Dissecting the Causal Mechanism of X-Linked Dystonia-Parkinsonism by Integrating Genome and Transcriptome Assembly.

X-linked Dystonia-Parkinsonism (XDP) is a Mendelian neurodegenerative disease that is endemic to the Philippines and is associated with a founder haplotype. We integrated multiple genome and transcriptome assembly technologies to narrow the causal mutation to the TAF1 locus, which included a SINE-VNTR-Alu (SVA) retrotransposition into intron 32 of the gene. Transcriptome analyses identified decreased expression of the canonical cTAF1 transcript among XDP probands, and de novo assembly across multiple pluripotent stem-cell-derived neuronal lineages discovered aberrant TAF1 transcription that involved alternative splicing and intron retention (IR) in proximity to the SVA that was anti-correlated with overall TAF1 expression. CRISPR/Cas9 excision of the SVA rescued this XDP-specific transcriptional signature and normalized TAF1 expression in probands. These data suggest an SVA-mediated aberrant transcriptional mechanism associated with XDP and may provide a roadmap for layered technologies and integrated assembly-based analyses for other unsolved Mendelian disorders.

Ultrasound Blood-Brain Barrier Opening and Aducanumab in Alzheimer's Disease.

Antiamyloid antibodies have been used to reduce cerebral amyloid-beta (Aß) load in patients with Alzheimer's disease. We applied focused ultrasound with each of six monthly aducanumab infusions to temporarily open the blood-brain barrier with the goal of enhancing amyloid removal in selected brain regions in three participants over a period of 6 months. The reduction in the level of Aß was numerically greater in regions treated with focused ultrasound than in the homologous regions in the contralateral hemisphere that were not treated with focused ultrasound, as measured by fluorine-18 florbetaben positron-emission tomography. Cognitive tests and safety evaluations were conducted over a period of 30 to 180 days after treatment. (Funded by the Harry T. Mangurian, Jr. Foundation and the West Virginia University Rockefeller Neuroscience Institute.).

TWO-SIGMA-G: a new competitive gene set testing framework for scRNA-seq data accounting for inter-gene and cell-cell correlation.

We propose TWO-SIGMA-G, a competitive gene set test for scRNA-seq data. TWO-SIGMA-G uses a mixed-effects regression model based on our previously published TWO-SIGMA to test for differential expression at the gene-level. This regression-based model provides flexibility and rigor at the gene-level in (1) handling complex experimental designs, (2) accounting for the correlation between biological replicates and (3) accommodating the distribution of scRNA-seq data to improve statistical inference. Moreover, TWO-SIGMA-G uses a novel approach to adjust for inter-gene-correlation (IGC) at the set-level to control the set-level false positive rate. Simulations demonstrate that TWO-SIGMA-G preserves type-I error and increases power in the presence of IGC compared with other methods. Application to two datasets identified HIV-associated interferon pathways in xenograft mice and pathways associated with Alzheimer's disease progression in humans.

Pleiotropic loci for cannabis use disorder severity in multi-ancestry high-risk populations.

Cannabis use disorder (CUD) is common and has in part a genetic basis. The risk factors underlying its development likely involve multiple genes that are polygenetic and interact with each other and the environment to ultimately lead to the disorder. Co-morbidity and genetic correlations have been identified between CUD and other disorders and traits in select populations primarily of European descent. If two or more traits, such as CUD and another disorder, are affected by the same genetic locus, they are said to be pleiotropic. The present study aimed to identify specific pleiotropic loci for the severity level of CUD in three high-risk population cohorts: American Indians (AI), Mexican Americans (MA), and European Americans (EA). Using a previously developed computational method based on a machine learning technique, we leveraged the entire GWAS catalog and identified 114, 119, and 165 potentially pleiotropic variants for CUD severity in AI, MA, and EA respectively. Ten pleiotropic loci were shared between the cohorts although the exact variants from each cohort differed. While majority of the pleiotropic genes were distinct in each cohort, they converged on numerous enriched biological pathways. The gene ontology terms associated with the pleiotropic genes were predominately related to synaptic functions and neurodevelopment. Notable pathways included Wnt/ß-catenin signaling, lipoprotein assembly, response to UV radiation, and components of the complement system. The pleiotropic genes were the most significantly differentially expressed in frontal cortex and coronary artery, up-regulated in adipose tissue, and down-regulated in testis, prostate, and ovary. They were significantly up-regulated in most brain tissues but were down-regulated in the cerebellum and hypothalamus. Our study is the first to attempt a large-scale pleiotropy detection scan for CUD severity. Our findings suggest that the different population cohorts may have distinct genetic factors for CUD, however they share pleiotropic genes from underlying pathways related to Alzheimer's disease, neuroplasticity, immune response, and reproductive endocrine systems.

