Genetics of circulating inflammatory proteins identifies drivers of immune-mediated disease risk and therapeutic targets.

Circulating proteins have important functions in inflammation and a broad range of diseases. To identify genetic influences on inflammation-related proteins, we conducted a genome-wide protein quantitative trait locus (pQTL) study of 91 plasma proteins measured using the Olink Target platform in 14,824 participants. We identified 180 pQTLs (59 cis, 121 trans). Integration of pQTL data with eQTL and disease genome-wide association studies provided insight into pathogenesis, implicating lymphotoxin-α in multiple sclerosis. Using Mendelian randomization (MR) to assess causality in disease etiology, we identified both shared and distinct effects of specific proteins across immune-mediated diseases, including directionally discordant effects of CD40 on risk of rheumatoid arthritis versus multiple sclerosis and inflammatory bowel disease. MR implicated CXCL5 in the etiology of ulcerative colitis (UC) and we show elevated gut CXCL5 transcript expression in patients with UC. These results identify targets of existing drugs and provide a powerful resource to facilitate future drug target prioritization.

An atlas of genetic scores to predict multi-omic traits.

The use of omic modalities to dissect the molecular underpinnings of common diseases and traits is becoming increasingly common. But multi-omic traits can be genetically predicted, which enables highly cost-effective and powerful analyses for studies that do not have multi-omics1. Here we examine a large cohort (the INTERVAL study2; n = 50,000 participants) with extensive multi-omic data for plasma proteomics (SomaScan, n = 3,175; Olink, n = 4,822), plasma metabolomics (Metabolon HD4, n = 8,153), serum metabolomics (Nightingale, n = 37,359) and whole-blood Illumina RNA sequencing (n = 4,136), and use machine learning to train genetic scores for 17,227 molecular traits, including 10,521 that reach Bonferroni-adjusted significance. We evaluate the performance of genetic scores through external validation across cohorts of individuals of European, Asian and African American ancestries. In addition, we show the utility of these multi-omic genetic scores by quantifying the genetic control of biological pathways and by generating a synthetic multi-omic dataset of the UK Biobank3 to identify disease associations using a phenome-wide scan. We highlight a series of biological insights with regard to genetic mechanisms in metabolism and canonical pathway associations with disease; for example, JAK-STAT signalling and coronary atherosclerosis. Finally, we develop a portal ( https://www.omicspred.org/ ) to facilitate public access to all genetic scores and validation results, as well as to serve as a platform for future extensions and enhancements of multi-omic genetic scores.

GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19.

Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte-macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).

Canonical correlation analysis for multi-omics: Application to cross-cohort analysis.

Integrative approaches that simultaneously model multi-omics data have gained increasing popularity because they provide holistic system biology views of multiple or all components in a biological system of interest. Canonical correlation analysis (CCA) is a correlation-based integrative method designed to extract latent features shared between multiple assays by finding the linear combinations of features-referred to as canonical variables (CVs)-within each assay that achieve maximal across-assay correlation. Although widely acknowledged as a powerful approach for multi-omics data, CCA has not been systematically applied to multi-omics data in large cohort studies, which has only recently become available. Here, we adapted sparse multiple CCA (SMCCA), a widely-used derivative of CCA, to proteomics and methylomics data from the Multi-Ethnic Study of Atherosclerosis (MESA) and Jackson Heart Study (JHS). To tackle challenges encountered when applying SMCCA to MESA and JHS, our adaptations include the incorporation of the Gram-Schmidt (GS) algorithm with SMCCA to improve orthogonality among CVs, and the development of Sparse Supervised Multiple CCA (SSMCCA) to allow supervised integration analysis for more than two assays. Effective application of SMCCA to the two real datasets reveals important findings. Applying our SMCCA-GS to MESA and JHS, we identified strong associations between blood cell counts and protein abundance, suggesting that adjustment of blood cell composition should be considered in protein-based association studies. Importantly, CVs obtained from two independent cohorts also demonstrate transferability across the cohorts. For example, proteomic CVs learned from JHS, when transferred to MESA, explain similar amounts of blood cell count phenotypic variance in MESA, explaining 39.0% ~ 50.0% variation in JHS and 38.9% ~ 49.1% in MESA. Similar transferability was observed for other omics-CV-trait pairs. This suggests that biologically meaningful and cohort-agnostic variation is captured by CVs. We anticipate that applying our SMCCA-GS and SSMCCA on various cohorts would help identify cohort-agnostic biologically meaningful relationships between multi-omics data and phenotypic traits.

