Methods: BIPGEN is a cross-sectional study on the genetics of bipolar disorder (BD). BIPGEN
includes a personality questionnaire (TEMPS-A). DNA is isolated in the BIPGEN study from
fasting blood with the QUIASYMPHONY robot from study participants with Bipolar Disorder
(diagnosis according to DSM-IV) and healthy controls. The DNA is then genotyped with classic
genotyping arrays (GWAS array). The aim of BIPGEN is to associate genetic variants
(single-nucleotide-polymorphisms/ SNPs or copy-number-variations/CNVs) with bipolar affective
disorder.
A subproject of BIPGEN is the BIP-COVID project, which is a cross-sectional genetics study
about risks & resilience in the COVID-19 pandemic in BD and healthy controls at the Medical
University of Graz. Study participants with BD and controls from the well-established BIPLONG
and BIPGEN studies will undergo a special BIP-COVID visit, which will include a COVID-19
specific online Lime survey about the psychological burden in the COVID-19 crisis, a COVID-19
antibody test (IgM and IgG), inflammation markers and isolation of DNA from fasting blood.
Genotyping of DNA will be done with the GSA V.3 array. Genetic analyses (Polygenic Risk
Scores of I. Stress or Major Depression and II. COVID-19 infection established with the
programs PLINK, PRSice and R) will be used to analyze the genetic mechanisms of COVID-19
pandemic associated psychological symptoms and COVID-19 infection risk. Systems biology
methods will be used to depict protective pathways against COVID-19 infection (e.g. Lithium
pathways) and against COVID-19 associated psychiatric symptoms
Aim:
We aim at analyzing the neuropsychological and genetic underpinning of COVID-19
associatedreactive psychiatric symptoms in BD and in healthy controls.
We aim at analyzing genetic predictors of COVID-19 infection in BD and in controls.
We aim at analyzing the protective effects of the GSK-3β inhibitor lithium against
COVID-19 infection.
Intervention: Cross-sectional genetics study
Key inclusion and exclusion criteria: Inclusion criteria are written consent after previous
written and verbal information, diagnosis of BD according to DSM-IV and age between 18 and 75
years. Exclusion criteria include acute suicidality, lack of consent, severe active drug
dependence (i.e., alcohol, benzodiazepines, morphine), other currently active severe mental /
cerebral organic disease (e.g. epilepsy, brain tumor), severe skull-brain trauma / brain
surgery in the past, known florid tumor disease, congenital / infantile mental retardation,
dementia (from Mini-Mental State Examination (MMSE) 20), severe florid autoimmune diseases or
current immunosuppression (e.g., lupus erythematosus, HIV (human immunodeficiency virus),
multiple sclerosis), cardiac, renal and pulmonary disorders or PTSD (post-traumatic stress
disorder) or anxiety.
Healthy controls do not have a history of mental disorder and do not have first- or
second-degree relatives with psychiatric disorders.
Primary and secondary endpoint(s) of the BIPCOVID project:
The primary endpoint is PRS of stress, the secondary endpoint is PRS of COVID-19 risk.
Sample size, statistical analyses, power calculation: The program GPower (Version 3.1) was
used for the calculation of the number of cases. Linear bivariate regression analyses for two
groups (BD and control cohort) will be calculated with the results from
psychological/psychiatric inventories as predictors (e.g. Pittsburgh Sleep Quality Index,
Mediterranean Diet Score, Resilience Scale) and the three PRS as criterion. GPower
calculates for a linear bivariate regression, with a Δ slope of 0.03, α = .05 and a power of
95 % a total sample size of 364 persons.
Trial duration of BIPCOVID: 3 years.
Participating centers: The BIP-COVID sample will be recruited as monocentric study at the
special outpatient department for Bipolar Disorders (managed by Univ.Prof. Eva Reininghaus)
at the Department of Psychiatry and Psychotherapeutic Medicine at the Medical University of
Graz, Austria. Psychiatric genetics and bioinformatics experts from the University of Basel,
the University of Marburg, the University of Bonn, the Karolinska Institutet & Medical
University of Vienna & CAMH Toronto will supervise the KLIF-funded doctoral student and will
support the state-of-the-art bioinformatics analyses.