Genetic structure correlates with ethnolinguistic diversity in eastern and southern Africa.

African populations are the most diverse in the world yet are sorely underrepresented in medical genetics research. Here, we examine the structure of African populations using genetic and comprehensive multi-generational ethnolinguistic data from the Neuropsychiatric Genetics of African Populations-Psychosis study (NeuroGAP-Psychosis) consisting of 900 individuals from Ethiopia, Kenya, South Africa, and Uganda. We find that self-reported language classifications meaningfully tag underlying genetic variation that would be missed with consideration of geography alone, highlighting the importance of culture in shaping genetic diversity. Leveraging our uniquely rich multi-generational ethnolinguistic metadata, we track language transmission through the pedigree, observing the disappearance of several languages in our cohort as well as notable shifts in frequency over three generations. We find suggestive evidence for the rate of language transmission in matrilineal groups having been higher than that for patrilineal ones. We highlight both the diversity of variation within Africa as well as how within-Africa variation can be informative for broader variant interpretation; many variants that are rare elsewhere are common in parts of Africa. The work presented here improves the understanding of the spectrum of genetic variation in African populations and highlights the enormous and complex genetic and ethnolinguistic diversity across Africa.

Genome-wide association study in 404,302 individuals identifies 7 significant loci for reaction time variability.

Reaction time variability (RTV), reflecting fluctuations in response time on cognitive tasks, has been proposed as an endophenotype for many neuropsychiatric disorders. There have been no large-scale genome-wide association studies (GWAS) of RTV and little is known about its genetic underpinnings. Here, we used data from the UK Biobank to conduct a GWAS of RTV in participants of white British ancestry (n = 404,302) as well as a trans-ancestry GWAS meta-analysis (n = 44,873) to assess replication. We found 161 genome-wide significant single nucleotide polymorphisms (SNPs) distributed across 7 genomic loci in our discovery GWAS. Functional annotation of the variants implicated genes involved in synaptic function and neural development. The SNP-based heritability (h2SNP) estimate for RTV was 3%. We investigated genetic correlations between RTV and selected neuropsychological traits using linkage disequilibrium score regression, and found significant correlations with several traits, including a positive correlation with mean reaction time and schizophrenia. Despite the high genetic correlation between RTV and mean reaction time, we demonstrate distinctions in the genetic underpinnings of these traits. Lastly, we assessed the predictive ability of a polygenic score (PGS) for RTV, calculated using PRSice and PRS-CS, and found that the RTV-PGS significantly predicted RTV in independent cohorts, but that the generalisability to other ancestry groups was poor. These results identify genetic underpinnings of RTV, and support the use of RTV as an endophenotype for neurological and psychiatric disorders.

Predictors of within-individual variability in cognitive performance in schizophrenia in a South African case-control study.

INTRODUCTION: Cognitive dysfunction in schizophrenia may be assessed by measuring within-individual variability (WIV) in performance across a range of cognitive tests. Previous studies have found increased WIV in people with schizophrenia, but no studies have been conducted in low- to middle-income countries where the different sociocultural context may affect WIV. We sought to address this gap by exploring the relationship between WIV and a range of clinical and demographic variables in a large study of people with schizophrenia and matched controls in South Africa. METHODS: 544 people with schizophrenia and 861 matched controls completed an adapted version of The University of Pennsylvania Computerized Neurocognitive Battery (PennCNB). Demographic and clinical information was collected using the Structured Clinical Interview for DSM-IV Diagnoses. Across-task WIV for performance speed and accuracy on the PennCNB was calculated. Multivariate linear regression was used to assess the relationship between WIV and a diagnosis of schizophrenia in the whole sample, and WIV and selected demographic and clinical variables in people with schizophrenia. RESULTS: Increased WIV of performance speed across cognitive tests was significantly associated with a diagnosis of schizophrenia. In people with schizophrenia, increased speed WIV was associated with older age, a lower level of education and a lower score on the Global Assessment of Functioning scale. Increased accuracy WIV was significantly associated with a younger age in people with schizophrenia. CONCLUSIONS: Measurements of WIV of performance speed can add to the knowledge gained from studies of cognitive dysfunction in schizophrenia in resource-limited settings.

Distributed genetic effects of the corpus callosum subregions suggest links to neuropsychiatric disorders and related traits.

