Phenome-wide screening of the putative causal determinants of depression using genetic data.

Depression is one of the most common mental health disorders and one of the top causes of disability throughout the world. The present study sought to identify putative causal associations between depression and hundreds of complex human traits through a genome-wide screening of genetic data and a hypothesis-free approach. We leveraged genome-wide association studies summary statistics for depression and 1504 complex traits and investigated potential causal relationships using the latent causal variable method. We identified 559 traits genetically correlated with depression risk at FDR < 5%. Of these, 46 were putative causal genetic determinants of depression, including lifestyle factors, diseases of the nervous system, respiratory disorders, diseases of the musculoskeletal system, traits related to the health of the gastrointestinal system, obesity, vitamin D levels and the use of prescription medications, among others. No phenotypes were identified as potential outcomes of depression. Our results suggest that genetic liability to multiple complex traits may contribute to a higher risk for depression. In particular, we show a putative causal genetic effect of pain, obesity and inflammation on depression. These findings provide novel insights into the potential causal determinants of depression and should be interpreted as testable hypotheses for future studies to confirm, which may facilitate the design of new prevention strategies to reduce depression's burden.

Genome-wide association study meta-analysis of dizygotic twinning illuminates genetic regulation of female fecundity.

STUDY QUESTION: Which genetic factors regulate female propensity for giving birth to spontaneous dizygotic (DZ) twins? SUMMARY ANSWER: We identified four new loci, GNRH1, FSHR, ZFPM1, and IPO8, in addition to previously identified loci, FSHB and SMAD3. WHAT IS KNOWN ALREADY: The propensity to give birth to DZ twins runs in families. Earlier, we reported that FSHB and SMAD3 as associated with DZ twinning and female fertility measures. STUDY DESIGN, SIZE, DURATION: We conducted a genome-wide association meta-analysis (GWAMA) of mothers of spontaneous dizygotic (DZ) twins (8265 cases, 264 567 controls) and of independent DZ twin offspring (26 252 cases, 417 433 controls). PARTICIPANTS/MATERIALS, SETTING, METHODS: Over 700 000 mothers of DZ twins, twin individuals and singletons from large cohorts in Australia/New Zealand, Europe, and the USA were carefully screened to exclude twins born after use of ARTs. Genetic association analyses by cohort were followed by meta-analysis, phenome wide association studies (PheWAS), in silico and in vivo annotations, and Zebrafish functional validation. MAIN RESULTS AND THE ROLE OF CHANCE: This study enlarges the sample size considerably from previous efforts, finding four genome-wide significant loci, including two novel signals and a further two novel genes that are implicated by gene level enrichment analyses. The novel loci, GNRH1 and FSHR, have well-established roles in female reproduction whereas ZFPM1 and IPO8 have not previously been implicated in female fertility. We found significant genetic correlations with multiple aspects of female reproduction and body size as well as evidence for significant selection against DZ twinning during human evolution. The 26 top single nucleotide polymorphisms (SNPs) from our GWAMA in European-origin participants weakly predicted the crude twinning rates in 47 non-European populations (r = 0.23 between risk score and population prevalence, s.e. 0.11, 1-tail P = 0.058) indicating that genome-wide association studies (GWAS) are needed in African and Asian populations to explore the causes of their respectively high and low DZ twinning rates. In vivo functional tests in zebrafish for IPO8 validated its essential role in female, but not male, fertility. In most regions, risk SNPs linked to known expression quantitative trait loci (eQTLs). Top SNPs were associated with in vivo reproductive hormone levels with the top pathways including hormone ligand binding receptors and the ovulation cycle. LARGE SCALE DATA: The full DZT GWAS summary statistics will made available after publication through the GWAS catalog (https://www.ebi.ac.uk/gwas/). LIMITATIONS, REASONS FOR CAUTION: Our study only included European ancestry cohorts. Inclusion of data from Africa (with the highest twining rate) and Asia (with the lowest rate) would illuminate further the biology of twinning and female fertility. WIDER IMPLICATIONS OF THE FINDINGS: About one in 40 babies born in the world is a twin and there is much speculation on why twinning runs in families. We hope our results will inform investigations of ovarian response in new and existing ARTs and the causes of female infertility. STUDY FUNDING/COMPETING INTEREST(S): Support for the Netherlands Twin Register came from