Early parental separation experiences among patients with bipolar disorder and major depression: a case–control study1On behalf of the Group for Longitudinal Affective Disorders Study (GLADS).1

1999 ◽  
Vol 52 (1-3) ◽  
pp. 85-91 ◽  
Author(s):  
T.A Furukawa ◽  
A Ogura ◽  
T Hirai ◽  
S Fujihara ◽  
T Kitamura ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Major Depression ◽  
Affective Disorders ◽  
Case Control ◽  
Parental Separation

Insights into the genomics of affective disorders

2020 ◽  
Vol 32 (1) ◽  
pp. 9-18
Author(s):  
Andreas J. Forstner ◽  
Per Hoffmann ◽  
Markus M. Nöthen ◽  
Sven Cichon
Keyword(s):  
Bipolar Disorder ◽  
Major Depression ◽  
Affective Disorders ◽  
Association Studies ◽  
Phenotypic Variability ◽  
Genetic Research ◽  
Autism Spectrum ◽  
Risk Scores ◽  
Depression Symptoms ◽  
Genome Wide Association Studies

Abstract Affective disorders, or mood disorders, are a group of neuropsychiatric illnesses that are characterized by a disturbance of mood or affect. Most genetic research in this field to date has focused on bipolar disorder and major depression. Symptoms of major depression include a depressed mood, reduced energy, and a loss of interest and enjoyment. Bipolar disorder is characterized by the occurrence of (hypo)manic episodes, which generally alternate with periods of depression. Formal and molecular genetic studies have demonstrated that affective disorders are multifactorial diseases, in which both genetic and environmental factors contribute to disease development. Twin and family studies have generated heritability estimates of 58–85 % for bipolar disorder and 40 % for major depression. Large genome-wide association studies have provided important insights into the genetics of affective disorders via the identification of a number of common genetic risk factors. Based on these studies, the estimated overall contribution of common variants to the phenotypic variability (single-nucleotide polymorphism [SNP]-based heritability) is 17–23 % for bipolar disorder and 9 % for major depression. Bioinformatic analyses suggest that the associated loci and implicated genes converge into specific pathways, including calcium signaling. Research suggests that rare copy number variants make a lower contribution to the development of affective disorders than to other psychiatric diseases, such as schizophrenia or the autism spectrum disorders, which would be compatible with their less pronounced negative impact on reproduction. However, the identification of rare sequence variants remains in its infancy, as available next-generation sequencing studies have been conducted in limited samples. Future research strategies will include the enlargement of genomic data sets via innovative recruitment strategies; functional analyses of known associated loci; and the development of new, etiologically based disease models. Researchers hope that deeper insights into the biological causes of affective disorders will eventually lead to improved diagnostics and disease prediction, as well as to the development of new preventative, diagnostic, and therapeutic strategies. Pharmacogenetics and the application of polygenic risk scores represent promising initial approaches to the future translation of genomic findings into psychiatric clinical practice.

scholarly journals Cancer incidence in people with affective disorder: nationwide cohort study in Taiwan, 1997–2010

2014 ◽  
Vol 205 (3) ◽  
pp. 183-188 ◽  
Author(s):  
Yen-Ni Hung ◽  
Shu-Yu Yang ◽  
Ming-Chyi Huang ◽  
For-Wey Lung ◽  
Shih-Ku Lin ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Major Depression ◽  
Cancer Risk ◽  
Affective Disorders ◽  
Psychiatric Inpatient ◽  
Public Health Problem ◽  
Cancer Risks ◽  
Holistic Approaches ◽  
Risk Of Cancer ◽  
Medical Claims Database

BackgroundCancer is a serious public health problem worldwide, and its relationship with affective disorders is not clear.AimsTo investigate alcohol- and tobacco-related cancer risk among patients with affective disorders in a large Taiwanese cohort.MethodRecords of newly admitted patients with affective disorders from January 1997 through December 2002 were retrieved from the Psychiatric Inpatient Medical Claims database in Taiwan. Cancers were stratified by site and grouped into tobacco- or alcohol-related cancers. Standardised incidence ratios (SIRs) were calculated to compare the risk of cancer between those with affective disorders and the general population.ResultsSome 10 207 patients with bipolar disorder and 9826 with major depression were included. The risk of cancer was higher in patients with major depression (SIR = 2.01, 95% CI 1.85–2.19) than in those with bipolar disorder (SIR 1.39, 95% CI 1.26–1.53). The elevated cancer risk among individuals ever admitted to hospital for affective disorders was more pronounced in tobacco- and/or alcohol-related cancers.ConclusionsElevated cancer risk was found in patients who had received in-patient care for affective disorders. They require holistic approaches to lifestyle behaviours and associated cancer risks.

Epidemiology of Affective Disorders: A Review

1997 ◽  
Vol 42 (4) ◽  
pp. 367-377 ◽  
Author(s):  
Roger C Bland
Keyword(s):  
Public Health ◽  
Bipolar Disorder ◽  
Major Depression ◽  
Continuing Education ◽  
Affective Disorders ◽  
Public Health Problem ◽  
Classification Systems ◽  
Major Public Health Problem ◽  
Education Programs ◽  
Standard Methods

Objective: To review the epidemiology of affective disorders. Methods: This paper reviews recent studies, many of which have used standardized methodology and classification systems, and summarizes their major findings. It also presents trends with particular reference to major depression. Results: There have been major advances in the last 15 years, with many investigators using standard methods in different countries, cultures, and races. Rates of major depression are probably increasing, and both major depression and bipolar disorder are occurring at younger ages. Conclusions: Affective disorders present a major public health problem with poor recognition, diagnosis, and treatment. There is little coordinated action to reduce untreated morbidity despite the availability of reasonably safe, effective, and economical treatments and the established effectiveness of continuing education programs for providers.

Individual responses of rodents in modelling of affective disorders and in their treatment: prospective review

2018 ◽  
Vol 30 (6) ◽  
pp. 323-333 ◽  
Author(s):  
Haim Einat ◽  
Itamar Ezer ◽  
Nirit Z Kara ◽  
Catherine Belzung
Keyword(s):  
Bipolar Disorder ◽  
Sex Differences ◽  
Major Depression ◽  
Affective Disorders ◽  
Drug Response ◽  
Individual Variability ◽  
The Past ◽  
Affective Behaviors ◽  
Important Approach ◽  
Major Bottleneck

AbstractIntroductionLack of good animal models for affective disorders, including major depression and bipolar disorder, is noted as a major bottleneck in attempts to study these disorders and develop better treatments. We suggest that an important approach that can help in the development and use of better models is attention to variability between model animals.ResultsDifferences between mice strains were studied for some decades now, and sex differences get more attention than in the past. It is suggested that one factor that is mostly neglected, individual variability within groups, should get much more attention. The importance of individual differences in behavioral biology and ecology was repeatedly mentioned but its application to models of affective illness or to the study of drug response was not heavily studied. The standard approach is to overcome variability by standardization and by increasing the number of animals per group.ConclusionsPossibly, the individuality of specific animals and their unique responses to a variety of stimuli and drugs, can be helpful in deciphering the underlying biology of affective behaviors as well as offer better prediction of drug responses in patients.

Manejo y comorbilidades de los trastornos bipolares en la infancia y adolescencia

2020 ◽  
Vol 63 (6) ◽  
pp. 40-50
Author(s):  
Hugo Enrique Hernández-Martínez ◽  
Marta Georgina Ochoa-Madrigal
Keyword(s):  
Bipolar Disorder ◽  
Key Words ◽  
Child Psychiatry ◽  
Affective Disorders ◽  
Age Of Onset ◽  
Bipolar Disorders ◽  
World Population ◽  
Key Words Bipolar Disorder ◽  
The World ◽  
Cardinal Symptoms

The diagnosis and treatment of bipolar disorders (BPD) in children is currently one of the biggest challenges and area of controversy in the field of child psychiatry. Bipolar disorders encompass several affective disorders that involve alterations in the degree of activity, content and form of thinking that are characterized by biphasic episodes of mood. This group of disorders affect approximately 1% of the world population and begin in youth (the average age of onset of ~20 years). However, in some studies a delay of 5 years has been observed since the presentation of symptoms at the beginning of the treatment. Currently, the diagnosis of TBP in children and adolescents should be based on the same set of symptoms applied to adults, as well as the general principles of the treatment. The research carried out around this disorder has resulted in changes in the conceptualization and approach of this pathology, now conceived as a group of disorders that share changes in mood and other cardinal symptoms, of a chronic and progressive nature that impacts in a negative way in those who suffer them. Key words: Bipolar disorder; childhood; mania; hypomania; depression.

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.

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