Scientific highlights

DNA methylation is a central epigenetic mark that has diverse roles in gene regulation, development, and maintenance of genome integrity. 5 methyl cytosine (5mC) can be interrogated at base resolution in single cells by using bisulfite sequencing (scWGBS). Several different scWGBS strategies have been described in recent years to study DNA methylation in single cells. However, there remain limitations with respect to cost-efficiency and yield. Herein, we present a new development in the field of scWGBS library preparation; single cell Splinted Ligation Adapter Tagging (scSPLAT). scSPLAT employs a pooling strategy to facilitate sample preparation at a higher scale and throughput than previously possible. We demonstrate the accuracy and robustness of the method by generating data from 225 single K562 cells and from 309 single liver nuclei and compare scSPLAT against other scWGBS methods.

Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30-50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. We employed the Explore PEA technology for high-precision analysis of 1463 plasma proteins and conducted a discovery and replication study using two clinical cohorts of previously untreated patients with benign or malignant ovarian tumours (N = 111 and N = 37). The discovery analysis identified 32 proteins that had significantly higher levels in malignant cases as compared to benign diagnoses, and for 28 of these, the association was replicated in the second cohort. Multivariate modelling identified three highly accurate models based on 4 to 7 proteins each for separating benign tumours from early-stage and/or late-stage ovarian cancers, all with AUCs above 0.96 in the replication cohort. We also developed a model for separating the early-stage from the late-stage achieving an AUC of 0.81 in the replication cohort. These models were based on eleven proteins in total (ALPP, CXCL8, DPY30, IL6, IL12, KRT19, PAEP, TSPAN1, SIGLEC5, VTCN1, and WFDC2), notably without MUCIN-16. The majority of the associated proteins have been connected to ovarian cancer but not identified as potential biomarkers. The results show the ability of using high-precision proteomics for the identification of novel plasma protein biomarker candidates for the early detection of ovarian cancer.

Shewanella spp. play important ecological and biogeochemical roles, due in part to their versatile metabolism and swift integration of stimuli. While Shewanella spp. are primarily considered environmental microbes, Shewanella algae is increasingly recognized as an occasional human pathogen. S. algae shares the broad metabolic and respiratory repertoire of Shewanella spp. and thrives in similar ecological niches. In S. algae, nitrate and dimethyl sulfoxide (DMSO) respiration promote biofilm formation strain specifically, with potential implication of taxis and cyclic diguanosine monophosphate (c-di-GMP) signaling. Signal transduction systems in S. algae have not been investigated. To fill these knowledge gaps, we provide here an inventory of the c-di-GMP turnover proteome and chemosensory networks of the type strain S. algae CECT 5071 and compare them with those of 41 whole-genome-sequenced clinical and environmental S. algae isolates. Besides comparative analysis of genetic content and identification of laterally transferred genes, the occurrence and topology of c-di-GMP turnover proteins and chemoreceptors were analyzed. We found S. algae strains to encode 61 to 67 c-di-GMP turnover proteins and 28 to 31 chemoreceptors, placing S. algae near the top in terms of these signaling capacities per Mbp of genome. Most c-di-GMP turnover proteins were predicted to be catalytically active; we describe in them six novel N-terminal sensory domains that appear to control their catalytic activity. Overall, our work defines the c-di-GMP and chemosensory signal transduction pathways in S. algae, contributing to a better understanding of its ecophysiology and establishing S. algae as an auspicious model for the analysis of metabolic and signaling pathways within the genus Shewanella. IMPORTANCE Shewanella spp. are widespread aquatic bacteria that include the well-studied freshwater model strain Shewanella oneidensis MR-1. In contrast, the physiology of the marine and occasionally pathogenic species Shewanella algae is poorly understood. Chemosensory and c-di-GMP signal transduction systems integrate environmental stimuli to modulate gene expression, including the switch from a planktonic to sessile lifestyle and pathogenicity. Here, we systematically dissect the c-di-GMP proteome and chemosensory pathways of the type strain S. algae CECT 5071 and 41 additional S. algae isolates. We provide insights into the activity and function of these proteins, including a description of six novel sensory domains. Our work will enable future analyses of the complex, intertwined c-di-GMP metabolism and chemotaxis networks of S. algae and their ecophysiological role.