the Netherlands Organization for Scientific Research (NWO) and The Netherlands Organization for Health Research and Development (ZonMW) grants, 904-61-193, 480-04-004, 400-05-717, Addiction-31160008, 911-09-032, Biobanking and Biomolecular Resources Research Infrastructure (BBMRI.NL, 184.021.007), Royal Netherlands Academy of Science Professor Award (PAH/6635) to DIB, European Research Council (ERC-230374), Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06), the Avera Institute, Sioux Falls, South Dakota (USA) and the National Institutes of Health (NIH R01 HD042157-01A1) and the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health and Grand Opportunity grants 1RC2 MH089951. The QIMR Berghofer Medical Research Institute (QIMR) study was supported by grants from the National Health and Medical Research Council (NHMRC) of Australia (241944, 339462, 389927, 389875, 389891, 389892, 389938, 443036, 442915, 442981, 496610, 496739, 552485, 552498, 1050208, 1075175). L.Y. is funded by Australian Research Council (Grant number DE200100425). The Minnesota Center for Twin and Family Research (MCTFR) was supported in part by USPHS Grants from the National Institute on Alcohol Abuse and Alcoholism (AA09367 and AA11886) and the National Institute on Drug Abuse (DA05147, DA13240, and DA024417). The Women's Genome Health Study (WGHS) was funded by the National Heart, Lung, and Blood Institute (HL043851 and HL080467) and the National Cancer Institute (CA047988 and UM1CA182913), with support for genotyping provided by Amgen. Data collection in the Finnish Twin Registry has been supported by the Wellcome Trust Sanger Institute, the Broad Institute, ENGAGE-European Network for Genetic and Genomic Epidemiology, FP7-HEALTH-F4-2007, grant agreement number 201413, National Institute of Alcohol Abuse and Alcoholism (grants AA-12502, AA-00145, AA-09203, AA15416, and K02AA018755) and the Academy of Finland (grants 100499, 205585, 118555, 141054, 264146, 308248, 312073 and 336823 to J. Kaprio). TwinsUK is funded by the Wellcome Trust, Medical Research Council, Versus Arthritis, European Union Horizon 2020, Chronic Disease Research Foundation (CDRF), Zoe Ltd and the National Institute for Health Research (NIHR) Clinical Research Network (CRN) and Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust in partnership with King's College London. For NESDA, funding was obtained from the Netherlands Organization for Scientific Research (Geestkracht program grant 10000-1002), the Center for Medical Systems Biology (CSMB, NVVO Genomics), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL), VU University's Institutes for Health and Care Research (EMGO+) and Neuroscience Campus Amsterdam, University Medical Center Groningen, Leiden University Medical Center, National Institutes of Health (NIH, ROI D0042157-01A, MH081802, Grand Opportunity grants 1 RC2 Ml-1089951 and IRC2 MH089995). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health. Computing was supported by BiG Grid, the Dutch e-Science Grid, which is financially supported by NWO. Work in the Del Bene lab was supported by the Programme Investissements d'Avenir IHU FOReSIGHT (ANR-18-IAHU-01). C.R. was supported by an EU Horizon 2020 Marie Sklodowska-Curie Action fellowship (H2020-MSCA-IF-2014 #661527). H.S. and K.S. are employees of deCODE Genetics/Amgen. The other authors declare no competing financial interests. TRIAL REGISTRATION NUMBER: N/A.

Genetic overlap between cortical brain morphometry and frontotemporal dementia risk.

Frontotemporal dementia (FTD) has a complex genetic etiology, where the precise mechanisms underlying the selective vulnerability of brain regions remain unknown. We leveraged summary-based data from genome-wide association studies (GWAS) and performed LD score regression to estimate pairwise genetic correlations between FTD risk and cortical brain imaging. Then, we isolated specific genomic loci with a shared etiology between FTD and brain structure. We also performed functional annotation, summary-data-based Mendelian randomization for eQTL using human peripheral blood and brain tissue data, and evaluated the gene expression in mice targeted brain regions to better understand the dynamics of the FTD candidate genes. Pairwise genetic correlation estimates between FTD and brain morphology measures were high but not statistically significant. We identified 5 brain regions with a strong genetic correlation (rg > 0.45) with FTD risk. Functional annotation identified 8 protein-coding genes. Building upon these findings, we show in a mouse model of FTD that cortical N-ethylmaleimide sensitive factor (NSF) expression decreases with age. Our results highlight the molecular and genetic overlap between brain morphology and higher risk for FTD, specifically for the right inferior parietal surface area and right medial orbitofrontal cortical thickness. In addition, our findings implicate NSF gene expression in the etiology of FTD.