SMNN: batch effect correction for single-cell RNA-seq data via supervised mutual nearest neighbor detection.

Batch effect correction has been recognized to be indispensable when integrating single-cell RNA sequencing (scRNA-seq) data from multiple batches. State-of-the-art methods ignore single-cell cluster label information, but such information can improve the effectiveness of batch effect correction, particularly under realistic scenarios where biological differences are not orthogonal to batch effects. To address this issue, we propose SMNN for batch effect correction of scRNA-seq data via supervised mutual nearest neighbor detection. Our extensive evaluations in simulated and real datasets show that SMNN provides improved merging within the corresponding cell types across batches, leading to reduced differentiation across batches over MNN, Seurat v3 and LIGER. Furthermore, SMNN retains more cell-type-specific features, partially manifested by differentially expressed genes identified between cell types after SMNN correction being biologically more relevant, with precision improving by up to 841.0%.

Noninvasive prenatal exome sequencing diagnostic utility limited by sequencing depth and fetal fraction.

OBJECTIVE: Sequencing cell-free DNA now allows detection of large chromosomal abnormalities and dominant Mendelian disorders in the prenatal period. Improving upon these methods would allow newborn screening programs to begin with prenatal genetics, ultimately improving the management of rare genetic disorders. METHODS: As a pilot study, we performed exome sequencing on the cell-free DNA from three mothers with singleton pregnancies to assess the viability of broad sequencing modalities in a noninvasive prenatal setting. RESULTS: We found poor resolution of maternal and fetal genotypes due to both sampling and technical issues. CONCLUSION: We find broad sequencing modalities inefficient for noninvasive prenatal applications. Alternatively, we suggest a more targeted path forward for noninvasive prenatal genotyping.

Pre-capture multiplexing provides additional power to detect copy number variation in exome sequencing.

BACKGROUND: As exome sequencing (ES) integrates into clinical practice, we should make every effort to utilize all information generated. Copy-number variation can lead to Mendelian disorders, but small copy-number variants (CNVs) often get overlooked or obscured by under-powered data collection. Many groups have developed methodology for detecting CNVs from ES, but existing methods often perform poorly for small CNVs and rely on large numbers of samples not always available to clinical laboratories. Furthermore, methods often rely on Bayesian approaches requiring user-defined priors in the setting of insufficient prior knowledge. This report first demonstrates the benefit of multiplexed exome capture (pooling samples prior to capture), then presents a novel detection algorithm, mcCNV ("multiplexed capture CNV"), built around multiplexed capture. RESULTS: We demonstrate: (1) multiplexed capture reduces inter-sample variance; (2) our mcCNV method, a novel depth-based algorithm for detecting CNVs from multiplexed capture ES data, improves the detection of small CNVs. We contrast our novel approach, agnostic to prior information, with the the commonly-used ExomeDepth. In a simulation study mcCNV demonstrated a favorable false discovery rate (FDR). When compared to calls made from matched genome sequencing, we find the mcCNV algorithm performs comparably to ExomeDepth. CONCLUSION: Implementing multiplexed capture increases power to detect single-exon CNVs. The novel mcCNV algorithm may provide a more favorable FDR than ExomeDepth. The greatest benefits of our approach derive from (1) not requiring a database of reference samples and (2) not requiring prior information about the prevalance or size of variants.

Projected t-SNE for batch correction.

MOTIVATION: Low-dimensional representations of high-dimensional data are routinely employed in biomedical research to visualize, interpret and communicate results from different pipelines. In this article, we propose a novel procedure to directly estimate t-SNE embeddings that are not driven by batch effects. Without correction, interesting structure in the data can be obscured by batch effects. The proposed algorithm can therefore significantly aid visualization of high-dimensional data. RESULTS: The proposed methods are based on linear algebra and constrained optimization, leading to efficient algorithms and fast computation in many high-dimensional settings. Results on artificial single-cell transcription profiling data show that the proposed procedure successfully removes multiple batch effects from t-SNE embeddings, while retaining fundamental information on cell types. When applied to single-cell gene expression data to investigate mouse medulloblastoma, the proposed method successfully removes batches related with mice identifiers and the date of the experiment, while preserving clusters of oligodendrocytes, astrocytes, and endothelial cells and microglia, which are expected to lie in the stroma within or adjacent to the tumours. AVAILABILITY AND IMPLEMENTATION: Source code implementing the proposed approach is available as an R package at https://github.com/emanuelealiverti/BC_tSNE, including a tutorial to reproduce the simulation studies. CONTACT: aliverti@stat.unipd.it.