The Nexilin F-Actin Binding Protein (Nexilin) encoded by NEXN is a cardiac Z-disc protein important for cardiac function and development in humans, zebrafish, and mice. Heterozygote variants in the human NEXN gene have been reported to cause dilated and hypertrophic cardiomyopathy. Homozygous variants in NEXN cause a lethal form of human fetal cardiomyopathy, only described in two patients before. In a Swedish, four-generation, non-consanguineous family comprising 42 individuals, one female had three consecutive pregnancies with intrauterine fetal deaths caused by a lethal form of dilated cardiomyopathy. Whole-exome sequencing and variant analysis revealed that the affected fetuses were homozygous for a NEXN variant (NM_144573:c.1302del;p.(Ile435Serfs*3)). Moreover, autopsy and histology staining declared that they presented with cardiomegaly and endocardial fibroelastosis. Immunohistochemistry staining for Nexilin in the affected fetuses revealed reduced antibody staining and loss of striation in the heart, supporting loss of Nexilin function. Clinical examination of seven heterozygote carriers confirmed dilated cardiomyopathy (two individuals), other cardiac findings (three individuals), or no cardiac deviations (two individuals), indicating incomplete penetrance or age-dependent expression of dilated cardiomyopathy. RNA sequencing spanning the variant in cDNA blood of heterozygote individuals revealed nonsense-mediated mRNA decay of the mutated transcripts. In the current study, we present the first natural course of the recessively inherited lethal form of human fetal cardiomyopathy caused by loss of Nexilin function. The affected family had uneventful pregnancies until week 23-24, followed by fetal death at week 24-30, characterized by cardiomegaly and endocardial fibroelastosis.

CRISPR-Cas9 genome editing has potential to cure diseases without current treatments, but therapies must be safe. Here we show that CRISPR-Cas9 editing can introduce unintended mutations in vivo, which are passed on to the next generation. By editing fertilized zebrafish eggs using four guide RNAs selected for off-target activity in vitro, followed by long-read sequencing of DNA from >1100 larvae, juvenile and adult fish across two generations, we find that structural variants (SVs), i.e., insertions and deletions ≥50 bp, represent 6% of editing outcomes in founder larvae. These SVs occur both at on-target and off-target sites. Our results also illustrate that adult founder zebrafish are mosaic in their germ cells, and that 26% of their offspring carries an off-target mutation and 9% an SV. Hence, pre-testing for off-target activity and SVs using patient material is advisable in clinical applications, to reduce the risk of unanticipated effects with potentially large implications.

A global international initiative, such as the Earth BioGenome Project (EBP), requires both agreement and coordination on standards to ensure that the collective effort generates rapid progress toward its goals. To this end, the EBP initiated five technical standards committees comprising volunteer members from the global genomics scientific community: Sample Collection and Processing, Sequencing and Assembly, Annotation, Analysis, and IT and Informatics. The current versions of the resulting standards documents are available on the EBP website, with the recognition that opportunities, technologies, and challenges may improve or change in the future, requiring flexibility for the EBP to meet its goals. Here, we describe some highlights from the proposed standards, and areas where additional challenges will need to be met.

Formalin-fixed, paraffin-embedded (FFPE) specimens are an underutilized resource in medical research, particularly in the setting of transcriptome sequencing, as RNA from these samples is often degraded. We took advantage of an exome capture-based RNA-sequencing protocol to explore global gene expression in paired fresh-frozen (FF) and FFPE samples from 16 diffuse large B-cell lymphoma (DLBCL) patients. While FFPE samples generated fewer mapped reads compared to their FF counterparts, these reads captured the same library complexity and had a similar number of genes expressed on average. Furthermore, gene expression demonstrated a high correlation when comparing housekeeping genes only or across the entire transcriptome (r = 0.99 for both comparisons). Differences in gene expression were primarily seen in lowly expressed genes and genes with small or large coding sequences. Using cell-of-origin classifiers and clinically relevant gene expression signatures for DLBCL, FF, and FFPE samples from the same biopsy paired nearly perfectly in clustering analysis. This was further confirmed in a validation cohort of 50 FFPE DLBCL samples. In summary, we found the biological differences between tumors to be far greater than artifacts created as a result of degraded RNA. We conclude that exome capture transcriptome sequencing data from archival samples can confidently be used for cell-of-origin classification of DLBCL samples.

