Biology subjects

Zandi, P. P.

Publications and source records attributed to Zandi, P. P..

3 recordsLinked to original sources

bioRxiv2020

Circadian rhythms in bipolar disorder patient-derived neurons predict lithium response

Bipolar disorder (BD) is a neuropsychiatric disorder with genetic risk factors defined by recurrent episodes of mania/hypomania, depression and circadian rhythm abnormalities. While lithium is an effective drug for BD, 30-40% of patients fail to respond adequately to treatment. Previous work has demonstrated that lithium affects the expression of "clock genes" and that lithium responders (Li-R) can be distinguished from non-responders (Li-NR) by differences in circadian rhythms. However, rhythm abnormalities in BD have not been evaluated in neurons and it is unknown if neuronal rhythms differ between Li-R and Li-NR. We used induced pluripotent stem cells (iPSCs) to culture neuronal precursor cells (NPC) and glutamatergic neurons from BD patients and controls. We identified strong circadian rhythms in Per2-luc expression in NPCs and neurons from controls and Li-R. NPC rhythms in Li-R had a shorter circadian period. Li-NR rhythms were low-amplitude and profoundly weakened. In NPCs and neurons, expression of PER2 was higher in both BD groups compared to controls. In neurons, PER2 protein expression was higher in BD than controls, especially in Li-NR samples. In single cells, NPC and neuron rhythms in both BD groups were desynchronized compared to controls. Lithium lengthened period in Li-R and control neurons but failed to alter rhythms in Li-NR. In contrast, temperature entrainment increased amplitude across all groups, and partly restored rhythms in Li-NR neurons. We conclude that neuronal circadian rhythm abnormalities are present in BD and most pronounced in Li-NR. Rhythm deficits in BD may be partly reversible through stimulation of entrainment pathways.

neuroscience↗

bioRxiv2019

lncRNAKB: A comprehensive knowledgebase of long non-coding RNAs

We have assembled a comprehensive long non-coding RNA knowledgebase (lncRNAKB) of 77,199 annotated human lncRNAs (224,286 transcripts) by methodically integrating widely used lncRNAs resources. To facilitate functional characterization of lncRNAs, we employed Genotype-Tissue Expression (GTEx) project to provide tissue-specific gene expression profiles of lncRNAs in 31 solid organ tissues. Additional information includes network analysis to identify co-expressed gene modules to potentially delineate lncRNA function. Tissue-specificity, phylogenetic conservation scores and coding potential for lncRNAs are included. Finally, using whole genome sequencing data from GTEx, expression quantitative trait loci (cis-eQTL) regulated lncRNAs were calculated in all tissues. lncRNAKB is available at http://www.lncrnakb.org.

bioinformatics↗

bioRxiv2017

Defining Depression Cohorts Using the EHR: Multiple Phenotypes Based on ICD-9 Codes and Medication Orders

BackgroundMajor Depressive Disorder (MDD) is one of the most common mental illnesses and a leading cause of disability worldwide. Electronic Health Records (EHR) allow researchers to conduct unprecedented large-scale observational studies investigating MDD, its disease development and its interaction with other health outcomes. While there exist methods to classify patients as clear cases or controls, given specific data requirements, there are presently no simple, generalizable, and validated methods to classify an entire patient population into varying groups of depression likelihood and severity. MethodsWe have tested a simple, pragmatic electronic phenotype algorithm that classifies patients into one of five mutually exclusive, ordinal groups, varying in depression phenotype. Using data from an integrated health system on 278,026 patients from a 10-year study period we have tested the convergent validity of these constructs using measures of external validation, including patterns of psychiatric prescriptions, symptom severity, indicators of suicidality, comorbidity, mortality, health care utilization, and polygenic risk scores for MDD. ResultsWe found consistent patterns of increasing morbidity and/or adverse outcomes across the five groups, providing evidence for convergent validity. LimitationsThe study population is from a single rural integrated health system which is predominantly white, possibly limiting its generalizability. ConclusionOur study provides initial evidence that a simple algorithm, generalizable to most EHR data sets, provides categories with meaningful face and convergent validity that can be used for stratification of an entire patient population.

epidemiology↗