Biology subjects

Amare, A. T.

Publications and source records attributed to Amare, A. T..

3 recordsLinked to original sources

bioRxiv2018

Polygenic scores for major depressive disorder and depressive symptoms predict response to lithium in patients with bipolar disorder

BackgroundLithium is a first-line medication for bipolar disorder (BD), but only [~]30% of patients respond optimally to the drug. Since genetic factors are known to mediate lithium treatment response, we hypothesized whether polygenic susceptibility to the spectrum of depression traits is associated with treatment outcomes in patients with BD. In addition, we explored the potential molecular underpinnings of this relationship.\n\nMethodsWeighted polygenic scores (PGSs) were computed for major depressive disorder (MDD) and depressive symptoms (DS) in BD patients from the Consortium on Lithium Genetics (ConLi+Gen; n=2,586) who received lithium treatment. Lithium treatment outcome was assessed using the ALDA scale. Summary statistics from genome-wide association studies (GWAS) in MDD (130,664 cases and 330,470 controls) and DS (n=161,460) were used for PGS weighting. Associations between PGSs of depression traits and lithium treatment response were assessed by binary logistic regression. We also performed a cross-trait meta-GWAS, followed by Ingenuity(R) Pathway Analysis.\n\nOutcomesBD patients with a low polygenic load for depressive traits were more likely to respond well to lithium, compared to patients with high polygenic load (MDD: OR =1.64 [95%CI: 1.26-2.15], lowest vs highest PGS quartiles; DS: OR=1.53 [95%CI: 1.18-2.00]). Associations were significant for type 1, but not type 2 BD. Cross-trait GWAS and functional characterization implicated voltage-gated potassium channels, insulin-related pathways, mitogen-activated protein-kinase (MAPK) signaling, and miRNA expression. Interpretation: Genetic loading to depression traits in BD patients lower their odds of responding optimally to lithium. Our findings support the emerging concept of a lithium-responsive biotype in BD.\n\nFundingsee attached details

genomics↗

bioRxiv2017

High genetic loading for schizophrenia predicts poor response to lithium in patients with bipolar disorder: A polygenic score and cross-trait genetic analysis

ImportanceLithium is a first-line mood stabilizer for the maintenance treatment of Bipolar Disorder (BPD). However, the efficacy of lithium varies widely, with a non-response rate of up to 30%. Biological response markers and predictors are lacking.\n\nObjectiveGenetic factors are thought to mediate lithium treatment response, and the previously reported genetic overlap between BPD and schizophrenia (SCZ) led us to test whether a polygenic score (PGS) for SCZ could predict lithium treatment response in BPD. Further, we explored the potential molecular underpinnings of this association.\n\nDesignWeighted SCZ PGSs were computed at ten p-value thresholds (PT) using summary statistics from a genome-wide association study (GWAS) of 36,989 SCZ cases, and genotype data for BPD patients from the Consortium on Lithium Genetics (ConLi+Gen). For functional exploration, we performed a cross-trait meta-GWAS and pathway analysis, combining GWAS summary statistics on SCZ and lithium treatment response.\n\nSettingInternational multicenter GWAS.\n\nParticipantsPatients with BPD who had undergone lithium treatment were genotyped and retrospectively assessed for long-term treatment response (n=2,586).\n\nMain outcome measuresClinical treatment response to lithium was defined on both the categorical and continuous scales using the ALDA score. The effect measures include odds ratios (ORs) and the proportion of variance explained (R2), and a significant association was determined at p<0.05.\n\nResultsThe PGS for SCZ was inversely associated with lithium treatment response in the categorical outcome (p=8x10-5), at PT <5x10-2. Patients with BPD who had low polygenic load for SCZ responded better to lithium, with ORs for lithium response ranging from 3.46 [95%CI: 1.42-8.41 at 1st decile] to 2.03 [95%CI: 0.86-4.81 at the 9th decile], compared to the patients in the 10th decile of SCZ risk. In the cross-trait meta-GWAS, 15 genetic loci that may have overlapping effects on lithium treatment response and susceptibility to SCZ were identified. Functional pathway and network analysis of these loci point to the HLA complex and inflammatory cytokines (TNF, IL-4, IFN{gamma}) as molecular contributors to lithium treatment response in BPD.\n\nConclusions and RelevanceThe study provides, for the first-time, evidence for a negative association between high genetic loading for SCZ and poor response to lithium in patients with BPD. These results suggest the potential for translational research aimed at personalized prescribing of lithium.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSDoes a polygenic score for Schizophrenia (SCZ) predict response to lithium in patients with Bipolar Disorder (BPD)? What are the molecular drivers of the association between SCZ and lithium treatment response?\n\nFindingsWe found an inverse association between genetic loading for SCZ risk variants and response to lithium in patients with BPD. Genetic variants in the HLA region on chromosome 6, the antigen presentation pathway and markers of inflammation (TNF, IL-4, IFN{gamma}) point to molecular underpinnings of lithium treatment response in BPD.\n\nMeaningIn patients with BPD, an assessment of a polygenic load for SCZ risk variants may assist in conjunction with clinical data to predict whether they would respond to lithium treatment.

genetics↗

bioRxiv2017

The genetic overlap between mood disorders and cardio-metabolic diseases: A systematic review of genome wide and candidate gene studies

Meta-analyses of genome-wide association studies (meta-GWAS) and candidate gene studies have identified genetic variants associated with cardiovascular diseases, metabolic diseases, and mood disorders. Although previous efforts were successful for individual disease conditions (single disease), limited information exists on shared genetic risk between these disorders. This article presents a detailed review and analysis of cardio-metabolic diseases risk (CMD-R) genes that are also associated with mood disorders. Firstly, we reviewed meta-GWA studies published until January 2016, for the diseases \"type 2 diabetes, coronary artery disease, hypertension\" and/or for the risk factors \"blood pressure, obesity, plasma lipid levels, insulin and glucose related traits\". We then searched the literature for published associations of these CMD-R genes with mood disorders. We considered studies that reported a significant association of at least one of the CMD-R genes and \"depressive disorder\" OR \"depressive symptoms\" OR \"bipolar disorder\" OR \"lithium treatment\", OR \"serotonin reuptake inhibitors treatment\". Our review revealed 24 potential pleiotropic genes that are likely to be shared between mood disorders and CMD-Rs. These genes include MTHFR, CACNA1D, CACNB2, GNAS, ADRB1, NCAN, REST, FTO, POMC, BDNF, CREB, ITIH4, LEP, GSK3B, SLC18A1, TLR4, PPP1R1B, APOE, CRY2, HTR1A, ADRA2A, TCF7L2, MTNR1B, and IGF1. A pathway analysis of these genes revealed significant pathways: corticotrophin-releasing hormone signaling, AMPK signaling, cAMP-mediated or G-protein coupled receptor signaling, axonal guidance signaling, serotonin and dopamine receptors signaling, dopamine-DARPP32 feedback in cAMP signaling, circadian rhythm signaling and leptin signaling. Our findings provide insights in to the shared biological mechanisms of mood disorders and cardio-metabolic diseases.

genomics↗