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Bipolar Disorder Type 2

Bipolar Disorder Type 2 is a mood disorder characterized by cyclical episodes of depression and hypomania, a less severe form of mania.
Individuals with this condition experience persistent low mood interspersed with periods of elevated mood, increased energy, and improved productivity.
Unlike Bipolar Disorder Type 1, the manic episodes in Type 2 do not reach the same level of severity and typically do not result in significant impairment in social or occupational functioning.
Reseachers and clinicians can utilize PubCompare.ai to optimize thier research protocols for this condition, enabling them to locate and compare the best protocols and products across litearture, pre-prints, and patents.
PubCompare.ai's AI-driven comparisons ensure reproducibility and accuracy, empowering researchers to make informed decisions and advance the understanding and treatment of Bipolar Disorder Type 2.

Most cited protocols related to «Bipolar Disorder Type 2»

Diagnostic Reliability and Validity

Cited 12 times

We derived 12-month and lifetime DSM-5 diagnoses of NUD and other DUDs (sedative or tranquilizer, cannabis, amphetamine, cocaine, club drug, opioid, heroin, hallucinogen, and solvent or inhalant) similarly to the procedure used for diagnoses of AUD. The DUD diagnoses were aggregated to yield a diagnosis of any DUD. Test-retest reliabilities were fair to excellent for NUD (diagnoses in the past 12 months, κ = 0.50; diagnoses before the past 12 months, κ = 0.87) and DUD (κ range, 0.40-0.54) diagnoses and higher for their dimensional counterparts (ICCs, 0.45-0.84).^{24 (link)} Concordance on NUD and DUD diagnoses in the AUDADIS-5 and PRISM-5 and in dimensional scales was fair to excellent (κ range, 0.36-0.66; ICCs, >0.68 [in general]).^{26 (link)}We assessed 12-month and lifetime DSM-5 mood, anxiety, trauma-related, eating, and PD diagnoses. Mood disorders included persistent depression and major depressive, bipolar I, and bipolar II disorders. Anxiety disorders included panic disorder, agoraphobia, generalized anxiety disorder, and social and specific phobias. Posttraumatic stress disorder, anorexia nervosa, bulimia nervosa, and binge-eating disorder in DSM-5 were also assessed. Consistent with DSM-5, all these diagnoses excluded substance- and medical illness–induced disorders. Lifetime PDs from the DSM-5 included antisocial, borderline, and schizotypal.
Test-retest reliability of AUDADIS-5 and DSM-5 diagnoses of psychiatric disorders was fair to good (κ range, 0.35-0.54).^{24 (link)} Reliability of associated DSM-5 dimensional scales was greater (κ range, 0.50-0.79). Concordance between AUDADIS-5 and PRISM-5 diagnoses for these disorders was fair to good (κ range, 0.20-0.59), with good concordance (ICCs, >0.53 [in general]) for many corresponding dimensional scales.⁴⁰

Grant B.F., Goldstein R.B., Saha T.D., Chou S.P., Jung J., Zhang H., Pickering R.P., Ruan W.J., Smith S.M., Huang B, & Hasin D.S. (2015). Epidemiology of DSM-5 Alcohol Use Disorder: Results From the National Epidemiologic Survey on Alcohol and Related Conditions III. JAMA psychiatry, 72(8), 757-766.

Publication 2015

Agoraphobia Amphetamines Anorexia Nervosa Anxiety Disorders Bipolar Disorder Type 2 Bulimia Nervosa Cannabis Club Drugs Cocaine Diagnosis Disorder, Binge-Eating Hallucinogens Heroin inecalcitol Inhalation Drug Administration Mental Disorders Mood Mood Disorders Opioids Panic Disorder Phobia, Specific Post-Traumatic Stress Disorder prisma Sedatives Solvents Tranquilizing Agents Wounds and Injuries

