Defining Suicidal Thought and Behavior Phenotypes for Genetic Studies.

Background: Standardized definitions of suicidality phenotypes, including suicidal ideation (SI), attempt (SA), and death (SD) are a critical step towards improving understanding and comparison of results in suicide research. The complexity of suicidality contributes to heterogeneity in phenotype definitions, impeding evaluation of clinical and genetic risk factors across studies and efforts to combine samples within consortia. Here, we present expert and data-supported recommendations for defining suicidality and control phenotypes to facilitate merging current/legacy samples with definition variability and aid future sample creation. Methods: A subgroup of clinician researchers and experts from the Suicide Workgroup of the Psychiatric Genomics Consortium (PGC) reviewed existing PGC definitions for SI, SA, SD, and control groups and generated preliminary consensus guidelines for instrument-derived and international classification of disease (ICD) data. ICD lists were validated in two independent datasets (N = 9,151 and 12,394). Results: Recommendations are provided for evaluated instruments for SA and SI, emphasizing selection of lifetime measures phenotype-specific wording. Recommendations are also provided for defining SI and SD from ICD data. As the SA ICD definition is complex, SA code list recommendations were validated against instrument results with sensitivity (range = 15.4% to 80.6%), specificity (range = 67.6% to 97.4%), and positive predictive values (range = 0.59-0.93) reported. Conclusions: Best-practice guidelines are presented for the use of existing information to define SI/SA/SD in consortia research. These proposed definitions are expected to facilitate more homogeneous data aggregation for genetic and multisite studies. Future research should involve refinement, improved generalizability, and validation in diverse populations.

Absence of nonfatal suicidal behavior preceding suicide death reveals differences in clinical risks.

Nonfatal suicidality is the most robust predictor of suicide death. However, only ~10% of those who survive an attempt go on to die by suicide. Moreover, ~50% of suicide deaths occur in the absence of prior known attempts, suggesting risks other than nonfatal suicide attempt need to be identified. We studied data from 4,000 population-ascertained suicide deaths and 26,191 population controls to improve understanding of risks leading to suicide death. This study included 2,253 suicide deaths and 3,375 controls with evidence of nonfatal suicidality (SUI_SI/SB and CTL_SI/SB) from diagnostic codes and natural language processing of electronic health records notes. Characteristics of these groups were compared to 1,669 suicides with no prior nonfatal SI/SB (SUI_None) and 22,816 controls with no lifetime suicidality (CTL_None). The SUI_None and CTL_None groups had fewer diagnoses and were older than SUI_SI/SB and CTL_SI/SB. Mental health diagnoses were far less common in both the SUI_None and CTL_None groups; mental health problems were less associated with suicide death than with presence of SI/SB. Physical health diagnoses were conversely more often associated with risk of suicide death than with presence of SI/SB. Pending replication, results indicate highly significant clinical differences among suicide deaths with versus without prior nonfatal SI/SB.

GWAS Meta-Analysis of Suicide Attempt: Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors.

OBJECTIVE: Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide association studies (GWASs) recently discovered and cross-validated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS meta-analysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures. METHODS: This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry admixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and genetic causal proportion analyses. RESULTS: Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values <5×10-8. These loci were mostly intergenic and implicated DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2. The multi-ancestry SNP-based heritability estimate of SA was 5.7% on the liability scale (SE=0.003, p=5.7×10-80). Significant brain tissue gene expression and drug set enrichment were observed. There was shared genetic variation of SA with attention deficit hyperactivity disorder, smoking, and risk tolerance after conditioning SA on both major depressive disorder and posttraumatic stress disorder. Genetic causal proportion analyses implicated shared genetic risk for specific health factors. CONCLUSIONS: This multi-ancestry analysis of suicide attempt identified several loci contributing to risk and establishes significant shared genetic covariation with clinical phenotypes. These findings provide insight into genetic factors associated with suicide attempt across ancestry admixture populations, in veteran and civilian populations, and in attempt versus death.

Whole-genome sequencing analysis of suicide deaths integrating brain-regulatory eQTLs data to identify risk loci and genes.