TwinsMX: Exploring the Genetic and Environmental Influences on Health Traits in the Mexican Population.

TwinsMX registry is a national research initiative in Mexico that aims to understand the complex interplay between genetics and environment in shaping physical and mental health traits among the country's population. With a multidisciplinary approach, TwinsMX aims to advance our knowledge of the genetic and environmental mechanisms underlying ethnic variations in complex traits and diseases, including behavioral, psychometric, anthropometric, metabolic, cardiovascular and mental disorders. With information gathered from over 2800 twins, this article updates the prevalence of several complex traits; and describes the advances and novel ideas we have implemented such as magnetic resonance imaging. The future expansion of the TwinsMX registry will enhance our comprehension of the intricate interplay between genetics and environment in shaping health and disease in the Mexican population. Overall, this report describes the progress in the building of a solid database that will allow the study of complex traits in the Mexican population, valuable not only for our consortium, but also for the worldwide scientific community, by providing new insights of understudied genetically admixed populations.

Elucidating the relationship between migraine risk and brain structure using genetic data.

Migraine is a highly common and debilitating disorder that often affects individuals in their most productive years of life. Previous studies have identified both genetic variants and brain morphometry differences associated with migraine risk. However, the relationship between migraine and brain morphometry has not been examined on a genetic level, and the causal nature of the association between brain structure and migraine risk has not been determined. Using the largest available genome-wide association studies to date, we examined the genome-wide genetic overlap between migraine and intracranial volume, as well as the regional volumes of nine subcortical brain structures. We further focused the identification and biological annotation of genetic overlap between migraine and each brain structure on specific regions of the genome shared between migraine and brain structure. Finally, we examined whether the size of any of the examined brain regions causally increased migraine risk using a Mendelian randomization approach. We observed a significant genome-wide negative genetic correlation between migraine risk and intracranial volume (rG = -0.11, P = 1 × 10-3) but not with any subcortical region. However, we identified jointly associated regional genomic overlap between migraine and every brain structure. Gene enrichment in these shared genomic regions pointed to possible links with neuronal signalling and vascular regulation. Finally, we provide evidence of a possible causal relationship between smaller total brain, hippocampal and ventral diencephalon volume and increased migraine risk, as well as a causal relationship between increased risk of migraine and a larger volume of the amygdala. We leveraged the power of large genome-wide association studies to show evidence of shared genetic pathways that jointly influence migraine risk and several brain structures, suggesting that altered brain morphometry in individuals with high migraine risk may be genetically mediated. Further interrogation of these results showed support for the neurovascular hypothesis of migraine aetiology and shed light on potentially viable therapeutic targets.

Phenotypic and genetic factors associated with donation of DNA and consent to record linkage for prescription history in the Australian Genetics of Depression Study.

Samples can be prone to ascertainment and attrition biases. The Australian Genetics of Depression Study is a large publicly recruited cohort (n = 20,689) established to increase the understanding of depression and antidepressant treatment response. This study investigates differences between participants who donated a saliva sample or agreed to linkage of their records compared to those who did not. We observed that older, male participants with higher education were more likely to donate a saliva sample. Self-reported bipolar disorder, ADHD, panic disorder, PTSD, substance use disorder, and social anxiety disorder were associated with lower odds of donating a saliva sample, whereas anorexia was associated with higher odds of donation. Male and younger participants showed higher odds of agreeing to record linkage. Participants with higher neuroticism scores and those with a history of bipolar disorder were also more likely to agree to record linkage whereas participants with a diagnosis of anorexia were less likely to agree. Increased likelihood of consent was associated with increased genetic susceptibility to anorexia and reduced genetic risk for depression, and schizophrenia. Overall, our results show moderate differences among these subsamples. Most current epidemiological studies do not search for attrition biases at the genetic level. The possibility to do so is a strength of samples such as the AGDS. Our results suggest that analyses can be made more robust by identifying attrition biases both on the phenotypic and genetic level, and either contextualising them as a potential limitation or performing sensitivity analyses adjusting for them.

Shared Genetic Etiology between Cortical Brain Morphology and Tobacco, Alcohol, and Cannabis Use.