Longitudinal Investigation of Bipolar Spectrum Disorders

Cited 10 times

Participants were recruited for the Longitudinal Investigation of Bipolar Spectrum Disorders (LIBS) Project using a two-stage screening procedure. In Stage I, approximately 20,500 Temple University (TU) and University of Wisconsin (UW) students, ages 18 – 24, completed the revised General Behavior Inventory (GBI; Depue, Krauss, Spoont, & Arbisi, 1989 (link)), to identify individuals prone to ‘soft’ bipolar conditions. A subset of participants who met the GBI cutoff criteria: 1) for bipolar spectrum conditions (Hypomania-Biphasic [HB] score > 13 and Depression [D] score > 11), or 2) for the absence of affective psychopathology (HB < 13 and D < 11), as specified by Depue et al. (1989) (link), were identified. Participants from these two groups were chosen to be similar on demographics (sex, age, and race) and invited to the next stage. In Stage II, 1,730 participants were administered an expanded Schedule for Affective Disorders and Schizophrenia--Lifetime diagnostic interview (exp-SADS-L; Endicott & Spitzer, 1978 (link)). The exp-SADS-L interview was modified to allow for derivation of both DSM-IV-TR (2000) and Research Diagnostic Criteria (RDC; Spitzer, Endicott, & Robins, 1978 ) diagnoses.
Exclusion criteria based on the exp-SADS-L were: 1) current or past DSM-IV and/or RDC Manic Episode diagnoses (i.e., bipolar I disorder); 2) current or past DSM-IV and/or RDC diagnoses of primary psychiatric disorder other than bipolar spectrum disorder (e.g., anxiety); and 3) bipolar disorder secondary to current physical illness (e.g., endocrinopathies). However, for the bipolar spectrum group, individuals with comorbid psychiatric disorder secondary to bipolar spectrum disorder (e.g., comorbid alcohol abuse) and, for the control group, individuals with only Specific Phobia diagnoses were included.¹ Finally, based on this two-stage screening procedure, two groups of individuals were identified and invited to participate in the longitudinal project: 1) individuals who met both the GBI cutoff criteria for bipolar spectrum conditions and the DSM-IV and/or RDC criteria for cyclothymia, BiNOS, or bipolar II disorder (i.e., the bipolar spectrum group); and 2) individuals who met both the GBI cutoff criteria for absence of affective psychopathology and the DSM-IV and/or RDC criteria for no lifetime diagnosis of psychopathology (i.e., control group). The longitudinal sample consisted of 414 participants (165 men, 249 women)—206 in the bipolar spectrum group (57 cyclothymia or BiNOS, 149 bipolar II disorder) and 208 in the control group. The bipolar spectrum and control groups did not differ on age, sex, or ethnicity (see Alloy et al., 2008 (link)). The longitudinal sample was representative of the Stage I screening sample on demographics and did not differ from Stage II eligible individuals who did not participate on demographics, diagnosis, treatment history, and GBI scores (see Alloy et al., 2008 (link)).
Given that the aims of the current study were to examine predictors of conversion to more severe diagnoses in the bipolar spectrum, only participants in the bipolar spectrum group were included in the present analyses. The ethnic composition of the bipolar spectrum group was 68.9% Caucasian, 13.1% African-American, 5.1% Hispanic, 3.6% Asian, 0.5% Native American, and 8.2% Other. Five bipolar spectrum participants (who did not differ from the remaining bipolar participants on demographics, clinical variables, or GBI scores) were excluded from the present analyses because they had too much missing data. This left 201 bipolar spectrum participants (43 Cyclothymia, 14 BiNOS, 144 bipolar II) in the present analyses.

Alloy L.B., Urošević S., Abramson L.Y., Jager-Hyman S., Nusslock R., Whitehouse W.G, & Hogan M. (2011). Progression along the Bipolar Spectrum: A Longitudinal Study of Predictors of Conversion from Bipolar Spectrum Conditions to Bipolar I and II Disorders. Journal of Abnormal Psychology, 121(1), 16-27.