Recent large-scale genome-wide association studies (GWAS) have started to identify potential genetic risk loci associated with risk of suicide; however, a large portion of suicide-associated genetic factors affecting gene expression remain elusive. Dysregulated gene expression, not assessed by GWAS, may play a significant role in increasing the risk of suicide death. We performed the first comprehensive genomic association analysis prioritizing brain expression quantitative trait loci (eQTLs) within regulatory regions in suicide deaths from the Utah Suicide Genetic Risk Study (USGRS). 440,324 brain-regulatory eQTLs were obtained by integrating brain eQTLs, histone modification ChIP-seq, ATAC-seq, DNase-seq, and Hi-C results from publicly available data. Subsequent genomic analyses were conducted in whole-genome sequencing (WGS) data from 986 suicide deaths of non-Finnish European (NFE) ancestry and 415 ancestrally matched controls. Additional independent USGRS suicide deaths with genotyping array data (n = 4657) and controls from the Genome Aggregation Database were explored for WGS result replication. One significant eQTL locus, rs926308 (p = 3.24e-06), was identified. The rs926308-T is associated with lower expression of RFPL3S, a gene important for neocortex development and implicated in arousal. Gene-based analyses performed using Sherlock Bayesian statistical integrative analysis also detected 20 genes with expression changes that may contribute to suicide risk. From analyzing publicly available transcriptomic data, ten of these genes have previous evidence of differential expression in suicide death or in psychiatric disorders that may be associated with suicide, including schizophrenia and autism (ZNF501, ZNF502, CNN3, IGF1R, KLHL36, NBL1, PDCD6IP, SNX19, BCAP29, and ARSA). Electronic health records (EHR) data was further merged to evaluate if there were clinically relevant subsets of suicide deaths associated with genetic variants. In summary, our study identified one risk locus and ten genes associated with suicide risk via gene expression, providing new insight into possible genetic and molecular mechanisms leading to suicide.

Genome-wide association study meta-analysis of suicide death and suicidal behavior.

Suicide is a worldwide health crisis. We aimed to identify genetic risk variants associated with suicide death and suicidal behavior. Meta-analysis for suicide death was performed using 3765 cases from Utah and matching 6572 controls of European ancestry. Meta-analysis for suicidal behavior using data across five cohorts (n = 8315 cases and 256,478 psychiatric or populational controls of European ancestry) was also performed. One locus in neuroligin 1 (NLGN1) passing the genome-wide significance threshold for suicide death was identified (top SNP rs73182688, with p = 5.48 × 10-8 before and p = 4.55 × 10-8 after mtCOJO analysis conditioning on MDD to remove genetic effects on suicide mediated by MDD). Conditioning on suicidal attempts did not significantly change the association strength (p = 6.02 × 10-8), suggesting suicide death specificity. NLGN1 encodes a member of a family of neuronal cell surface proteins. Members of this family act as splice site-specific ligands for beta-neurexins and may be involved in synaptogenesis. The NRXN-NLGN pathway was previously implicated in suicide, autism, and schizophrenia. We additionally identified ROBO2 and ZNF28 associations with suicidal behavior in the meta-analysis across five cohorts in gene-based association analysis using MAGMA. Lastly, we replicated two loci including variants near SOX5 and LOC101928519 associated with suicidal attempts identified in the ISGC and MVP meta-analysis using the independent FinnGen samples. Suicide death and suicidal behavior showed positive genetic correlations with depression, schizophrenia, pain, and suicidal attempt, and negative genetic correlation with educational attainment. These correlations remained significant after conditioning on depression, suggesting pleiotropic effects among these traits. Bidirectional generalized summary-data-based Mendelian randomization analysis suggests that genetic risk for the suicidal attempt and suicide death are both bi-directionally causal for MDD.

Extended familial risk of suicide death is associated with younger age at death and elevated polygenic risk of suicide.

Suicide accounts for >800,000 deaths annually worldwide; prevention is an urgent public health issue. Identification of risk factors remains challenging due to complexity and heterogeneity. The study of suicide deaths with increased extended familial risk provides an avenue to reduce etiological heterogeneity and explore traits associated with increased genetic liability. Using extensive genealogical records, we identified high-risk families where distant relatedness of suicides implicates genetic risk. We compared phenotypic and polygenic risk score (PRS) data between suicides in high-risk extended families (high familial risk (HFR), n = 1,634), suicides linked to genealogical data not in any high-risk families (low familial risk (LFR), n = 147), and suicides not linked to genealogical data with unknown familial risk (UFR, n = 1,865). HFR suicides were associated with lower age at death (mean = 39.34 years), more suicide attempts, and more PTSD and trauma diagnoses. For PRS tests, we included only suicides with >90% European ancestry and adjusted for residual ancestry effects. HFR suicides showed markedly higher PRS of suicide death (calculated using cross-validation), supporting specific elevation of genetic risk of suicide in this subgroup, and also showed increased PRS of PTSD, suicide attempt, and risk taking. LFR suicides were substantially older at death (mean = 49.10 years), had fewer psychiatric diagnoses of depression and pain, and significantly lower PRS of depression. Results suggest extended familiality and trauma/PTSD may provide specificity in identifying individuals at genetic risk for suicide death, especially among younger ages, and that LFR of suicide warrants further study regarding the contribution of demographic and medical risks.