BACKGROUND: The corpus callosum (CC) is a brain structure with a high heritability and potential role in psychiatric disorders. However, the genetic architecture of the CC and the genetic link with psychiatric disorders remain largely unclear. We investigated the genetic architectures of the volume of the CC and its subregions and the genetic overlap with psychiatric disorders. METHODS: We applied multivariate genome-wide association study (GWAS) to genetic and T1-weighted magnetic resonance imaging (MRI) data of 40,894 individuals from the UK Biobank, aiming to boost genetic discovery and to assess the pleiotropic effects across volumes of the five subregions of the CC (posterior, mid-posterior, central, mid-anterior and anterior) obtained by FreeSurfer 7.1. Multivariate GWAS was run combining all subregions, co-varying for relevant variables. Gene-set enrichment analyses were performed using MAGMA. Linkage disequilibrium score regression (LDSC) was used to determine Single nucleotide polymorphism (SNP)-based heritability of total CC volume and volumes of its subregions as well as their genetic correlations with relevant psychiatric traits. RESULTS: We identified 70 independent loci with distributed effects across the five subregions of the CC (p < 5 × 10-8). Additionally, we identified 33 significant loci in the anterior subregion, 23 in the mid-anterior, 29 in the central, 7 in the mid-posterior and 56 in the posterior subregion. Gene-set analysis revealed 156 significant genes contributing to volume of the CC subregions (p < 2.6 × 10-6). LDSC estimated the heritability of CC to (h2SNP = 0.38, SE = 0.03) and subregions ranging from 0.22 (SE = 0.02) to 0.37 (SE = 0.03). We found significant genetic correlations of total CC volume with bipolar disorder (BD, rg = -0.09, SE = 0.03; p = 5.9 × 10-3) and drinks consumed per week (rg = -0.09, SE = 0.02; p = 4.8 × 10-4), and volume of the mid-anterior subregion with BD (rg = -0.12, SE = 0.02; p = 2.5 × 10-4), major depressive disorder (MDD) (rg = -0.12, SE = 0.04; p = 3.6 × 10-3), drinks consumed per week (rg = -0.13, SE = 0.04; p = 1.8 × 10-3) and cannabis use (rg = -0.09, SE = 0.03; p = 8.4 × 10-3). CONCLUSIONS: Our results demonstrate that the CC has a polygenic architecture implicating multiple genes and show that CC subregion volumes are heritable. We found that distinct genetic factors are involved in the development of anterior and posterior subregions, consistent with their divergent functional specialisation. Significant genetic correlation between volumes of the CC and BD, drinks per week, MDD and cannabis consumption subregion volumes with psychiatric traits is noteworthy and deserving of further investigation.

Delineating the Spread and Prevalence of SARS-CoV-2 Omicron Sublineages (BA.1-BA.5) and Deltacron Using Wastewater in the Western Cape, South Africa.

This study was one of the first to detect Omicron sublineages BA.4 and BA.5 in wastewater from South Africa. Spearman rank correlation analysis confirmed a strong positive correlation between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral RNA in wastewater samples and clinical cases (r = 0.7749, P < .0001). SARS-CoV-2 viral load detected in wastewater, resulting from the Delta-driven third wave, was significantly higher than during the Omicron-driven fourth wave. Whole-genome sequencing confirmed presence of Omicron lineage defining mutations in wastewater with the first occurrence reported 23 November 2021 (BA.1 predominant). The variant spread rapidly, with prevalence of Omicron-positive wastewater samples rising to >80% by 10 January 2022 with BA.2 as the predominant sublineage by 10 March 2022, whilst on 18 April 2022 BA.4 and BA.5 were detected in selected wastewater sites. These findings demonstrate the value of wastewater-based epidemiology to monitor the spatiotemporal spread and potential origin of new Omicron sublineages.

Social Genomics of Methamphetamine Use, HIV Viral Load, and Social Adversity.