Genome-wide association studies (GWAS) have identified genetic variants associated with brain morphology and substance use behaviors (SUB). However, the genetic overlap between brain structure and SUB has not been well characterized. We leveraged GWAS summary data of 71 brain imaging measures and alcohol, tobacco, and cannabis use to investigate their genetic overlap using linkage disequilibrium score regression. We used genomic structural equation modeling to model a "common SUB genetic factor" and investigated its genetic overlap with brain structure. Furthermore, we estimated SUB polygenic risk scores (PRS) and examined whether they predicted brain imaging traits using the Adolescent Behavior and Cognitive Development (ABCD) study. We identified 8 significant negative genetic correlations, including between (1) alcoholic drinks per week and average cortical thickness, and (2) intracranial volume with age of smoking initiation. We observed 5 positive genetic correlations, including those between (1) insula surface area and lifetime cannabis use, and (2) the common SUB genetic factor and pericalcarine surface area. SUB PRS were associated with brain structure variation in ABCD. Our findings highlight a shared genetic etiology between cortical brain morphology and SUB and suggest that genetic variants associated with SUB may be causally related to brain structure differences.

Estimating the Genetic Contribution to Astigmatism and Myopia in the Mexican Population.

Astigmatism and myopia are two common ocular refractive errors that can impact daily life, including learning and productivity. Current knowledge suggests that the etiology of these conditions is the result of a complex interplay between genetic and environmental factors. Studies in populations of European ancestry have demonstrated a higher concordance of refractive errors in monozygotic (MZ) twins compared to dizygotic (DZ) twins. However, there is a lack of studies on genetically informative samples of multi-ethnic ancestry. This study aimed to estimate the genetic contribution to astigmatism and myopia in the Mexican population. A sample of 1399 families, including 243 twin pairs and 1156 single twins, completed a medical questionnaire about their own and their co-twin's diagnosis of astigmatism and myopia. Concordance rates for astigmatism and myopia were estimated, and heritability and genetic correlations were determined using a bivariate ACE Cholesky decomposition method, decomposed into A (additive genetic), C (shared environmental) and E (unique environmental) components. The results showed a higher concordance rate for astigmatism and myopia for MZ twins (.74 and .74, respectively) than for DZ twins (.50 and .55). The AE model, instead of the ACE model, best fitted the data. Based on this, heritability estimates were .81 for astigmatism and .81 for myopia, with a cross-trait genetic correlation of rA = .80, nonshared environmental correlation rE = .89, and a phenotypic correlation of rP = .80. These results are consistent with previous findings in other populations, providing evidence for a similar genetic architecture of these conditions in the multi-ethnic Mexican population.

Genomics-driven screening for causal determinants of suicide attempt.

OBJECTIVE: Each year, around one million people die by suicide. Despite its recognition as a public health concern, large-scale research on causal determinants of suicide attempt risk is scarce. Here, we leverage results from a recent genome-wide association study (GWAS) of suicide attempt to perform a data-driven screening of traits causally associated with suicide attempt. METHODS: We performed a hypothesis-generating phenome-wide screening of causal relationships between suicide attempt risk and 1520 traits, which have been systematically aggregated on the Complex-Traits Genomics Virtual Lab platform. We employed the latent causal variable (LCV) method, which uses results from GWAS to assess whether a causal relationship can explain a genetic correlation between two traits. If a trait causally influences another one, the genetic variants that increase risk for the causal trait will also increase the risk for the outcome inducing a genetic correlation. Nonetheless, a genetic correlation can also be observed when traits share common pathways. The LCV method can assess whether the pattern of genetic effects for two genetically correlated traits support a causal association rather than a shared aetiology. RESULTS: Our approach identified 62 traits that increased risk for suicide attempt. Risk factors identified can be broadly classified into (1) physical health disorders, including oesophagitis, fibromyalgia, hernia and cancer; (2) mental health-related traits, such as depression, substance use disorders and anxiety; and (3) lifestyle traits including being involved in combat or exposure to a war zone, and specific job categories such as being a truck driver or machine operator. CONCLUSIONS: Suicide attempt risk is likely explained by a combination of behavioural phenotypes and risk for both physical and psychiatric disorders. Our results also suggest that substance use behaviours and pain-related conditions are associated with an increased suicide attempt risk, elucidating important causal mechanisms that underpin this significant public health problem.

Genetic impact of blood C-reactive protein levels on chronic spinal & widespread pain.