Common genetic substrates of alcohol and substance use disorder severity revealed by pleiotropy detection against GWAS catalog in two populations.

Alcohol and other substance use disorders (AUD and SUD) are complex diseases that are postulated to have a polygenic inheritance and are often comorbid with other disorders. The comorbidities may arise partially through genetic pleiotropy. Identification of specific gene variants accounting for large parts of the variance in these disorders has yet to be accomplished. We describe a flexible strategy that takes a variant-trait association database and determines if a subset of disease/straits are potentially pleiotropic with the disorder under study. We demonstrate its usage in a study of use disorders in two independent cohorts: alcohol, stimulants, cannabis (CUD), and multi-substance use disorders (MSUD) in American Indians (AI) and AUD and CUD in Mexican Americans (MA). Using a machine learning method with variants in GWAS catalog, we identified 229 to 246 pleiotropic variants for AI and 153 to 160 for MA for each SUD. Inflammation was the most enriched for MSUD and AUD in AIs. Neurological disorder was the most significantly enriched for CUD in both cohorts, and for AUD and stimulants in AIs. Of the select pleiotropic genes shared among substances-cohorts, multiple biological pathways implicated in SUD and other psychiatric disorders were enriched, including neurotrophic factors, immune responses, extracellular matrix, and circadian regulation. Shared pleiotropic genes were significantly up-regulated in brain regions playing important roles in SUD, down-regulated in esophagus mucosa, and differentially regulated in adrenal gland. This study fills a gap for pleiotropy detection in understudied admixed populations and identifies pleiotropic variants that may be potential targets of interest for SUD.

An approach to integrating exome sequencing for fetal structural anomalies into clinical practice.

PURPOSE: We investigated the diagnostic and clinical performance of trio exome sequencing (ES) in parent-fetus trios where the fetus had sonographic abnormalities but normal karyotype, microarray and, in some cases, normal gene-specific sequencing. METHODS: ES was performed from DNA of 102 anomalous fetuses and from peripheral blood from their parents. Parents provided consent for the return of diagnostic results in the fetus, medically actionable findings in the parents, and identification as carrier couple for significant autosomal recessive conditions. RESULTS: In 21/102 (20.6%) fetuses, ES provided a positive-definitive or positive-probable diagnosis. In 10/102 (9.8%), ES provided an inconclusive-possible result. At least 2/102 (2.0%) had a repeat pregnancy during the study period and used the information from the study for prenatal diagnosis in the next pregnancy. Six of 204 (2.9%) parents received medically actionable results that affected their own health and 3/102 (2.9%) of couples received results that they were carriers for the same autosomal recessive condition. CONCLUSION: ES has diagnostic utility in a select population of fetuses where a genetic diagnosis was highly suspected. Challenges related to genetics literacy, variant interpretation, and various types of diagnostic results affecting both fetal and parental health must be addressed by highly tailored pre- and post-test genetic counseling.

Correction: An approach to integrating exome sequencing for fetal structural anomalies into clinical practice.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Meta-Analysis of Genetic Influences on Initial Alcohol Sensitivity.

BACKGROUND: Previous studies indicate that low initial sensitivity to alcohol may be a risk factor for later alcohol misuse. Evidence suggests that initial sensitivity is influenced by genetic factors, but few molecular genetic studies have been reported. METHODS: We conducted a meta-analysis of 2 population-based genome-wide association studies of the Self-Rating of the Effects of Alcohol scale. Our final sample consisted of 7,339 individuals (82.3% of European descent; 59.2% female) who reported having used alcohol at least 5 times. In addition, we estimated single nucleotide polymorphism (SNP)-based heritability and conducted a series of secondary aggregate genetic analyses. RESULTS: No individual locus reached genome-wide significance. Gene and set based analyses, both overall and using tissue-specific expression data, yielded largely null results, and genes previously implicated in alcohol problems and consumption were overall not associated with initial sensitivity. Only 1 gene set, related to hormone signaling and including core clock genes, survived correction for multiple testing. A meta-analysis of SNP-based heritability resulted in a modest estimate of hSNP2  = 0.19 (SE = 0.10), though this was driven by 1 sample (N = 3,683, hSNP2  = 0.36, SE = 0.14, p = 0.04). No significant genetic correlations with other relevant outcomes were observed. CONCLUSIONS: Findings yielded only modest support for a genetic component underlying initial alcohol sensitivity. Results suggest that its biological underpinnings may diverge somewhat from that of other alcohol outcomes and may be related to core clock genes or other aspects of hormone signaling. Larger samples, ideally of prospectively assessed samples, are likely necessary to improve gene identification efforts and confirm the current findings.