Identifying causal serum protein-cardiometabolic trait relationships using whole genome sequencing.

Cardiometabolic diseases, such as type 2 diabetes and cardiovascular disease, have a high public health burden. Understanding the genetically determined regulation of proteins that are dysregulated in disease can help to dissect the complex biology underpinning them. Here, we perform a protein quantitative trait locus (pQTL) analysis of 248 serum proteins relevant to cardiometabolic processes in 2893 individuals. Meta-analyzing whole-genome sequencing (WGS) data from two Greek cohorts, MANOLIS (n = 1356; 22.5× WGS) and Pomak (n = 1537; 18.4× WGS), we detect 301 independently associated pQTL variants for 170 proteins, including 12 rare variants (minor allele frequency < 1%). We additionally find 15 pQTL variants that are rare in non-Finnish European populations but have drifted up in the frequency in the discovery cohorts here. We identify proteins causally associated with cardiometabolic traits, including Mep1b for high-density lipoprotein (HDL) levels, and describe a knock-out (KO) Mep1b mouse model. Our findings furnish insights into the genetic architecture of the serum proteome, identify new protein-disease relationships and demonstrate the importance of isolated populations in pQTL analysis.

Polygenic transcriptome risk scores for COPD and lung function improve cross-ethnic portability of prediction in the NHLBI TOPMed program.

While polygenic risk scores (PRSs) enable early identification of genetic risk for chronic obstructive pulmonary disease (COPD), predictive performance is limited when the discovery and target populations are not well matched. Hypothesizing that the biological mechanisms of disease are shared across ancestry groups, we introduce a PrediXcan-derived polygenic transcriptome risk score (PTRS) to improve cross-ethnic portability of risk prediction. We constructed the PTRS using summary statistics from application of PrediXcan on large-scale GWASs of lung function (forced expiratory volume in 1 s [FEV1] and its ratio to forced vital capacity [FEV1/FVC]) in the UK Biobank. We examined prediction performance and cross-ethnic portability of PTRS through smoking-stratified analyses both on 29,381 multi-ethnic participants from TOPMed population/family-based cohorts and on 11,771 multi-ethnic participants from TOPMed COPD-enriched studies. Analyses were carried out for two dichotomous COPD traits (moderate-to-severe and severe COPD) and two quantitative lung function traits (FEV1 and FEV1/FVC). While the proposed PTRS showed weaker associations with disease than PRS for European ancestry, the PTRS showed stronger association with COPD than PRS for African Americans (e.g., odds ratio [OR] = 1.24 [95% confidence interval [CI]: 1.08-1.43] for PTRS versus 1.10 [0.96-1.26] for PRS among heavy smokers with ≥ 40 pack-years of smoking) for moderate-to-severe COPD. Cross-ethnic portability of the PTRS was significantly higher than the PRS (paired t test p < 2.2 × 10-16 with portability gains ranging from 5% to 28%) for both dichotomous COPD traits and across all smoking strata. Our study demonstrates the value of PTRS for improved cross-ethnic portability compared to PRS in predicting COPD risk.

A large source of cloud condensation nuclei from new particle formation in the tropics.

Cloud condensation nuclei (CCN) can affect cloud properties and therefore Earth's radiative balance1-3. New particle formation (NPF) from condensable vapours in the free troposphere has been suggested to contribute to CCN, especially in remote, pristine atmospheric regions4, but direct evidence is sparse, and the magnitude of this contribution is uncertain5-7. Here we use in situ aircraft measurements of vertical profiles of aerosol size distributions to present a global-scale survey of NPF occurrence. We observe intense NPF at high altitudes in tropical convective regions over both Pacific and Atlantic oceans. Together with the results of chemical-transport models, our findings indicate that NPF persists at all longitudes as a global-scale band in the tropical upper troposphere, covering about 40 per cent of Earth's surface. Furthermore, we find that this NPF in the tropical upper troposphere is a globally important source of CCN in the lower troposphere, where CCN can affect cloud properties. Our findings suggest that the production of CCN as new particles descend towards the surface is not adequately captured in global models, which tend to underestimate both the magnitude of tropical upper tropospheric NPF and the subsequent growth of new particles to CCN sizes.