PURPOSE: Causal mechanisms underlying systemic inflammation in spinal & widespread pain remain an intractable experimental challenge. Here we examined whether: (i) associations between blood C-reactive protein (CRP) and chronic back, neck/shoulder & widespread pain can be explained by shared underlying genetic variants; and (ii) higher CRP levels causally contribute to these conditions. METHODS: Using genome-wide association studies (GWAS) of chronic back, neck/shoulder & widespread pain (N = 6063-79,089 cases; N = 239,125 controls) and GWAS summary statistics for blood CRP (Pan-UK Biobank N = 400,094 & PAGE consortium N = 28,520), we employed cross-trait bivariate linkage disequilibrium score regression to determine genetic correlations (rG) between these chronic pain phenotypes and CRP levels (FDR < 5%). Latent causal variable (LCV) and generalised summary data-based Mendelian randomisation (GSMR) analyses examined putative causal associations between chronic pain & CRP (FDR < 5%). RESULTS: Higher CRP levels were genetically correlated with chronic back, neck/shoulder & widespread pain (rG range 0.26-0.36; P ≤ 8.07E-9; 3/6 trait pairs). Although genetic causal proportions (GCP) did not explain this finding (GCP range - 0.32-0.08; P ≥ 0.02), GSMR demonstrated putative causal effects of higher CRP levels contributing to each pain type (beta range 0.027-0.166; P ≤ 9.82E-03; 3 trait pairs) as well as neck/shoulder pain effects on CRP levels (beta [S.E.] 0.030 [0.021]; P = 6.97E-04). CONCLUSION: This genetic evidence for higher CRP levels in chronic spinal (back, neck/shoulder) & widespread pain warrants further large-scale multimodal & prospective longitudinal studies to accelerate the identification of novel translational targets and more effective therapeutic strategies.

Discontinuation of antidepressant treatment: a retrospective cohort study on more than 20,000 participants.

BACKGROUND: Factors influencing antidepressant treatment discontinuation are poorly understood. In the present study, we aimed to estimate the prevalence of antidepressant treatment discontinuation and identify demographic characteristics, psychiatric comorbidities, and specific side effects associated with treatment discontinuation. METHODS: We leveraged data from the Australian Genetics of Depression Study (AGDS; N = 20,941) to perform a retrospective cohort study on antidepressant treatment discontinuation. Participants were eligible if they were over 18 years of age, had taken antidepressants in the past 4 years, and provided informed consent. RESULTS: Among the ten antidepressants studied, the highest discontinuation rates were observed for Mirtazapine (57.3%) and Amitriptyline (51.6%). Discontinuation rates were comparable across sexes except for Mirtazapine, for which women were more likely to discontinue. The two most common side effects, reduced sexual function and weight gain, were not associated with increased odds of treatment discontinuation. Anxiety, agitation, suicidal thoughts, vomiting, and rashes were associated with higher odds for treatment discontinuation, as were lifetime diagnoses of PTSD, ADHD, and a higher neuroticism score. Educational attainment showed a negative (protective) association with discontinuation across medications. CONCLUSIONS: Our study suggests that not all side effects contribute equally to discontinuation. Common side effects such as reduced sexual function and weight gain may not necessarily increase the risk of treatment discontinuation. Side effects linked to discontinuation can be divided into two groups, psychopathology related and allergy/intolerance.

A supervised machine learning approach identifies gene-regulating factor-mediated competing endogenous RNA networks in hormone-dependent cancers.

Competing endogenous RNAs (ceRNAs) have become an emerging topic in cancer research due to their role in gene regulatory networks. To date, traditional ceRNA bioinformatic studies have investigated microRNAs as the only factor regulating gene expression. Growing evidence suggests that genomic (e.g., copy number alteration [CNA]), transcriptomic (e.g., transcription factors [TFs]), and epigenomic (e.g., DNA methylation [DM]) factors can influence ceRNA regulatory networks. Herein, we used the Least absolute shrinkage and selection operator regression, a machine learning approach, to integrate DM, CNA, and TFs data with RNA expression to infer ceRNA networks in cancer risk. The gene-regulating factors-mediated ceRNA networks were identified in four hormone-dependent (HD) cancer types: prostate, breast, colorectal, and endometrial. The shared ceRNAs across HD cancer types were further investigated using survival analysis, functional enrichment analysis, and protein-protein interaction network analysis. We found two (BUB1 and EXO1) and one (RRM2) survival-significant ceRNA(s) shared across breast-colorectal-endometrial and prostate-colorectal-endometrial combinations, respectively. Both BUB1 and BUB1B genes were identified as shared ceRNAs across more than two HD cancers of interest. These genes play a critical role in cell division, spindle-assembly checkpoint signalling, and correct chromosome alignment. Furthermore, shared ceRNAs across multiple HD cancers have been involved in essential cancer pathways such as cell cycle, p53 signalling, and chromosome segregation. Identifying ceRNAs' roles across multiple related cancers will improve our understanding of their shared disease biology. Moreover, it contributes to the knowledge of RNA-mediated cancer pathogenesis.

