≈10k), along with Deep Ensemble, allows DL to learn robust and transferable representations to smaller-scale clinical datasets (N≤1k). It largely outperforms SML on 2 out of 3 clinical tasks both in internal and external test sets. These findings suggest that the improvement of DL over SML in anatomical neuroimaging mainly comes from its capacity to learn meaningful and useful abstract representations of the brain anatomy, and it sheds light on the potential of transfer learning for personalized medicine in psychiatry.
Topics: Humans; Neuroimaging; Female; Schizophrenia; Male; Deep Learning; Adult; Brain; Machine Learning; Autism Spectrum Disorder; Bipolar Disorder; Middle Aged; Young Adult; Psychiatry
PubMed: 38848981
DOI: 10.1016/j.neuroimage.2024.120665 -
JAMA Network Open Jun 2024Alcohol use disorder (AUD) is present in nearly half of individuals with bipolar disorder (BD) and is associated with markedly worsening outcomes. Yet, the concurrent...
IMPORTANCE
Alcohol use disorder (AUD) is present in nearly half of individuals with bipolar disorder (BD) and is associated with markedly worsening outcomes. Yet, the concurrent treatment of BD and AUD remains neglected in both research and clinical care; characterizing their dynamic interplay is crucial in improving outcomes.
OBJECTIVE
To characterize the longitudinal alcohol use patterns in BD and examine the temporal associations among alcohol use, mood, anxiety, and functioning over time.
DESIGN, SETTING, AND PARTICIPANTS
This cohort study selected participants and analyzed data from the Prechter Longitudinal Study of Bipolar Disorder (PLS-BD), an ongoing cohort study that recruits through psychiatric clinics, mental health centers, and community outreach events across Michigan and collects repeated phenotypic data. Participants selected for the present study were those with a diagnosis of BD type I (BDI) or type II (BDII) who had been in the study for at least 5 years. Data used were extracted from February 2006 to April 2022, and follow-up ranged from 5 to 16 years.
MAIN OUTCOMES AND MEASURES
Alcohol use was measured using the Alcohol Use Disorders Identification Test. Depression, mania or hypomania, anxiety, and functioning were measured using the 9-Item Patient Health Questionnaire, the Altman Self-Rating Mania Scale, the 7-item Generalized Anxiety Disorder assessment scale, and the Life Functioning Questionnaire, respectively.
RESULTS
A total of 584 individuals (386 females (66.1%); mean [SD] age, 40 [13.6] years) were included. These participants had a BDI (445 [76.2%]) or BDII (139 [23.8%]) diagnosis, with or without a lifetime diagnosis of AUD, and a median (IQR) follow-up of 9 (0-16) years. More problematic alcohol use was associated with worse depressive (β = 0.04; 95% credibility interval [CrI], 0.01-0.07) and manic or hypomanic symptoms (β = 0.04; 95% CrI, 0.01-0.07) as well as lower workplace functioning (β = 0.03; 95% CrI, 0.00-0.06) over the next 6 months, but increased depressive and manic or hypomanic symptoms were not associated with greater subsequent alcohol use. These latter 2 associations were more pronounced in BDII than BDI (mania or hypomania: β = 0.16 [95% CrI, 0.02-0.30]; workplace functioning: β = 0.26 [95% CrI, 0.06-0.45]). Alcohol use was not associated with anxiety over time.
CONCLUSIONS AND RELEVANCE
This study found that alcohol use, regardless of diagnostic status, was associated with mood instability and poorer work functioning in BD, but increased mood symptoms were not associated with subsequent alcohol use. Given its prevalence and repercussions, dimensional and longitudinal assessment and management of alcohol use are necessary and should be integrated into research and standard treatment of BD.
Topics: Humans; Bipolar Disorder; Female; Male; Adult; Longitudinal Studies; Middle Aged; Alcohol Drinking; Alcoholism; Affect; Michigan; Anxiety
PubMed: 38848066
DOI: 10.1001/jamanetworkopen.2024.15295 -
Frontiers in Psychiatry 2024A high homocysteine (Hcy) level is a risk factor for schizophrenia, depression, and bipolar disorder. However, the role of hyperhomocysteinemia as either an independent...