Whole genome sequence study of cannabis dependence in two independent cohorts.

Recent advances in genome wide sequencing techniques and analytical methods allow for more comprehensive examinations of the genome than microarray-based genome-wide association studies (GWAS). The present report provides the first application of whole genome sequencing (WGS) to identify low frequency variants involved in cannabis dependence across two independent cohorts. The present study used low-coverage whole genome sequence data to conduct set-based association and enrichment analyses of low frequency variation in protein-coding regions as well as regulatory regions in relation to cannabis dependence. Two cohorts were studied: a population-based Native American tribal community consisting of 697 participants nested within large multi-generational pedigrees and a family-based sample of 1832 predominantly European ancestry participants largely nested within nuclear families. Participants in both samples were assessed for Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) lifetime cannabis dependence, with 168 and 241 participants receiving a positive diagnosis in each sample, respectively. Sequence kernel association tests identified one protein-coding region, C1orf110 and one regulatory region in the MEF2B gene that achieved significance in a meta-analysis of both samples. A regulatory region within the PCCB gene, a gene previously associated with schizophrenia, exhibited a suggestive association. Finally, a significant enrichment of regions within or near genes with multiple splice variants or involved in cell adhesion or potassium channel activity were associated with cannabis dependence. This initial study demonstrates the potential utility of low pass whole genome sequencing for identifying genetic variants involved in the etiology of cannabis use disorders.

Integration of expression quantitative trait loci and pleiotropy identifies a novel psoriasis susceptibility gene, PTPN1.

BACKGROUND: Psoriasis is a common inflammatory skin disease, whereas schizophrenia is a psychiatric disorder with substantial comorbidity. Although these two disorders manifest with apparently unrelated phenotypes, there is some evidence suggesting that they share common genetic factors. METHODS: We implemented a genetic analysis incorporating pleiotropy and annotation to genome-wide association summary statistics data for approximately 120 000 psoriasis and schizophrenia samples, as well as whole blood expression quantitative trait loci in 5311 samples. RESULTS: We observed a significant pleiotropic effect between psoriasis and schizophrenia (p = 5.92 × 10-43 ). We characterized an enrichment of whole blood expression quantitative trait loci in genome-wide association data for psoriasis and schizophrenia (q1 /q0  > 1.5, p < 10-77 ) and we revealed that common variants for both diseases were more likely to confer expression quantitative trait loci effects (q1 /q0  = 4.197, SE = 0.183). Through joint analysis of the associations in the combined psoriasis and schizophrenia data set, we identified a potential susceptibility PTPN1 gene for psoriasis, which may affect the risk of psoriasis through modulation of the function of TYK2 kinase. CONCLUSIONS: The results of the present study highlight the expression quantitative trait loci enrichment and pleiotropy in psoriasis and schizophrenia, and also suggest a possible key role of the PTPN1 gene in the etiology of psoriasis.

Prenatal exome sequencing in anomalous fetuses: new opportunities and challenges.

PurposeWe investigated the diagnostic and clinical performance of exome sequencing in fetuses with sonographic abnormalities with normal karyotype and microarray and, in some cases, normal gene-specific sequencing.MethodsExome sequencing was performed on DNA from 15 anomalous fetuses and from the peripheral blood of their parents. Parents provided consent to be informed of diagnostic results in the fetus, medically actionable findings in the parents, and their identification as carrier couples for significant autosomal recessive conditions. We assessed the perceptions and understanding of exome sequencing using mixed methods in 15 mother-father dyads.ResultsIn seven (47%) of 15 fetuses, exome sequencing provided a diagnosis or possible diagnosis with identification of variants in the following genes: COL1A1, MUSK, KCTD1, RTTN, TMEM67, PIEZO1 and DYNC2H1. One additional case revealed a de novo nonsense mutation in a novel candidate gene (MAP4K4). The perceived likelihood that exome sequencing would explain the results (5.2 on a 10-point scale) was higher than the approximately 30% diagnostic yield discussed in pretest counseling.ConclusionExome sequencing had diagnostic utility in a highly select population of fetuses where a genetic diagnosis was highly suspected. Challenges related to genetics literacy and variant interpretation must be addressed by highly tailored pre- and posttest genetic counseling.