Impact of CYP2C19 metaboliser status on SSRI response: a retrospective study of 9500 participants of the Australian Genetics of Depression Study.

BACKGROUND: Variation within the CYP2C19 gene has been linked to differential metabolism of selective serotonin reuptake inhibitors (SSRIs). Pharmacogenetic recommendations based on the effect of CYP2C19 variants have been made available and are used increasingly by clinical practitioners. Nonetheless, the underlying assumption linking differential metabolism to efficacy or adverse side effects remains understudied. Here, we aim to fill this gap by studying CYP2C19 polymorphisms and inferred metabolism and patient-reported antidepressant response in a sample of 9531 Australian adults who have taken SSRIs. METHODS: Metaboliser status was inferred for participants based on CYP2C19 alleles. Primary analysis consisted of assessing differences in treatment efficacy and tolerability between normal (reference) and: ultrarapid, rapid, intermediate and poor metabolisers. RESULTS: Across medications, poor metabolisers reported a higher efficacy, whereas rapid metabolisers reported higher tolerability. When stratified by drug, associations between metaboliser status and efficacy did not survive multiple testing correction. Intermediate metabolisers were at greater odds of reporting any side effect for sertraline and higher number of side effects across medications and for sertraline. CONCLUSIONS: The effects between metaboliser status and treatment efficacy, tolerability and side effects were in the expected direction. Our power analysis suggests we would detect moderate to large effects, at least nominally. Reduced power may also be explained by heterogeneity in antidepressant dosages or concomitant medications, which we did not measure. The fact that we identify slower metabolisers to be at higher risk of side effects even without adjusting for clinical titration, and the nominally significant associations consistent with the expected metabolic effects provide new evidence for the link between CYP2C19 metabolism and SSRI response. Nonetheless, longitudinal and interventional designs such as randomized clinical trials that stratify by metaboliser status are necessary to establish the effects of CYP2C19 metabolism on SSRI treatment efficacy or adverse effects.

Classification of suicidal thoughts and behaviour in children: results from penalised logistic regression analyses in the Adolescent Brain Cognitive Development study.

BACKGROUND: Despite efforts to predict suicide risk in children, the ability to reliably identify who will engage in suicide thoughts or behaviours has remained unsuccessful. AIMS: We apply a novel machine-learning approach and examine whether children with suicide thoughts or behaviours could be differentiated from children without suicide thoughts or behaviours based on a combination of traditional (sociodemographic, physical health, social-environmental, clinical psychiatric) risk factors, but also more novel risk factors (cognitive, neuroimaging and genetic characteristics). METHOD: The study included 5885 unrelated children (50% female, 67% White, 9-11 years of age) from the Adolescent Brain Cognitive Development (ABCD) study. We performed penalised logistic regression analysis to distinguish between: (a) children with current or past suicide thoughts or behaviours; (b) children with a mental illness but no suicide thoughts or behaviours (clinical controls); and (c) healthy control children (no suicide thoughts or behaviours and no history of mental illness). The model was subsequently validated with data from seven independent sites involved in the ABCD study (n = 1712). RESULTS: Our results showed that we were able to distinguish the suicide thoughts or behaviours group from healthy controls (area under the receiver operating characteristics curve: 0.80 child-report, 0.81 for parent-report) and clinical controls (0.71 child-report and 0.76-0.77 parent-report). However, we could not distinguish children with suicidal ideation from those who attempted suicide (AUROC: 0.55-0.58 child-report; 0.49-0.53 parent-report). The factors that differentiated the suicide thoughts or behaviours group from the clinical control group included family conflict, prodromal psychosis symptoms, impulsivity, depression severity and history of mental health treatment. CONCLUSIONS: This work highlights that mostly clinical psychiatric factors were able to distinguish children with suicide thoughts or behaviours from children without suicide thoughts or behaviours. Future research is needed to determine if these variables prospectively predict subsequent suicidal behaviour.

