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. 2024 Jun 11;18(1):61.
doi: 10.1186/s40246-024-00620-w.

Trace amine associated receptor 1: predicted effects of single nucleotide variants on structure-function in geographically diverse populations

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Trace amine associated receptor 1: predicted effects of single nucleotide variants on structure-function in geographically diverse populations

Britto Shajan et al. Hum Genomics. .

Abstract

Trace Amine Associated Receptor 1 (TAAR1) is a novel pharmaceutical target under investigation for the treatment of several neuropsychiatric conditions. TAAR1 single nucleotide variants (SNV) have been found in patients with schizophrenia and metabolic disorders. However, the frequency of variants in geographically diverse populations and the functional effects of such variants are unknown. In this study, we aimed to characterise the distribution of TAAR1 SNVs in five different WHO regions using the Database of Genotypes and Phenotypes (dbGaP) and conducted a critical computational analysis using available TAAR1 structural data to identify SNVs affecting ligand binding and/or functional regions. Our analysis shows 19 orthosteric, 9 signalling and 16 micro-switch SNVs hypothesised to critically influence the agonist induced TAAR1 activation. These SNVs may non-proportionally influence populations from discrete regions and differentially influence the activity of TAAR1-targeting therapeutics in genetically and geographically diverse populations. Notably, our dataset presented with orthosteric SNVs D1033.32N (found only in the South-East Asian Region and Western Pacific Region) and T1945.42A (found only in South-East Asian Region), and 2 signalling SNVs (V1253.54A/T2526.36A, found in African Region and commonly, respectively), all of which have previously demonstrated to influence ligand induced functions of TAAR1. Furthermore, bioinformatics analysis using SIFT4G, MutationTaster 2, PROVEAN and MutationAssessor predicted all 16 micro-switch SNVs are damaging and may further influence the agonist activation of TAAR1, thereby possibly impacting upon clinical outcomes. Understanding the genetic basis of TAAR1 function and the impact of common mutations within clinical populations is important for the safe and effective utilisation of novel and existing pharmacotherapies.

Keywords: Agonists; Aminergic receptors; Amphetamines; Demographic; Genetic variants; Neuropsychiatric disorders; Neurotransmitters; Ralmitaront; Trace amines; Ulotaront.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Snake plot of human TAAR1 demonstrating allelic heterogeneity observed in this dataset. The data was accrued from NCBI dbGaP consisting of 290 TAAR1 SNVs. The allelic heterogeneity was characterised using the TAAR1 snake plot, accessed from GPCRdb (TA1 human structure). As shown, up to four variants were originated from six individual residues. Three predicted post-translational modification sites (PTM sites) have been identified (T672.48 (phosphorylation), K134ICL2 (methylation) and K322C − term (acetylation)) using GPCRdb, with two residues affected by SNVs (T672.48 and K134ICL2).
Fig. 2
Fig. 2
Distribution of TAAR1 SNVs across different demographic regions. The data was accrued from NCBI dbGaP and characterised into five WHO regions of classifications; WPR, AR, ROA, SEAR, and ER. (A) Venn analysis showing the distribution of SNVs across five regions. The analysis was conducted using the ggVenndiagram package in R studio. (B) Burden of TAAR1 SNV in each region. All SNVs, including unique and shared variants found in each demographic region were tallied. (C) World map showing each WHO regions of classification. Eastern Mediterranean Region and Antarctica (grey colour) were not considered in this study due to very low SNV prevalence. The bar graph and World map was generated in R studio using ggplot and maps packages, respectively
Fig. 3
Fig. 3
SNVs affecting residues involved in ligand binding, defined as orthosteric SNVs. Amino acid residues involved in ligand binding were curated using the human ligand-TAAR1 complexes deposited in RSCB, including 8W8A, 8W89, 8W88, 8W87, 8JSO, 8JLN, 8JLO, 8JLP, 8JLQ, 8JLR, 8JSO, 8WC8, 8WCA and 8UHB (ligand name is displayed in parenthesis). Primary SNV data was accrued from NCBI dbGaP and mapped on the ulotaront-TAAR1-Gαs coupled cryo-EM complex (RCSB: 8JLO). (A) Ulotaront-TAAR1-Gαs coupled cryo-EM complex (RCSB: 8JLO) (i) residues involved in synthetic and endogenous agonist binding affected by SNVs (shown in sticks), (ii) complexed ulotaront at the binding site with WT residues affected by SNVs, including D1033.32 which establishes a critical ionic bond required for ligand recognition. (B) River plot demonstrating the demographic distribution of orthosteric SNVs. Top panel displays the proportional burden of orthosteric SNVs in WPR, AR, ROA, SEAR and ER. Bottom panels show the list of orthosteric SNVs. The ribbons link each region with associated SNVs. Unique SNVs are colour matched with respective WHO region, and shared SNVs are coloured using light grey. (C) List of residues found to interact with complexed ligands. The river plot and scatter plot were generated using the ggalluvial package and ggplot of R studio, respectively. 3D structure depictions were created using ChimeraX and OpenEye Scientific VIDA. *Indicates presence of mutation/s. PEA (β-phenethylamine), METH (methamphetamine), AMPH (amphetamine) and T1AM (3-Iodothyronamine)
Fig. 4
Fig. 4
Demographic distribution and predicted effects of class A micro-switch SNVs. Primary SNV data was accrued from NCBI dbGaP and mapped on the ulotaront-TAAR1-Gαs cryo-EM complex (RCSB: 8JLO). (A) Micro-switch residues containing SNVs, shown in sticks; residues of CWxP motif with SNVs (W2646.48 not shown), residues of DRY motif with SNVs residues of NPxxY and PIF motif with SNVs (B) River plot displaying demographic distribution of microswitch SNVs. The bottom panel show the list of SNVs. The ribbons link each region with associated SNVs. Unique SNVs are colour matched with respective WHO region, and shared SNVs are coloured using light grey. (C) Prediction of putative effects of micro-switch SNVs using SIFT4G, MutationTaster 2, PROVEAN and MutationAssessor. The tools were accessed using dbNSFP database. Variants were called damaging upon meeting the following threshold scores (denoted by the red vertical line): <0.05 (SIFT4G), > 0.5 (MutationTaster 2), < -2.5 (PROVEAN) and > 3.5 (MutationAssesor)
Fig. 5
Fig. 5
SNVs identified at the G-protein coupling interface of TAAR1, referred to as signalling SNVs. Primary SNV data was accrued from NCBI dbGaP and current cryo-EM literature was utilised to map signalling SNVs. (A) SNVs identified at residues demonstrated to be critical for different TAAR1 signalling pathways, shown in sticks. (B) River plot displaying demographic distribution of signalling SNVs. Unique SNVs are colour matched with respective WHO region, and shared SNVs are coloured using light grey. Alanine variants present in this subset has been functionally validated and shown to disrupt G-protein activity

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