Associations Between Genomic Variants in Alcohol Dehydrogenase Genes and Alcohol Symptomatology in American Indians and European Americans: Distinctions and Convergence.

BACKGROUND: Higher rates of alcohol use disorders (AUD) have been observed in some Native American populations than other ethnic groups such as European Americans (EAs) in the United States. Previous studies have shown that variation in the alcohol dehydrogenase (ADH) genes may affect the risk for development of AUD and that the prevalence of these variants differs depending on the ancestral origins of a population. METHODS: In this study, we assessed sequencing variants in the ADH genomic region (ADH1-7) and tested for their associations with AUD phenotypes in 2 independent populations: an American Indian (AI) community sample and an EA cohort from the San Francisco Family Alcohol Study. Association tests were conducted for both common and rare variants using sequencing data for 2 phenotypes: the number of alcohol-related life events and the count of alcohol dependence drinking symptoms. A regularized regression method was used to select the best set of ADH variants associated with phenotypes. Variance component model was incorporated in all analyses to leverage the admixture and relatedness. RESULTS: Two variants near ADH4 and 2 near ADH1C exhibited significant associations with AUD in AIs; no variant was significant in EAs. Common risk variants in AIs were either absent from or much less frequent in EAs. The feature selection method selected mostly distinct yet often colocated subsets of ADH variants to be associated with AUD phenotypes between the 2 cohorts. In the rare-variant analyses, the only association was observed between the whole region and the alcohol-related life events in AIs. CONCLUSIONS: Our results suggest that ADH variants, both common and rare, are more likely to impact risk for alcohol-related symptomatology in this AI population than in this EA sample, and ADH variants that might affect AUD are likely different but convergent on similar regions between the 2 populations.

A Novel Tobacco Use Phenotype Suggests the 15q25 and 19q13 Loci May be Differentially Associated With Cigarettes per Day and Tobacco-Related Problems.

INTRODUCTION: Tobacco use is associated with variation at the 15q25 gene cluster and the cytochrome P450 (CYP) genes CYP2A6 and CYP2B6. Despite the variety of outcomes associated with these genes, few studies have adopted a data-driven approach to defining tobacco use phenotypes for genetic association analyses. We used factor analysis to generate a tobacco use measure, explored its incremental validity over a simple indicator of tobacco involvement: cigarettes per day (CPD), and tested both phenotypes in a genetic association study. METHODS: Data were from the University of California, San Francisco Family Alcoholism Study (n = 1942) and a Native American sample (n = 255). Factor analyses employed a broad array of tobacco use variables to establish the candidate phenotype. Subsequently, we conducted tests for association with variants in the nicotinic acetylcholine receptor and CYP genes. We explored associations with CPD and our measure. We then examined whether the variants most strongly associated with our measure remained associated after controlling for CPD. RESULTS: Analyses identified one factor that captured tobacco-related problems. Variants at 15q25 were significantly associated with CPD after multiple testing correction (rs938682: p = .00002, rs1051730: p = .0003, rs16969968: p = .0003). No significant associations were obtained with the tobacco use phenotype; however, suggestive associations were observed for variants in CYP2B6 near CYP2A6 (rs45482602: ps = .0082, .0075) and CYP4Z2P (rs10749865: ps = .0098, .0079). CONCLUSIONS: CPD captures variation at 15q25. Although strong conclusions cannot be drawn, these finding suggest measuring additional dimensions of problems may detect genetic variation not accounted for by smoking quantity. Replication in independent samples will help further refine phenotype definition efforts. IMPLICATIONS: Different facets of tobacco-related problems may index unique genetic risk. CPD, a simple measure of tobacco consumption, is associated with variants at the 15q25 gene cluster. Additional dimensions of tobacco problems may help to capture variation at 19q13. Results demonstrate the utility of adopting a data-driven approach to defining phenotypes for genetic association studies of tobacco involvement and provide results that can inform replication efforts.

