Epidemiologic association and shared genetic architecture between cataract and hearing difficulties among middle-aged and older adults.

Age-related cataract and hearing difficulties are major sensory disorders that often co-exist in the global-wide elderly and have a tangible influence on the quality of life. However, the epidemiologic association between cataract and hearing difficulties remains unexplored, while little is known about whether the two share their genetic etiology. We first investigated the clinical association between cataract and hearing difficulties using the UK Biobank covering 502,543 individuals. Both unmatched analysis (adjusted for confounders) and a matched analysis (one control matched for each patient with cataract according to confounding factors) were undertaken and confirmed that cataract was associated with hearing difficulties (OR, 2.12; 95% CI, 1.98-2.27; OR, 2.03; 95% CI, 1.86-2.23, respectively). Furthermore, we explored and quantified the shared genetic architecture of these two complex sensory disorders at the common variant level using the bivariate causal mixture model (MiXeR) and conditional/conjunctional false discovery rate method based on the largest available genome-wide association studies of cataract (N = 585,243) and hearing difficulties (N = 323,978). Despite detecting only a negligible genetic correlation, we observe polygenic overlap between cataract and hearing difficulties and identify 6 shared loci with mixed directions of effects. Follow-up analysis of the shared loci implicates candidate genes QKI, STK17A, TYR, NSF, and TCF4 likely contribute to the pathophysiology of cataracts and hearing difficulties. In conclusion, this study demonstrates the presence of epidemiologic association between cataract and hearing difficulties and provides new insights into the shared genetic architecture of these two disorders at the common variant level.

Genetic insights into Cyphocharax magdalenae (Characiformes: Curimatidae): Microsatellite loci development and population analysis in the Cauca River, Colombia.

Cyphocharax magdalenae, a Colombian freshwater fish species, plays a vital role in nutrients distribution and serves as a significant food source for other fish species and local fishing communities. Considered a short-distance migratory species, C. magdalenae populations face substantial extinction risk due to human activities impacting their habitats. To address the lack of knowledge on genetic diversity and population structure, this study used next-generation sequencing technology to develop species-specific microsatellite loci and conducted a population genetics analysis of C. magdalenae in the middle and lower sections of the Cauca River, Colombia. Out of 30 pairs of microsatellite primers evaluated in 324 individuals, 14 loci were found to be polymorphic, at linkage equilibrium and, in at least one population, their genotypic frequencies were in Hardy-Weinberg equilibrium. Results showed high genetic diversity levels compared to other neotropical Characiformes, with inbreeding coefficients similar to those reported for phylogenetically related species. Moreover, C. magdalenae exhibits seasonal population structure (rainy-dry) consisting of two genetic stocks showing bottleneck signals and high effective population sizes. This information is essential for understanding the current species genetics and developing future management programs for this fishery resource.

Unsupervised deep representation learning enables phenotype discovery for genetic association studies of brain imaging.

Understanding the genetic architecture of brain structure is challenging, partly due to difficulties in designing robust, non-biased descriptors of brain morphology. Until recently, brain measures for genome-wide association studies (GWAS) consisted of traditionally expert-defined or software-derived image-derived phenotypes (IDPs) that are often based on theoretical preconceptions or computed from limited amounts of data. Here, we present an approach to derive brain imaging phenotypes using unsupervised deep representation learning. We train a 3-D convolutional autoencoder model with reconstruction loss on 6130 UK Biobank (UKBB) participants' T1 or T2-FLAIR (T2) brain MRIs to create a 128-dimensional representation known as Unsupervised Deep learning derived Imaging Phenotypes (UDIPs). GWAS of these UDIPs in held-out UKBB subjects (n = 22,880 discovery and n = 12,359/11,265 replication cohorts for T1/T2) identified 9457 significant SNPs organized into 97 independent genetic loci of which 60 loci were replicated. Twenty-six loci were not reported in earlier T1 and T2 IDP-based UK Biobank GWAS. We developed a perturbation-based decoder interpretation approach to show that these loci are associated with UDIPs mapped to multiple relevant brain regions. Our results established unsupervised deep learning can derive robust, unbiased, heritable, and interpretable brain imaging phenotypes.

Novel genetic loci of inhibitory control in ADHD and healthy children and genetic correlations with ADHD.