Mosaic loss of Y chromosome (LOY) is the most common somatic change that occurs in circulating white blood cells of older men. LOY in leukocytes is associated with increased risk for all-cause mortality and a range of common disease such as hematological and non-hematological cancer, Alzheimer's disease, and cardiovascular events. Recent genome-wide association studies identified up to 156 germline variants associated with risk of LOY. The objective of this study was to use these variants to calculate a novel polygenic risk score (PRS) for LOY, and to assess the predictive performance of this score in a large independent population of older men. We calculated a PRS for LOY in 5131 men aged 70 years and older. Levels of LOY were estimated using microarrays and validated by whole genome sequencing. After adjusting for covariates, the PRS was a significant predictor of LOY (odds ratio [OR] = 1.74 per standard deviation of the PRS, 95% confidence intervals [CI] 1.62-1.86, p < 0.001). Men in the highest quintile of the PRS distribution had > fivefold higher risk of LOY than the lowest (OR = 5.05, 95% CI 4.05-6.32, p < 0.001). Adding the PRS to a LOY prediction model comprised of age, smoking and alcohol consumption significantly improved prediction (AUC = 0.628 [CI 0.61-0.64] to 0.695 [CI 0.67-0.71], p < 0.001). Our results suggest that a PRS for LOY could become a useful tool for risk prediction and targeted intervention for common disease in men.

Cytosine modifications in DNA such as 5-methylcytosine (5mC) underlie a broad range of developmental processes, maintain cellular lineage specification, and can define or stratify types of cancer and other diseases. However, the wide variety of approaches available to interrogate these modifications has created a need for harmonized materials, methods, and rigorous benchmarking to improve genome-wide methylome sequencing applications in clinical and basic research. Here, we present a multi-platform assessment and cross-validated resource for epigenetics research from the FDA's Epigenomics Quality Control Group. Each sample is processed in multiple replicates by three whole-genome bisulfite sequencing (WGBS) protocols (TruSeq DNA methylation, Accel-NGS MethylSeq, and SPLAT), oxidative bisulfite sequencing (TrueMethyl), enzymatic deamination method (EMSeq), targeted methylation sequencing (Illumina Methyl Capture EPIC), single-molecule long-read nanopore sequencing from Oxford Nanopore Technologies, and 850k Illumina methylation arrays. After rigorous quality assessment and comparison to Illumina EPIC methylation microarrays and testing on a range of algorithms (Bismark, BitmapperBS, bwa-meth, and BitMapperBS), we find overall high concordance between assays, but also differences in efficiency of read mapping, CpG capture, coverage, and platform performance, and variable performance across 26 microarray normalization algorithms. The data provided herein can guide the use of these DNA reference materials in epigenomics research, as well as provide best practices for experimental design in future studies. By leveraging seven human cell lines that are designated as publicly available reference materials, these data can be used as a baseline to advance epigenomics research.

There is increasing evidence that honeybees (Apis mellifera L.) can adapt naturally to survive Varroa destructor, the primary cause of colony mortality world-wide. Most of the adaptive traits of naturally varroa-surviving honeybees concern varroa reproduction. Here we investigate whether factors in the honeybee metagenome also contribute to this survival. The quantitative and qualitative composition of the bacterial and viral metagenome fluctuated greatly during the active season, but with little overall difference between varroa-surviving and varroa-susceptible colonies. The main exceptions were Bartonella apis and sacbrood virus, particularly during early spring and autumn. Bombella apis was also strongly associated with early and late season, though equally for all colonies. All three affect colony protein management and metabolism. Lake Sinai virus was more abundant in varroa-surviving colonies during the summer. Lake Sinai virus and deformed wing virus also showed a tendency towards seasonal genetic change, but without any distinction between varroa-surviving and varroa-susceptible colonies. Whether the changes in these taxa contribute to survival or reflect demographic differences between the colonies (or both) remains unclear.