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors.

BACKGROUND: Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. METHODS: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. RESULTS: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. CONCLUSIONS: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.

Suicide and Psychosis: Results From a Population-Based Cohort of Suicide Death (N = 4380).

Approximately 5% of individuals with schizophrenia die from suicide. However, suicide in psychosis is still poorly characterized, partly due to a lack of adequate population-based clinical or genetic data on suicide death. The Utah Suicide Genetics Research Study (USGRS) provides a large population-based cohort of suicide deaths with medical record and genome-wide data (N = 4380). Examination of this cohort identified medical and genetic risks associated with type of suicide death and investigated the relative contributions of psychotic and affective symptoms to method of suicide. Key differences in method of suicide (common vs. atypical methods) were tested in relation to lifetime psychosis and genome-wide genetic risk for schizophrenia, major depressive disorder, and neuroticism. Consistent with previous studies, psychosis-spectrum disorders were observed to be common in suicide (15% of the cohort). Individuals with psychosis more frequently died from atypical methods, with rates of atypical suicide increasing across the schizophrenia spectrum. Genetic risk for schizophrenia was also associated with atypical suicide, regardless of clinical diagnosis, though this association weakened when filtering individuals with schizophrenia from the analysis. Follow-up examination indicated that high rates of atypical suicide observed in schizophrenia are not likely accounted for by restricted access to firearms. Overall, better accounting for the increased risk of atypical suicide methods in psychosis could lead to improved prevention strategies in a large portion of the suicide risk population.

Ethical concerns relating to genetic risk scores for suicide.

Genome-wide association studies (GWAS) provide valuable information in research contexts regarding genomic changes that contribute to risks for complex psychiatric conditions like major depressive disorder. GWAS results can be used to calculate polygenic risk scores (PRS) for psychiatric conditions, such as bipolar disorder or schizophrenia, as well as for other traits, such as obesity or hypertension. Private companies that provide direct-to-consumer (DTC) genetic testing sometimes report PRS for a variety of traits. Recently, the first well-powered GWAS study for suicide death was published. PRS reports that claim to assess suicide risk are therefore likely to appear soon in the DTC setting. We describe ethical concerns regarding the commercial use of GWAS results related to suicide. We identify several issues that must be addressed before PRS for suicide risk is made available to the public through DTC: (a) the potential for misinterpretation of results, (b) consumers' perceptions about determinism and behavior change, (c) potential contributions to stigma, discrimination, and health disparities; and (d) ethical problems regarding the testing of children and vulnerable adults. Tests for genetic prediction of suicidality may eventually have clinical significance, but until then, the potential for individual and public harm significantly outweighs any potential benefit. Even if genetic prediction of suicidality improves significantly, information about genetic risk scores must be distributed cautiously, with genetic counseling, and with adequate safeguards.

Assessment of suicide attempt and death in bipolar affective disorder: a combined clinical and genetic approach.

Bipolar disorder (BP) suicide death rates are 10-30 times greater than the general population, likely arising from environmental and genetic risk factors. Though suicidal behavior in BP has been investigated, studies have not addressed combined clinical and genetic factors specific to suicide death. To address this gap, a large, harmonized BP cohort was assessed to identify clinical risk factors for suicide death and attempt which then directed testing of underlying polygenic risks. 5901 individuals of European ancestry were assessed: 353 individuals with BP and 2498 without BP who died from suicide (BPS and NBPS, respectively) from a population-derived sample along with a volunteer-derived sample of 799 individuals with BP and a history of suicide attempt (BPSA), 824 individuals with BP and no prior attempts (BPNSA), and 1427 individuals without several common psychiatric illnesses per self-report (C). Clinical and subsequent directed genetic analyses utilized multivariable logistic models accounting for critical covariates and multiple testing. There was overrepresentation of diagnosis of PTSD (OR = 4.9, 95%CI: 3.1-7.6) in BPS versus BPSA, driven by female subjects. PRS assessments showed elevations in BPS including PTSD (OR = 1.3, 95%CI:1.1-1.5, versus C), female-derived ADHD (OR = 1.2, 95%CI:1.1-1.4, versus C), and male insomnia (OR = 1.4, 95%CI: 1.1-1.7, versus BPSA). The results provide support from genetic and clinical standpoints for dysregulated traumatic response particularly increasing risk of suicide death among individuals with BP of Northern European ancestry. Such findings may direct more aggressive treatment and prevention of trauma sequelae within at-risk bipolar individuals.