Publication 2011

Abuse, Alcohol African American Alloys American Indian or Alaska Native Anxiety Disorders Asian Americans Bipolar Disorder Bipolar Disorder Type 2 Caucasoid Races Cyclothymic Disorder Diagnosis Endocrine System Diseases Ethnicity Hispanics Manic Episode Mental Disorders Phobia, Specific Physical Examination Robins Sadness Schizophrenia Student Woman

Radiofrequency Neuromodulation for Bipolar Disorder

Cited 9 times

The charts of 56 patients attending the Rinaldi-Fontani Institute in Florence and the Centro di Studi Psichici in Cagliari were retrospectively evaluated. Patients diagnosed with bipolar disorder I or II according to the revised fourth edition of the Diagnostic Statistical Manual for Mental Disorders (DSM-IVTR) criteria were included. Inclusion criteria were as follows: both genders; age 18–65 years; written informed consent obtained; history of at least 12 months of psychopharmacologically treated bipolar disorder I/II; and at least four cycles of REAC treatment. Exclusion criteria included a history of seizures, head trauma, or brain disease, and evidence of chronic or severe disease (renal or hepatic impairment, or cancer). REAC treatment was administered following the standard Rinaldi-Fontani Institute schedule of one session of neuropostural optimization followed by 18 sessions of neuropsychophysical optimization. Add-on treatments were allowed in the event of manic or depressive recurrence. Patients were divided into four follow-up groups before and after REAC-lithium treatment, as follows: at least 72 months (Group 1); at least 48 months (Group 2); at least 36 months (Group 3); and at least 18 months (Group 4). Information on demographic variables, psychiatric history, concomitant treatments, and comorbid disorders were collected for each patient. The evaluation of REAC-lithium effectiveness was made by collecting the recurrence of mood episodes (manic or depressive according to DSM IV-TR). The Structured Clinical Interview for Diagnosis, the 21-item Hamilton Depression Rating Scale, and the Young Mania Rating Scale (YMRS) were been used. Statistical analysis was performed using a t-test for comparative groups, and all results with a P < 0.05 were considered significant. Tolerability and safety were evaluated by collecting the reports of adverse events. Demographic variables and the psychiatric-psychopharmacologic history of the patients are reported in Table 1. Eight patients (Group 1) were followed for 30.2 ± 3.0 months, 14 patients (Group 2) for 25.3 ± 3.3 months, 25 patients (Group 3) for 20.3 ± 1.6 months, and nine patients (Group 4) for 16.2 ± 0.5 months. Lithium was dosed at 980.0 ± 135.6 mg/day, 825.0 ± 50.0 mg/day, 850.5 ± 100.0 mg/day, and 950.5 ± 75.5 mg/day in the four groups of patients, respectively. The demographic variables and psychiatric history of the patients are reported in Table 1.
REAC26 ,27 is a medical device based on innovative technology for biostimulation. REAC works with a typical range frequency of 2.4, 5.8, or 10.5 gHz, as selected by the operator for each specific protocol used. A frequency of 10.5 gHz was used in the brain stimulation protocols used in this study, with a specific absorption rate28 (link)–30 (link) of 7 μW/kg. REAC treatments have proven efficacy in ameliorating stress-related disorders, depression, and anxiety.20 (link)–25 (link) The REAC pulse used in this study was a 7 radiofrequency burst of 500 msec, applied by touching the metallic tip of the REAC probe to the ear pavilion using neuropostural optimization and neuropsychophysical optimization protocols. The treatments are painless, noninvasive, and without negative adverse effects.

Mannu P., Rinaldi S., Fontani V, & Castagna A. (2011). Long-term treatment of bipolar disorder with a radioelectric asymmetric conveyor. Neuropsychiatric Disease and Treatment, 7, 373-379.

Publication 2011

Anxiety Bipolar Disorder Bipolar Disorder Type 2 Brain Brain Diseases Craniocerebral Trauma Diagnosis Gender Kidney Lithium Malignant Neoplasms Mania Medical Devices Mental Disorders Metals Mood Patients Pulse Rate Recurrence Safety Seizures Stress Disorders, Traumatic

