Most previous genome-wide association studies (GWAS) of depression have used data from individuals of European descent. This limits the understanding of the underlying biology of depression and raises questions about the transferability of findings between populations.
The drug binding to plasma and tissue proteins are fundamental factors in determining the overall pharmacological activity of a drug.Human serum albumin (HSA), together with a 1 -acid glycoprotein (AGP), are the most important plasma proteins, which act as drug carriers, with drug pharmacokinetic implications, resulting in important clinical impacts for drugs that have a relatively narrow therapeutic index.This review focuses on the combination of biochromatography and circular dichroism as an effective approach for the characterization of albumin binding sites and their enantioselectivity.Furthermore, their applications to the study of changes in the binding properties of the protein arising by the reversible or covalent binding of drugs are discussed, and examples of physiological relevance reported.Perspectives of these studies reside in supporting the development of new drugs, which require miniaturization to facilitate the screening of classes of compounds for their binding to the target protein, and a deeper characterization of the mechanisms involved in the molecular recognition processes.
Abstract Schizophrenia (SCZ) and bipolar disorder (BD) are highly heritable disorders that share a significant proportion of common risk variation. Understanding the genetic factors underlying the specific symptoms of these disorders will be crucial for improving diagnosis, intervention and treatment. In case-control data consisting of 53,555 cases (20,129 BD, 33,426 SCZ) and 54,065 controls, we identified 114 genome-wide significant loci (GWS) when comparing all cases to controls, of which 41 represented novel findings. Two genome-wide significant loci were identified when comparing SCZ to BD and a third was found when directly incorporating functional information. Regional joint association identified a genomic region of overlapping association in BD and SCZ with disease-independent causal variants indicating a fourth region contributing to differences between these disorders. Regional SNP-heritability analyses demonstrated that the estimated heritability of BD based on the SCZ GWS regions was significantly higher than that based on the average genomic region (91 regions, p = 1.2×10 −6 ) while the inverse was not significant (19 regions, p=0.89). Using our BD and SCZ GWAS we calculated polygenic risk scores and identified several significant correlations with: 1) SCZ subphenotypes: negative symptoms (SCZ, p=3.6×10 −6 ) and manic symptoms (BD, p=2×10 −5 ), 2) BD subphenotypes: psychotic features (SCZ p=1.2×10 −10 , BD p=5.3×10 −5 ) and age of onset (SCZ p=7.9×10 −4 ). Finally, we show that psychotic features in BD has significant SNP-heritability (h 2 snp =0.15, SE=0.06), and a significant genetic correlation with SCZ (r g =0.34) in addition there is a significant sign test result between SCZ GWAS and a GWAS of BD cases contrasting those with and without psychotic features (p=0.0038, one-side binomial test). For the first time, we have identified specific loci pointing to a potential role of 4 genes ( DARS2 , ARFGEF2 , DCAKD and GATAD2A ) that distinguish between BD and SCZ, providing an opportunity to understand the biology contributing to clinical differences of these disorders. Our results provide the best evidence so far of genomic components distinguishing between BD and SCZ that contribute directly to specific symptom dimensions.
The wide-scale analysis of protein expression provides a powerful strategy for the molecular exploration of complex pathophysiological mechanisms, such as the response to antidepressants. Using a 2D proteomic approach we investigated the Flinders Sensitive Line (FSL), a genetically selected rat model of depression, and the control Flinders Resistant Line (FRL). To evaluate gene–environment interactions, FSL and FRL pups were separated from their mothers for 3 h (maternal separation, MS), as early-life trauma is considered an important antecedent of depression. All groups were treated with either escitalopram (Esc) admixed to food (25 mg/kg.d) or vehicle for 1 month. At the week 3, forced swim tests were performed. Protein extracts from prefrontal/frontal cortex and hippocampus were separated by 2D electrophoresis. Proteins displaying statistically significant differences in expression levels were identified by mass spectrometry. Immobility time values in the forced swim test were higher in FSL rats and reduced by antidepressant treatment. Moreover, the Esc-induced reduction in immobility time was not detected in MS rats. The impact of genetic background in response to Esc was specifically investigated here. Bioinformatics analyses highlighted gene ontology terms showing tighter associations with the modulated proteins. Esc modulated protein belonging to cytoskeleton organization in FSL; carbohydrate metabolism and intracellular transport in FRL. Proteins differently modulated in the two strains after MS and Esc play a role in cytoskeleton organization, vesicle-mediated transport, apoptosis regulation and macromolecule catabolism. These findings suggest pathways involved in neuronal remodelling as molecular correlates of response to antidepressants in a model of vulnerability.
Blood has been the object of a search for biomarkers for psychiatric disorders since long before the advent of proteomics. A series of investigations have been conducted on serum or plasma, either by focusing on protein candidates such as cytokines or brain-derived neurotrophic factor (BDNF) or by testing multiple candidates simultaneously. Notwithstanding the amount of suggestive evidence for depression, no real biomarker application has made an impact on clinical practice so far. Relatively consistent findings have been obtained for a few candidate proteins, such as BDNF - which, however, appears to be nonspecifically dysregulated across many neuropsychiatric conditions. Combination of biomarkers and the broader picture represented by proteomic profiles are providing a better chance to divide the disorder into subtypes and gain specificity versus other diseases. Most efforts have focused on the identification of proteomic signatures able to discriminate patients from controls, even leading to the proposal of diagnostic tests for mental disorders; however, no major attempts have been made to fulfill the clinical need for signatures able to predict response to antidepressants. In this review, the most interesting findings obtained by searching serum or plasma by proteomic approaches are put into the context of their potential clinical application, highlighting potential pitfalls and opportunities. New directions in proteomic biomarker efforts beyond cross-sectional studies in case-control collections as defined by diagnosis are advocated, and the need for an effective integration of biomarkers at different levels is emphasized. Capturing the contribution of genetic variability to protein expression, and ultimately integrating this information with imaging measures of brain structure and function, will open new avenues for the discovery of mechanisms and circuits involved in disease pathophysiology and drug response.
'%3e%3cpath fill='%23012169' d='M0 0v30h60V0z'/%3e%3cpath stroke='%23fff' stroke-width='6' d='m0 0 60 30m0-30L0 30'/%3e%3cpath stroke='%23C8102E' stroke-width='4' d='m0 0 60 30m0-30L0 30' clip-path='url(%23b)'/%3e%3cpath stroke='%23fff' stroke-width='10' d='M30 0v30M0 15h60'/%3e%3cpath stroke='%23C8102E' stroke-width='6' d='M30 0v30M0 15h60'/%3e%3c/g%3e%3c/svg%3e)