BACKGROUND: Social genomics has demonstrated altered inflammatory and type I interferon (IFN) gene expression among people experiencing chronic social adversity. Adverse social experiences such as discrimination and violence are linked to stimulant misuse and HIV, conditions that dysregulate inflammatory and innate antiviral responses, leading to increased HIV viral replication and risk of chronic diseases. PURPOSE: We aimed to determine whether methamphetamine (MA) use, unsuppressed HIV viral load (VL) (≥200 c/mL), and experienced intimate partner violence (IPV) (past 12 months) predicted inflammatory and type I IFN gene expression in HIV-positive Black and Latinx men who have sex with men (MSM). METHODS: Participants were 147 HIV-positive Black and Latinx MSM recruited from the mSTUDY, a cohort of 561 MSM aged 18-45 in Los Angeles, CA, of whom half are HIV-positive and substance-using. Transcriptomic measures of inflammatory and type I IFN activity were derived from RNA sequencing of peripheral blood mononuclear cells and matched to urine drug tests, VL, and survey data across two time points 12 months apart. Analysis used linear random intercept modeling of MA use, unsuppressed VL, and experienced IPV on inflammatory and type I IFN expression. RESULTS: In adjusted models, MA use predicted 27% upregulated inflammatory and 31% upregulated type I IFN expression; unsuppressed VL predicted 84% upregulated type I IFN but not inflammatory expression; and experienced IPV predicted 31% upregulated inflammatory and 26% upregulated type I IFN expression. CONCLUSIONS: In Black and Latinx MSM with HIV, MA use, unsuppressed VL, and experienced IPV predicted upregulated social genomic markers of immune functioning.

Post genome-wide association analysis: dissecting computational pathway/network-based approaches.

Over thousands of genetic associations to diseases have been identified by genome-wide association studies (GWASs), which conceptually is a single-marker-based approach. There are potentially many uses of these identified variants, including a better understanding of the pathogenesis of diseases, new leads for studying underlying risk prediction and clinical prediction of treatment. However, because of inadequate power, GWAS might miss disease genes and/or pathways with weak genetic or strong epistatic effects. Driven by the need to extract useful information from GWAS summary statistics, post-GWAS approaches (PGAs) were introduced. Here, we dissect and discuss advances made in pathway/network-based PGAs, with a particular focus on protein-protein interaction networks that leverage GWAS summary statistics by combining effects of multiple loci, subnetworks or pathways to detect genetic signals associated with complex diseases. We conclude with a discussion of research areas where further work on summary statistic-based methods is needed.

Correction: Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia.

Prior to and following the publication of this article the authors noted that the complete list of authors was not included in the main article and was only present in Supplementary Table 1. The author list in the original article has now been updated to include all authors, and Supplementary Table 1 has been removed. All other supplementary files have now been updated accordingly. Furthermore, in Table 1 of this Article, the replication cohort for the row Close relative in data set, n (%) was incorrect. All values have now been corrected to 0(0%). The publishers would like to apologise for this error and the inconvenience it may have caused.

Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia.

Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia. We compared subcortical brain volumes of 12 16p11.2 distal deletion and 12 duplication carriers to 6882 non-carriers from the large-scale brain Magnetic Resonance Imaging collaboration, ENIGMA-CNV. After stringent CNV calling procedures, and standardized FreeSurfer image analysis, we found negative dose-response associations with copy number on intracranial volume and on regional caudate, pallidum and putamen volumes (ß = -0.71 to -1.37; P < 0.0005). In an independent sample, consistent results were obtained, with significant effects in the pallidum (ß = -0.95, P = 0.0042). The two data sets combined showed significant negative dose-response for the accumbens, caudate, pallidum, putamen and ICV (P = 0.0032, 8.9 × 10-6, 1.7 × 10-9, 3.5 × 10-12 and 1.0 × 10-4, respectively). Full scale IQ was lower in both deletion and duplication carriers compared to non-carriers. This is the first brain MRI study of the impact of the 16p11.2 distal CNV, and we demonstrate a specific effect on subcortical brain structures, suggesting a neuropathological pattern underlying the neurodevelopmental syndromes.

Significant concordance of genetic variation that increases both the risk for obsessive-compulsive disorder and the volumes of the nucleus accumbens and putamen.

BACKGROUND: Many studies have identified changes in the brain associated with obsessive-compulsive disorder (OCD), but few have examined the relationship between genetic determinants of OCD and brain variation.AimsWe present the first genome-wide investigation of overlapping genetic risk for OCD and genetic influences on subcortical brain structures. METHOD: Using single nucleotide polymorphism effect concordance analysis, we measured genetic overlap between the first genome-wide association study (GWAS) of OCD (1465 participants with OCD, 5557 controls) and recent GWASs of eight subcortical brain volumes (13 171 participants). RESULTS: We found evidence of significant positive concordance between OCD risk variants and variants associated with greater nucleus accumbens and putamen volumes. When conditioning OCD risk variants on brain volume, variants influencing putamen, amygdala and thalamus volumes were associated with risk for OCD. CONCLUSIONS: These results are consistent with current OCD neurocircuitry models. Further evidence will clarify the relationship between putamen volume and OCD risk, and the roles of the detected variants in this disorder.Declaration of interestThe authors have declared that no competing interests exist.

