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 crossvalidated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS metaanalysis 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 &lt;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.</p

Bi-allelic loss-of-function CACNA1B mutations in progressive epilepsy-dyskinesia

The occurrence of non-epileptic hyperkinetic movements in the context of developmental epileptic encephalopathies is an increasingly recognized phenomenon. Identification of causative mutations provides an important insight into common pathogenic mechanisms that cause both seizures and abnormal motor control. We report bi-allelic loss-of-function CACNA1B variants in six children from three unrelated families whose affected members present with a complex and progressive neurological syndrome. All affected individuals presented with epileptic encephalopathy, severe neurodevelopmental delay (often with regression), and a hyperkinetic movement disorder. Additional neurological features included postnatal microcephaly and hypotonia. Five children died in childhood or adolescence (mean age of death: 9 years), mainly as a result of secondary respiratory complications. CACNA1B encodes the pore-forming subunit of the pre-synaptic neuronal voltage-gated calcium channel Cav2.2/N-type, crucial for SNARE-mediated neurotransmission, particularly in the early postnatal period. Bi-allelic loss-of-function variants in CACNA1B are predicted to cause disruption of Ca2+ influx, leading to impaired synaptic neurotransmission. The resultant effect on neuronal function is likely to be important in the development of involuntary movements and epilepsy. Overall, our findings provide further evidence for the key role of Cav2.2 in normal human neurodevelopment

Composition of woody species in a dynamic forest-woodland-savannah mosaic in Uganda: implications for conservation and management

Forest¿woodland¿savannah mosaics are a common feature in the East African landscape. For the conservation of the woody species that occur in such landscapes, the species patterns and the factors that maintain it need to be understood. We studied the woody species distribution in a forest¿woodland¿savannah mosaic in Budongo Forest Reserve, Uganda. The existing vegetation gradients were analyzed using data from a total of 591 plots of 400 or 500 m2 each. Remotely sensed data was used to explore current vegetation cover and the gradients there in for the whole area. A clear species gradient exists in the study area ranging from forest, where there is least disturbance, to wooded grassland, where frequent fire disturbance occurs. Most species are not limited to a specific part of the gradient although many show a maximum abundance at some point along the gradient. Fire and accessibility to the protected area were closely related to variation in species composition along the ordination axis with species like Cynometra alexandri and Uvariopsis congensis occurring at one end of the gradient and Combretum guenzi and Lonchocarpus laxiflorus at the other. The vegetation cover classes identified in the area differed in diversity, density and, especially, basal area. All vegetation cover classes, except open woodland, had indicator species. Diospyros abyssinica, Uvariopsis congensis, Holoptelea grandis and all Celtis species were the indicator species for the forest class, Terminalia velutina and Albizia grandbracteata for closed woodland, Grewia mollis and Combretum mole for very open woodland and Lonchocarpus laxiflorus, Grewia bicolor and Combretum guenzi for the wooded grassland class. Eleven of the species occurred in all cover classes and most of the species that occurred in more than one vegetation cover class showed peak abundance in a specific cover class. Species composition in the study area changes gradually from forest to savannah. Along the gradient, the cover classes are distinguishable in terms of species composition and vegetation structure. These classes are, however, interrelated in species composition. For conservation of the full range of the species within this East African landscape, the mosaic has to be managed as an integrated whole. Burning should be varied over the area with the forest not being burnt at all and the wooded grassland burnt regularly. The different vegetation types that occur between these two extremes should be maintained using a varied fire regim

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.National Institutes of HealthVoRSUNY DownstatePsychiatry and Behavioral SciencesInstitute for Genomics in HealthN/

Improved forest classification in the northern Lake States using multi-temporal Landsat imagery

Forest classifications using single date Landsat data have been only moderately successful in separating forest cover types in the northern Lake States region. Few regional forest classifications have been presented that achieve genus or species level accuracy. We developed a more specific forest cover classification using data from early summer in conjunction with four MSS dates to capture phenological changes of different tree species. Among the 22 forest types classified, multi-temporal image analysis aided in separating 13 types. Of greatest significance, trembling aspen, sugar maple, northern red oak, northern pin oak, black ash, and tamarack were successfully classified. The overall classification accuracy was s83.2 percent and the forest classification accuracy was 80.1 percent. This approach may be useful for broad-scale forest cover monitoring in other areas, particularly where ancillary data layers are not available