SARS-CoV-2, the causal agent of COVID-19, enters human cells using the ACE2 (angiotensin-converting enzyme 2) protein as a receptor. ACE2 is thus key to the infection and treatment of the coronavirus. ACE2 is highly expressed in the heart and respiratory and gastrointestinal tracts, playing important regulatory roles in the cardiovascular and other biological systems. However, the genetic basis of the ACE2 protein levels is not well understood. We have conducted the largest genome-wide association meta-analysis of plasma ACE2 levels in >28 000 individuals of the SCALLOP Consortium (Systematic and Combined Analysis of Olink Proteins). We summarize the cross-sectional epidemiological correlates of circulating ACE2. Using the summary statistics-based high-definition likelihood method, we estimate relevant genetic correlations with cardiometabolic phenotypes, COVID-19, and other human complex traits and diseases. We perform causal inference of soluble ACE2 on vascular disease outcomes and COVID-19 severity using mendelian randomization. We also perform in silico functional analysis by integrating with other types of omics data. We identified 10 loci, including 8 novel, capturing 30% of the heritability of the protein. We detected that plasma ACE2 was genetically correlated with vascular diseases, severe COVID-19, and a wide range of human complex diseases and medications. An X-chromosome cis-protein quantitative trait loci-based mendelian randomization analysis suggested a causal effect of elevated ACE2 levels on COVID-19 severity (odds ratio, 1.63 [95% CI, 1.10-2.42]; P=0.01), hospitalization (odds ratio, 1.52 [95% CI, 1.05-2.21]; P=0.03), and infection (odds ratio, 1.60 [95% CI, 1.08-2.37]; P=0.02). Tissue- and cell type-specific transcriptomic and epigenomic analysis revealed that the ACE2 regulatory variants were enriched for DNA methylation sites in blood immune cells. Human plasma ACE2 shares a genetic basis with cardiovascular disease, COVID-19, and other related diseases. The genetic architecture of the ACE2 protein is mapped, providing a useful resource for further biological and clinical studies on this coronavirus receptor.

Neonatal lupus erythematosus (NLE) may develop after transplacental transfer of maternal autoantibodies with cardiac manifestations (congenital heart block, CHB) including atrioventricular block, atrial and ventricular arrhythmias, and cardiomyopathies. The association with anti-Ro/SSA antibodies is well established, but a recurrence rate of only 12%-16% despite persisting maternal autoantibodies suggests that additional factors are required for CHB development. Here, we identify fetal genetic variants conferring risk of CHB and elucidate their effects on cardiac function. A genome-wide association study was performed in families with at least one case of CHB. Gene expression was analysed by microarrays, RNA sequencing and PCR and protein expression by western blot, immunohistochemistry, immunofluorescence and flow cytometry. Calcium regulation and connectivity were analysed in primary cardiomyocytes and cells induced from pleuripotent stem cells. Fetal heart performance was analysed by Doppler/echocardiography. We identified DNAJC6 as a novel fetal susceptibility gene, with decreased cardiac expression of DNAJC6 associated with the disease risk genotype. We further demonstrate that fetal cardiomyocytes deficient in auxilin, the protein encoded by DNAJC6, have abnormal connectivity and Ca2+ homoeostasis in culture, as well as decreased cell surface expression of the Cav1.3 calcium channel. Doppler echocardiography of auxilin-deficient fetal mice revealed cardiac NLE abnormalities in utero, including abnormal heart rhythm with atrial and ventricular ectopias, as well as a prolonged atrioventricular time intervals. Our study identifies auxilin as the first genetic susceptibility factor in NLE modulating cardiac function, opening new avenues for the development of screening and therapeutic strategies in CHB.

There is ample support for developmental regulation of glioblastoma stem cells. To examine how cell lineage controls glioblastoma stem cell function, we present a cross-species epigenome analysis of mouse and human glioblastoma stem cells. We analyze and compare the chromatin-accessibility landscape of nine mouse glioblastoma stem cell cultures of three defined origins and 60 patient-derived glioblastoma stem cell cultures by assay for transposase-accessible chromatin using sequencing. This separates the mouse cultures according to cell of origin and identifies three human glioblastoma stem cell clusters that show overlapping characteristics with each of the mouse groups, and a distribution along an axis of proneural to mesenchymal phenotypes. The epigenetic-based human glioblastoma stem cell clusters display distinct functional properties and can separate patient survival. Cross-species analyses reveals conserved epigenetic regulation of mouse and human glioblastoma stem cells. We conclude that epigenetic control of glioblastoma stem cells primarily is dictated by developmental origin which impacts clinically relevant glioblastoma stem cell properties and patient survival.

