Biology subjects

Kranzler, H. R.

Publications and source records attributed to Kranzler, H. R..

11 recordsLinked to original sources

bioRxiv2024

Identification of SLC45A4 as a pain gene encoding a neuronal polyamine transporter.

Polyamines are regulatory metabolites with key roles in transcription, translation, cell signalling and autophagy1. They are implicated in multiple neurological disorders including stroke, epilepsy and neurodegeneration and can regulate neuronal excitability through interactions with ion channels2. Polyamines have been linked to pain showing altered levels in human persistent pain states and modulation of pain behaviour in animal models3. However, the systems governing polyamine transport within the nervous system remain unclear. In undertaking a Genome Wide Association Study (GWAS) of chronic pain intensity in the UK-Biobank we found significant association with variants mapping to the SLC45A4 gene locus. In the mouse nervous system SLC45A4 expression is enriched in all sensory neuron sub-types within the dorsal root ganglion including nociceptors. Cell-based assays show that SLC45A4 is a selective plasma membrane polyamine transporter, whilst the cryo-EM structure reveals a novel regulatory domain and basis for polyamine recognition. Mice lacking SLC45A4 show normal mechanosensitivity but reduced sensitivity to noxious heat and algogen induced tonic pain that is associated with reduced excitability of peptidergic nociceptors. Our findings thus establish a role for neuronal polyamine transport in pain perception and identify a new target for therapeutic intervention in pain treatment.

neuroscience↗

bioRxiv2024

A single-nucleus transcriptomic atlas of medium spiny neurons in the rat nucleus accumbens

Neural processing of rewarding stimuli involves several distinct regions, including the nucleus accumbens (NAc). The majority of NAc neurons are GABAergic projection neurons known as medium spiny neurons (MSNs). MSNs are broadly defined by dopamine receptor expression, but evidence suggests that a wider array of subtypes exist. To study MSN heterogeneity, we analyzed single-nucleus RNA sequencing data from the largest available rat NAc dataset. Analysis of 48,040 NAc MSN nuclei identified major populations belonging to the striosome and matrix compartments. Integration with mouse and human data indicated consistency across species and disease-relevance scoring using genome-wide association study results revealed potentially differential roles for MSN populations in substance use disorders. Additional high-resolution clustering identified 34 transcriptomically distinct subtypes of MSNs definable by a limited number of marker genes. Together, these data demonstrate the diversity of MSNs in the NAc and provide a basis for more targeted genetic manipulation of specific populations.

genetics↗

bioRxiv2022

Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program

Smoking behaviors and alcohol use disorder (AUD), moderately heritable traits, commonly co-occur in the general population. Single-trait genome-wide association studies (GWAS) have identified multiple loci for smoking and AUD. However, GWASs that have aimed to identify loci contributing to comorbid smoking and AUD have used small samples and thus have not been highly informative. Applying multi-trait analysis of GWASs (MTAG), we conducted a joint GWAS of smoking and AUD with data from the Million Veteran Program (N=318,694). By leveraging GWAS summary statistics for AUD, MTAG identified 21 genome-wide significant (GWS) loci associated with smoking initiation and 18 loci associated with smoking cessation compared to 16 and 8 loci, respectively, identified by single-trait GWAS. The novel loci for smoking behaviors identified by MTAG included those previously associated with psychiatric or substance use traits. Colocalization analysis identified 10 loci shared by AUD and smoking status traits, all of which achieved GWS in MTAG, including variants on SIX3, NCAM1, and near DRD2. Functional annotation of the MTAG variants highlighted biologically important regions on ZBTB20, DRD2, PPP6C, and GCKR that contribute to smoking behaviors. In contrast, MTAG of smoking behaviors and alcohol consumption (AC) did not enhance discovery compared with single-trait GWAS for smoking behaviors. We conclude that using MTAG to augment the power of GWAS enables the identification of novel genetic variants for commonly comorbid phenotypes, providing new insights into their pleiotropic effects on smoking behavior and AUD.

genetics↗

bioRxiv2021

Antagonism of GluK1-containing Kainate Receptors Reduces Ethanol Consumption by Modulating Ethanol Reward and Withdrawal

Alcohol use disorder (AUD) is a neuropsychiatric condition affecting millions of people worldwide. Topiramate (TPM) is an antiepileptic drug that has been shown to reduce ethanol drinking in humans. However, TPM is associated with a variety of adverse effects due to its interaction with many receptor systems and intracellular pathways. Thus, a better understanding of the role of TPMs main molecular targets in AUD could yield better therapeutic tools. GluK1-containing kainate receptors (GluK1*KARs) are non-selectively inhibited by TPM, and genetic association studies suggest that this receptor system could be targeted to reduce drinking in AUD patients. We examined the efficacy of LY466195, a selective inhibitor of GluK1*KAR, in reducing ethanol consumption in the intermittent two-bottle choice paradigm in mice. The effect of LY466195 on various ethanol-related phenotypes was investigated by quantification of alcohol intake, physical signs of withdrawal, conditioned place preference (CPP) and in vivo microdialysis in the nucleus accumbens. Selective GluK1*KAR inhibition reduced ethanol intake and preference in a dose-dependent manner. LY466195 treatment attenuated the physical manifestations of ethanol withdrawal and influenced the rewarding properties of ethanol. Interestingly, LY466195 injection also normalized changes in dopamine levels in response to acute ethanol in ethanol-dependent mice, but had no effect in ethanol-naive mice, suggesting ethanol state-dependent effects. The data point to GluK1*KARs as an attractive pharmacological target for the treatment of AUD.

pharmacology and toxicology↗

bioRxiv2020

Multimodal brain imaging study of 19,825 participants reveals adverse effects of moderate drinking

Heavy alcohol consumption can have significant deleterious neural consequences, including brain atrophy, neuronal loss, poorer white matter fiber integrity, and cognitive decline. However, the effects of light-to-moderate alcohol consumption on brain structure remain unclear. Here, we examine the associations between alcohol intake and brain structure using multimodal imaging data from 36,678 generally healthy middle-aged and older adults from the UK Biobank, controlling for numerous potential confounds. We find negative associations between alcohol intake and global gray matter volume (GMV) and white matter volume (WMV), which become stronger as intake increases. An examination of the associations between alcohol intake and 139 regional GMV imaging-derived phenotypes (IDPs) and 375 WM microstructure IDPs yielded 304 (59.1%) significant findings, including 125 GMV IDPs that are spread across the brain and 179 WM microstructure IDPs across multiple tract regions. In general, findings comport with the existing literature. However, a daily alcohol intake of as little as one to two units - 250 to 500 ml of a 4% beer or 76 to 146 ml of a 13% wine - is already associated with GMV deficits and altered WMV microstructure, placing moderate drinkers at risk. One Sentence SummaryModerate alcohol intake, consuming one or more daily alcohol units, has adverse effects on brain health.

neuroscience↗

bioRxiv2020

Expanding the Genetic Architecture of Nicotine Dependence and its Shared Genetics with Multiple Traits: Findings from the Nicotine Dependence GenOmics (iNDiGO) Consortium

Cigarette smoking is the leading cause of preventable morbidity and mortality. Knowledge is evolving on genetics underlying initiation, regular smoking, nicotine dependence (ND), and cessation. We performed a genome-wide association study using the Fagerstrom Test for ND (FTND) in 58,000 smokers of European or African ancestry. Five genome-wide significant loci, including two novel loci MAGI2/GNAI1 (rs2714700) and TENM2 (rs1862416) were identified, and loci reported for other smoking traits were extended to ND. Using the heaviness of smoking index (HSI) in the UK Biobank (N=33,791), rs2714700 was consistently associated, but rs1862416 was not associated, likely reflecting ND features not captured by the HSI. Both variants were cis-eQTLs (rs2714700 for MAGI2-AS3 in hippocampus, rs1862416 for TENM2 in lung), and expression of genes spanning ND-associated variants was enriched in cerebellum. SNP-based heritability of ND was 8.6%, and ND was genetically correlated with 17 other smoking traits (rg=0.40-0.95) and co-morbidities. Our results emphasize the FTND as a composite phenotype that expands genetic knowledge of smoking, including loci specific to ND.

genomics↗

bioRxiv2019

Genetic Underpinnings of Risky Behavior Relate to Altered Neuroanatomy

Previous research points to the heritability of risk-taking behaviour. However, evidence on how genetic dispositions are translated into risky behaviour is scarce. Here, we report a genetically-informed neuroimaging study of real-world risky behaviour across the domains of drinking, smoking, driving, and sexual behaviour, in a European sample from the UK Biobank (N= 12,675). We find negative associations between risky behaviour and grey matter volume (GMV) in distinct brain regions, including amygdala, ventral striatum, hypothalamus, and dorsolateral prefrontal cortex (dlPFC). These effects replicate in an independent sample recruited from the same population (N=13,004). Polygenic risk scores for risky behaviour, derived from a genome-wide association study in an independent sample (N=297,025), are inversely associated with GMV in dlPFC, putamen, and hypothalamus. This relation mediates ~2.2% of the association between genes and behaviour. Our results highlight distinct heritable neuroanatomical features as manifestations of the genetic propensity for risk taking. One Sentence SummaryRisky behaviour and its genetic associations are linked to less grey matter volume in distinct brain regions.

neuroscience↗

bioRxiv2019

Meta-analysis of problematic alcohol use in 435,563 individuals identifies 29 risk variants and yields insights into biology, pleiotropy and causality

Problematic alcohol use (PAU) is a leading cause of death and disability worldwide. Although genome-wide association studies (GWASs) have identified PAU risk genes, the genetic architecture of this trait is not fully understood. We conducted a proxy-phenotype meta-analysis of PAU combining alcohol use disorder and problematic drinking in 435,563 European-ancestry individuals. We identified 29 independent risk variants, 19 of them novel. PAU was genetically correlated with 138 phenotypes, including substance use and psychiatric traits. Phenome-wide polygenic risk score analysis in an independent biobank sample (BioVU, n=67,589) confirmed the genetic correlations between PAU and substance use and psychiatric disorders. Genetic heritability of PAU was enriched in brain and in genomic conserved and regulatory regions. Mendelian randomization suggested causal effects on liability to PAU of substance use, psychiatric status, risk-taking behavior, and cognitive performance. In summary, this large PAU meta-analysis identified novel risk loci and revealed genetic relationships with numerous other outcomes.