High-dose systemic adeno-associated virus vector administration causes liver and sinusoidal endothelial cell injury.

We analyzed retrospective data from toxicology studies involving administration of high doses of adeno-associated virus expressing different therapeutic transgenes to 21 cynomolgus and 15 rhesus macaques. We also conducted prospective studies to investigate acute toxicity following high-dose systemic administration of enhanced green fluorescent protein-expressing adeno-associated virus to 10 rhesus macaques. Toxicity was characterized by transaminitis, thrombocytopenia, and alternative complement pathway activation that peaked on post-administration day 3. Although most animals recovered, some developed ascites, generalized edema, hyperbilirubinemia, and/or coagulopathy that prompted unscheduled euthanasia. Study endpoint livers from animals that recovered and from unscheduled necropsies of those that succumbed to toxicity were analyzed via hypothesis-driven histopathology and unbiased single-nucleus RNA sequencing. All liver cell types expressed high transgene transcript levels at early unscheduled timepoints that subsequently decreased. Thrombocytopenia coincided with sinusoidal platelet microthrombi and sinusoidal endothelial injury identified via immunohistology and single-nucleus RNA sequencing. Acute toxicity, sinusoidal injury, and liver platelet sequestration were similarly observed with therapeutic transgenes and enhanced green fluorescent protein at doses ≥1 × 1014 GC/kg, suggesting it was the consequence of high-dose systemic adeno-associated virus administration, not green fluorescent protein toxicity. These findings highlight a potential toxic effect of high-dose intravenous adeno-associated virus on nonhuman primate liver microvasculature.

Using genetic variation to disentangle the complex relationship between food intake and health outcomes.

Diet is considered as one of the most important modifiable factors influencing human health, but efforts to identify foods or dietary patterns associated with health outcomes often suffer from biases, confounding, and reverse causation. Applying Mendelian randomization in this context may provide evidence to strengthen causality in nutrition research. To this end, we first identified 283 genetic markers associated with dietary intake in 445,779 UK Biobank participants. We then converted these associations into direct genetic effects on food exposures by adjusting them for effects mediated via other traits. The SNPs which did not show evidence of mediation were then used for MR, assessing the association between genetically predicted food choices and other risk factors, health outcomes. We show that using all associated SNPs without omitting those which show evidence of mediation, leads to biases in downstream analyses (genetic correlations, causal inference), similar to those present in observational studies. However, MR analyses using SNPs which have only a direct effect on the exposure on food exposures provided unequivocal evidence of causal associations between specific eating patterns and obesity, blood lipid status, and several other risk factors and health outcomes.

Ancient DNA at the edge of the world: Continental immigration and the persistence of Neolithic male lineages in Bronze Age Orkney.

Orkney was a major cultural center during the Neolithic, 3800 to 2500 BC. Farming flourished, permanent stone settlements and chambered tombs were constructed, and long-range contacts were sustained. From ∼3200 BC, the number, density, and extravagance of settlements increased, and new ceremonial monuments and ceramic styles, possibly originating in Orkney, spread across Britain and Ireland. By ∼2800 BC, this phenomenon was waning, although Neolithic traditions persisted to at least 2500 BC. Unlike elsewhere in Britain, there is little material evidence to suggest a Beaker presence, suggesting that Orkney may have developed along an insular trajectory during the second millennium BC. We tested this by comparing new genomic evidence from 22 Bronze Age and 3 Iron Age burials in northwest Orkney with Neolithic burials from across the archipelago. We identified signals of inward migration on a scale unsuspected from the archaeological record: As elsewhere in Bronze Age Britain, much of the population displayed significant genome-wide ancestry deriving ultimately from the Pontic-Caspian Steppe. However, uniquely in northern and central Europe, most of the male lineages were inherited from the local Neolithic. This suggests that some male descendants of Neolithic Orkney may have remained distinct well into the Bronze Age, although there are signs that this had dwindled by the Iron Age. Furthermore, although the majority of mitochondrial DNA lineages evidently arrived afresh with the Bronze Age, we also find evidence for continuity in the female line of descent from Mesolithic Britain into the Bronze Age and even to the present day.