Genetic basis to structural grey matter associations with chronic pain.

Structural neuroimaging studies of individuals with chronic pain conditions have often observed decreased regional grey matter at a phenotypic level. However, it is not known if this association can be attributed to genetic factors. Here we employed a novel integrative data-driven and hypothesis-testing approach to determine whether there is a genetic basis to grey matter morphology differences in chronic pain. Using publicly available genome-wide association study summary statistics for regional chronic pain conditions (n = 196 963) and structural neuroimaging measures (n = 19 629-34 000), we applied bivariate linkage disequilibrium-score regression and latent causal variable analyses to determine the genetic correlations (rG) and genetic causal proportion (GCP) between these complex traits, respectively. Five a priori brain regions (i.e. prefrontal cortex, cingulate cortex, insula, thalamus and superior temporal gyrus) were selected based on systematic reviews of grey matter morphology studies in chronic pain. Across this evidence-based selection of five brain regions, 10 significant negative genetic correlations (out of 369) were found (false discovery rate < 5%), suggesting a shared genetic basis to both reduced regional grey matter morphology and the presence of chronic pain. Specifically, negative genetic correlations were observed between reduced insula grey matter morphology and chronic pain in the abdomen (mean insula cortical thickness), hips (left insula volume) and neck/shoulders (left and right insula volume). Similarly, a shared genetic basis was found for reduced posterior cingulate cortex volume in chronic pain of the hip (left and right posterior cingulate), neck/shoulder (left posterior cingulate) and chronic pain at any site (left posterior cingulate); and for reduced pars triangularis volume in chronic neck/shoulder (left pars triangularis) and widespread pain (right pars triangularis). Across these negative genetic correlations, a significant genetic causal proportion was only found between mean insula thickness and chronic abdominal pain [rG (standard error, SE) = -0.25 (0.08), P = 1.06 × 10-3; GCP (SE) = -0.69 (0.20), P = 4.96 × 10-4]. This finding suggests that the genes underlying reduced cortical thickness of the insula causally contribute to an increased risk of chronic abdominal pain. Altogether, these results provide independent corroborating evidence for observational reports of decreased grey matter of particular brain regions in chronic pain. Further, we show for the first time that this association is mediated (in part) by genetic factors. These novel findings warrant further investigation into the neurogenetic pathways that underlie the development and prolongation of chronic pain conditions.

Dehydroepiandrosterone Sulfate and Colorectal Cancer Risk: A Mendelian Randomization Analysis.

Colorectal cancer is the third most common and second most deadly type of cancer worldwide, with approximately 1.9 million cases and 0.9 million deaths worldwide in 2020. Previous studies have shown that estrogen and testosterone hormones are associated with colorectal cancer risk and mortality. However, the potential effect of their precursor, dehydroepiandrosterone sulfate (DHEAS), on colorectal cancer risk has not been investigated. Therefore, evaluating DHEAS's effect on colorectal cancer will expand our understanding of the hormonal contribution to colorectal cancer risk. In this study, we conducted a two-sample Mendelian randomization (MR) analysis to investigate the causal effect of DHEAS on colorectal cancer. We obtained DHEAS and colorectal cancer genomewide association study (GWAS) summary statistics from the Leipzig Health Atlas and the GWAS catalog and conducted MR analyses using the TwoSampleMR R package. Our results suggest that higher DHEAS levels are causally associated with decreased colorectal cancer risk (odds ratio per unit increase in DHEAS levels z score = 0.70; 95% confidence interval [0.51, 0.96]), which is in line with previous observations in a case-control study of colon cancer. The outcome of this study will be beneficial in developing plasma DHEAS-based biomarkers in colorectal cancer. Further studies should be conducted to interpret the DHEAS-colorectal cancer association among different ancestries and populations.

Genetic risk for chronic pain is associated with lower antidepressant effectiveness: Converging evidence for a depression subtype.