A high homocysteine (Hcy) level is a risk factor for schizophrenia, depression, and bipolar disorder. However, the role of hyperhomocysteinemia as either an independent factor or an auxiliary contributor to specific psychiatric symptoms or disorders remains unclear. This study aimed to examine Hcy levels in first-episode inpatients with psychotic symptoms and various psychiatric diseases to elucidate the association between Hcy levels and psychiatric disorders. This study enrolled 191 patients (aged 18-40 years) with psychiatric disorders. Seventy-five patients were diagnosed with schizophrenia, 48 with acute and transient psychotic disorders, 36 with manic episodes with psychosis, 32 with major depressive episodes with psychosis, and 56 healthy controls. Serum Hcy levels were measured using the enzyme cycle method. A Hcy concentration level of > 15 μmol/L was defined as hyperhomocysteinemia. Hcy levels were significantly higher in first-episode patients with psychiatric disorders compared to healthy controls (5.99 ± 3.60 vs. 19.78 ± 16.61 vs. 15.50 ± 9.08 vs. 20.00 ± 11.33 vs. 16.22 ± 12.06, = 12.778, < 0.001). Hcy levels were significantly higher in males with schizophrenia, acute and transient psychotic disorder, and major depressive disorder but not in mania [schizophrenia, ( = -4.727, < 0.001); acute and transient psychotic disorders, ( = -3.389, = 0.001); major depressive episode with psychosis, ( = -3.796, < 0.001); manic episodes with psychosis, ( = -1.684, = 0.101)]. However, serum Hcy levels were not significantly different among the psychiatric disorder groups ( = 0.139, = 0.968). Multivariate linear regression showed that males had an increased risk for homocysteinemia. (95% CI = 8.192-15.370, < 0.001). These results suggest that first-episode patients with psychiatric disorders have higher Hcy levels than in the general population, and men are at greater risk for psychiatric disorders. In conclusion, elevated Hcy levels may contribute to the pathogenesis of first-episode patients with psychotic symptoms.
PubMed: 38846917
DOI: 10.3389/fpsyt.2024.1380900 -
Sleep Science (Sao Paulo, Brazil) Jun 2024Insomnia is highly prevalent among individuals with Attention-Deficit/Hyperactivity Disorder (ADHD). However, the biological mechanisms shared between both...
Insomnia is highly prevalent among individuals with Attention-Deficit/Hyperactivity Disorder (ADHD). However, the biological mechanisms shared between both conditions is still elusive. We aimed to investigate whether insomnia's genomic component is able to predict ADHD in childhood and adolescence. A Brazilian sample of 259 ADHD probands and their biological parents were included in the study. Their genomic DNA genotypes were used to construct the polygenic risk score for insomnia (Insomnia PRS), using the largest GWAS summary statistics as a discovery sample. The association was tested using logistic regression, under a case-pseudocontrol design. Insomnia PRS was nominally associated with ADHD (OR = 1.228, = 0.022), showing that the alleles that increase the risk for insomnia also increase the risk for ADHD. Our results suggest that genetic factors associated with insomnia may play a role in the ADHD genetic etiology, with both phenotypes likely to have a shared genetic mechanism.
PubMed: 38846582
DOI: 10.1055/s-0043-1777787 -
Frontiers in Neurology 2024The prevalence of comorbid pain and Bipolar Disorder in clinical practice continues to be high, with an increasing number of related publications. However, no study has...
PURPOSE
The prevalence of comorbid pain and Bipolar Disorder in clinical practice continues to be high, with an increasing number of related publications. However, no study has used bibliometric methods to analyze the research progress and knowledge structure in this field. Our research is dedicated to systematically exploring the global trends and focal points in scientific research on pain comorbidity with bipolar disorder from 2003 to 2023, with the goal of contributing to the field.
METHODS
Relevant publications in this field were retrieved from the Web of Science core collection database (WOSSCC). And we used VOSviewer, CiteSpace, and the R package "Bibliometrix" for bibliometric analysis.
RESULTS
A total of 485 publications (including 360 articles and 125 reviews) from 66 countries, 1019 institutions, were included in this study. Univ Toront and Kings Coll London are the leading research institutions in this field. J Affect Disorders contributed the largest number of articles, and is the most co-cited journal. Of the 2,537 scholars who participated in the study, Stubbs B, Vancampfort D, and Abdin E had the largest number of articles. Stubbs B is the most co-cited author. "chronic pain," "neuropathic pain," "psychological pain" are the keywords in the research.