Hypersexual disorder (HD) - a nonparaphilic sexual desire disorder with impulsivity component - was evaluated for inclusion as a diagnosis in the DSM-5 and the diagnosis compulsive sexual behavior disorder is included as an impulse control disorder in the ICD-11. Hypothalamic-pituitary-adrenal (HPA)-axis hyperactivity is believed to affect cellular senescence and has been implicated in HD. No previous study investigated HD or HPA-axis dysregulation in relation to measures of epigenetic age (EA) acceleration. This study reports on a case-control study set-up from a well-characterized cohort, contrasting EA predictors in relation to 60 HD patients and 33 healthy volunteers (HV) and 19 mixed HD/HV exhibiting dexamethasone suppression test (DST) non-suppression to 73 mixed HD/HV DST controls. The genome-wide methylation pattern was measured in whole blood from 94 subjects using the Illumina Infinium Methylation EPIC BeadChip and preprocessed according to specialized protocols suitable for epigenetic age estimation. The online DNAm Age Calculator (https://dnamage. ucla.edu/) was implemented to retrieve various EA predictors, which were compared between the in-silico generated subgroups. Quality control analyses indicated strong correlations between the EA measure DNA methylation GrimAge (DNAm GrimAge - the EA clock most reliably associated with mortality risk) and chronological age in all sub-groups. The study was adequately powered to detect differences of 2.5 and 3.0 years in DNAm GrimAge minus age in relation to both HD and HPA-axis dysregulation, respectively. Baseline DNAm GrimAge exceeded chronological age by 2.8 years on average across all samples. No EA acceleration marker was associated with HD or DST suppression status (p > 0.05). EA acceleration markers shown to be strongly predictive of physiological dysregulation and mortality-risk, are not related to HD or DST non-suppression status (measured after 0.5 mg dexamethasone). The independency of HPA-axis dysregulation to EA acceleration does not support the biological relevance of this dosage-regimen when applied to patients with HD. These findings do not support the notion of accelerated cellular senescence in HD. Studies stratifying DST non-suppressors according to established dosage-regimens in somatic settings are needed to fully elucidate the putative contribution of HPA-axis dysregulation to EA.

Target sequence capture has emerged as a powerful method to sequence hundreds or thousands of genomic regions in a cost- and time-efficient approach. In most cases, however, targeted regions lack full sequence information for certain samples, due to taxonomic, laboratory, or stochastic factors. Loci lacking molecular data for a large number of samples are commonly excluded from downstream analyses, even though they may still contain valuable information. On the other hand, including data-poor loci may bias phylogenetic analyses. Here we use a target sequence capture dataset of an ecologically and taxonomically diverse group of spiny sunflowers (Asteraceae, or Compositae: Barnadesioideae) to test how the inclusion or exclusion of such data-poor loci affects phylogenetic inference. We investigate the sensitivity of concatenation and coalescent approaches to missing data with matrices of varying taxonomic completeness by filtering loci with different proportions of missing samples prior to data analysis. We find that missing data affect both the topology and branch support of the resulting phylogenies. The matrix containing all loci yielded the overall highest node support values, independently of the amount of missing nucleotides. These results provide empirical support to earlier suggestions based on single genes and data simulations that taxa with high amounts of missing data should not be readily dismissed as they can provide essential information for phylogenomic reconstruction.

The factors shaping the composition of the tree mycobiome are still under investigation. We tested the effects of host genotype, site, host phenotypic traits, and air fungal spore communities on the assembly of the fungi inhabiting Norway spruce needles. We used Norway spruce clones and spore traps within the collection sites and characterized both needle and air mycobiome communities by high-throughput sequencing of the ITS2 region. The composition of the needle mycobiome differed between Norway spruce clones, and clones with high genetic similarity had a more similar mycobiome. The needle mycobiome also varied across sites and was associated with the composition of the local air mycobiome and climate. Phenotypic traits such as diameter at breast height or crown health influenced the needle mycobiome to a lesser extent than host genotype and air mycobiome. Altogether, our results suggest that the needle mycobiome is mainly driven by the host genotype in combination with the composition of the local air spore communities. Our work highlights the role of host intraspecific variation in shaping the mycobiome of trees and provides new insights on the ecological processes structuring fungal communities inhabiting woody plants.