Adolescent Psychiatric Diagnosis Protocol

Cited 7 times

Adolescents were administered the fully-structured Composite International Diagnostic Interview (CIDI) modified to simplify language and use examples relevant to adolescents (Merikangas et al., 2009 (link)). The 15 DSM-IV disorders assessed include mood disorders (major depressive disorder/dysthymia, bipolar I-II disorder and sub-threshold bipolar disorder), anxiety disorders (panic disorder with or without agoraphobia, agoraphobia without panic disorder, social phobia, specific phobia, generalized anxiety disorder, post-traumatic stress disorder, separation anxiety disorder), behavior disorders (attention-deficit/hyperactivity disorder, oppositional-defiant disorder, conduct disorder, eating disorders [anorexia nervosa, bulimia nervosa, binge-eating behavior]), and substance disorders (alcohol and drug abuse, alcohol and drug dependence with abuse). There were no other exclusionary diagnoses. These disorders include all those assessed in most previous adolescent epidemiological studies.
Adolescent interviews assessed all disorders. Parent questionnaires assessed only disorders for which parent reports have previously been found important in diagnosis: behavior disorders (Johnston & Murray, 2003 (link)) and depression/dysthymia (Braaten et al., 2001 (link)). Parent and adolescent reports were combined at the symptom level using an “or” rule (except in the case of attention-deficit/hyperactivity disorder, where only parent reports were used based on evidence of invalidity of adolescent reports). All diagnoses were made using DSM-IV distress/impairment criteria and organic exclusion rules, but diagnostic hierarchy rules were not used because we wanted to study comorbidity among hierarchy-free disorders.
A clinical reappraisal study interviewed adolescent-parent pairs by telephone with the Schedule for Affective Disorders and Schizophrenia for School-Age Children (K-SADS) Lifetime Version (Kaufman et al., 1997 (link)). As detailed elsewhere, concordance was good between survey and clinical diagnoses (Kessler et al., 2009c (link)), with area under the receiver operating characteristic curve (AUC) of .81-.94 for fear disorders, .79-.86 for distress disorders, .78-.98 for behavior disorders, and .92-.98 for substance disorders. Parent and adolescent reports both contributed to AUC when both were assessed for depression/dysthymia (.75, .71, and .87 for adolescent, parent, and combined reports, respectively), oppositional-defiant disorder (.71, .66, and .85), and conduct disorder (.59, .96, and .98), but only parent reports contributed to AUC for attention-deficit/hyperactivity disorder (.57, .71, and .78). Adolescent disorder AOO reports were obtained retrospectively using probes shown experimentally to maximize recall accuracy among adults (Knauper et al., 1999 ).

Kessler R.C., Avenevoli S., McLaughlin K.A., Green J.G., Lakoma M.D., Petukhova M., Pine D.S., Sampson N.A., Zaslavsky A.M, & Merikangas K.R. (2012). Lifetime comorbidity of DSM-IV disorders in the NCS-R Adolescent Supplement (NCS-A). Psychological medicine, 42(9), 1997-2010.

Publication 2012

Adolescent Adult Agoraphobia Anorexia Nervosa Anxiety Disorders Behavior Disorders Bipolar Disorder Bipolar Disorder Type 2 Bulimia Nervosa Conduct Disorder Diagnosis Disorder, Attention Deficit-Hyperactivity Drug Abuse Drug Dependence Dysthymic Disorder Eating Disorders Ethanol Fear of disease Feeding Behaviors Major Depressive Disorder Mental Recall Mood Disorders Oppositional Defiant Disorder Panic Disorder Parent Phobia, Social Phobia, Specific Post-Traumatic Stress Disorder Sadness Schizophrenia, Childhood Separation Anxiety Disorder

Evaluating MDQ for Bipolar Disorder Diagnosis

Cited 7 times

SCID: the Structured Clinical Interview for DSM-IV Disorders of Axis I [5 ] is a semi-structured interview aimed at formulating the main diagnoses covered by Axis I of DSM-IV [6 ].
MDQ: the Mood Disorder Questionnaire [2 (link)-4 (link)] is a self-administered single-page paper and pencil inventory made up of 13 yes/no items derived from both the DSM-IV criteria [6 ] and clinical experience, which assess the macro-area of mood, a lifetime history of a manic or hypomanic syndrome, placing particular emphasis on a marked subjective variation in the dimensions of irritability, activity, sociability, sleep, libido, thoughts, attention, energy, behaviour, etc.
We evaluated the discriminatory capacity (patients with a diagnosis of Bipolar Disorder I or II or Schizoaffective Disorder Bipolar type versus patients with other psychiatric diagnoses or with no psychiatric diagnosis, according to the findings of the SCID) of all 13 items contemplated in the MDQ.
The accuracy of the MDQ questionnaire was calculated in terms of sensitivity and specificity for each theoretically possible cut-off point (number of positive answers). Overall performance of the questionnaire was graphically assessed by means of the Relative Operating Characteristic Analysis [7 ]. The specific accuracy for detecting bipolar II disorders was calculated at best performing cut-off points 4, 5 and 6.