Neurexin 1 variants as risk factors for suicide death.

Suicide is a significant public health concern with complex etiology. Although the genetic component of suicide is well established, the scope of gene networks and biological mechanisms underlying suicide has yet to be defined. Previously, we reported genome-wide evidence that neurexin 1 (NRXN1), a key synapse organizing molecule, is associated with familial suicide risk. Here we present new evidence for two non-synonymous variants (rs78540316; P469S and rs199784139; H885Y) associated with increased familial risk of suicide death. We tested the impact of these variants on binding interactions with known partners and assessed functionality in a hemi-synapse formation assay. Although the formation of hemi-synapses was not altered with the P469S variant relative to wild-type, both variants increased binding to the postsynaptic binding partner, leucine-rich repeat transmembrane neuronal 2 (LRRTM2) in vitro. Our findings indicate that variants in NRXN1 and related synaptic genes warrant further study as risk factors for suicide death.

Rare protein-coding variants implicate genes involved in risk of suicide death.

Identification of genetic factors leading to increased risk of suicide death is critical to combat rising suicide rates, however, only a fraction of the genetic variation influencing risk has been accounted for. To address this limitation, we conducted the first comprehensive analysis of rare genetic variation in suicide death leveraging the largest suicide death biobank, the Utah Suicide Genetic Risk Study (USGRS). We conducted a single-variant association analysis of rare (minor allele frequency <1%) putatively functional single-nucleotide polymorphisms (SNPs) present on the Illumina PsychArray genotyping array in 2,672 USGRS suicide deaths of non-Finnish European (NFE) ancestry and 51,583 NFE controls from the Genome Aggregation Database. Secondary analyses used an independent control sample of 21,324 NFE controls from the Psychiatric Genomics Consortium. Five novel, high-impact, rare SNPs were identified with significant associations with suicide death (SNAPC1, rs75418419; TNKS1BP1, rs143883793; ADGRF5, rs149197213; PER1, rs145053802; and ESS2, rs62223875). 119 suicide decedents carried these high-impact SNPs. Both PER1 and SNAPC1 have other supporting gene-level evidence of suicide risk, and psychiatric associations exist for PER1 (bipolar disorder, schizophrenia), and for TNKS1BP1 and ESS2 (schizophrenia). Three of the genes (PER1, TNKS1BP1, and ADGRF5), together with additional genes implicated by genome-wide association studies on suicidal behavior, showed significant enrichment in immune system, homeostatic and signal transduction processes. No specific diagnostic phenotypes were associated with the subset of suicide deaths with the identified rare variants. These findings suggest an important role for rare variants in suicide risk and implicate genes and gene pathways for targeted replication.

Genetic contributions to suicidal thoughts and behaviors.

Suicidal ideation, suicide attempt (SA) and suicide are significantly heritable phenotypes. However, the extent to which these phenotypes share genetic architecture is unclear. This question is of great relevance to determining key risk factors for suicide, and to alleviate the societal burden of suicidal thoughts and behaviors (STBs). To help address the question of heterogeneity, consortia efforts have recently shifted from a focus on suicide within the context of major psychopathology (e.g. major depressive disorder, schizophrenia) to suicide as an independent entity. Recent molecular studies of suicide risk by members of the Psychiatric Genomics Consortium and the International Suicide Genetics Consortium have identified genome-wide significant loci associated with SA and with suicide death, and have examined these phenotypes within and outside of the context of major psychopathology. This review summarizes important insights from epidemiological and biometrical research on suicide, and discusses key empirical findings from molecular genetic examinations of STBs. Polygenic risk scores for these phenotypes have been observed to be associated with case-control status and other risk phenotypes. In addition, estimated shared genetic covariance with other phenotypes suggests specific medical and psychiatric risks beyond major depressive disorder. Broadly, molecular studies suggest a complexity of suicide etiology that cannot simply be accounted for by depression. Discussion of the state of suicide genetics, a growing field, also includes important ethical and clinical implications of studying the genetic risk of suicide.

