Genetic Drivers of Epigenetic and Transcriptional Variation in Human Immune Cells.

Characterizing the multifaceted contribution of genetic and epigenetic factors to disease phenotypes is a major challenge in human genetics and medicine. We carried out high-resolution genetic, epigenetic, and transcriptomic profiling in three major human immune cell types (CD14+ monocytes, CD16+ neutrophils, and naive CD4+ T cells) from up to 197 individuals. We assess, quantitatively, the relative contribution of cis-genetic and epigenetic factors to transcription and evaluate their impact as potential sources of confounding in epigenome-wide association studies. Further, we characterize highly coordinated genetic effects on gene expression, methylation, and histone variation through quantitative trait locus (QTL) mapping and allele-specific (AS) analyses. Finally, we demonstrate colocalization of molecular trait QTLs at 345 unique immune disease loci. This expansive, high-resolution atlas of multi-omics changes yields insights into cell-type-specific correlation between diverse genomic inputs, more generalizable correlations between these inputs, and defines molecular events that may underpin complex disease risk.

Next-generation forward genetic screens: uniting high-throughput perturbations with single-cell analysis.

Programmable genome-engineering technologies, such as CRISPR (clustered regularly interspaced short palindromic repeats) nucleases and massively parallel CRISPR screens that capitalize on this programmability, have transformed biomedical science. These screens connect genes and noncoding genome elements to disease-relevant phenotypes, but until recently have been limited to individual phenotypes such as growth or fluorescent reporters of gene expression. By pairing massively parallel screens with high-dimensional profiling of single-cell types/states, we can now measure how individual genetic perturbations or combinations of perturbations impact the cellular transcriptome, proteome, and epigenome. We review technologies that pair CRISPR screens with single-cell multiomics and the unique opportunities afforded by extending pooled screens using deep multimodal phenotyping.

Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures.

Although there have been major advances in elucidating the functional biology of the human brain, relatively little is known of its cellular and molecular organization. Here we report a large-scale characterization of the expression of ∼1,000 genes important for neural functions by in situ hybridization at a cellular resolution in visual and temporal cortices of adult human brains. These data reveal diverse gene expression patterns and remarkable conservation of each individual gene's expression among individuals (95%), cortical areas (84%), and between human and mouse (79%). A small but substantial number of genes (21%) exhibited species-differential expression. Distinct molecular signatures, comprised of genes both common between species and unique to each, were identified for each major cortical cell type. The data suggest that gene expression profile changes may contribute to differential cortical function across species, and in particular, a shift from corticosubcortical to more predominant corticocortical communications in the human brain.

Efficient combinatorial targeting of RNA transcripts in single cells with Cas13 RNA Perturb-seq.

Pooled CRISPR screens coupled with single-cell RNA-sequencing have enabled systematic interrogation of gene function and regulatory networks. Here, we introduce Cas13 RNA Perturb-seq (CaRPool-seq), which leverages the RNA-targeting CRISPR-Cas13d system and enables efficient combinatorial perturbations alongside multimodal single-cell profiling. CaRPool-seq encodes multiple perturbations on a cleavable CRISPR array that is associated with a detectable barcode sequence, allowing for the simultaneous targeting of multiple genes. We compared CaRPool-seq to existing Cas9-based methods, highlighting its unique strength to efficiently profile combinatorially perturbed cells. Finally, we apply CaRPool-seq to perform multiplexed combinatorial perturbations of myeloid differentiation regulators in an acute myeloid leukemia (AML) model system and identify extensive interactions between different chromatin regulators that can enhance or suppress AML differentiation phenotypes.

An autoimmune disease risk variant: A trans master regulatory effect mediated by IRF1 under immune stimulation?

Functional mechanisms remain unknown for most genetic loci associated to complex human traits and diseases. In this study, we first mapped trans-eQTLs in a data set of primary monocytes stimulated with LPS, and discovered that a risk variant for autoimmune disease, rs17622517 in an intron of C5ORF56, affects the expression of the transcription factor IRF1 20 kb away. The cis-regulatory effect specific to IRF1 is active under early immune stimulus, with a large number of trans-eQTL effects across the genome under late LPS response. Using CRISPRi silencing, we showed that perturbation of the SNP locus downregulates IRF1 and causes widespread transcriptional effects. Genome editing by CRISPR had suggestive recapitulation of the LPS-specific trans-eQTL signal and lent support for the rs17622517 site being functional. Our results suggest that this common genetic variant affects inter-individual response to immune stimuli via regulation of IRF1. For this autoimmune GWAS locus, our work provides evidence of the functional variant, demonstrates a condition-specific enhancer effect, identifies IRF1 as the likely causal gene in cis, and indicates that overactivation of the downstream immune-related pathway may be the cellular mechanism increasing disease risk. This work not only provides rare experimental validation of a master-regulatory trans-eQTL, but also demonstrates the power of eQTL mapping to build mechanistic hypotheses amenable for experimental follow-up using the CRISPR toolkit.

An effector index to predict target genes at GWAS loci.