CONCLUSION
This is the first bibliometric analysis of pain-related bipolar disorder. There is growing interest in the area of pain and comorbid bipolar disorder. Focusing on different types of pain in bipolar disorder and emphasizing pain management in bipolar disorder are research hotspots and future trends. The study of pain related bipolar disorder still has significant potential for development, and we look forward to more high-quality research in the future.
PubMed: 38846044
DOI: 10.3389/fneur.2024.1393022 -
The Australian and New Zealand Journal... Jun 2024Harmonized tools are essential for reliable data sharing and accurate identification of relevant factors in mental health research. The primary objective of this study... (Review)
Review
OBJECTIVE
Harmonized tools are essential for reliable data sharing and accurate identification of relevant factors in mental health research. The primary objective of this study was to create a harmonized questionnaire to collect demographic, clinical and behavioral data in diverse clinical trials in adult psychiatry.
METHODS
We conducted a literature review and examined 24 questionnaires used in previously published randomized controlled trials in psychiatry, identifying a total of 27 domains previously explored. Using a Delphi-method process, a task force team comprising experts in psychiatry, epidemiology and statistics selected 15 essential domains for inclusion in the final questionnaire.
RESULTS
The final selection resulted in a concise set of 22 questions. These questions cover factors such as age, sex, gender, ancestry, education, living arrangement, employment status, home location, relationship status, and history of medical and mental illness. Behavioral factors like physical activity, diet, smoking, alcohol and illicit drug use were also included, along with one question addressing family history of mental illness. Income was excluded due to high confounding and redundancy, while language was included as a measure of migration status.
CONCLUSION
The recommendation and adoption of this harmonized tool for the assessment of demographic, clinical and behavioral data in mental health research can enhance data consistency and enable comparability across clinical trials.
PubMed: 38845137
DOI: 10.1177/00048674241253452 -
BMC Psychiatry Jun 2024People with severe mental illness (SMI) such as schizophrenia and bipolar disorder are at a substantially higher risk of premature death in that they die between 10 and...
BACKGROUND
People with severe mental illness (SMI) such as schizophrenia and bipolar disorder are at a substantially higher risk of premature death in that they die between 10 and 20 years earlier than the general population. Cardiovascular disease (CVD) and diabetes are the main potentially avoidable contributors to early death. Research that explores the experiences of people with SMI highlights their struggles in engaging with health professionals and accessing effective and timely interventions for physical health conditions. A consequence of such struggles to navigate and access physical healthcare results in many people with SMI relying heavily on support provided by informal carers (e.g., family members, close friends). Despite this, the experiences of informal carers, and the roles they undertake in relation to supporting the physical health and psychotropic medication use of people with SMI, remains under-researched.
AIMS
To explore the impacts of providing care for physical health in severe mental illness on informal carers.
METHOD
Thematic analysis of semi-structured interviews with eight informal carers of people with SMI in United Kingdom (UK) national health services.
RESULTS
Informal carers played an active part in the management of the patient's conditions and shared their illness experience. Involvement of informal carers was both emotional and practical and informal carers' own lives were affected in ways that were sometimes deeply profound. Informal carers were involved in both 'looking after' the patient from the perspective of doing practical tasks such as collecting dispensed medication from a community pharmacy (caring for) and managing feelings and emotions (caring about).
CONCLUSIONS
Providing care for the physical health of someone with SMI can be understood as having two dimensions - 'caring for' and 'caring about'. The findings suggest a bidirectional relationship between these two dimensions, and both have a cost for the informal carer. With appropriate support informal carers could be more actively involved at all stages of care without increasing their burden. This should be with an awareness that carers may minimise the information they share about their own needs and impacts of their role to spare the person they care and themselves any distress.
Topics: Humans; Caregivers; Male; Female; Qualitative Research; Middle Aged; Mental Disorders; Adult; Aged; United Kingdom; Social Support; Health Status; Schizophrenia
PubMed: 38844879
DOI: 10.1186/s12888-024-05864-3 -
Turk Psikiyatri Dergisi = Turkish... 2024Lithium may cause toxicity as it has a narrow therapeutic range. Lithium intoxication may manifest in the form of acute, acute on chronic and chronic intoxication....