CYP4F2 is a human-specific determinant of circulating N-acyl amino acid levels.

N-acyl amino acids are a large family of circulating lipid metabolites that modulate energy expenditure and fat mass in rodents. However, little is known about the regulation and potential cardiometabolic functions of N-acyl amino acids in humans. Here, we analyze the cardiometabolic phenotype associations and genomic associations of four plasma N-acyl amino acids (N-oleoyl-leucine, N-oleoyl-phenylalanine, N-oleoyl-serine, and N-oleoyl-glycine) in 2351 individuals from the Jackson Heart Study. We find that plasma levels of specific N-acyl amino acids are associated with cardiometabolic disease endpoints independent of free amino acid plasma levels and in patterns according to the amino acid head group. By integrating whole genome sequencing data with N-acyl amino acid levels, we identify that the genetic determinants of N-acyl amino acid levels also cluster according to the amino acid head group. Furthermore, we identify the CYP4F2 locus as a genetic determinant of plasma N-oleoyl-leucine and N-oleoyl-phenylalanine levels in human plasma. In experimental studies, we demonstrate that CYP4F2-mediated hydroxylation of N-oleoyl-leucine and N-oleoyl-phenylalanine results in metabolic diversification and production of many previously unknown lipid metabolites with varying characteristics of the fatty acid tail group, including several that structurally resemble fatty acid hydroxy fatty acids. These studies provide a structural framework for understanding the regulation and disease associations of N-acyl amino acids in humans and identify that the diversity of this lipid signaling family can be significantly expanded through CYP4F-mediated ω-hydroxylation.

Prednisolone and rapamycin reduce the plasma cell gene signature and may improve AAV gene therapy in cynomolgus macaques.

Adeno-associated virus (AAV) vector gene therapy is a promising approach to treat rare genetic diseases; however, an ongoing challenge is how to best modulate host immunity to improve transduction efficiency and therapeutic outcomes. This report presents two studies characterizing multiple prophylactic immunosuppression regimens in male cynomolgus macaques receiving an AAVrh10 gene therapy vector expressing human coagulation factor VIII (hFVIII). In study 1, no immunosuppression was compared with prednisolone, rapamycin (or sirolimus), rapamycin and cyclosporin A in combination, and cyclosporin A and azathioprine in combination. Prednisolone alone demonstrated higher mean peripheral blood hFVIII expression; however, this was not sustained upon taper. Anti-capsid and anti-hFVIII antibody responses were robust, and vector genomes and transgene mRNA levels were similar to no immunosuppression at necropsy. Study 2 compared no immunosuppression with prednisolone alone or in combination with rapamycin or methotrexate. The prednisolone/rapamycin group demonstrated an increase in mean hFVIII expression and a mean delay in anti-capsid IgG development until after rapamycin taper. Additionally, a significant reduction in the plasma cell gene signature was observed with prednisolone/rapamycin, suggesting that rapamycin's tolerogenic effects may include plasma cell differentiation blockade. Immunosuppression with prednisolone and rapamycin in combination could improve therapeutic outcomes in AAV vector gene therapy.

Genetic and phenotypic links between obesity and extracellular vesicles.

Obesity has a highly complex genetic architecture, making it difficult to understand the genetic mechanisms, despite the large number of discovered loci via genome-wide association studies (GWAS). Omics techniques have provided a better resolution to view this problem. As a proxy of cell-level biology, extracellular vesicles (EVs) are useful for studying cellular regulation of complex phenotypes such as obesity. Here, in a well-established Scottish cohort, we utilized a novel technology to detect surface proteins across millions of single EVs in each individual's plasma sample. Integrating the results with established obesity GWAS, we inferred 78 types of EVs carrying one or two of 12 surface proteins to be associated with adiposity-related traits such as waist circumference. We then verified that particular EVs' abundance is negatively correlated with body adiposity, while no association with lean body mass. We also revealed that genetic variants associated with protein-specific EVs capture 2-4-fold heritability enrichment for blood cholesterol levels. Our findings provide evidence that EVs with specific surface proteins have phenotypic and genetic links to obesity and blood lipids, respectively, guiding future EV biomarker research.

