scholarly journals Platelet’s Fatty Acids and Differential Diagnosis of Major Depression and Bipolar Disorder through the Use of an Unsupervised Competitive-Learning Network Algorithm (SOM)

2014 ◽  
Vol 03 (02) ◽  
pp. 52-73 ◽  
Author(s):  
Serena Benedetti ◽  
Sabina Bucciarelli ◽  
Franco Canestrari ◽  
Simona Catalani ◽  
Silvia Mandolini ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Bipolar Disorder ◽  
Differential Diagnosis ◽  
Major Depression ◽  
Competitive Learning ◽  
Learning Network ◽  
Network Algorithm

Borderline Personality Disorder and Mood Disorders

2017 ◽  
Author(s):  
Eric A. Fertuck ◽  
Megan S. Chesin ◽  
Brian Johnston
Keyword(s):  
Bipolar Disorder ◽  
Differential Diagnosis ◽  
Borderline Personality Disorder ◽  
Major Depression ◽  
Personality Disorder ◽  
Mood Disorders ◽  
Suicide Risk ◽  
Borderline Personality ◽  
Mood Symptoms ◽  
Affective Instability

Borderline personality disorder (BPD) and mood disorder (MD) can be difficult to differentiate from each other due to several overlapping clinical features. Among BPD symptoms, chronic dysphoria can be mistaken for major depression, while affective instability may be confused with the depressed and elevated mood episodes of bipolar disorder (BD). Conversely, in those with BPD, co-occurring MDs can be difficult to rigorously assess and treat. Even though there is moderate to high co-occurrence between these conditions, BPD and MDs have distinct facets of impulsivity, affective instability, and mood symptoms. Furthermore, BPD, MD, and their co-occurrence predict courses of illness, prognosis, treatment outcomes, and suicide risk. Consequently, thorough assessment and differential diagnosis of these conditions should inform treatment planning and clinical management in both BPD and MD.

scholarly journals Reply to “Replication of association of 3p21.1 with susceptibility to bipolar disorder but not major depression”

2010 ◽  
Vol 43 (1) ◽  
pp. 5-5 ◽  
Author(s):  
Francis J McMahon ◽  
Nirmala Akula ◽  
Sven Cichon ◽  
Sevilla D Detera-Wadleigh ◽  
Howard Edenberg ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Major Depression

scholarly journals Prediction of response to drug therapy in psychiatric disorders

Open Biology ◽  
2018 ◽  
Vol 8 (5) ◽  
pp. 180031 ◽  
Author(s):  
Shani Stern ◽  
Sara Linker ◽  
Krishna C. Vadodaria ◽  
Maria C. Marchetto ◽  
Fred H. Gage
Keyword(s):  
Autism Spectrum Disorder ◽  
Bipolar Disorder ◽  
Major Depression ◽  
Personalized Medicine ◽  
Psychiatric Disorders ◽  
Association Studies ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Genome Wide Association Studies ◽  
Patient Reported

Personalized medicine has become increasingly relevant to many medical fields, promising more efficient drug therapies and earlier intervention. The development of personalized medicine is coupled with the identification of biomarkers and classification algorithms that help predict the responses of different patients to different drugs. In the last 10 years, the Food and Drug Administration (FDA) has approved several genetically pre-screened drugs labelled as pharmacogenomics in the fields of oncology, pulmonary medicine, gastroenterology, haematology, neurology, rheumatology and even psychiatry. Clinicians have long cautioned that what may appear to be similar patient-reported symptoms may actually arise from different biological causes. With growing populations being diagnosed with different psychiatric conditions, it is critical for scientists and clinicians to develop precision medication tailored to individual conditions. Genome-wide association studies have highlighted the complicated nature of psychiatric disorders such as schizophrenia, bipolar disorder, major depression and autism spectrum disorder. Following these studies, association studies are needed to look for genomic markers of responsiveness to available drugs of individual patients within the population of a specific disorder. In addition to GWAS, the advent of new technologies such as brain imaging, cell reprogramming, sequencing and gene editing has given us the opportunity to look for more biomarkers that characterize a therapeutic response to a drug and to use all these biomarkers for determining treatment options. In this review, we discuss studies that were performed to find biomarkers of responsiveness to different available drugs for four brain disorders: bipolar disorder, schizophrenia, major depression and autism spectrum disorder. We provide recommendations for using an integrated method that will use available techniques for a better prediction of the most suitable drug.

Emotional availability in women with bipolar disorder and major depression: A longitudinal pregnancy cohort study

2021 ◽  
pp. 000486742199879
Author(s):  
Pavitra Aran ◽  
Andrew J Lewis ◽  
Stuart J Watson ◽  
Thinh Nguyen ◽  
Megan Galbally
Keyword(s):  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Depressive Symptoms ◽  
Major Depression ◽  
Depressive Disorder ◽  
Emotional Availability ◽  
Major Depressive ◽  
Interaction Quality ◽  
Pregnancy Cohort ◽  
The Impact

Objective: Poorer mother–infant interaction quality has been identified among women with major depression; however, there is a dearth of research examining the impact of bipolar disorder. This study sought to compare mother–infant emotional availability at 6 months postpartum among women with perinatal major depressive disorder, bipolar disorder and no disorder (control). Methods: Data were obtained for 127 mother–infant dyads from an Australian pregnancy cohort. The Structured Clinical Interview for the DSM-5 was used to diagnose major depressive disorder ( n = 60) and bipolar disorder ( n = 12) in early pregnancy (less than 20 weeks) and review diagnosis at 6 months postpartum. Prenatal and postnatal depressive symptoms were measured using the Edinburgh Postnatal Depression Scale, along with self-report psychotropic medication use. Mother and infant’s interaction quality was measured using the Emotional Availability Scales when infants reached 6 months of age. Multivariate analyses of covariance examining the effects of major depressive disorder and bipolar disorder on maternal emotional availability (sensitivity, structuring, non-intrusiveness, non-hostility) and child emotional availability (responsiveness, involvement) were conducted. Results: After controlling for maternal age and postpartum depressive symptoms, perinatal disorder (major depressive disorder, bipolar disorder) accounted for 17% of the variance in maternal and child emotional availability combined. Compared to women with major depressive disorder and their infants, women with bipolar disorder and their infants displayed lower ratings across all maternal and child emotional availability qualities, with the greatest mean difference seen in non-intrusiveness scores. Conclusions: Findings suggest that perinatal bipolar disorder may be associated with additional risk, beyond major depressive disorder alone, to a mother and her offspring’s emotional availability at 6 months postpartum, particularly in maternal intrusiveness.

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