The neural correlates of Childhood Trauma Questionnaire scores in adults: A meta-analysis and review of functional magnetic resonance imaging studies.

Childhood maltreatment, including abuse and neglect, may have sustained effects on the integrity and functioning of the brain, alter neurophysiological responsivity later in life, and predispose individuals toward psychiatric conditions involving socioaffective disturbances. This meta-analysis aims to quantify associations between self-reported childhood maltreatment and brain function in response to socioaffective cues in adults. Seventeen functional magnetic resonance imaging studies reporting on data from 848 individuals examined with the Childhood Trauma Questionnaire were included in a meta-analysis of whole-brain findings, or a review of region of interest findings. The spatial consistency of peak activations associated with maltreatment exposure was tested using activation likelihood estimation, using a threshold of p < .05 corrected for multiple comparisons. Adults exposed to childhood maltreatment showed significantly increased activation in the left superior frontal gyrus and left middle temporal gyrus, and decreased activation in the left superior parietal lobule and the left hippocampus. Although hyperresponsivity to socioaffective cues in the amygdala and ventral anterior cingulate cortex in correlation with maltreatment severity is a replicated finding in region of interest studies, null results are reported as well. The findings suggest that childhood maltreatment has sustained effects on brain function into adulthood, and highlight potential mechanisms for conveying vulnerability to development of psychopathology.

Genetic variation within GRIN2B in adolescents with alcohol use disorder may be associated with larger left posterior cingulate cortex volume.

OBJECTIVE: Brain structure differences and adolescent alcohol dependence both show substantial heritability. However, exactly which genes are responsible for brain volume variation in adolescents with substance abuse disorders are currently unknown. The aim of this investigation was to determine whether genetic variants previously implicated in psychiatric disorders are associated with variation in brain volume in adolescents with alcohol use disorder (AUD). METHODS: The cohort consisted of 58 adolescents with DSM-IV AUD and 58 age and gender-matched controls of mixed ancestry ethnicity. An Illumina Infinium iSelect custom 6000 bead chip was used to genotype 5348 single nucleotide polymorphisms (SNPs) in 378 candidate genes. Magnetic resonance images were acquired and volumes of global and regional structures were estimated using voxel-based morphometry. To determine whether any of the genetic variants were associated with brain volume, association analysis was conducted using linear regression in Plink. RESULTS: From the exploratory analysis, the GRIN2B SNP rs219927 was associated with brain volume in the left posterior cingulate cortex (p<0.05), whereby having a G-allele was associated with a bigger volume. CONCLUSION: The GRIN2B gene is involved in glutamatergic signalling and may be associated with developmental differences in AUD in brain regions such as the posterior cingulate cortex. Such differences may play a role in risk for AUD, and deserve more detailed investigation.

Glutamatergic and HPA-axis pathway genes in bipolar disorder comorbid with alcohol- and substance use disorders.

Glutamatergic neurotransmission has been shown to be dysregulated in bipolar disorder (BD), alcohol use disorder (AUD) and substance use disorder (SUD). Similarly, disruption in the hypothalamic-pituitary-adrenal (HPA)-axis has also been observed in these conditions. BD is often comorbid with AUD and SUD. The effects of the glutamatergic and HPA systems have not been extensively examined in individuals with BD-AUD and BD-SUD comorbidity. The aim of this investigation was to determine whether variants in the glutamatergic pathway and HPA-axis are associated with BD-AUD and BD-SUD comorbidity. The research cohort consisted of 498 individuals with BD type I from the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD). A subset of the cohort had comorbid current AUD and current SUD. A total of 1935 SNPs from both the glutamatergic and HPA pathways were selected from the STEP-BD genome-wide dataset. To identify population stratification, IBS clustering was performed using the program Plink 1.07. Single SNP association and gene-based association testing were conducted using logistic regression. A pathway analysis of glutamatergic and HPA genes was performed, after imputation using IMPUTE2. No single SNP was associated with BD-AUD or BD-SUD comorbidity after correction for multiple testing. However, from the gene-based analysis, the gene PRKCI was significantly associated with BD-AUD. The pathway analysis provided overall negative findings, although several genes including GRIN2B showed high percentage of associated SNPs for BD-AUD. Even though the glutamatergic and HPA pathways may not be involved in BD-AUD and BD-SUD comorbidity, PRKCI deserves further investigation in BD-AUD.

