Multivariate brain-behaviour associations in psychiatric disorders.

Mapping brain-behaviour associations is paramount to understand and treat psychiatric disorders. Standard approaches involve investigating the association between one brain and one behavioural variable (univariate) or multiple variables against one brain/behaviour feature ('single' multivariate). Recently, large multimodal datasets have propelled a new wave of studies that leverage on 'doubly' multivariate approaches capable of parsing the multifaceted nature of both brain and behaviour simultaneously. Within this movement, canonical correlation analysis (CCA) and partial least squares (PLS) emerge as the most popular techniques. Both seek to capture shared information between brain and behaviour in the form of latent variables. We provide an overview of these methods, review the literature in psychiatric disorders, and discuss the main challenges from a predictive modelling perspective. We identified 39 studies across four diagnostic groups: attention deficit and hyperactive disorder (ADHD, k = 4, N = 569), autism spectrum disorders (ASD, k = 6, N = 1731), major depressive disorder (MDD, k = 5, N = 938), psychosis spectrum disorders (PSD, k = 13, N = 1150) and one transdiagnostic group (TD, k = 11, N = 5731). Most studies (67%) used CCA and focused on the association between either brain morphology, resting-state functional connectivity or fractional anisotropy against symptoms and/or cognition. There were three main findings. First, most diagnoses shared a link between clinical/cognitive symptoms and two brain measures, namely frontal morphology/brain activity and white matter association fibres (tracts between cortical areas in the same hemisphere). Second, typically less investigated behavioural variables in multivariate models such as physical health (e.g., BMI, drug use) and clinical history (e.g., childhood trauma) were identified as important features. Finally, most studies were at risk of bias due to low sample size/feature ratio and/or in-sample testing only. We highlight the importance of carefully mitigating these sources of bias with an exemplar application of CCA.

Solid-supported lipid membranes as a tool for determination of membrane affinity: high-throughput screening of a physicochemical parameter.

Quantification of membrane affinity is an important early screening step in modern drug design. However, current approaches using different lipid membrane models usually are time-consuming or show severe experimental drawbacks. In this paper we describe the use of solid-supported lipid membranes (TRANSIL) as a new tool for the determination of membrane affinity. Eighteen pharmaceuticals (neutrals, acids, and bases) have been analyzed for their lipophilicity at physiological pH in an automated setup; phase separation of lipid and aqueous phase can be achieved simply by a short low-speed centrifugation or filtration. The membrane affinity is then calculated by quantification of the total drug concentration and the amount of drug remaining in the aqueous phase after incubation with solid-supported lipid membranes. Lipophilicity parameters relying on solid-supported lipid membranes correlate well with octanol-water partition coefficients K(ow) for neutral organic compounds (range of log K(ow) = 1.5-5, n = 7, r = 0.93). Data acquisition with this lipid membrane model system is highly re-producible. Even in the case of ionizable drugs, where K(ow) tends to underestimate membrane affinity, the latter can be correctly quantified using solid-supported lipid membranes: data comparison shows good agreement of the presented approach with established but time-consuming standardized lipid/buffer systems. Solid-supported lipid membranes allow a fast and reliable quantification of membrane affinity, enabling high-throughput screening of this physicochemical parameter.

Multilamellar liposomes and solid-supported lipid membranes (TRANSIL): screening of lipid-water partitioning toward a high-throughput scale.

PURPOSE: Lipid-water partitioning of 187 pharmaceuticals has been assessed with solid-supported lipid membranes (TRANSIL) in microwell plates and with multilamellar liposomes for a data comparison. The high-throughput potential of the new approach was evaluated. METHODS: Drugs were incubated at pH 7.4 with egg yolk lecithin membranes either on a solid support (TRANSIL beads) or in the form of multilamellar liposomes. Phase separation of lipid and water phase was achieved by ultracentrifugation in case of liposomes or by a short filtration step in case of solid-supported lipid membranes. RESULTS: Lipid-water partitioning data of both approaches correlate well without systematic deviations in the investigated lipophilicity range. The solid-supported lipid membrane approach provides high-precision data in an automated microwell-plate setup. The lipid composition of the solid-supported lipid membranes was varied to study the influence of membrane change on lipid-water partitioning. In addition, pH-dependent measurements have been performed with minimal experimental effort. CONCLUSIONS: Solid-supported lipid membranes represent a valuable tool to determine physiologically relevant lipid-water partitioning data of pharmaceuticals in an automated setup and is well suited for high-throughput data generation in lead optimization programs.

Lignans interfering with 5 alpha-dihydrotestosterone binding to human sex hormone-binding globulin.

The natural lignans (-)-3,4-divanillyltetrahydrofuran (1), (-)-matairesinol (2), (-)-secoisolariciresinol (3), (+/-)-enterolactone (4), (+/-)-enterodiol (5), and nordihydroguaiaretic acid (NDGA) (6) reduce the binding of 3H-labeled 5 alpha-dihydrotestosterone (DHT) to human sex hormone-binding globulin (SHBG). (-)-3,4-Divanillyltetrahydrofuran (1) has the highest binding affinity (Ka = 3.2 +/- 1.7 x 10(6)M-1) of all lignans investigated so far; the reversibility of its binding and a double reciprocal plot suggest a competitive inhibition of the SHBG-DHT interaction. Increasing hydrophobity in the aliphatic part of the lignans (butane-1,4-diol-butanolide-tetrahydrofuran structures) leads to higher binding affinity. In the aromatic part, a 3-methoxy-4-hydroxy substitution pattern is most effective for binding to SHBG.

Interaction of lignans with human sex hormone binding globulin (SHBG).

Lignans bind to sex hormone-binding globulin (SHBG). The lignan with the highest binding affinity is (+/-)-3,4-divanillyltetrahydrofuran. In a double Stobbe condensation--without use of protecting groups--a wide variety of lignans with different substitution pattern in the aromatic and aliphatic part of the molecule was synthesized. These lignans were tested in a SHBG-binding assay which allowed to deduce the following relationship between structure and activity: 1) (+/-)-diastereoisomers are more active than meso compounds 2.) the 4-hydroxy-3-methoxy (guajacyl) substitution pattern in the aromatic part is most effective 3.) the activity increases with the decline in polarity of the aliphatic part of the molecule.

Lignans from the roots of Urtica dioica and their metabolites bind to human sex hormone binding globulin (SHBG).

Polar extracts of the stinging nettle (Urtica dioica L.) roots contain the ligans (+)-neoolivil, (-)-secoisolariciresinol, dehydrodiconiferyl alcohol, isolariciresinol, pinoresinol, and 3,4-divanillyltetrahydrofuran. These compounds were either isolated from Urtica roots, or obtained semisynthetically. Their affinity to human sex hormone binding globulin (SHBG) was tested in an in vitro assay. In addition, the main intestinal transformation products of plant lignans in humans, enterodiol and enterolactone, together with enterofuran were checked for their activity. All lignans except (-)-pinoresinol developed a binding affinity to SHBG in the in vitro assay. The affinity of (-)-3,4-divanillyltetrahydrofuran was outstandingly high. These findings are discussed with respect to potential beneficial effects of plant lignans on benign prostatic hyperplasia (BPH).