Inbreeding, Native American ancestry and child mortality: linking human selection and paediatric medicine.

The children of related parents show increased risk of early mortality. The Native American genome typically exhibits long stretches of homozygosity, and Latin Americans are highly heterogeneous regarding the individual burden of homozygosity, the proportion and the type of Native American ancestry. We analysed nationwide mortality and genome-wide genotype data from admixed Chileans to investigate the relationship between common causes of child mortality, homozygosity and Native American ancestry. Results from two-stage linear-Poisson regression revealed a strong association between the sum length of runs of homozygosity (SROH) above 1.5 Megabases (Mb) in each genome and mortality due to intracranial non-traumatic haemorrhage of foetus and newborn (5% increased risk of death per Mb in SROH, P = 1 × 10-3) and disorders related to short gestation and low birth weight (P = 3 × 10-4). The major indigenous populations in Chile are Aymara-Quechua in the north of the country and the Mapuche-Huilliche in the south. The individual proportion of Aymara-Quechua ancestry was associated with an increased risk of death due to anencephaly and similar malformations (P = 4 × 10-5), and the risk of death due to Edwards and Patau trisomy syndromes decreased 4% per 1% Aymara-Quechua ancestry proportion (P = 4 × 10-4) and 5% per 1% Mapuche-Huilliche ancestry proportion (P = 2 × 10-3). The present results suggest that short gestation, low birth weight and intracranial non-traumatic haemorrhage mediate the negative effect of inbreeding on human selection. Independent validation of the identified associations between common causes of child death, homozygosity and fine-scale ancestry proportions may inform paediatric medicine.

Investigation of the causal relationships between human IgG N-glycosylation and 12 common diseases associated with changes in the IgG N-glycome.

Changes in the N-glycosylation of immunoglobulin G (IgG) are often observed in pathological states, such as autoimmune, inflammatory, neurodegenerative, cardiovascular diseases and some types of cancer. However, in most cases, it is not clear if the disease onset causes these changes, or if the changes in IgG N-glycosylation are among the risk factors for the diseases. The aim of this study was to investigate the casual relationships between IgG N-glycosylation traits and 12 diseases, in which the alterations of IgG N-glycome were previously reported, using two sample Mendelian randomization (MR) approach. We have performed two sample MR using publicly available summary statistics of genome-wide association studies of IgG N-glycosylation and disease risks. Our results indicate positive causal effect of systemic lupus erythematosus (SLE) on the abundance of N-glycans with bisecting N-acetylglucosamine in the total IgG N-glycome. Therefore, we suggest regarding this IgG glycosylation trait as a biomarker of SLE. We also emphasize the need for more powerful GWAS studies of IgG N-glycosylation to further elucidate the causal effect of IgG N-glycome on the diseases.

Vector Affinity and Receptor Distribution Define Tissue-Specific Targeting in an Engineered AAV Capsid.

Unbiased in vivo selections of diverse capsid libraries can yield engineered capsids that overcome gene therapy delivery challenges like traversing the blood-brain barrier (BBB), but little is known about the parameters of capsid-receptor interactions that govern their improved activity. This hampers broader efforts in precision capsid engineering and is a practical impediment to ensuring the translatability of capsid properties between preclinical animal models and human clinical trials. In this work, we utilize the adeno-associated virus (AAV)-PHP.B-Ly6a model system to better understand the targeted delivery and BBB penetration properties of AAV vectors. This model offers a defined capsid-receptor pair that can be used to systematically define relationships between target receptor affinity and in vivo activity of engineered AAV vectors. Here, we report a high-throughput method for quantifying capsid-receptor affinity and demonstrate that direct binding assays can be used to organize a vector library into families with varied affinity for their target receptor. Our data indicate that efficient central nervous system transduction requires high levels of target receptor expression at the BBB, but it is not a requirement for receptor expression to be limited to the target tissue. We observed that enhanced receptor affinity leads to reduced transduction of off-target tissues but can negatively impact on-target cellular transduction and penetration of endothelial barriers. Together, this work provides a set of tools for defining vector-receptor affinities and demonstrates how receptor expression and affinity interact to impact the performance of engineered AAV vectors in targeting the central nervous system. IMPORTANCE Novel methods for measuring adeno-associated virus (AAV)-receptor affinities, especially in relation to vector performance in vivo, would be useful to capsid engineers as they develop AAV vectors for gene therapy applications and characterize their interactions with native or engineered receptors. Here, we use the AAV-PHP.B-Ly6a model system to assess the impact of receptor affinity on the systemic delivery and endothelial penetration properties of AAV-PHP.B vectors. We discuss how receptor affinity analysis can be used to isolate vectors with optimized properties, improve the interpretation of library selections, and ultimately translate vector activities between preclinical animal models and humans.