The GBS-MeDIP protocol combines two previously described techniques, Genotype-by-Sequencing (GBS) and Methylated-DNA-Immunoprecipitation (MeDIP). Our method allows for parallel and cost-efficient interrogation of genetic and methylomic variants in the DNA of many reduced genomes, taking advantage of the barcoding of DNA samples performed in the GBS and the subsequent creation of DNA pools, then used as an input for the MeDIP. The GBS-MeDIP is particularly suitable to identify genetic and methylomic biomarkers when resources for whole genome interrogation are lacking.

DNA methylation patterns in chronic pulmonary obstructive disease (COPD) might offer new insights into disease pathogenesis. To assess methylation profiles in the main COPD target organ, we performed an epigenome-wide association study on bronchoalveolar lavage (BAL) cells. Bronchoscopies were performed in 18 COPD subjects and 15 controls (ex- and current smokers). DNA methylation was measured with Illumina MethylationEPIC BeadChip covering >850,000 CpGs. Differentially methylated positions (DMPs) were examined for 1) enrichment in pathways and functional gene relationships using Kyoto Encyclopedia of Genes and Genomes and Gene Ontology; 2) accelerated aging using Horvath's epigenetic clock; 3) correlation with gene expression; and 4) co-localization with genetic variation. We found 1,155 Bonferroni significant (P < 6.74 × 10-8) DMPs associated with COPD, many with large effect sizes. Functional analysis identified biologically plausible pathways and gene relationships, including enrichment for transcription factor activity. Strong correlation was found between COPD and chronological age, but not with accelerated epigenetic aging. For 79 unique DMPs, DNA methylation correlated significantly with gene expression in BAL cells. Thirty-nine percent of DMPs were co-localized with COPD-associated SNPs. To the best of our knowledge, this is the first EWAS of COPD on BAL cells, and our analyses revealed many differential methylation sites. Integration with mRNA data showed a strong functional readout for relevant genes, identifying sites where DNA methylation might directly impact expression. Almost half of DMPs were co-located with SNPs identified in previous GWAS of COPD, suggesting joint genetic and epigenetic pathways related to disease. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Spinal cord ependymal cells display neural stem cell properties in vitro and generate scar-forming astrocytes and remyelinating oligodendrocytes after injury. We report that ependymal cells are functionally heterogeneous and identify a small subpopulation (8% of ependymal cells and 0.1% of all cells in a spinal cord segment), which we denote ependymal A (EpA) cells, that accounts for the in vitro stem cell potential in the adult spinal cord. After spinal cord injury, EpA cells undergo self-renewing cell division as they give rise to differentiated progeny. Single-cell transcriptome analysis revealed a loss of ependymal cell gene expression programs as EpA cells gained signaling entropy and dedifferentiated to a stem-cell-like transcriptional state after an injury. We conclude that EpA cells are highly differentiated cells that can revert to a stem cell state and constitute a therapeutic target for spinal cord repair.

Obsessive-compulsive disorder (OCD) is known to be substantially heritable; however, the contribution of genetic variation across the allele frequency spectrum to this heritability remains uncertain. The authors used two new homogeneous cohorts to estimate the heritability of OCD from inherited genetic variation and contrasted the results with those of previous studies. The sample consisted of 2,090 Swedish-born individuals diagnosed with OCD and 4,567 control subjects, all genotyped for common genetic variants, specifically >400,000 single-nucleotide polymorphisms (SNPs) with minor allele frequency (MAF) ≥0.01. Using genotypes of these SNPs to estimate distant familial relationships among individuals, the authors estimated the heritability of OCD, both overall and partitioned according to MAF bins. Narrow-sense heritability of OCD was estimated at 29% (SE=4%). The estimate was robust, varying only modestly under different models. Contrary to an earlier study, however, SNPs with MAF between 0.01 and 0.05 accounted for 10% of heritability, and estimated heritability per MAF bin roughly followed expectations based on a simple model for SNP-based heritability. These results indicate that common inherited risk variation (MAF ≥0.01) accounts for most of the heritable variation in OCD. SNPs with low MAF contribute meaningfully to the heritability of OCD, and the results are consistent with expectation under the "infinitesimal model" (also referred to as the "polygenic model"), where risk is influenced by a large number of loci across the genome and across MAF bins.