Hardoy M.C., Cadeddu M., Murru A., Dell'Osso B., Carpiniello B., Morosini P.L., Calabrese J.R, & Carta M.G. (2005). Validation of the Italian version of the "Mood Disorder Questionnaire" for the screening of bipolar disorders. Clinical Practice and Epidemiology in Mental Health : CP & EMH, 1, 8.

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Publication 2005

Attention Bipolar Disorder Bipolar Disorder Type 2 Diagnosis Diagnosis, Psychiatric Epistropheus Libido Mania Mood Mood Disorders Patients Schizoaffective Disorder SCID Mice Sleep Syndrome Thinking

Most recents protocols related to «Bipolar Disorder Type 2»

Mood Disorders and Cervical Cancer Risk

We constructed a population-based retrospective cohort study to determine whether patients with mood disorders are more susceptible to developing cervical cancer. The mood-disorder cohort included women aged above 18 years who received a diagnosis of mood disorders (depression and bipolar) with at least two outpatient visits or at least one hospitalization record from 2000 to 2012 (Figure 1). Participants in the non-mood-disorder cohort were defined as participants without mood disorders. The diagnostic codes for mood disorders used to identify patients in this study are listed below. For depressive disorder, we used ICD-9-CM code 296.2 (major depressive disorder single episode), code 296.3 (major depressive disorder recurrent episode), code 300.4 (dysthymic disorder), and code 311 (depressive disorder, not elsewhere classified). For bipolar disorder, we used code 296.0 (manic disorder, single manic episode), code 296.1 (manic disorder, recurrent episode), code 296.4 (bipolar I disorder, most recent episode (or current) manic), code 296.5 (bipolar I disorder, most recent episode (or current) depressed), code 296.6 (bipolar I disorder, most recent episode (or current) mixed), code 296.7 (bipolar I disorder, most recent episode (or current) unspecified), code 296.8 (other affective psychoses), code 296.80 (bipolar disorder, unspecified), and code 296.89 (bipolar II disorder). The date of the first diagnosis of mood disorders was defined as the index date. Women aged above 18 years who had never received a diagnosis of mood disorders during the study period were randomly selected as the comparison cohort and propensity-matched with the mood-disorder cohort at a 4:1 ratio according to age and index year. We excluded participants with a history of any cancer (ICD-9-CM 140-208) before the index date. The main outcome was a new diagnosis of cervical cancer (ICD-9-CM 180.9 and 233.1) during the follow-up period. All participants in this study were followed from the index date until being diagnosed with cervical cancer and censored because of the loss to follow-up, withdrawal from insurance, or at the end of 2013. Baseline comorbidities before the index date including diabetes mellitus (ICD-9-CM 250), hypertension (ICD-9-CM 401-40 and A26), hyperlipidemia (ICD-9-CM 272), cardiovascular disease (ICD-9-CM 402, 410-414, 420-429, 430-438), chronic kidney disease (ICD-9-CM 580-589, A350), dementia (ICD-9-CM 290 and 294), and sexually transmitted diseases (ICD-9-CM 042, 054.1, 078.11, 091-098, 099.5 and 131) were investigated in this study. We also considered utilization of Pap smears in this study, and Pap smear density was calculated as the number of Pap smears per year during the follow-up period. The participants’ demographic characteristics were collected from both cohorts including age, urbanization level, employment category, and the follow-up duration.

Wu C.T, & Chiu L.T. (2023). The Impact of Psychological Distress on Cervical Cancer. Cancers, 15(4), 1100.