Cumulative evidence has showed the deficits of inhibitory control in patients with attention deficit hyperactivity disorder (ADHD), which is considered as an endophenotype of ADHD. Genetic study of inhibitory control could advance gene discovery and further facilitate the understanding of ADHD genetic basis, but the studies were limited in both the general population and ADHD patients. To reveal genetic risk variants of inhibitory control and its potential genetic relationship with ADHD, we conducted genome-wide association studies (GWAS) on inhibitory control using three datasets, which included 783 and 957 ADHD patients and 1350 healthy children. Subsequently, we employed polygenic risk scores (PRS) to explore the association of inhibitory control with ADHD and related psychiatric disorders. Firstly, we identified three significant loci for inhibitory control in the healthy dataset, two loci in the case dataset, and one locus in the meta-analysis of three datasets. Besides, we found more risk genes and variants by applying transcriptome-wide association study (TWAS) and conditional FDR method. Then, we constructed a network by connecting the genes identified in our study, leading to the identification of several vital genes. Lastly, we identified a potential relationship between inhibitory control and ADHD and autism by PRS analysis and found the direct and mediated contribution of the identified genetic loci on ADHD symptoms by mediation analysis. In conclusion, we revealed some genetic risk variants associated with inhibitory control and elucidated the benefit of inhibitory control as an endophenotype, providing valuable insights into the mechanisms underlying ADHD.

Genome wide association study in Swedish Labrador retrievers identifies genetic loci associated with hip dysplasia and body weight.

Genome wide association studies (GWAS) have been utilized to identify genetic risk loci associated with both simple and complex inherited disorders. Here, we performed a GWAS in Labrador retrievers to identify genetic loci associated with hip dysplasia and body weight. Hip dysplasia scores were available for 209 genotyped dogs. We identified a significantly associated locus for hip dysplasia on chromosome 24, with three equally associated SNPs (p = 4.3 × 10-7) in complete linkage disequilibrium located within NDRG3, a gene which in humans has been shown to be differentially expressed in osteoarthritic joint cartilage. Body weight, available for 85 female dogs, was used as phenotype for a second analysis. We identified two significantly associated loci on chromosome 10 (p = 4.5 × 10-7) and chromosome 31 (p = 2.5 × 10-6). The most associated SNPs within these loci were located within the introns of the PRKCE and CADM2 genes, respectively. PRKCE has been shown to play a role in regulation of adipogenesis whilst CADM2 has been associated with body weight in multiple human GWAS. In summary, we identified credible candidate loci explaining part of the genetic inheritance for hip dysplasia and body weight in Labrador retrievers with strong candidate genes in each locus previously implicated in the phenotypes investigated.

Genetic Loci of Plant Pathogenic Dickeya solani IPO 2222 Expressed in Contact with Weed-Host Bittersweet Nightshade (Solanum dulcamara L.) Plants.

Dickeya solani, belonging to the Soft Rot Pectobacteriaceae, are aggressive necrotrophs, exhibiting both a wide geographic distribution and a wide host range that includes many angiosperm orders, both dicot and monocot plants, cultivated under all climatic conditions. Little is known about the infection strategies D. solani employs to infect hosts other than potato (Solanum tuberosum L.). Our earlier study identified D. solani Tn5 mutants induced exclusively by the presence of the weed host S. dulcamara. The current study assessed the identity and virulence contribution of the selected genes mutated by the Tn5 insertions and induced by the presence of S. dulcamara. These genes encode proteins with functions linked to polyketide antibiotics and polysaccharide synthesis, membrane transport, stress response, and sugar and amino acid metabolism. Eight of these genes, encoding UvrY (GacA), tRNA guanosine transglycosylase Tgt, LPS-related WbeA, capsular biosynthesis protein VpsM, DltB alanine export protein, glycosyltransferase, putative transcription regulator YheO/PAS domain-containing protein, and a hypothetical protein, were required for virulence on S. dulcamara plants. The implications of D. solani interaction with a weed host, S. dulcamara, are discussed.

Multiple genetic loci influence vaccine-induced protection against Mycobacterium tuberculosis in genetically diverse mice.