Lithium may cause toxicity as it has a narrow therapeutic range. Lithium intoxication may manifest in the form of acute, acute on chronic and chronic intoxication. Neurotoxicity is a common component of chronic lithium intoxication and the symptoms include tremor, ataxia, dysarthria, extrapyramidal symptoms, hyperreflexia, seizures and status epilepticus. Although rare, catatonia could as a manifestation of lithium neurotoxicity. In this report, we present a patient with bipolar disorder presenting with catatonic symptoms secondary to lithium intoxication. We will discuss the risk factors, differential diagnosis and the treatment of catatonic symptoms. Lithium neurotoxicity may present with various clinical symptoms including catatonia, and differential diagnosis should be made well in such cases. If lithium neurotoxicity is suspected, rapid and appropriate intervention is required to prevent permanent neurological damage. Keywords: Lithium, Neurotoxicity, Catatonia.
Topics: Humans; Antimanic Agents; Bipolar Disorder; Catatonia; Diagnosis, Differential; Neurotoxicity Syndromes
PubMed: 38842156
DOI: 10.5080/u27074 -
Communications Biology Jun 2024Advanced methods such as REACT have allowed the integration of fMRI with the brain's receptor landscape, providing novel insights transcending the multiscale...
Advanced methods such as REACT have allowed the integration of fMRI with the brain's receptor landscape, providing novel insights transcending the multiscale organisation of the brain. Similarly, normative modelling has allowed translational neuroscience to move beyond group-average differences and characterise deviations from health at an individual level. Here, we bring these methods together for the first time. We used REACT to create functional networks enriched with the main modulatory, inhibitory, and excitatory neurotransmitter systems and generated normative models of these networks to capture functional connectivity deviations in patients with schizophrenia, bipolar disorder (BPD), and ADHD. Substantial overlap was seen in symptomatology and deviations from normality across groups, but these could be mapped into a common space linking constellations of symptoms through to underlying neurobiology transdiagnostically. This work provides impetus for developing novel biomarkers that characterise molecular- and systems-level dysfunction at the individual level, facilitating the transition towards mechanistically targeted treatments.
Topics: Humans; Schizophrenia; Magnetic Resonance Imaging; Adult; Male; Brain; Female; Bipolar Disorder; Attention Deficit Disorder with Hyperactivity; Mental Disorders; Young Adult; Models, Neurological; Middle Aged; Nerve Net
PubMed: 38839931
DOI: 10.1038/s42003-024-06391-3 -
Frontiers in Genetics 2024Observational studies have reported that mental disorders are comorbid with temporomandibular joint disorder (TMD). However, the causal relationship remains uncertain....
OBJECTIVE
Observational studies have reported that mental disorders are comorbid with temporomandibular joint disorder (TMD). However, the causal relationship remains uncertain. To clarify the causal relationship between three common mental illnesses and TMD, we conduct this Mendelian Randomization (MR) study.
METHODS
The large-scale genome-wide association studies data of major depression, bipolar disorder and schizophrenia were retrieved from the Psychiatric Genomics Consortium. The summary data of TMD was obtained from the Finn-Gen consortium, including 211,023 subjects of European descent (5,668 cases and 205,355 controls). The main approach utilized was inverse variance weighting (IVW) to evaluate the causal association between the three mental disorders and TMD. Five sensitivity analyses including MR-Egger, Maximum Likelihood, Weighted median, MR. RAPS and MR-PRESSO were used as supplements. We conducted heterogeneity tests and pleiotropic tests to ensure the robustness.
RESULTS
As shown by the IVW method, genetically determined major depression was associated with a 1.65-fold risk of TMD (95% CI = 1.10-2.47, < 0.05). The direction and effect size remained consistent with sensitivity analyses. The odds ratios (ORs) were 1.51 (95% CI = 0.24-9.41, > 0.05) for MR-Egger, 1.60 (95% CI = 0.98-2.61, > 0.05) for Weighted median, 1.68 (95% CI = 1.19-2.38, < 0.05) for Maximum likelihood, 1.56 (95% CI = 1.05-2.33, < 0.05) for MR. RAPS, and 1.65 (95% CI = 1.10-2.47, < 0.05) for MR-PRESSO, respectively. No pleiotropy was observed (both for MR-Egger intercept and Global test >0.05). In addition, the IVW method identified no significant correlation between bipolar disorder, schizophrenia and TMD.
CONCLUSION
Genetic evidence supports a causal relationship between major depression and TMD, instead of bipolar disorder and schizophrenia. These findings emphasize the importance of assessing a patient's depressive status in clinical settings.
PubMed: 38836036
DOI: 10.3389/fgene.2024.1395219