Ignite Creation Date:
2025-12-24 @ 1:41 PM
Ignite Modification Date:
2025-12-24 @ 1:41 PM
Study NCT ID:
NCT05064995
Status:
UNKNOWN
Last Update Posted:
2021-10-01
First Post:
2021-09-14
Is Possible Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
BIPLONG - The Bipolar Disorder in the Longitudinal Course
Sponsor:
Medical University of Graz
Organization:
Study Overview
Official Title:
The Bipolar Disorder in the Longitudinal Course- Genom-wide Analysis of the genotype1 - phenotype2- Relationships in the Longitudinal Course of Psychosis
Status:
UNKNOWN
Status Verified Date:
2021-09
Last Known Status:
RECRUITING
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
BIPLONG
Brief Summary:
The BIPLONG (The Bipolar Disorder in the Longitudinal Course ) study is a longitudinal study on the course of bipolar disorders and comprises two sub-studies: On the one hand, BIPLONG examines the genetic foundation and change in bipolar disorder, on the other hand, metabolic changes, clinical symptoms and cognition in bipolar disorders is evaluated. A current subproject of BIPLONG is the analysis of the psychological response of the COVID-19 (Corona virus disease) pandemic. With the parameters examined in BIPLONG, it is hoped to gain better understanding of the bipolar disorder in the longitudinal course.
Detailed Description:
Study Procedure:
In addition to the bipolar patients, healthy controls will also be included. The same inventories will be used for the control subjects and the same examinations or visits will be performed; bipolar-specific disease questions will not be asked in controls.
Intervention: Longitudinal study
Method:
All patients and controls undergo several assessments every six months:
Blood samples are collected with the following main parameters of interest being examined:
* Collection and analysis of DNA, establishment of permanent cell lines, determination of mRNA and gene products (proteins), proteomics, lipidomics.
* Routine parameters: Blood count, TSH, T3, T4, homocysteine, creatinine, amylase, lipase, CK, urea, uric acid, coagulation, HBA1c, glucose, lipids (triglyceryl, LDL, HDL, cholesterol, mass spectrometry), transaminases, CRP- levels, vitamin D.
* Biomarkers: oxidative stress parameters and antioxidants, neuroinflammatory markers (e.g. interleukins, tumor necrosis factor, interferons, GDNF, VEGF, etc.), neurotrophins (BDNF, NT, Trk..), insulin, IGF, adipokines, Apo-E and AAT analysis, tryptophan/kynurenine metabolites
* Intestinal hormones grehlin, glucagon-like peptides 1 and 2 (GLP-1/2) and cholecystokinin
Additionally, socio-demographic data and psychological data are collected by administering self-assessment questionnaires. Further, neurocognitive tests are administered.
The current psychological and psychiatric state of all subjects is examined by external ratings done by experts.
Anthropomethric measures are examined (waist-to-hip ratio, blood pressure, weight, height).
Additionally, MRI is conducted on all subjects (for patients every 6 months, for controls every 12 months).
Primary hypothesis:
* Gene-environment interactions are significantly contributory to bipolar affective disorder.
* There are pathologically altered neurobiological markers that play a role in the pathogenesis of bipolar disorder.
* There is an influence of anthropometric data on the course of bipolar disorder.
Statistical analysis and anticipated sample size:
Baseline data analysis will be investigated using a multi-factorial between subject design, with the variables of group (bipolar patients versus healthy controls), gender (males versus females), weight (normal weight versus overweight), etc. as independent factors, depending on the research question. As dependent variables, in addition to sociodemographic and clinical variables (number of episodes, etc.), physiological parameters (blood parameters, anthropometry and lipometer data, EEG, ECG, MRI) and psychological variables (psychological questionnaires) will be investigated. Likewise, covariates such as age or body mass index will be included as needed.