Mycobacterium tuberculosis (M.tb.) infection leads to over 1.5 million deaths annually, despite widespread vaccination with BCG at birth. Causes for the ongoing tuberculosis endemic are complex and include the failure of BCG to protect many against progressive pulmonary disease. Host genetics is one of the known factors implicated in susceptibility to primary tuberculosis, but less is known about the role that host genetics plays in controlling host responses to vaccination against M.tb. Here, we addressed this gap by utilizing Diversity Outbred (DO) mice as a small animal model to query genetic drivers of vaccine-induced protection against M.tb. DO mice are a highly genetically and phenotypically diverse outbred population that is well suited for fine genetic mapping. Similar to outcomes in people, our previous studies demonstrated that DO mice have a wide range of disease outcomes following BCG vaccination and M.tb. challenge. In the current study, we used a large population of BCG-vaccinated/M.tb.-challenged mice to perform quantitative trait loci mapping of complex infection traits; these included lung and spleen M.tb. burdens, as well as lung cytokines measured at necropsy. We found sixteen chromosomal loci associated with complex infection traits and cytokine production. QTL associated with bacterial burdens included a region encoding major histocompatibility antigens that are known to affect susceptibility to tuberculosis, supporting validity of the approach. Most of the other QTL represent novel associations with immune responses to M.tb. and novel pathways of cytokine regulation. Most importantly, we discovered that protection induced by BCG is a multigenic trait, in which genetic loci harboring functionally-distinct candidate genes influence different aspects of immune responses that are crucial collectively for successful protection. These data provide exciting new avenues to explore and exploit in developing new vaccines against M.tb.

Hybrid Mimulus flowers attract a new pollinator.

Hybridization is common in flowering plants and is believed to be an important force driving adaptation and speciation. The flowers of hybrids often exhibit new trait combinations, which, theoretically, could attract new species of pollinators. In this study, we found that the hybrids between a hummingbird-pollinated species Mimulus cardinalis and a self-pollinated species Mimulus parishii attract bumblebees (Bombus impatiens), a pollinator not attracted to either of the progenitor species. This novel attraction is explained by new combinations of floral traits in hybrids, including, most importantly, petal color, in addition to nectar concentration and corolla size. To understand how petal color variation is perceived by bumblebees, we performed reflectance spectroscopy and multispectral imaging to model the flower appearance in bee vision. This analysis showed that color variation would impact the ease of detection. We also found that YUP, the genetic locus responsible for a large portion of floral color variation and previously shown to be important in bee interactions with other Mimulus species, also played an important role in this novel attraction. These results together suggest that the attraction of new pollinators to hybrid plants could be an underexplored avenue for pollinator shift and speciation.

Chromosomal mapping of a major genetic locus from Agropyron cristatum chromosome 6P that influences grain number and spikelet number in wheat.

KEY MESSAGE: A novel locus on Agropyron cristatum chromosome 6P that increases grain number and spikelet number was identified in wheat-A. cristatum derivatives and across 3 years. Agropyron cristatum (2n = 4x = 28, PPPP), which has the characteristics of high yield with multiple flowers and spikelets, is a promising gene donor for wheat high-yield improvement. Identifying the genetic loci and genes that regulate yield could elucidate the genetic variations in yield-related traits and provide novel gene sources and insights for high-yield wheat breeding. In this study, cytological analysis and molecular marker analysis revealed that del10a and del31a were wheat-A. cristatum chromosome 6P deletion lines. Notably, del10a carried a segment of the full 6PS and 6PL bin (1-13), while del31a carried a segment of the full 6PS and 6PL bin (1-8). The agronomic characterization and genetic population analysis confirmed that the 6PL bin (9-13) brought about an increase in grain number per spike (average increase of 10.43 grains) and spikelet number per spike (average increase of 3.67) over the three growing seasons. Furthermore, through resequencing, a multiple grain number locus was mapped to the physical interval of 593.03-713.89 Mb on chromosome 6P of A. cristatum Z559. The RNA-seq analysis revealed the expression of 537 genes in the del10a young spike tissue, with the annotation indicating that 16 of these genes were associated with grain number and spikelet number. Finally, a total of ten A. cristatum-specific molecular markers were developed for this interval. In summary, this study presents novel genetic material that is useful for high-yield wheat breeding initiatives to meet the challenge of global food security through enhanced agricultural production.

Relationship between stress and coronary artery disease: A comprehensive review.

Coronary artery disease (CAD) poses a substantial public health challenge. This review examines the intricate relationship between psychological stress and CAD, drawing from recent research spanning the last 5 to 10 years. The literature review is organized around critical themes. It includes an analysis of genetic loci in CAD susceptibility and underscores the role of green environments in reducing cardiovascular risk. A quantitative analysis presents numerical findings for clarity, while pathophysiological mechanisms are elucidated through informative figures and diagrams. The review engages with controversies and disparities in the literature, offering a balanced perspective. A tabular comparative analysis outlines the strengths and limitations of existing approaches, emphasizing conflicting findings, and environmental factors. The review concludes by distilling key takeaways for healthcare professionals and researchers. Practical implications are explored, and lessons learned from the research process are reflected upon. The conclusion also suggests avenues for further study in understanding stress's impact on CAD.