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Publication 2023

Affective Disorders, Psychotic Bipolar Disorder Bipolar Disorder Type 2 Cardiovascular Diseases Cervical Cancer Chronic Kidney Diseases Dementia Diabetes Mellitus Disorder, Depressive Dysthymic Disorder High Blood Pressures Hospitalization Hyperlipidemia Major Depressive Disorder Malignant Neoplasms Mania Manic Disorder Manic Episode Mood Disorders Outpatients Patients Sexually Transmitted Diseases Urbanization Vaginal Smears Woman

Utilizing GWAS Data for Disease Subtyping

Inflammatory bowel disease subtypes. As base sample, we used publicly available summary statistics from a case/control inflammatory bowel disease GWAS [40 (link)]. The SNP effect sizes of this GWAS were used to calculate pathway and genome-wide PRS for each individual in the target sample, composed by UK Biobank participants diagnosed with Crohn’s disease and with ulcerative colitis. The target sample phenotype was encoded as individuals with Crohn’s disease vs individuals with ulcerative colitis.
Bipolar disorder subtypes. We obtained access to individual genotype data from 55 bipolar disorder cohorts collected by the PGC Bipolar Disorder Working group (Table K in S1 Tables). Quality control, imputation and harmonisation was performed on this data as previously described [41 (link)]. Out of the 55 cohorts, we selected 34 as base sample and meta-analysed each cohort case/control GWAS results using the software METAL (2011-03-25) [58 (link)] with the sample-size weighted fixed-effects algorithm. We used the remaining 21 cohorts as target sample and calculated for each individual with bipolar disorder pathway and genome-wide PRS. The target sample phenotype was encoded as individuals with bipolar disorder I vs bipolar disorder II.
Pseudo subtypes of paired major diseases. We obtained previously published GWAS summary statistics for four major diseases: type 2 diabetes, coronary artery disease, obesity (defined as body mass index > 30) and hypercholesterolemia (defined as low-density lipoproteins > 4.9 mmol/L) and performed a meta-analysis for each pair of traits. Meta-analyses were performed using METAL [58 (link)] with the sample-size weighted fixed-effects algorithm. To truly mimic a composite phenotype GWAS, only variants included in both GWAS summary statistics were retained. The resulting meta-analysis summary statistics were used as base sample. As target sample, we generated composite phenotypes by combining cases of the two paired phenotypes using UK Biobank. To calculate the PRS, target sample phenotypes were encoded mimicking sub-phenotypes of a given disease, for example, for the phenotype coronary artery disease-obesity, samples with coronary artery disease (and not obesity) were coded as 0 and those with obesity (and not coronary artery disease) were coded as 1 (Tables L-N in S1 Tables).
Comorbid subtypes of major diseases. For the analysis of subtypes with presence/absence of comorbid diseases, we used type 2 diabetes, coronary artery disease, obesity, hypertension and hypercholesterolemia, as these diseases present high comorbidity between them (Tables L-N in S1 Tables). As base sample, we used publicly available GWAS summary statistics for one of the diseases (e.g. type 2 diabetes). As target sample phenotypes, we defined subtypes of a disease as the presence/absence of the other disorders (e.g. type 2 diabetes with obesity vs type 2 diabetes without obesity).

Choi S.W., García-González J., Ruan Y., Wu H.M., Porras C., Johnson J., Hoggart C.J, & O’Reilly P.F. (2023). PRSet: Pathway-based polygenic risk score analyses and software. PLOS Genetics, 19(2), e1010624.

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Publication 2023

Bipolar Disorder Bipolar Disorder Type 2 Coronary Artery Disease Crohn Disease Diabetes Mellitus, Non-Insulin-Dependent Genome Genome-Wide Association Study Genotype High Blood Pressures Hypercholesterolemia Index, Body Mass Inflammatory Bowel Diseases Low-Density Lipoproteins Metals Obesity Phenotype Ulcerative Colitis