INTRODUCTION: Chronic pain and depression are highly comorbid and difficult-to-treat disorders. We previously showed this comorbidity is associated with higher depression severity, lower antidepressant treatment effectiveness and poorer prognosis in the Australian Genetics of Depression Study. OBJECTIVE: The current study aimed to assess whether a genetic liability to chronic pain is associated with antidepressant effectiveness over and above the effect of genetic factors for depression in a sample of 12,863 Australian Genetics of Depression Study participants. METHODS: Polygenic risk scores were calculated using summary statistics from genome-wide association studies of multisite chronic pain and major depression. Cumulative linked regressions were employed to assess the association between polygenic risk scores and antidepressant treatment effectiveness across 10 different medications. RESULTS: Mixed-effects logistic regressions showed that individual genetic propensity for chronic pain, but not major depression, was significantly associated with patient-reported chronic pain (PainPRS OR = 1.17 [1.12, 1.22]; MDPRS OR = 1.01 [0.98, 1.06]). Significant associations were also found between lower antidepressant effectiveness and genetic risk for chronic pain or for major depression. However, a fully adjusted model showed the effect of PainPRS (adjOR = 0.93 [0.90, 0.96]) was independent of MDPRS (adjOR = 0.96 [0.93, 0.99]). Sensitivity analyses were performed to assess the robustness of these results. After adjusting for depression severity measures (i.e. age of onset; number of depressive episodes; interval between age at study participation and at depression onset), the associations between PainPRS and patient-reported chronic pain with lower antidepressant effectiveness remained significant (0.95 [0.92, 0.98] and 0.84 [0.78, 0.90], respectively). CONCLUSION: These results suggest genetic risk for chronic pain accounted for poorer antidepressant effectiveness, independent of the genetic risk for major depression. Our results, along with independent converging evidence from other studies, point towards a difficult-to-treat depression subtype characterised by comorbid chronic pain. This finding warrants further investigation into the implications for biologically based nosology frameworks in pain medicine and psychiatry.

Clinical, demographic, and genetic risk factors of treatment-attributed suicidality in >10,000 Australian adults taking antidepressants.

Emergence of suicidal symptoms has been reported as a potential antidepressant adverse drug reaction. Identifying risk factors associated could increase our understanding of this phenomenon and stratify individuals at higher risk. Logistic regressions were used to identify risk factors of self-reported treatment-attributed suicidal ideation (TASI). We then employed classifiers to test the predictive ability of the variables identified. A TASI GWAS, as well as SNP-based heritability estimation, were performed. GWAS replication was sought from an independent study. Significant associations were found for age and comorbid conditions, including bipolar and personality disorders. Participants reporting TASI from one antidepressant were more likely to report TASI from other antidepressants. No genetic loci associated with TAS I (p < 5e-8) were identified. Of 32 independent variants with suggestive association (p < 1e-5), 27 lead SNPs were available in a replication dataset from the GENDEP study. Only one variant showed a consistent effect and nominal association in the independent replication sample. Classifiers were able to stratify non-TASI from TASI participants (AUC = 0.77) and those reporting treatment-attributed suicide attempts (AUC = 0.85). The pattern of TASI co-occurrence across participants suggest nonspecific factors underlying its etiology. These findings provide insights into the underpinnings of TASI and serve as a proof-of-concept of the use of classifiers for risk stratification.

Phenome-wide screening of GWAS data reveals the complex causal architecture of obesity.

OBJECTIVE: In the present study, we sought to identify causal relationships between obesity and other complex traits and conditions using a data-driven hypothesis-free approach that uses genetic data to infer causal associations. METHODS: We leveraged available summary-based genetic data from genome-wide association studies on 1498 phenotypes and applied the latent causal variable method (LCV) between obesity and all traits. RESULTS: We identified 110 traits causally associated with obesity. Of those, 109 were causal outcomes of obesity, while only leg pain in calves was a causal determinant of obesity. Causal outcomes of obesity included 26 phenotypes associated with cardiovascular diseases, 22 anthropometric measurements, nine with the musculoskeletal system, nine with behavioural or lifestyle factors including loneliness or isolation, six with respiratory diseases, five with body bioelectric impedances, four with psychiatric phenotypes, four related to the nervous system, four with disabilities or long-standing illness, three with the gastrointestinal system, three with use of analgesics, two with metabolic diseases, one with inflammatory response and one with the neurodevelopmental disorder ADHD, among others. In particular, some causal outcomes of obesity included hypertension, stroke, ever having a period of extreme irritability, low forced vital capacity and forced expiratory volume, diseases of the musculoskeletal system, diabetes, carpal tunnel syndrome, loneliness or isolation, high leukocyte count, and ADHD. CONCLUSIONS: Our results indicate that obesity causally affects a wide range of traits and comorbid diseases, thus providing an overview of the metabolic, physiological, and neuropsychiatric impact of obesity on human health.

Common genetic variants influence human subcortical brain structures.

The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume and intracranial volume. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10(-33); 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.