Shared genetic architecture between hypothyroidism and rheumatoid arthritis: A large-scale cross-trait analysis.

BACKGROUND: In recent years, mounting evidence has indicated a co-morbid relationship between hypothyroidism and rheumatoid arthritis (RA), however, the shared genetic factors underlying this association remain unclear. This study aims to investigate the common genetic architecture between hypothyroidism and RA. METHODS: Genome-wide association study (GWAS) summary statistics from recently published studies were utilized to examine the genetic correlation, shared genetic loci, and potential causal relationship between hypothyroidism and RA. Statistical methods included linkage disequilibrium score regression (LDSC), high-definition likelihood (HDL), cross-trait meta-analyses, colocalization analysis, multi-marker analysis of genomic annotation (MAGMA), tissue-specific enrichment analysis (TSEA), functional enrichment analysis, and latent causal variable method (LCV). RESULTS: Our study demonstrated a significant genetic correlation between hypothyroidism and RA(LDSC:rg=0.3803,p=7.23e-11;HDL:rg=0.3849,p=1.02e-21). Through cross-trait meta-analysis, we identified 1035 loci, including 43 novel genetic loci. By integrating colocalization analysis and the MAGMA algorithm, we found a substantial number of genes, such as PTPN22, TYK2, and CTLA-4, shared between the two diseases, which showed significant enrichment across 14 tissues. These genes were primarily associated with the regulation of alpha-beta T cell proliferation, positive regulation of T cell activation, positive regulation of leukocyte cell-cell adhesion, T cell receptor signaling pathway, and JAK-STAT signaling pathway. However, our study did not reveal a significant causal association between the two diseases using the LCV approach. CONCLUSION: Based on these findings, there is a significant genetic correlation between hypothyroidism and RA, suggesting a shared genetic basis for these conditions.

Integrative analysis of noncoding mutations identifies the druggable genome in preterm birth.

Preterm birth affects ~10% of pregnancies in the US. Despite familial associations, identifying at-risk genetic loci has been challenging. We built deep learning and graphical models to score mutational effects at base resolution via integrating the pregnant myometrial epigenome and large-scale patient genomes with spontaneous preterm birth (sPTB) from European and African American cohorts. We uncovered previously unidentified sPTB genes that are involved in myometrial muscle relaxation and inflammatory responses and that are regulated by the progesterone receptor near labor onset. We studied genomic variants in these genes in our recruited pregnant women administered progestin prophylaxis. We observed that mutation burden in these genes was predictive of responses to progestin treatment for preterm birth. To advance therapeutic development, we screened ~4000 compounds, identified candidate molecules that affect our identified genes, and experimentally validated their therapeutic effects on regulating labor. Together, our integrative approach revealed the druggable genome in preterm birth and provided a generalizable framework for studying complex diseases.

Nuclear and mitochondrial genetic variants associated with mitochondrial DNA copy number.

Mitochondrial DNA copy number (mtDNA-CN) is a biomarker for mitochondrial dysfunction associated with several diseases. Previous genome-wide association studies (GWAS) have been performed to unravel underlying mechanisms of mtDNA-CN regulation. However, the identified gene regions explain only a small fraction of mtDNA-CN variability. Most of this data has been estimated from microarrays based on various pipelines. In the present study we aimed to (1) identify genetic loci for qPCR-measured mtDNA-CN from three studies (16,130 participants) using GWAS, (2) identify potential systematic differences between our qPCR derived mtDNA-CN measurements compared to the published microarray intensity-based estimates, and (3) disentangle the nuclear from mitochondrial regulation of the mtDNA-CN phenotype. We identified two genome-wide significant autosomal loci associated with qPCR-measured mtDNA-CN: at HBS1L (rs4895440, p = 3.39 × 10-13) and GSDMA (rs56030650, p = 4.85 × 10-08) genes. Moreover, 113/115 of the previously published SNPs identified by microarray-based analyses were significantly equivalent with our findings. In our study, the mitochondrial genome itself contributed only marginally to mtDNA-CN regulation as we only detected a single rare mitochondrial variant associated with mtDNA-CN. Furthermore, we incorporated mitochondrial haplogroups into our analyses to explore their potential impact on mtDNA-CN. However, our findings indicate that they do not exert any significant influence on our results.