Possible involvement of the circadian pathway in alcohol use disorder in a South African adolescent cohort.

Alcoholism has an estimated heritability of between 40 and 60% and it is thought that several genes of small effect may contribute to the risk of developing this disorder. Studies of the genetics of alcohol use disorder (AUD) may, however, be confounded by issues of comorbidity. The aim of this investigation was to assess associations between variants in a range of candidate genes and AUD in a unique sample of adolescents without comorbidity. Our cohort consisted of 80 adolescents with an AUD diagnosis and 80 matched controls of mixed ancestry ethnicity. An Illumina Infinium iSelect custom 6000 bead chip was used to genotype 5348 SNPs in 378 candidate genes. Association analysis, gene-based analysis and polygenic scoring were performed. There was no statistical association between any of the investigated SNPs and AUD after correction for multiple testing. However, from the gene-based analysis it was found that the circadian rhythm genes NR1D1 and BHLHE41 are associated with AUD. While preliminary, these data provide some evidence that the circadian pathway may be relevant to the pathophysiology of AUD. Study of early onset non-comorbid populations with AUD may be useful in identifying target genes for study in larger more representative samples.

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.

Childhood adversity is linked to differential brain volumes in adolescents with alcohol use disorder: a voxel-based morphometry study.

Previous neuroimaging studies link both alcohol use disorder (AUD) and early adversity to neurobiological differences in the adult brain. However, the association between AUD and childhood adversity and effects on the developing adolescent brain are less clear, due in part to the confound of psychiatric comorbidity. Here we examine early life adversity and its association with brain volume in a unique sample of 116 South African adolescents (aged 12-16) with AUD but without psychiatric comorbidity. Participants were 58 adolescents with DSM-IV alcohol dependence and with no other psychiatric comorbidities, and 58 age-, gender- and protocol-matched light/non-drinking controls (HC). Assessments included the Childhood Trauma Questionnaire (CTQ). MR images were acquired on a 3T Siemens Magnetom Allegra scanner. Volumes of global and regional structures were estimated using SPM8 Voxel Based Morphometry (VBM), with analysis of covariance (ANCOVA) and regression analyses. In whole brain ANCOVA analyses, a main effect of group when examining the AUD effect after covarying out CTQ was observed on brain volume in bilateral superior temporal gyrus. Subsequent regression analyses to examine how childhood trauma scores are linked to brain volumes in the total cohort revealed a negative correlation in the left hippocampus and right precentral gyrus. Furthermore, bilateral (but most significantly left) hippocampal volume was negatively associated with sub-scores on the CTQ in the total cohort. These findings support our view that some alterations found in brain volumes in studies of adolescent AUD may reflect the impact of confounding factors such as psychiatric comorbidity rather than the effects of alcohol per se. In particular, early life adversity may influence the developing adolescent brain in specific brain regions, such as the hippocampus.

Haplotype-based study of the association of alcohol and acetaldehyde-metabolising genes with alcohol dependence (with or without comorbid anxiety symptoms) in a Cape Mixed Ancestry population.

Alcohol dependence (AD) has a large heritable component. Genetic variation in genes involved in the absorption and elimination of ethanol have been associated with AD. However, some of these polymorphisms are not present in an African population. Previous studies have reported that a type of AD which is characterized by anxious behaviour may be a genetically specific subtype of AD. We investigated whether variation in genes encoding cytochrome P450 2E1 (CYP2E1) or acetaldehyde-metabolising enzymes (ALDH1A1, ALDH2) might alter the risk of AD, with and without symptoms of anxiety, in a Cape population with mixed ancestry. Eighty case control pairs (one with AD, one without AD) were recruited and individually matched for potential confounders. Genotype data were available for 29 single-nucleotide polymorphisms (SNPs) across the three genes. Linkage disequilibrium D' values were evaluated for all pairwise comparisons. Allele and haplotype frequencies were compared between cases and controls using a χ2 test. The ACAG haplotype in block 4 of the ALDH1A1 gene provided evidence of an association with AD (p = 0.03) and weak evidence of an association with AD without symptoms of anxiety (p = 0.06). When a genetic score was constructed using SNPs showing nominal evidence of association with AD, every extra risk allele increased the odds of AD by 35% (OR 1.35, 95% CI 1.08, 1.68, p = 0.008) and the odds of having AD with anxiety symptoms increased by 53% (OR 1.53, 95% CI 1.14, 2.05, p = 0.004). Although our results are supported by previous studies in other populations, they must be interpreted with caution due to the small sample size and the potential influence of population stratification.