Genetic Complexity of Mitral Valve Prolapse Revealed by Clinical and Genetic Evaluation of a Large Family.

BACKGROUND: A genetic component to familial mitral valve prolapse (MVP) has been proposed for decades. Despite this, very few genes have been linked to MVP. Herein is described a four-generation pedigree with numerous individuals affected with severe MVP, some at strikingly young ages. METHODS: A detailed clinical evaluation performed on all affected family members demonstrated a spectrum of MVP morphologies and associated phenotypes. RESULTS: Linkage analysis failed to identify strong candidate loci, but revealed significant regions, which were investigated further using whole-exome sequencing of one of the severely affected family members. Whole-exome sequencing identified variants in this individual that fell within linkage analysis peak regions, but none was an obvious pathogenic candidate. Follow up segregation analysis of all exome-identified variants was performed to genotype other affected and unaffected individuals in the family, but no variants emerged as clear pathogenic candidates. Two notable variants of uncertain significance in candidate genes were identified: p.I1013S in PTPRJ at 11p11.2 and FLYWCH1 p.R540Q at 16p13.3. Neither gene has been previously linked to MVP in humans, although PTPRJ mutant mice display defects in endocardial cushions, which give rise to the cardiac valves. PTPRJ and FLYWCH1 expression was detected in adult human mitral valve cells, and in-silico analysis of these variants suggests they may be deleterious. However, neither variant segregated completely with all of the affected individuals in the family, particularly when 'affected' was broadly defined. CONCLUSIONS: While a contributory role for PTPRJ and FLYWCH1 in this family cannot be excluded, the study results underscored the difficulties involved in uncovering the genomic contribution to MVP, even in apparently Mendelian families.

Genome-Wide Association Study of Post-Traumatic Stress Disorder in Two High-Risk Populations.

Mexican Americans (MAs) and American Indians (AIs) constitute conspicuously understudied groups with respect to risk for post-traumatic stress disorder (PTSD), especially in light of findings showing racial/ethnic differences in trauma exposure and risk for PTSD. The purpose of this study was to examine genetic influences on PTSD in two minority cohorts. A genome-wide association study (GWAS) with sum PTSD symptoms for trauma-exposed subjects was run in each cohort. Six highly correlated variants in olfactory receptor family 11 subfamily L member 1 (OR11L1) were suggestively associated with PTSD in the MA cohort. These associations remained suggestively significant after permutation testing. A signal in a nearby olfactory receptor on chromosome 1, olfactory receptor family 2 subfamily L member 13 (OR2L13), tagged by rs151319968, was nominally associated with PTSD in the AI sample. Although no variants were significantly associated after correction for multiple testing in a meta-analysis of the two cohorts, pathway analysis of the top hits showed an enrichment cluster of terms related to sensory transduction, olfactory receptor activity, G-protein coupled receptors, and membrane. As previous studies have proposed a role for olfaction in PTSD, our results indicate this influence may be partially driven by genetic variation in the olfactory system.

Genetic Influences on Evening Preference Overlap with Those for Bipolar Disorder in a Sample of Mexican Americans and American Indians.

Diurnal preference (e.g., being an owl or lark) has been associated with several psychiatric disorders including bipolar disorder (BP), major depressive disorder, and substance use disorders. Previous large-scale genome-wide association studies (GWAS) aimed at identifying genetic influences on diurnal preference have exclusively included subjects of European ancestry. This study examined the genetic architecture of diurnal preference in two minority samples: a young adult sample of Mexican Americans (MAs), and a family-based sample of American Indians (AIs). Typed or imputed variants from exome chip data from the MA sample and low pass whole-genome sequencing from the AI cohort were analyzed using a mixed linear model approach for association with being an owl, as defined by a usual bedtime after 23:00 hrs. Genetic risk score (GRS) profiling detected shared genetic risk between evening preference and related disorders. Four variants in KIAA1549 like (KIAA1549L), a gene previously associated with attempted suicide in bipolar patients, were suggestively associated with being an owl at p < 1.82E-05; post hoc analyses showed the top variant trending in both the MA and AI cohorts at p = 2.50E-05 and p = .030, respectively. Variants associated with BP at p < .03 from the Psychiatric Genomics Consortium nominally predicted being an owl in the MA/AI cohort at p = .012. This study provides some additional evidence that genetic risk factors for BP also confer risk for being an owl in MAs/AIs and that evening preference may be a useful endophenotype for future studies of BP.