Mood Disorders Diagnostic Protocol

This study analyzed data from 715 patients (267 patients with major depressive disorder [MDD], 94 patients with bipolar disorder I [BD I], and 354 patients with bipolar disorder II [BD II]) from July 2013 to February 2021. The sample comprised 222 men and 493 women ranging from 16 to 71 years old. The patients were from the mood disorder clinic of Seoul National University Bundang Hospital (SNUBH). Their medical records were used to acquire all pertinent information. Based on a structured diagnostic interview (Mini-International Neuropsychiatric Interview [M.I.N.I]) [20 ] and review of case files, two board-certified psychiatrists (T.H.H. and W.M.) confirmed the patients’ diagnosis in accordance with the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) [21 ]. We also gathered additional pertinent data, such as age, gender, education level, employment status, marital status, alcohol use, smoking history, and history of psychiatric hospitalizations. The Institutional Review Board of Seoul National University Bundang Hospital gave its approval for this study (protocol code B-2205-756-111, approved 2 May 2022). Because information was gathered retroactively through a review of medical records, patient informed consent was waived.

Choi S., Yu H., Yoon J., Jang Y., Lee D., Park Y.S., Ihm H.K., Ryoo H.A., Cho N., Woo J.M., Kang H.S., Ha T.H, & Myung W. (2023). Korean Validation of the Short Version of the TEMPS-A (Temperament Evaluation of Memphis, Pisa, Paris, and San Diego Autoquestionnaire) in Patients with Mood Disorders. Medicina, 59(1), 115.

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Publication 2023

Bipolar Disorder Bipolar Disorder Type 2 CODE protocol Diagnosis Ethics Committees, Research Gender Hospitalization Major Depressive Disorder Mood Disorders Patients Psychiatrist Woman

Hormonal Profiles in MDD and Schizophrenia

We included 129 patients with MDD, 71 patients with schizophrenia, and 71 healthy volunteers aged 18–64 years. Patients with MDD and schizophrenia were recruited from December 2015 to April 2021 from Niigata University Medical and Dental Hospital, and healthy control individuals matched for age, sex, and BMI were recruited from the community.
As of February 2017, we had recruited 91 patients with MDD for an initial study, which showed serum cortisol and IGF-1 levels were associated with symptom severity in patients with MDD^{40 (link)}. Subsequently, as of March 2020, we had enrolled 54 male patients with MDD and 37 healthy male volunteers in a second study, which found serum IGF-1 levels were significantly higher in patients than in controls^{41 (link)}. These studies included a total of 107 patients with MDD and 37 healthy male volunteers. The current study extended the observation period and recruited additional participants including 71 patients with schizophrenia who were not included in our previous studies^{40 (link),41 (link)}. Of the participants in our previous studies, 84 patients (61 males and 23 females) with MDD and 35 healthy male individuals were included in the current study. Seventy-one patients (48 males and 23 females) with MDD overlapped between the current and initial^{40 (link)} studies, and 44 male patients with MDD and 35 healthy male controls overlapped between our current study and second study^{41 (link)}. Twenty-three patients were excluded for the following reasons: 14 met the diagnostic criteria for a psychiatric comorbidity other than MDD (bipolar II disorder, personality disorder, major neurocognitive disorder, adjustment disorder, unspecified depressive disorder, other specified depressive disorder, or persistent depressive disorder), four did not meet the age range inclusion criteria, four were diagnosed with a concurrent physical illness, and one had missing data. Two healthy volunteers were excluded because of declaration of protocol non-compliance (smoking or exercise).
Patients were diagnosed with MDD or schizophrenia according to the criteria in the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5), and those with concurrent diagnoses of other mental illnesses were excluded because of the possible impact on cortisol and IGF-1^{8 (link),17 (link),20 (link),21 (link),53 (link)–55 (link)}.
Comorbid diagnoses were determined by the active diagnoses at the time of enrollment (including diagnoses under treatment). The diagnostic requirements for the MDD group included current depressive episodes or remissions during treatment. Diagnoses were made by at least two psychiatrists. Patients were individually treated by clinicians. Eligibility criteria for the control group were no history of psychiatric consultation or medical history that met DSM-5 diagnostic criteria.
None of the participants had any physical illness (e.g., endocrine disorders; autoimmune disorders; malignant tumors; heart, lung, kidney, gastrointestinal, or nervous disorders; or infections in the past 2 weeks) that could affect their hormone levels, and none of the participants were pregnant, breastfeeding, or taking steroids or birth control pills.
This research was approved by the Ethics Committee on Genetics of Niigata University and conducted in compliance with the Declaration of Helsinki. Before participating in the study, all participants provided verbal and written informed consent, and if the ability to consent was questionable, informed consent was obtained from the participant’s parent and/or legal guardian.