A genome-wide association meta-analysis implicates Hedgehog and Notch signaling in Dupuytren's disease.

Dupuytren's disease (DD) is a highly heritable fibrotic disorder of the hand with incompletely understood etiology. A number of genetic loci, including Wnt signaling members, have been previously identified. Our overall aim was to identify novel genetic loci, to prioritize genes within the loci for functional studies, and to assess genetic correlation with associated disorders. We performed a meta-analysis of six DD genome-wide association studies from three European countries and extensive bioinformatic follow-up analyses. Leveraging 11,320 cases and 47,023 controls, we identified 85 genome-wide significant single nucleotide polymorphisms in 56 loci, of which 11 were novel, explaining 13.3-38.1% of disease variance. Gene prioritization implicated the Hedgehog and Notch signaling pathways. We also identified a significant genetic correlation with frozen shoulder. The pathways identified highlight the potential for new therapeutic targets and provide a basis for additional mechanistic studies for a common disorder that can severely impact hand function.

The selection landscape and genetic legacy of ancient Eurasians.

The Holocene (beginning around 12,000 years ago) encompassed some of the most significant changes in human evolution, with far-reaching consequences for the dietary, physical and mental health of present-day populations. Using a dataset of more than 1,600 imputed ancient genomes1, we modelled the selection landscape during the transition from hunting and gathering, to farming and pastoralism across West Eurasia. We identify key selection signals related to metabolism, including that selection at the FADS cluster began earlier than previously reported and that selection near the LCT locus predates the emergence of the lactase persistence allele by thousands of years. We also find strong selection in the HLA region, possibly due to increased exposure to pathogens during the Bronze Age. Using ancient individuals to infer local ancestry tracts in over 400,000 samples from the UK Biobank, we identify widespread differences in the distribution of Mesolithic, Neolithic and Bronze Age ancestries across Eurasia. By calculating ancestry-specific polygenic risk scores, we show that height differences between Northern and Southern Europe are associated with differential Steppe ancestry, rather than selection, and that risk alleles for mood-related phenotypes are enriched for Neolithic farmer ancestry, whereas risk alleles for diabetes and Alzheimer's disease are enriched for Western hunter-gatherer ancestry. Our results indicate that ancient selection and migration were large contributors to the distribution of phenotypic diversity in present-day Europeans.

GWAS for systemic sclerosis identifies six novel susceptibility loci including one in the Fcγ receptor region.

Here we report the largest Asian genome-wide association study (GWAS) for systemic sclerosis performed to date, based on data from Japanese subjects and comprising of 1428 cases and 112,599 controls. The lead SNP is in the FCGR/FCRL region, which shows a penetrating association in the Asian population, while a complete linkage disequilibrium SNP, rs10917688, is found in a cis-regulatory element for IRF8. IRF8 is also a significant locus in European GWAS for systemic sclerosis, but rs10917688 only shows an association in the presence of the risk allele of IRF8 in the Japanese population. Further analysis shows that rs10917688 is marked with H3K4me1 in primary B cells. A meta-analysis with a European GWAS detects 30 additional significant loci. Polygenic risk scores constructed with the effect sizes of the meta-analysis suggest the potential portability of genetic associations beyond populations. Prioritizing the top 5% of SNPs of IRF8 binding sites in B cells improves the fitting of the polygenic risk scores, underscoring the roles of B cells and IRF8 in the development of systemic sclerosis. The results also suggest that systemic sclerosis shares a common genetic architecture across populations.

Genome-wide association study suggests genetic candidate loci of insulin dysregulation in Finnhorses.