Genome-Wide Association Study of Suicide Death and Polygenic Prediction of Clinical Antecedents.

OBJECTIVE: Death by suicide is a highly preventable yet growing worldwide health crisis. To date, there has been a lack of adequately powered genomic studies of suicide, with no sizable suicide death cohorts available for analysis. To address this limitation, the authors conducted the first comprehensive genomic analysis of suicide death using previously unpublished genotype data from a large population-ascertained cohort. METHODS: The analysis sample comprised 3,413 population-ascertained case subjects of European ancestry and 14,810 ancestrally matched control subjects. Analytical methods included principal component analysis for ancestral matching and adjusting for population stratification, linear mixed model genome-wide association testing (conditional on genetic-relatedness matrix), gene and gene set-enrichment testing, and polygenic score analyses, as well as single-nucleotide polymorphism (SNP) heritability and genetic correlation estimation using linkage disequilibrium score regression. RESULTS: Genome-wide association analysis identified two genome-wide significant loci (involving six SNPs: rs34399104, rs35518298, rs34053895, rs66828456, rs35502061, and rs35256367). Gene-based analyses implicated 22 genes on chromosomes 13, 15, 16, 17, and 19 (q<0.05). Suicide death heritability was estimated at an h2SNP value of 0.25 (SE=0.04) and a value of 0.16 (SE=0.02) when converted to a liability scale. Notably, suicide polygenic scores were significantly predictive across training and test sets. Polygenic scores for several other psychiatric disorders and psychological traits were also predictive, particularly scores for behavioral disinhibition and major depressive disorder. CONCLUSIONS: Multiple genome-wide significant loci and genes were identified and polygenic score prediction of suicide death case-control status was demonstrated, adjusting for ancestry, in independent training and test sets. Additionally, the suicide death sample was found to have increased genetic risk for behavioral disinhibition, major depressive disorder, depressive symptoms, autism spectrum disorder, psychosis, and alcohol use disorder compared with the control sample.

Brief Report: Genetic Links Between Autism and Suicidal Behavior-A Preliminary Investigation.

Evidence suggests there may be increased risk for suicidal behavior among individuals with autism spectrum disorder (ASD). An emerging body of research explores social factors that may contribute to increased risk, however little is known about the potential role of biological factors. The current project addresses this knowledge gap through a preliminary study of genes associated with both ASD and suicidal behavior. Gene set enrichment tests of eight genes strongly associated with both ASD and suicidal behavior revealed overrepresentation of nine biological processes, including cognition and synapse function, and 14 cellular components, including the neuron, the synapse, and the synaptic and postsynaptic membrane. These results can be used to inform future investigations of the biological underpinnings of suicidal behavior and ASD.

Genome-wide significant regions in 43 Utah high-risk families implicate multiple genes involved in risk for completed suicide.

Suicide is the 10th leading cause of death in the United States. Although environment has undeniable impact, evidence suggests that genetic factors play a significant role in completed suicide. We linked a resource of ~ 4500 DNA samples from completed suicides obtained from the Utah Medical Examiner to genealogical records and medical records data available on over eight million individuals. This linking has resulted in the identification of high-risk extended families (7-9 generations) with significant familial risk of completed suicide. Familial aggregation across distant relatives minimizes effects of shared environment, provides more genetically homogeneous risk groups, and magnifies genetic risks through familial repetition. We analyzed Illumina PsychArray genotypes from suicide cases in 43 high-risk families, identifying 30 distinct shared genomic segments with genome-wide evidence (p = 2.02E-07-1.30E-18) of segregation with completed suicide. The 207 genes implicated by the shared regions provide a focused set of genes for further study; 18 have been previously associated with suicide risk. Although PsychArray variants do not represent exhaustive variation within the 207 genes, we investigated these for specific segregation within the high-risk families, and for association of variants with predicted functional impact in ~ 1300 additional Utah suicides unrelated to the discovery families. None of the limited PsychArray variants explained the high-risk family segregation; sequencing of these regions will be needed to discover segregating risk variants, which may be rarer or regulatory. However, additional association tests yielded four significant PsychArray variants (SP110, rs181058279; AGBL2, rs76215382; SUCLA2, rs121908538; APH1B, rs745918508), raising the likelihood that these genes confer risk of completed suicide.

Contrasting effects of host tree isolation on population connectedness in two tropical epiphytic bromeliads.

