Pathomechanisms and Signatures in the Longitudinal Course of Psychosis

13.01.2015

2020-12-02

038_ Genetic contributions to transdiagnostic symptom dimensions in patients with major depressive disorder, bipolar disorder, schizoaffective disorder, and schizophrenia

Research Question and Aims

In clinical practice, major depressive disorder, bipolar disorder, and schizophrenia are treated as distinct diagnostic categories despite a considerable degree of phenotypic and genetic overlap (e.g., Lee et al. 2019). Factor analyses of psychopathological symptoms have identified underlying transdiagnostic symptom dimensions, supporting the notion of shared etiological factors. Recently, Stein et al. (2020) have described a 5-factor model of psychopathological symptoms in a large group of psychiatric patients from the FOR2107 cohort (Kircher et al. 2019). To follow up on genetic contributions, the genetic associations with each of the 5 factor dimensions have been investigated within the FOR2107 cohort (unpublished data). In the here proposed analysis, selected associations are sought to be replicated in the independent PsyCourse cohort.

Analytic Plan

Replication analyses of selected genetic associations with the transdiagnostic symptom dimensions will be conducted in individuals of the PsyCourse study that were diagnosed with major depressive disorder, bipolar disorder, schizophrenia, or schizoaffective disorder. The factor dimensions as quantitative phenotypes will be remodeled using relevant items of symptom rating scales collected in the PsyCourse study such as PANSS and YMRS. For selected genetic markers, associations with the quantitative phenotypes will be examined using the linear regression approach in PLINK 1.90 including sex, age, and relevant ancestry components as covariates. Subsequently, association results will be meta-analyzed with results from the discovery cohort using METAL.

Resources needed

Phenotypic data ("200715_v4.1_psycourse_wd.RData"):
v1_id
gwas_id
v1_sex
v1_age
v1_stat
v1_scid_dsm_dx
v1_scid_dsm_dx_cat
v1_panss_p1
v1_panss_p2
v1_panss_p3
v1_panss_p4
v1_panss_p5
v1_panss_p6
v1_panss_p7
v1_panss_sum_pos
v1_panss_n1
v1_panss_n2
v1_panss_n3
v1_panss_n4
v1_panss_n5
v1_panss_n6
v1_panss_n7
v1_panss_sum_neg
v1_panss_g1
v1_panss_g2
v1_panss_g3
v1_panss_g4
v1_panss_g5
v1_panss_g6
v1_panss_g7
v1_panss_g8
v1_panss_g9
v1_panss_g10
v1_panss_g11
v1_panss_g12
v1_panss_g13
v1_panss_g14
v1_panss_g15
v1_panss_g16
v1_panss_sum_gen
v1_panss_sum_tot
v1_ymrs_itm1
v1_ymrs_itm2
v1_ymrs_itm3
v1_ymrs_itm4
v1_ymrs_itm5
v1_ymrs_itm6
v1_ymrs_itm7
v1_ymrs_itm8
v1_ymrs_itm9
v1_ymrs_itm10
v1_ymrs_itm11
v1_ymrs_sum
v1_idsc_itm1
v1_idsc_itm2
v1_idsc_itm3
v1_idsc_itm4
v1_idsc_itm5
v1_idsc_itm6
v1_idsc_itm7
v1_idsc_itm8
v1_idsc_itm9
v1_idsc_itm9a
v1_idsc_itm9b
v1_idsc_itm10
v1_idsc_itm11
v1_idsc_itm12
v1_idsc_itm13
v1_idsc_itm14
v1_idsc_itm15
v1_idsc_itm16
v1_idsc_itm17
v1_idsc_itm18
v1_idsc_itm19
v1_idsc_itm20
v1_idsc_itm21
v1_idsc_itm22
v1_idsc_itm23
v1_idsc_itm24
v1_idsc_itm25
v1_idsc_itm26
v1_idsc_itm27
v1_idsc_itm28
v1_idsc_itm29
v1_idsc_itm30
v1_idsc_sum
v1_cgi_s
v1_gaf

Biological analysis data:
Imputed genome-wide genotype data
Ancestry components (from MDS or PCA) if available