Equine metabolic syndrome (EMS) is a common welfare problem in horses worldwide. It is characterized by insulin dysregulation (ID), predisposition to laminitis and often obesity. EMS is multifactorial by nature, with both the environment and genetics contributing to the phenotype. Environmental factors, such as feeding and exercise, can be controlled, thus forming the basis for treatment and prevention. Genetic factors, by contrast, are less well-known and not easily controllable. The aim of this study was to identify potential genetic loci influencing ID/EMS in Finnhorses. A single-breed (Finnhorse) case-control genome-wide association study (GWAS) of ID was conducted with controls that included age-appropriate non-ID horses. ID status was determined with an oral sugar test (OST) for fasted horses. Seventy-one Finnhorses participated (n = 34 ID, n = 37 control). DNA samples (hair roots) were genotyped for 65 157 single-nucleotide polymorphisms (SNPs) with the Illumina Equine SNP70 BeadChip, and these data were analysed for association and FST outliers with genomic tools. P-values that exceeded the suggestive threshold (P = 1.00 ×10-5) were found in SNP BIEC2_383954 (P = 3.45 ×10-6) in chromosome 17 and SNP BIEC2_312374 (P = 1.89 ×10-5) in chromosome 15. Hierarchical and Bayesian FST outlier tests also detected these SNPs. Potential candidate genes associated with the ID close to SNP BIEC2_383954, with functions in carbohydrate metabolism, were Arginine and Glutamate Rich 1 (ARGLU1) and Ephrin-B2 (EFNB2).

Protein interaction networks in the vasculature prioritize genes and pathways underlying coronary artery disease.

Population-based association studies have identified many genetic risk loci for coronary artery disease (CAD), but it is often unclear how genes within these loci are linked to CAD. Here, we perform interaction proteomics for 11 CAD-risk genes to map their protein-protein interactions (PPIs) in human vascular cells and elucidate their roles in CAD. The resulting PPI networks contain interactions that are outside of known biology in the vasculature and are enriched for genes involved in immunity-related and arterial-wall-specific mechanisms. Several PPI networks derived from smooth muscle cells are significantly enriched for genetic variants associated with CAD and related vascular phenotypes. Furthermore, the networks identify 61 genes that are found in genetic loci associated with risk of CAD, prioritizing them as the causal candidates within these loci. These findings indicate that the PPI networks we have generated are a rich resource for guiding future research into the molecular pathogenesis of CAD.

TADB 3.0: an updated database of bacterial toxin-antitoxin loci and associated mobile genetic elements.

TADB 3.0 (https://bioinfo-mml.sjtu.edu.cn/TADB3/) is an updated database that provides comprehensive information on bacterial types I to VIII toxin-antitoxin (TA) loci. Compared with the previous version, three major improvements are introduced: First, with the aid of text mining and manual curation, it records the details of 536 TA loci with experimental support, including 102, 403, 8, 14, 1, 1, 3 and 4 TA loci of types I to VIII, respectively; Second, by leveraging the upgraded TA prediction tool TAfinder 2.0 with a stringent strategy, TADB 3.0 collects 211 697 putative types I to VIII TA loci predicted in 34 789 completely sequenced prokaryotic genomes, providing researchers with a large-scale dataset for further follow-up analysis and characterization; Third, based on their genomic locations, relationships of 69 019 TA loci and 60 898 mobile genetic elements (MGEs) are visualized by interactive networks accessible through the user-friendly web page. With the recent updates, TADB 3.0 may provide improved in silico support for comprehending the biological roles of TA pairs in prokaryotes and their functional associations with MGEs.

Identifying risk loci for obsessive-compulsive disorder and shared genetic component with schizophrenia: A large-scale multi-trait association analysis with summary statistics.

Due to limited samples, no genetic loci have been identified for obsessive-compulsive disorder (OCD) in genome-wide association studies. Additionally, although co-morbidities between OCD and schizophrenia (SCZ) were observed, their common genetic etiology was not completely known. Here, we conducted a comprehensive investigation regarding the genetic architecture of OCD and the common genetic foundation shared by OCD and SCZ using summary statistics data (2688 cases and 7037 controls for OCD; 53,386 cases and 77,258 controls for SCZ). We discovered significant genetic correlation between OCD and SCZ (r̂g=0.296, P = 2.82 × 10-11). We then performed two multi-trait association analyses to detect OCD-associated loci and colocalization analysis to detect causal variants. Parallel gene-level analyses were also implemented. We identified 323 OCD-relevant variants located within 12 loci, with four loci shared the same causal variants between OCD and SCZ. Further, the gene-level analyses discovered 8 OCD-associated genes. Finally, multiple functional analyses at both SNP and gene levels showed that these genetic association signals had significant enrichments in the regions of left ventricle and anterior cingulate cortex, and suggested an important role of pathways involving regulation of telomere maintenance, histone phosphorylation, and GnRH secretion. Overall, this study identified new genetic loci for OCD and provided substantial evidence supporting common genetic foundation underlying OCD and SCZ. The findings advanced our understanding of genetic architecture and pathophysiology of OCD as well as shedding light on shared genetic etiology of the two disorders.