PREMISE: Conversion of primary forests to pastures is a major cause of habitat fragmentation in the tropics. Fragmentation is expected to impede gene flow for many plant species that are restricted to remaining forest fragments. Epiphytes may be especially vulnerable to this effect of forest fragmentation because they depend on host trees. However, trees that remain in pastures may enhance connectivity across the landscape for epiphyte species that can thrive on such trees. To investigate this possibility, we studied the genetic structures of two such species on isolated pasture trees and surrounding forest, in relation to their local abundances in different habitat types and aspects of their reproductive biology including pollen and seed dispersal agents, and looked for evidence of increased or diminished gene flow. METHODS: We used microsatellite markers to assess geographic patterns of genetic diversity and differentiation in two epiphytic bromeliads, Catopsis nitida and Werauhia tonduziana, in the Monteverde region of Costa Rica. RESULTS: About 85% of the FST value for Catopsis nitida was found among pastures within regions, while for Weruahia tonduziana, about 80% of the FST value was contributed by differences between regions, indicating much more gene flow within regions, relative to C. nitida. CONCLUSIONS: Although there was substantial genetic differentiation among epiphyte populations, those on isolated pasture trees were not substantially less diverse than those in adjacent forests, suggesting that pasture trees may serve as "stepping stones" that help these species maintain their genetic connectedness and diversity at larger geographic scales.

Polygenic risk scoring and prediction of mental health outcomes.

Psychiatric conditions are highly polygenic, meaning that genetic risk arises from many hundreds or thousands of genetic variants. Psychiatric genomics and psychological science are increasingly using polygenic risk scoring-the integration of all common genetic variant effects into a single risk metric-to model latent risk and to predict mental health outcomes. This review discusses the use of these scores in psychology and psychiatry to date, important methodological considerations, and potential of scoring methods for informing psychological science. Polygenic risk scores can easily be added to environmental and behavioral genetic models of latent risk, making them desirable metrics for use in psychological research.

Phoretic dispersal influences parasite population genetic structure.

Dispersal is a fundamental component of the life history of most species. Dispersal influences fitness, population dynamics, gene flow, genetic drift and population genetic structure. Even small differences in dispersal can alter ecological interactions and trigger an evolutionary cascade. Linking such ecological processes with evolutionary patterns is difficult, but can be carried out in the proper comparative context. Here, we investigate how differences in phoretic dispersal influence the population genetic structure of two different parasites of the same host species. We focus on two species of host-specific feather lice (Phthiraptera: Ischnocera) that co-occur on feral rock pigeons (Columba livia). Although these lice are ecologically very similar, "wing lice" (Columbicola columbae) disperse phoretically by "hitchhiking" on pigeon flies (Diptera: Hippoboscidae), while "body lice" (Campanulotes compar) do not. Differences in the phoretic dispersal of these species are thought to underlie observed differences in host specificity, as well as the degree of host-parasite cospeciation. These ecological and macroevolutionary patterns suggest that body lice should exhibit more genetic differentiation than wing lice. We tested this prediction among lice on individual birds and among lice on birds from three pigeon flocks. We found higher levels of genetic differentiation in body lice compared to wing lice at two spatial scales. Our results indicate that differences in phoretic dispersal can explain microevolutionary differences in population genetic structure and are consistent with macroevolutionary differences in the degree of host-parasite cospeciation.

Host and parasite morphology influence congruence between host and parasite phylogenies.

Comparisons of host and parasite phylogenies often show varying degrees of phylogenetic congruence. However, few studies have rigorously explored the factors driving this variation. Multiple factors such as host or parasite morphology may govern the degree of phylogenetic congruence. An ideal analysis for understanding the factors correlated with congruence would focus on a diverse host-parasite system for increased variation and statistical power. In this study, we focused on the Brueelia-complex, a diverse and widespread group of feather lice that primarily parasitise songbirds. We generated a molecular phylogeny of the lice and compared this tree with a phylogeny of their avian hosts. We also tested for the contribution of each host-parasite association to the overall congruence. The two trees overall were significantly congruent, but the contribution of individual associations to this congruence varied. To understand this variation, we developed a novel approach to test whether host, parasite or biogeographic factors were statistically associated with patterns of congruence. Both host plumage dimorphism and parasite ecomorphology were associated with patterns of congruence, whereas host body size, other plumage traits and biogeography were not. Our results lay the framework for future studies to further elucidate how these factors influence the process of host-parasite coevolution.