Genome-wide association analyses using machine learning-based phenotyping reveal genetic architecture of occupational creativity and overlap with psychiatric disorders.

Creativity is known to be heritable and exhibits familial aggregation with psychiatric disorders; however, the complex nature of their relationship has not been well-established. In the present study, we demonstrate that using an expanded and validated machine learning (ML)-based phenotyping of occupational creativity (OC) can allow us to further understand the trait of creativity, which was previously difficult to define and study. We conducted the largest genome-wide association study (GWAS) on OC with 241,736 participants from the UK Biobank and identified 25 lead variants that have not yet been reported and three candidate causal genes that were previously associated with educational attainment and psychiatric disorders. We found extensive genetic overlap between OC and psychiatric disorders with mixed effect direction through various post-GWAS analyses, including the bivariate causal mixture model. In addition, we discovered a strongly genetic correlation between our original GWAS and the GWAS adjusted for education years (rg = 0.95). Our GWAS analysis via ML-based phenotyping contributes to the understanding of the genetic architecture of creativity, which may inform genetic discovery and genetic prediction in human cognition and psychiatric disorders.

A new species of the genus Proutia Tutt (Lepidoptera, Psychidae) from Korea, based on morphology and DNA barcodes.

Background: The genus Proutia Tutt, 1899 (Lepidoptera, Psychidae) comprises 14 species found throughout the world. In East Asia, three species, Proutiachinensis Hättenschwiler & Chao, 1990, P.maculatella Saigusa & Sugimoto, 2014 and P.nigra Saigusa & Sugimoto, 2014, are known from Korea, Japan and China. New information: Proutiacornucervae Roh & Lee, sp. nov. is newly recognised from Korea. In addition, Bruandellaniphonica (Hori) is transferred to genus Proutia. Male and genitalia of the species are described and DNA barcodes are provided.

Leveraging genetic overlap between irritability and psychiatric disorders to identify genetic variants of major psychiatric disorders.

Irritability is a heritable core mental trait associated with several psychiatric illnesses. However, the genomic basis of irritability is unclear. Therefore, this study aimed to 1) identify the genetic variants associated with irritability and investigate the associated biological pathways, genes, and tissues as well as single-nucleotide polymorphism (SNP)-based heritability; 2) explore the relationships between irritability and various traits, including psychiatric disorders; and 3) identify additional and shared genetic variants for irritability and psychiatric disorders. We conducted a genome-wide association study (GWAS) using 379,506 European samples (105,975 cases and 273,531 controls) from the UK Biobank. We utilized various post-GWAS analyses, including linkage disequilibrium score regression, the bivariate causal mixture model (MiXeR), and conditional and conjunctional false discovery rate approaches. This GWAS identified 15 independent loci associated with irritability; the total SNP heritability estimate was 4.19%. Genetic correlations with psychiatric disorders were most pronounced for major depressive disorder (MDD) and bipolar II disorder (BD II). MiXeR analysis revealed polygenic overlap with schizophrenia (SCZ), bipolar I disorder (BD I), and MDD. Conditional false discovery rate analyses identified additional loci associated with SCZ (number [n] of additional SNPs = 105), BD I (n = 54), MDD (n = 107), and irritability (n = 157). Conjunctional false discovery rate analyses identified 85, 41, and 198 shared loci between irritability and SCZ, BD I, and MDD, respectively. Multiple genetic loci were associated with irritability and three main psychiatric disorders. Given that irritability is a cross-disorder trait, these findings may help to elucidate the genomics of psychiatric disorders.

Complete mitochondrial genome of little ringed plover Charadrius dubius (Charadriiformes, Charadriidae).

This study encoded the complete mitochondrial genomic sequence of the little ringed plover Charadrius dubius. The mitochondrial genome has a total length of 16,864 bp, consisting of 13 protein-coding genes, 22 tRNA genes, two rRNA genes, and a control region. The nucleotide composition was 23.8% T, 31.6% A, 30.8% C, and 13.8% G. This study provides the basic information on the mitogenome of C. dubius and supports the understanding of mitogenomic information and its phylogenetic relationship within Charadriiformes.

Review of the genus Meganola Dyar, 1898 (Lepidoptera: Nolidae, Nolinae) from Korea, with the description of a new species.

The genus Meganola Dyar, 1898 is reviewed for Korea, with 12 species, including the new species, Meganola parki Oh Cha, sp. n. Illustrations of adults and genitalia of all the Korean species are provided, with a key to species of Meganola based on the external morphology and male genitalia. All known host plants are provided, some of them newly recorded.

Three new species of Diduga Moore, [1887] (Lepidoptera, Erebidae, Arctiinae) from Cambodia.

Three new species of the genus Diduga, D. dubatolovi n. sp., D. kohkongensis n. sp., and D. bispinosa n. sp. are described from Cambodia along with other five recorded species, D. albicosta Hampson, 1891, D. barlowi Holloway, 2001, D. amoenusa Bucsek, 2012, D. annulata Hampson, 1900, and D. alternota Bucsek, 2014. A key to the Cambodian species of the genus Diduga with illustrations of adults and genitalia are presented.

Genus Microlithosia (Lepidoptera, Erebidae, Arctiinae) in Laos, with the description of a new species.

Microlithosia Daniel, 1954 from Laos is reviewed. A new species, Microlithosia laosana Bayarsaikhan Bae, n. sp., is described along with two newly recorded species, M. umbripuncta (de Joannis, 1928) and M. nanlingica Dubatolov, Kishida Wang, 2012. Illustrations of adults and male genitalia are provided. The checklist of the genus is updated.