Arinami H., Watanabe Y., Suzuki Y., Tajiri M., Tsuneyama N, & Someya T. (2023). Serum cortisol and insulin-like growth factor 1 levels in major depressive disorder and schizophrenia. Scientific Reports, 13, 1148.

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Publication 2023

Adjustment Disorders Autoimmune Diseases Bipolar Disorder Type 2 Contraceptives, Oral Dental Health Services Diagnosis Disorder, Depressive Eligibility Determination Endocrine System Diseases Ethics Committees Females Healthy Volunteers Heart Hormones Hydrocortisone IGF1 protein, human Infection Kidney Legal Guardians Lung Males Malignant Neoplasms Mental Disorders Nervous System Disorder Neurocognitive Disorders Parent Patients Personality Disorders Physical Examination Psychiatrist Schizophrenia Serum Steroids

Infection, Immunity, and Psychiatric Disorders

Participants were individuals diagnosed with schizophrenia, bipolar disorder, major depressive disorder, or persons without a psychiatric disorder Who were enrolled in the Stanley Research Program at Sheppard Pratt in Baltimore, MD USA for a study of the association between infection, immunity, and psychiatric disorders. The participants with schizophrenia, bipolar disorder, and the non-psychiatric comparison group were enrolled between January 1, 2008, and December 31, 2021, and the participants with major depression in the period between March 1, 2013, and December 31, 2021.
The inclusion criterion for individuals with schizophrenia was a diagnosis of schizophrenia, schizophreniform disorder, or schizoaffective disorder. The inclusion criterion for individuals with bipolar disorder was a diagnosis of bipolar disorder including bipolar I disorder, bipolar II disorder, or bipolar disorder not otherwise specified. Those with major depressive disorder had either a single or recurrent episode. The psychiatric participants were recruited from inpatient and day hospital programs of Sheppard Pratt and from affiliated psychiatric programs. The diagnosis of each psychiatric participant was established by the research team including a board-certified psychiatrist and was based on the Structured Clinical Interview for DSM-IV Axis 1 Disorders and available medical records.
The inclusion criterion for the individuals without a psychiatric disorder was the absence of a current or past psychiatric disorder as determined by screening with the DSM-IV Axis I Disorders, Non-patient Edition. Persons in this group were recruited from posted announcements at local health facilities and universities in the same geographic area where the psychiatric participants were recruited.
Participants in all groups met the following additional criteria: age 18-65 (except the non-psychiatric controls who were aged 20-60); proficient in English; absence of any history of intravenous substance abuse; absence of intellectual disability by history; absence of HIV-1 infection; absence of serious medical disorder that would affect cognitive functioning; absence of a primary diagnosis of substance use disorder within the past three months per DSM-IV criteria.
The studies were approved by the Institutional Review Boards of the Sheppard Pratt and the Johns Hopkins Medical Institutions following established guidelines. IRB approval was obtained before study recruitment. All participants provided written informed consent after the study procedures were explained. Competence to give consent was assessed by research staff in the form of a short quiz following review of the written informed consent document; this method was approved by the Sheppard Pratt IRB.

Dickerson F., Katsafanas E., Origoni A., Newman T., Rowe K., Ziemann R.S., Bhatia K., Severance E., Ford G, & Yolken R. (2023). Cigarette smoking is associated with Herpesviruses in persons with and without serious mental illness. PLOS ONE, 18(1), e0280443.

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Publication 2023

Bipolar Disorder Bipolar Disorder Type 2 Diagnosis Diagnosis, Psychiatric Epistropheus HIV Infections Infection Inpatient Intellectual Disability Major Depressive Disorder Mental Disorders Patients Psychiatrist Response, Immune Schizoaffective Disorder Schizophrenia Schizophreniform Disorders Substance Abuse, Intravenous Substance Use Disorders

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What are the key characteristics of Bipolar Disorder Type 2?

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