Sex matters: acute functional connectivity changes as markers of remission in late-life depression differ by sex.

The efficacy of antidepressant treatment in late-life is modest, a problem magnified by an aging population and increased prevalence of depression. Understanding the neurobiological mechanisms of treatment response in late-life depression (LLD) is imperative. Despite established sex differences in depression and neural circuits, sex differences associated with fMRI markers of antidepressant treatment response are underexplored. In this analysis, we assess the role of sex on the relationship of acute functional connectivity changes with treatment response in LLD. Resting state fMRI scans were collected at baseline and day one of SSRI/SNRI treatment for 80 LLD participants. One-day changes in functional connectivity (differential connectivity) were related to remission status after 12 weeks. Sex differences in differential connectivity profiles that distinguished remitters from non-remitters were assessed. A random forest classifier was used to predict the remission status with models containing various combinations of demographic, clinical, symptomatological, and connectivity measures. Model performance was assessed with area under the curve, and variable importance was assessed with permutation importance. The differential connectivity profile associated with remission status differed significantly by sex. We observed evidence for a difference in one-day connectivity changes between remitters and non-remitters in males but not females. Additionally, prediction of remission was significantly improved in male-only and female-only models over pooled models. Predictions of treatment outcome based on early changes in functional connectivity show marked differences between sexes and should be considered in future MR-based treatment decision-making algorithms.

Shared and distinct abnormalities in sleep-wake patterns and their relationship with the negative symptoms of Schizophrenia Spectrum Disorder patients.

Sleep and rest-activity-rhythm (RAR) abnormalities are commonly reported in schizophrenia spectrum disorder (SSD) patients. However, an in-depth characterization of sleep/RAR alterations in SSD, including patients in different treatment settings, and the relationship between these alterations and SSD clinical features (e.g., negative symptoms) is lacking. SSD (N = 137 altogether, N = 79 residential and N = 58 outpatients) and healthy control (HC) subjects (N = 113) were recruited for the DiAPAson project. Participants wore an ActiGraph for seven consecutive days to monitor habitual sleep-RAR patterns. Sleep/rest duration, activity (i.e., M10, calculated on the 10 most active hours), rhythm fragmentation within days (i.e., intra-daily variability, IV; beta, steepness of rest-active changes), and rhythm regularity across days (i.e., inter-daily stability, IS) were computed in each study participant. Negative symptoms were assessed in SSD patients with the Brief Negative Symptom Scale (BNSS). Both SSD groups showed lower M10 and longer sleep/rest duration vs. HC, while only residential patients had more fragmented and irregular rhythms than HC. Compared to outpatients, residential patients had lower M10 and higher beta, IV and IS. Furthermore, residential patients had worse BNSS scores relative to outpatients, and higher IS contributed to between-group differences in BNSS score severity. Altogether, residentials and outpatients SSD had both shared and unique abnormalities in Sleep/RAR measures vs. HC and relative to one another, which also contributed to the patients' negative symptom severity. Future work will help establish whether improving some of these measures may ameliorate the quality of life and clinical symptoms of SSD patients.

Runs of homozygosity: windows into population history and trait architecture.

Long runs of homozygosity (ROH) arise when identical haplotypes are inherited from each parent and thus a long tract of genotypes is homozygous. Cousin marriage or inbreeding gives rise to such autozygosity; however, genome-wide data reveal that ROH are universally common in human genomes even among outbred individuals. The number and length of ROH reflect individual demographic history, while the homozygosity burden can be used to investigate the genetic architecture of complex disease. We discuss how to identify ROH in genome-wide microarray and sequence data, their distribution in human populations and their application to the understanding of inbreeding depression and disease risk.