2021-02-25

039_ An integrative genomic and proteomic data approach to identify biomarkers related to psychopathology of bipolar disorder and schizophrenia

Research Question and Aims

The use of state-of-the-art proteomics and genomics techniques and the integration of both data modalities holds promise for the identification of reliable biomarkers in molecular psychiatry (Azmeraw T. Amare et al., 2017). In this research proposal, we have the following objectives:
1) Characterizing the genetic and longitudinal circulating proteomic signatures in bipolar patients (BD) that are potentially related to changes in psychopathology over time.
2) Determining the correlation between genetic and circulating protein biomarkers with cross-sectional psychopathological features in BD and schizophrenia (SCZ).

Analytic Plan

Data
Phenotypic data:
State variables in PsyCourse related to psychopathology would be used in this study as target variables.

Biological data:
Proteomics: A first-pass screening (Mass Spectrometry) of ~450 proteins in the serum of ~120 BD patients and also ~100 proteins quantified by high-throughput antibody-based assay in serum of 113 SCZ and 125 BD patients (Papiol et al., 2019) are already available for analysis from the PsyCourse cohort.
Genomics: Raw genotypes (GSA chip) and imputed data from PsyCourse patients.

Association analyses & statistical approach
Using the aforementioned data, we will investigate:
1) The associations between polygenic load, protein (Mass Spectrometry) level changes and psychopathological variations over time in BD patients. These analyses will be adjusted for age, sex, treatment, population stratification (PCA or MDS components) and other relevant covariates in the context of repeated measures / linear mixed models.
2) The cross-sectional associations of polygenic load and a selected panel of ~100 serum proteins in 125 BD and 113 SCZ patients with psychopathological severity will be assessed. These analyses will be adjusted for age, sex, treatment, population stratification (PCA or MDS components) and other relevant covariates in the context of linear/logistic models.

Resources needed

For those subjects with "Y" in v1_prot_id, v2_prot_id, v3_prot_id, v4_prot_id, v1_ab_prof_id, v2_ab_prof_id, v3_ab_prof_id:
Demographics
v1_sex

v1_age
v2_age
v3_age
v4_age

Clinics, psychopathology
v1_cur_psy_trm
v2_cur_psy_trm
v3_cur_psy_trm
v4_cur_psy_trm

v1_dur_illness

v1_scid_dsm_dx_cat

v1_panss_sum_pos
v2_panss_sum_pos
v3_panss_sum_pos
v4_panss_sum_pos

v1_panss_sum_neg
v2_panss_sum_neg
v3_panss_sum_neg
v4_panss_sum_neg

v1_panss_sum_gen
v2_panss_sum_gen
v3_panss_sum_gen
v4_panss_sum_gen

v1_ymrs_sum
v2_ymrs_sum
v3_ymrs_sum
v4_ymrs_sum

v1_idsc_sum
v2_idsc_sum
v3_idsc_sum
v4_idsc_sum

v1_bdi2_sum
v2_bdi2_sum
v3_bdi2_sum
v4_bdi2_sum

v1_asrm_sum
v2_asrm_sum
v3_asrm_sum
v4_asrm_sum

v1_idsc_sum
v2_idsc_sum
v3_idsc_sum
v4_idsc_sum

v1_mss_sum
v2_mss_sum
v3_mss_sum
v4_mss_sum

Raw data on medication and drug use
200715_v4.1_psycourse_clin_raw_med_(visit1 to visit4).RData
200715_v4.1_psycourse_clin_raw_ill_drg_(visit1 to visit4).RData

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

Proteomics: The first-pass screening (Mass Spectrometry) of ~450 proteins in the serum of ~120 BD patients and also the ~100 proteins quantified by high-throughput antibody-based assay in serum of 113 SCZ and 125 BD patients that are already available for analysis from the PsyCourse cohort.