Genomic insights into the shared and distinct genetic architecture of cognitive function and schizophrenia.

Cognitive impairment is a major determinant of functional outcomes in schizophrenia, however, understanding of the biological mechanisms underpinning cognitive dysfunction in the disorder remains incomplete. Here, we apply Genomic Structural Equation Modelling to identify latent cognitive factors capturing genetic liabilities to 12 cognitive traits measured in the UK Biobank. We identified three broad factors that underly the genetic correlations between the cognitive tests. We explore the overlap between latent cognitive factors, schizophrenia, and schizophrenia symptom dimensions using a complementary set of statistical approaches, applied to data from the latest schizophrenia genome-wide association study (Ncase = 53,386, Ncontrol = 77,258) and the Thematically Organised Psychosis study (Ncase = 306, Ncontrol = 1060). Global genetic correlations showed a significant moderate negative genetic correlation between each cognitive factor and schizophrenia. Local genetic correlations implicated unique genomic regions underlying the overlap between schizophrenia and each cognitive factor. We found substantial polygenic overlap between each cognitive factor and schizophrenia and biological annotation of the shared loci implicated gene-sets related to neurodevelopment and neuronal function. Lastly, we show that the common genetic determinants of the latent cognitive factors are not predictive of schizophrenia symptoms in the Norwegian Thematically Organized Psychosis cohort. Overall, these findings inform our understanding of cognitive function in schizophrenia by demonstrating important differences in the shared genetic architecture of schizophrenia and cognitive abilities.

Blood-based DNA methylation and exposure risk scores predict PTSD with high accuracy in military and civilian cohorts.

Background: Incorporating genomic data into risk prediction has become an increasingly useful approach for rapid identification of individuals most at risk for complex disorders such as PTSD. Our goal was to develop and validate Methylation Risk Scores (MRS) using machine learning to distinguish individuals who have PTSD from those who do not. Methods: Elastic Net was used to develop three risk score models using a discovery dataset (n = 1226; 314 cases, 912 controls) comprised of 5 diverse cohorts with available blood-derived DNA methylation (DNAm) measured on the Illumina Epic BeadChip. The first risk score, exposure and methylation risk score (eMRS) used cumulative and childhood trauma exposure and DNAm variables; the second, methylation-only risk score (MoRS) was based solely on DNAm data; the third, methylation-only risk scores with adjusted exposure variables (MoRSAE) utilized DNAm data adjusted for the two exposure variables. The potential of these risk scores to predict future PTSD based on pre-deployment data was also assessed. External validation of risk scores was conducted in four independent cohorts. Results: The eMRS model showed the highest accuracy (92%), precision (91%), recall (87%), and f1-score (89%) in classifying PTSD using 3730 features. While still highly accurate, the MoRS (accuracy = 89%) using 3728 features and MoRSAE (accuracy = 84%) using 4150 features showed a decline in classification power. eMRS significantly predicted PTSD in one of the four independent cohorts, the BEAR cohort (beta = 0.6839, p-0.003), but not in the remaining three cohorts. Pre-deployment risk scores from all models (eMRS, beta = 1.92; MoRS, beta = 1.99 and MoRSAE, beta = 1.77) displayed a significant (p < 0.001) predictive power for post-deployment PTSD. Conclusion: Results, especially those from the eMRS, reinforce earlier findings that methylation and trauma are interconnected and can be leveraged to increase the correct classification of those with vs. without PTSD. Moreover, our models can potentially be a valuable tool in predicting the future risk of developing PTSD. As more data become available, including additional molecular, environmental, and psychosocial factors in these scores may enhance their accuracy in predicting the condition and, relatedly, improve their performance in independent cohorts.

Genetic variants for head size share genes and pathways with cancer.

The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We perform a genome-wide association study on head size (N = 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimaging studies show that 17 variants affect specific brain areas, but most have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer.