Genetic analysis of bipolar disorder and alcohol use disorder

Includes bibliographical referencesBackground: Mental health disorders represent a major public health problem in most countries around the world. In South Africa, the lifetime prevalence of psychiatric disorders is 30.3%, with substance-use disorders and mood disorders being the second and third most prevalent classes of lifetime disorders, respectively. Bipolar disorder (BD) has a lifetime prevalence of 1.4% and alcohol use disorder (AUD) a lifetime prevalence of 30.3%, and they are frequently comorbid. Both of these disorders have a relatively high heritability, yet the exact genetic basis of each remains unknown. Genetic variants within the hypothalamic-pituitary-adrenal (HPA)-axis and glutamatergic pathways have previously been implicated in both phenotypes. The aim of this project was to investigate the aetiology of BD and AUD, using high-throughput genomic technologies, bioinformatics, brain-imaging and environmental measures. An additional aim was to assess the genetic aetiology of BD-AUD comorbidity. Methods: For the genetic analysis underlying BD, a South African 'Afrikaner' family was investigated. Whole-genome sequencing (WGS) and whole-genome linkage analysis was performed for individuals with BD Type I (BDI) and unaffected family members using the Illumina HiSeq2000 and Affymetrix Axiom TM Genome-wide CEU 1 Array, respectively. For the AUD analysis, two groups were investigated; a South African adolescent group comprising 80 individuals with AUD and 80 controls, and a group of 8123 individuals from the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort. The South African group of adolescents were genotyped using the Illumina Infinium iSelect custom 6000 BeadChip, childhood trauma data was obtained and brain magnetic resonance images were collected for a subset of this group. Genotype data on HPA-axis genes were obtained from a previous study for the ALSPAC cohort. The fourth group of individuals investigated in this thesis comprised 233 individuals with BD-AUD comorbidity from the Systemic Treatment Enhancement Program for BD (STEP-BD). Genotype data for genes from the glutamatergic and HPA-axis pathways were obtained from a previous study conducted on these individuals. Results: The chromosomal regions 6p25, 10p14-10p15.1, 11q23-11q25, and 13q21-22 scored the highest LOD scores for BD and the most over-represented pathway in the affected family members was the T-cell receptor signalling pathway. In the South African adolescent group, circadian rhythm genes were associated with AUD and childhood trauma predicted alcohol use in adolescence. The gene-imaging analysis identified a SNP in the glutamate receptor, ionotropic, N-methyl D-aspartate 2B (GRIN2B) gene as being associated with brain volume in the left orbitofrontal cortex and posterior cingulate. HPA-axis genes did not show an association with AUD and no significant gene x environment interactions were detected for AUD in the ALSPAC cohort. Single variants in the glutamatergic genes and HPA-axis were not associated with BD-AUD comorbidity. However, from the gene-based analysis, the glutamatergic gene PRKCI was associated with BD-AUD comorbidity. Conclusions: It appears that disruption in immune-related genes may contribute to the development of BD in an Afrikaner family. No significant gene x environment interactions were detected for adolescent AUD. The circadian pathway and childhood trauma may play a role in the development of adolescent AUD. Differential brain volume and BD-AUD comorbidity may be characterised by variation in the glutamatergic pathway. These pathways and the interactions between them should be further investigated in BD and AUD

Elucidation of bipolar disorder : a convergent approach using genetics and imaging

The aims were to determine whether variants, within ten selected candidate genes, have an association with BPD and whether any relationship exists between these variants and brain imaging volumes in subjects with BPD. The objectives were to i) select a list of BPD candidate genes, ii) identify a cohort of individuals from the BPD registry, iii) genotype the candidate genes using a polymerase chain reaction (PCR) based technology, iv) analyse the genotyping data with the appropriate statistical methods, and v) obtain brain imaging data and perform the appropriate statistical analysis

Novel CYP2E1 haplotype identified in a South African cohort

Alcohol abuse accounts for approximately 2.5 million deaths annually and is the third highest risk factor for disease and disability. Alcohol is metabolised by polymorphic enzymes and the status of an individual with respect to alcohol metabolising enzymes may have forensic relevance in post-mortems. Baseline frequencies of gene variants involved in alcohol metabolism need to be established to aid the identification of suitable population-specific polymorphisms to genotype during molecular autopsies. The principal alcohol metabolising enzymes include alcohol dehydrogenase (ADH), aldehyde dehydrogenase (ALDH) and cytochrome P450 2E1 (CYP2E1). Six single nucleotide polymorphisms (SNPs) - rs1229984G>A and rs2066702C>Tin ADH1B, rs671G>A in ALDH2, and rs3813867G>C, rs2031920C>T and rs6413432T>A in CYP2E1 - were genotyped in 150 individuals from four South African populations: Xhosa, Zulu, South African white and South African coloured. Allele frequencies for each SNP in the four population groups were 0-10% for rs1229984A, 2-12% for rs2066702T, 0-2% for rs671A, 1-4% for rs3813867C, 0-1% for rs2031920T and 3-15% for rs6413432A. Haplotype analysis revealed a novel combination of three SNPs in CYP2E1 whose effects on alcohol metabolism need further investigation. Establishment of baseline frequencies adds to our knowledge of genetic variation in alcohol metabolising enzymes and additional research is required to determine the functional significance of this novel CYP2E1 haplotype

Systematic review of genome-wide association studies of anxiety disorders and neuroticism

Objectives: To summarise SNP associations identified by genome-wide association studies (GWASs) of anxiety disorders and neuroticism; to appraise the quality of individual studies, and to assess the ancestral diversity of study participants. Methods: We searched PubMed, Scopus, PsychInfo and PubPsych for GWASs of anxiety disorders, non-diagnostic traits (such as anxiety sensitivity), and neuroticism, and extracted all SNPs that surpassed genome-wide significance. We graded study quality using Q-genie scores and reviewed the ancestral diversity of included participants. Results: 32 studies met our inclusion criteria. A total of 563 independent significant variants were identified, of which 29 were replicated nominally in independent samples, and 3 were replicated significantly. The studies had good global quality, but many smaller studies were underpowered. Phenotypic heterogeneity for anxiety (and less so for neuroticism) seemed to reflect the complexity of capturing this trait. Ancestral diversity was poor, with 70% of studies including only populations of European ancestry. Conclusion: The functionality of genes identified by GWASs of anxiety and neuroticism deserves further investigation. Future GWASs should have larger sample sizes, more rigorous phenotyping and include more ancestrally diverse population groups

Characterising the shared genetic influences between schizophrenia and subcortical brain regions

Background: Abnormalities in brain structural volumes are well established in schizophrenia (SZ) and have been proposed as an endophenotype for the disorder. Despite increasing interest in the genetic relationship between brain structural volumes and SZ, our knowledge of the genetic overlap between the phenotypes is limited. This study aims to extend our current understanding of the shared genetic influences between SZ and subcortical brain volumes using data from the latest genome-wide association studies for the respective phenotypes (GWAS) and novel statistical approaches. Additionally, we will explore whether the association between schizophrenia and abnormal regional brain volumes is causal in nature. Methods: Summary statistics were obtained from the largest Psychiatric Genomic Consortium (PGC)-SZ GWAS (Ncase = 69,369, Ncontrol = 236,642) and the CHARGEENIGMA-UKBB GWAS of volumetric measures for eight subcortical brain regions (the nucleus accumbens, amygdala, brainstem, caudate nucleus, hippocampus, globus pallidus, putamen, and thalamus), and total intracranial volume (N = 30,983 - 40,380). Single nucleotide polymorphism (SNP) effect concordance analysis (SECA) was used to assess pleiotropy and concordance. Genetic correlation was assessed using linkage disequilibrium score regression (LDSR) and the pleiotropy informed conditional FDR approach was applied to identify SNPs associated with SZ conditional on their association with subcortical brain volumes. Mendelian randomization (MR) was used to test for causal association between SZ and each brain region. Results: There was evidence of global pleiotropy between SZ, and all examined subcortical brain regions. Inverse concordance between the genetic determinants of SZ and volumes of the nucleus accumbens, amygdala, brainstem, hippocampus, and thalamus was observed. Increased statistical power to detect SZ risk loci was shown when conditioning on subcortical brain volumes. There was no significant evidence for a causal effect of any of the examined brain regions on schizophrenia risk. Discussion: These data confirm the shared genetic basis of SZ and specific intracranial and subcortical brain volumes and provide evidence for negative concordance between SZ and volumes of the nucleus accumbens, amygdala, brainstem, hippocampus, and thalamus. Leveraging the genetic overlap between SZ and subcortical brain volumes has the potential to provide novel insights into the biological basis of the disorder

Neuroimaging genomics in psychiatry—a translational approach

Neuroimaging genomics is a relatively new field focused on integrating genomic and imaging data in order to investigate the mechanisms underlying brain phenotypes and neuropsychiatric disorders. While early work in neuroimaging genomics focused on mapping the associations of candidate gene variants with neuroimaging measures in small cohorts, the lack of reproducible results inspired better-powered and unbiased large-scale approaches. Notably, genome-wide association studies (GWAS) of brain imaging in thousands of individuals around the world have led to a range of promising findings. Extensions of such approaches are now addressing epigenetics, gene-gene epistasis, and gene-environment interactions, not only in brain structure, but also in brain function. Complementary developments in systems biology might facilitate the translation of findings from basic neuroscience and neuroimaging genomics to clinical practice. Here, we review recent approaches in neuroimaging genomics-we highlight the latest discoveries, discuss advantages and limitations of current approaches, and consider directions by which the field can move forward to shed light on brain disorders

Large scale genetic research on neuropsychiatric disorders in african populations is needed

In recent years there have been significant insights into the complex aetiologies of neurodevelopmental brain disorders. For example, neuropsychiatric genetics has achieved success with the identification of 108 loci for schizophrenia (Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2014). Furthermore, meta-analyses of genomewide association study (GWAS) results encompassing thousands of samples have been completed for other psychiatric disorders including attention-deficit/hyperactivity disorder (ADHD), autis

The genetic architecture of the corpus callosum and its subregions

Background: Regional surface area and thickness of the cerebral cortex and volume of subcortical structures are highly heritable brain morphological features with complex genetic architectures, involving many common genetic variants with small effect sizes. However, the genetic architecture of the corpus callosum (CC) and its subregions remains largely unclear. We aim to determine the heritability and genetic architecture of CC volume and each subregion and the extent to which this overlaps with that of psychiatric disorders. Methods: Genetic and T1-weighted MRI data of 40,894 individuals from the UK-biobank was used to construct a multivariate GWAS. Here, we utilized a multivariate approach (Multivariate Omnibus Statistical Test, MOSTest) to assess the distributive effects of common variants across the five subregions of the CC (posterior, mid posterior, central, mid anterior and anterior) obtained by running the automatic subcortical segmentation algorithm in FreeSurfer 5.3. Gene-set enrichment analyses were performed using MAGMA. Linkage disequilibrium score regression was used to determine the SNP-based heritability of the CC and will be used to assess the genetic correlation between each subregion and a variety of psychiatric disorders. Results: Following MOSTest, 70 independent loci show pooled effects across the 5 subregions of the CC (p more than 5×10-8). Using LDSC, we found evidence to suggest that CC volume is heritable (h2SNP= 0.38, SE=0.03). Significant variants showed enrichment in pathways related to regulation of the nervous system and cell development, neurogenesis, and regulation of neuron differentiation. Gene-set analysis revealed 156 significant genes (p is less than 2.6x10-6). Many of the significant SNPs have been previously associated with white matter hyperintensity volume as well as a range of psychiatric disorders. Discussion: Here we provide the first preliminary evidence to suggest that volume of the CC is heritable. Gene set enrichment analyses identified pathways related to neuron development and neurogenesis, suggesting that CC alteration may have an independent developmental origin. Further investigation into the shared genetic architecture of CC subregions and psychiatric disorders may provide novel insight into disease manifestation

The BDNF p.Val66Met polymorphism, childhood trauma, and brain volumes in adolescents with alcohol abuse

Background: Previous studies have indicated that early life adversity, genetic factors and alcohol dependence are associated with reduced brain volume in adolescents. However, data on the interactive effects of early life adversity, genetic factors (e.g. p.Met66 allele of BDNF), and alcohol dependence, on brain structure in adolescents is limited. We examined whether the BDNF p.Val66Met polymorphism interacts with childhood trauma to predict alterations in brain volume in adolescents with alcohol use disorders (AUDs). Methods: We examined 160 participants (80 adolescents with DSM-IV AUD and 80 age- and gender-matched controls) who were assessed for trauma using the Childhood Trauma Questionnaire (CTQ). Magnetic resonance images were acquired for a subset of the cohort (58 AUD and 58 controls) and volumes of global and regional structures were estimated using voxel-based morphometry (VBM). Samples were genotyped for the p.Val66Met polymorphism using the TaqMan® Assay. Analysis of covariance (ANCOVA) and post-hoc t-tests were conducted using SPM8 VBM. Results: No significant associations, corrected for multiple comparisons, were found between the BDNF p.Val66Met polymorphism, brain volumes and AUD in adolescents with childhood trauma. Conclusions: These preliminary findings suggest that the BDNF p.Met66 allele and childhood trauma may not be associated with reduced structural volumes in AUD. Other genetic contributors should be investigated in future studies

Host and microbiome genome-wide association studies : current state and challenges

CITATION: Awany, D., et al. 2019. Host and microbiome genome-wide association studies : current state and challenges. Frontiers in Genetics, 9:637, doi:10.3389/fgene.2018.00637.The original publication is available at https://www.frontiersin.orgThe involvement of the microbiome in health and disease is well established. Microbiome genome-wide association studies (mGWAS) are used to elucidate the interaction of host genetic variation with the microbiome. The emergence of this relatively new field has been facilitated by the advent of next generation sequencing technologies that enable the investigation of the complex interaction between host genetics and microbial communities. In this paper, we review recent studies investigating host–microbiome interactions using mGWAS. Additionally, we highlight the marked disparity in the sampling population of mGWAS carried out to date and draw attention to the critical need for inclusion of diverse populations.https://www.frontiersin.org/articles/10.3389/fgene.2018.00637/fullPublisher's versio