genetics↗

bioRxiv2019

Factors associated with opioid cessation: a machine learning approach

Background and AimsPeople with opioid use disorder (OUD) can stop using opioids on their own, with help from groups and with treatment, but there is limited research on the factors that influence opioid cessation.\n\nMethodsWe employed multiple machine learning prediction algorithms (LASSO, random forest, deep neural network, and support vector machine) to assess factors associated with ceasing opioid use in a sample comprised of African Americans (AAs) and European Americans (EAs) who met DSM-5 criteria for mild to severe OUD. Values for several thousand demographic, alcohol and other drug use, general health, and behavioral variables, as well as diagnoses for other psychiatric disorders, were obtained for each participant from a detailed semi-structured interview.\n\nResultsSupport vector machine models performed marginally better on average than those derived using other machine learning methods with maximum prediction accuracies of 75.4% in AAs and 79.4% in EAs. Subsequent stepwise regression analyses that considered the 83 most highly ranked variables across all methods and models identified less recent cocaine use (p<5x10-8), a shorter duration of opioid use (p<5x10-6), and older age (p<5x10-9) as the strongest independent predictors of opioid cessation. Factors related to drug use comprised about half of the significant independent predictors, with other predictors related to non-drug use behaviors, psychiatric disorders, overall health, and demographics.\n\nConclusionsThese proof-of-concept findings provide information that can help develop strategies for improving OUD management and the methods we applied provide a framework for personalizing OUD treatment.

neuroscience↗

bioRxiv2019

Genomic Influences on Self-Reported Childhood Maltreatment

Childhood maltreatment is highly prevalent and serves as a risk factor for mental and physical disorders. Self-reported childhood maltreatment appears heritable, but the specific genetic influences on this phenotype are largely unknown. The aims of this study were to 1) identify genetic variation associated with reported childhood maltreatment, 2) calculate the relevant SNP-based heritability estimates, and 3) quantify the genetic overlap of reported childhood maltreatment with mental and physical health-related phenotypes. Genome-wide association analysis for childhood maltreatment was undertaken, using a discovery sample from the UK Biobank (UKBB) (n=124,000) and a replication sample from the Psychiatric Genomics Consortium-posttraumatic stress disorder working group (PGC-PTSD) (n=26,290). Heritability estimations for childhood maltreatment and genetic correlations with mental/physical health traits were calculated using linkage disequilibrium score regression (LDSR). Two genome-wide significant loci associated with childhood maltreatment, located on chromosomes 3p13 (rs142346759, beta=0.015, p=4.35x10-8, FOXP1) and 7q31.1 (rs10262462, beta=-0.016, p=3.24x10-8, FOXP2), were identified in the discovery dataset but were not replicated in the PGC-PTSD sample. SNP-based heritability for childhood maltreatment was estimated to be [~]6%. Childhood maltreatment was most significantly genetically correlated with depressive symptoms (rg=0.70, p=4.65x10-40). This is the first large-scale genetic study to identify specific variants associated with self-reported childhood maltreatment. FOXP genes could influence traits such as depression and thereby be relevant to childhood maltreatment. Alternatively, these variants may be associated with a greater likelihood of reporting maltreatment. A clearer understanding of the genetic relationships of childhood maltreatment, including particular abuse subtypes, with various psychiatric disorders, may ultimately be useful in in developing targeted treatment and prevention strategies.

genomics↗

bioRxiv2019

Molecular correlates of topiramate and GRIK1 rs2832407 genotype in pluripotent stem cell-derived neural cultures

There is growing evidence that the anticonvulsant topiramate is efficacious in reducing alcohol consumption. Further, an intronic single nucleotide polymorphism (rs2832407, C A) in the GRIK1 gene, which encodes the GluK1 subunit of the excitatory kainate receptor, predicted topiramates effectiveness in reducing heavy drinking in a clinical trial. In the current study, we differentiated a total of 22 induced pluripotent stem cell (iPSCs) lines characterized by GRIK1 rs2832407 genotype (10 A/A and 12 C/C) into forebrain-lineage neural cultures to explore molecular correlates of GRIK1 genotype that may relate to topiramates ability to reduce drinking. Our differentiation protocol yielded mixed neural cultures enriched for glutamatergic neurons. Characterization of the GRIK1 locus revealed no effect of rs2832407 genotype on GRIK1 isoform mRNA expression, however a significant difference was observed on GRIK1 antisense-2, with higher expression in C/C neural cultures. Differential effects of acute exposure to 5 M topiramate were observed on the frequency of spontaneous synaptic activity in A/A vs. C/C neurons, with a smaller reduction in excitatory event frequency and a greater reduction in inhibitory event frequency observed in C/C donor neurons. This work highlights the use of iPSC technologies to study pharmacogenetic treatment effects in psychiatric disorders and furthers our understanding of the molecular effects of topiramate exposure in human neural cells.

neuroscience↗