Correlation analyses (bivariate, partial) should show possible correlations between the variables. Discriminant analyses should find out which variable best separates the investigated groups (e.g. patients vs. controls). Furthermore, regression analyses (linear, multiple) will be performed to obtain additional information about the predictive value of the variables under investigation. All analyses will be computed using IBM SPSS Statistics 20.
For the "a priori analysis" of the follow-up study (T1-T5), a repeated measures design (repeated measures within factors) was adopted. The case number calculation (effect size d between .30 and .80; Cohen, 1988) for the F-test thus results in a sample size of 47 patients with a target effect size of .40 (power 95%; alpha .05; calculated with GPower 3.1). The correlation analyses at the first measurement time point (power .95, alpha .05, effect size: .35) yields 79 subjects per group (Pat. vs. controls) at all time-points.
In addition to the bipolar patients, healthy controls will also be included. The same inventories will be used for the control subjects and the same examinations or visits will be performed; bipolar-specific disease questions will not be asked in controls.
Intervention: Longitudinal study
Method:
All patients and controls undergo several assessments every six months:
Blood samples are collected with the following main parameters of interest being examined:
* Collection and analysis of DNA, establishment of permanent cell lines, determination of mRNA and gene products (proteins), proteomics, lipidomics.
* Routine parameters: Blood count, TSH, T3, T4, homocysteine, creatinine, amylase, lipase, CK, urea, uric acid, coagulation, HBA1c, glucose, lipids (triglyceryl, LDL, HDL, cholesterol, mass spectrometry), transaminases, CRP- levels, vitamin D.
* Biomarkers: oxidative stress parameters and antioxidants, neuroinflammatory markers (e.g. interleukins, tumor necrosis factor, interferons, GDNF, VEGF, etc.), neurotrophins (BDNF, NT, Trk..), insulin, IGF, adipokines, Apo-E and AAT analysis, tryptophan/kynurenine metabolites
* Intestinal hormones grehlin, glucagon-like peptides 1 and 2 (GLP-1/2) and cholecystokinin
Additionally, socio-demographic data and psychological data are collected by administering self-assessment questionnaires. Further, neurocognitive tests are administered.
The current psychological and psychiatric state of all subjects is examined by external ratings done by experts.
Anthropomethric measures are examined (waist-to-hip ratio, blood pressure, weight, height).
Additionally, MRI is conducted on all subjects (for patients every 6 months, for controls every 12 months).
Primary hypothesis:
* Gene-environment interactions are significantly contributory to bipolar affective disorder.
* There are pathologically altered neurobiological markers that play a role in the pathogenesis of bipolar disorder.
* There is an influence of anthropometric data on the course of bipolar disorder.
Statistical analysis and anticipated sample size:
Baseline data analysis will be investigated using a multi-factorial between subject design, with the variables of group (bipolar patients versus healthy controls), gender (males versus females), weight (normal weight versus overweight), etc. as independent factors, depending on the research question. As dependent variables, in addition to sociodemographic and clinical variables (number of episodes, etc.), physiological parameters (blood parameters, anthropometry and lipometer data, EEG, ECG, MRI) and psychological variables (psychological questionnaires) will be investigated. Likewise, covariates such as age or body mass index will be included as needed.
Correlation analyses (bivariate, partial) should show possible correlations between the variables. Discriminant analyses should find out which variable best separates the investigated groups (e.g. patients vs. controls). Furthermore, regression analyses (linear, multiple) will be performed to obtain additional information about the predictive value of the variables under investigation. All analyses will be computed using IBM SPSS Statistics 20.
For the "a priori analysis" of the follow-up study (T1-T5), a repeated measures design (repeated measures within factors) was adopted. The case number calculation (effect size d between .30 and .80; Cohen, 1988) for the F-test thus results in a sample size of 47 patients with a target effect size of .40 (power 95%; alpha .05; calculated with GPower 3.1). The correlation analyses at the first measurement time point (power .95, alpha .05, effect size: .35) yields 79 subjects per group (Pat. vs. controls) at all time-points.
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?: