Pathomechanisms and Signatures in the Longitudinal Course of Psychosis

13.01.2015

2022-12-14

061_ Investigating the effect of metabolic syndrome components in cognitive performance of patients with bipolar disorder, schizophrenia and depression

Research Question and Aims

Previous evidence shows that psychiatric illnesses (such as major depression, bipolar disorder and schizophrenia) are characterized by an increased risk of metabolic syndrome (MetS). MetS is a clustering of cardiovascular risk factors characterized by abdominal obesity, high fasting glucose, dyslipemia and hypertension, and it is related to several adverse health outcomes, including an increased risk of developing cognitive impairment. The incidence of MS in these psychiatric conditions is multifactorial, where psychopharmacological treatments (certain mood stabilizers, antipsychotics or antidepressants) and genetics might play a critical role. The use of specific psychotropic medications is associated with an increased risk of cardiometabolic abnormalities. Previous evidence also reports a common genetic background of psychiatric and metabolic disorders.
On the other hand, cognitive impairment is common among patients with these psychiatric conditions during both euthymia and illness episodes. Some studies have suggested that cardiovascular risk factors as blood pressure, cholesterol and elevated triglycerides are important predictors of cognition in individuals with severe mental illnesses, and abdominal obesity is one of the predictors of cognitive impairment and quality of life. Whereas the relationship between cognition and MetS has received more attention in schizophrenia, it has been less studied in bipolar disorder, with conflicting results. This relationship between MetS and cognition might be also mediated by genetic factors.
The relation between cognition and MetS, and the influence of genetics, comorbidities and the effect of pharmacological treatments in severe psychiatric disorders has been little studied. The objective of the study is i) to determine if MetS components could predict cognitive impairment, and ii) if MetS components mediate the relationship of cognition with morbidity, pharmacological treatment, and polygenic risk scores in a sample of different psychiatric conditions.

Analytic Plan

Analysis will include the PsyCourse samples (schizophrenia, bipolar disorder and major depression patients). Using these data we will investigate the association of variables related to MetS with cognitive variables and the potential role of genetics and medical variables. A descriptive analysis of will be performed for all the target variables, for the cognitive variables we will create composite scores according to each cognitive domain. The whole sample will be divided according to presence/absence of MetS and potential differences between groups with and without MetS with regard to demographic and clinical measures with f-tests for continuous variables and chi-square tests for categorical ones. The differences in cognitive measures will be tested using two-way analyses of covariance (ANCOVAS) with grouping variable Group (BD vs. SCZ vs. MDD) and MetsS (with vs. without) controlling for age and sex.
The association of morbidities (comorbidity/somatic disorder), pharmacological treatments, and polygenic burden (PRScs) for several traits (schizophrenia, bipolar disorder, major depressive disorder, Type-2 Diabetes, MetS, triglyceride levels, cholesterol levels, HDL, LDL, educational attainment) with cognitive performance and MetS variables will be tested using linear models and adequate covariates.
Finally, a mediation analysis will be carried out to check whether the of association of cognitive outcomes and morbidities, pharmacological treatments, and polygenic risk scores are mediated by MetS-related variables. Mediation analyses will be carried out using the R package Mediation.

Resources needed

Neuropsychological variables
v1_nrpsy_tmt_A_rt
v1_nrpsy_tmt_B_rt
v1_nrpsy_dgt_sp_frw
v1_nrpsy_dgt_sp_bck
v1_nrpsy_dg_sym
v1_nrpsy_mwtb
v2_nrpsy_vlmt_corr
v2_nrpsy_vlmt_lss_d
v2_nrpsy_vlmt_lss_t
v2_nrpsy_vlmt_rec

Demographic
v1_sex
v1_age
v1_marital_stat
v1_partner
v1_no_bio_chld
v1_stp_chld
v1_liv_aln
v1_school
v1_prof_dgr
v1_ed_status
v1_curr_paid_empl
v1_disabl_pens

Clinical
v1_cur_psy_trm
v1_age_1st_out_trm
v1_daypat_inpat_trm
v1_age_1st_inpat_trm
v1_dur_illness
v1_1st_ep

Medication
v1_Antidepressants
v1_Antipsychotics
v1_Mood_stabilizers
v1_Tranquilizers
v1_Other_psychiatric
v1_lith
v1_lith_prd

Family
v1_fam_hist

Substance use
v1_ever_smkd
v1_lftm_alc_dep
v1_evr_ill_drg

Somatic disease
v1_waist
v1_bmi
v1_chol_trig
v1_hyperten
v1_ang_pec
v1_heart_att
v1_stroke
v1_diabetes
v1_hyperthy
v1_hypothy
v1_osteopor
v1_asthma
v1_autoimm
v1_cancer
v1_stom_ulc
v1_kid_fail
v1_epilepsy
v1_migraine
v1_parkinson
v1_tbi
v1_liv_cir_inf

Suicide
v1_scid_evr_suic_ide
v1_suic_attmpt
v1_scid_no_suic_attmpt

Diagnostic
v1_scid_dsm_dx_cat
v1_scid_age_MDE
v1_scid_no_MDE
v1_scid_age_mania
v1_scid_no_mania
v1_scid_age_hypomania
v1_scid_no_hypomania
v1_scid_ever_delus
v1_scid_ever_halls
v1_scid_ever_psyc
v1_scid_age_fst_psyc

Scales
V1_ panss_sum_pos
V1_panss_sum_neg
V1_panss_sum_gen
V1_panss_sum_tot
v1_idsc_sum
v1_ymrs_sum
v1_gaf
v1_bdi2_sum
v1_whoqol_itm14
v1_whoqol_dom_glob
v1_whoqol_dom_phys
v1_whoqol_dom_psy
v1_whoqol_dom_soc
v1_whoqol_dom_env

Raw data on medication
210908_v5.0_psycourse_clin_raw_med_(visit1 to visit4).RData
210908_v5.0_psycourse_con_raw_med_(visit1 to visit4).RData

Genomics data: Raw genotypes (GSA chip) and imputed data from PsyCourse patients.