Immunoglobulin genes expressed in lymphoblast cell lines discern and predict lithium response in bipolar disorder patients

Abstract

Bipolar disorder (BD) is a neuropsychiatric mood disorder manifested by recurrent episodes of mania and depression. More than half of BD patients are non-responsive to lithium, the first-line treatment drug, complicating BD clinical management. Given its unknown etiology, it is pertinent to understand the genetic signatures that lead to variability in lithium treatment. We discovered a set of differentially expressed genes from the LCLs of 10 controls and 19 BD patients belonging mainly to the immunoglobulin gene family that can be used as potential biomarkers to diagnose and treat BD. Importantly, we trained a machine learning algorithm on our datasets that predicted the lithium response of BD subtypes with no errors, even when used on a different cohort of 24 BD patients acquired by a different laboratory. This proves the scalability of our methodology for predicting lithium response in BD and for a prompt and suitable decision on therapeutic interventions.

Brain Extracellular Matrix implications in multiple neurological disorders are revealed through a meta-analysis of transcriptional changes

“…Alternative models were deemed less suitable for our objectives. Notably, peripheral blood emerges as a crucial tool for researching the diagnosis and prognosis of diseases, including neurological disorders [73, 74]. Recently, clinical trials have commenced for blood-based biomarkers of Alzheimer’s disease.…”

Predicting Suicide Risk in Bipolar Disorder patients from Lymphoblastoid Cell Lines genetic signatures

“…An elevated fast after-hyper-polarization (AHP) was shown to be a distinct trait in BD neurons, which has been implicated in various neurological disorders [34][35][36]. The study led to the development of computational models for the prediction of lithium treatment [37,38]. Given the high risk of suicide among patients with BD, there is a strong need to understand the neurobiological and genetic factors of suicide, an iPSC model may shed more light on the related mechanism [39].…”

“…Additionally, the PENK gene, along with IL-7 and TMX3 , involved in stress and anxiety responses, were linked to suicidal behavior in BD patients [57]. Comprehensive multi-ancestry GWAS analysis has pinpointed genes such as DRD2 , FURIN , NLGN1 , SOX5 , PDE4B , and CACNG2 as involved in suicidal behavior, alongside identifying potential biomarkers within the immunoglobulin gene family for BD [38, 58]. Despite these advancements, a classification based solely on GWAS data remains challenging.…”