Drug development and biological discovery require effective strategies to map existing genetic associations to causal genes. To approach this problem, we selected 12 common diseases and quantitative traits for which highly powered genome-wide association studies (GWAS) were available. For each disease or trait, we systematically curated positive control gene sets from Mendelian forms of the disease and from targets of medicines used for disease treatment. We found that these positive control genes were highly enriched in proximity of GWAS-associated single-nucleotide variants (SNVs). We then performed quantitative assessment of the contribution of commonly used genomic features, including open chromatin maps, expression quantitative trait loci (eQTL), and chromatin conformation data. Using these features, we trained and validated an Effector Index (Ei), to map target genes for these 12 common diseases and traits. Ei demonstrated high predictive performance, both with cross-validation on the training set, and an independently derived set for type 2 diabetes. Key predictive features included coding or transcript-altering SNVs, distance to gene, and open chromatin-based metrics. This work outlines a simple, understandable approach to prioritize genes at GWAS loci for functional follow-up and drug development, and provides a systematic strategy for prioritization of GWAS target genes.

Comprehensive Analysis of Long-Range Connectivity from and to the Posterior Parietal Cortex of the Mouse.

The posterior parietal cortex (PPC) is a major multimodal association cortex implicated in a variety of higher order cognitive functions, such as visuospatial perception, spatial attention, categorization, and decision-making. The PPC is known to receive inputs from a collection of sensory cortices as well as various subcortical areas and integrate those inputs to facilitate the execution of functions that require diverse information. Although many recent works have been performed with the mouse as a model system, a comprehensive understanding of long-range connectivity of the mouse PPC is scarce, preventing integrative interpretation of the rapidly accumulating functional data. In this study, we conducted a detailed neuroanatomic and bioinformatic analysis of the Allen Mouse Brain Connectivity Atlas data to summarize afferent and efferent connections to/from the PPC. Then, we analyzed variability between subregions of the PPC, functional/anatomical modalities, and species, and summarized the organizational principle of the mouse PPC. Finally, we confirmed key results by using additional neurotracers. A comprehensive survey of the connectivity will provide an important future reference to comprehend the function of the PPC and allow effective paths forward to various studies using mice as a model system.

Childhood obesity and multiple sclerosis: A Mendelian randomization study.

BACKGROUND: Higher childhood body mass index (BMI) has been associated with an increased risk of multiple sclerosis (MS). OBJECTIVE: To evaluate whether childhood BMI has a causal influence on MS, and whether this putative effect is independent from early adult obesity and pubertal timing. METHODS: We performed Mendelian randomization (MR) using summary genetic data on 14,802 MS cases and 26,703 controls. Large-scale genome-wide association studies provided estimates for BMI in childhood (n = 47,541) and adulthood (n = 322,154). In multivariable MR, we examined the direct effects of each timepoint and further adjusted for age at puberty. Findings were replicated using the UK Biobank (n = 453,169). RESULTS: Higher genetically predicted childhood BMI was associated with increased odds of MS (odds ratio (OR) = 1.26/SD BMI increase, 95% confidence interval (CI): 1.07-1.50). However, there was little evidence of a direct effect after adjusting for adult BMI (OR = 1.03, 95% CI: 0.70-1.53). Conversely, the effect of adult BMI persisted independent of childhood BMI (OR = 1.43; 95% CI: 1.01-2.03). The addition of age at puberty did not alter the findings. UK Biobank analyses showed consistent results. Sensitivity analyses provided no evidence of pleiotropy. CONCLUSION: Genetic evidence supports an association between childhood obesity and MS susceptibility, mediated by persistence of obesity into early adulthood but independent of pubertal timing.

FAM210A is a novel determinant of bone and muscle structure and strength.

Osteoporosis and sarcopenia are common comorbid diseases, yet their shared mechanisms are largely unknown. We found that genetic variation near FAM210A was associated, through large genome-wide association studies, with fracture, bone mineral density (BMD), and appendicular and whole body lean mass, in humans. In mice, Fam210a was expressed in muscle mitochondria and cytoplasm, as well as in heart and brain, but not in bone. Grip strength and limb lean mass were reduced in tamoxifen-inducible Fam210a homozygous global knockout mice (TFam210a-/- ), and in tamoxifen-inducible Fam210 skeletal muscle cell-specific knockout mice (TFam210aMus-/- ). Decreased BMD, bone biomechanical strength, and bone formation, and elevated osteoclast activity with microarchitectural deterioration of trabecular and cortical bones, were observed in TFam210a-/- mice. BMD of male TFam210aMus-/- mice was also reduced, and osteoclast numbers and surface in TFam210aMus-/- mice increased. Microarray analysis of muscle cells from TFam210aMus-/- mice identified candidate musculoskeletal modulators. FAM210A, a novel gene, therefore has a crucial role in regulating bone structure and function, and may impact osteoporosis through a biological pathway involving muscle as well as through other mechanisms.

Development of a polygenic risk score to improve screening for fracture risk: A genetic risk prediction study.

BACKGROUND: Since screening programs identify only a small proportion of the population as eligible for an intervention, genomic prediction of heritable risk factors could decrease the number needing to be screened by removing individuals at low genetic risk. We therefore tested whether a polygenic risk score for heel quantitative ultrasound speed of sound (SOS)-a heritable risk factor for osteoporotic fracture-can identify low-risk individuals who can safely be excluded from a fracture risk screening program. METHODS AND FINDINGS: A polygenic risk score for SOS was trained and selected in 2 separate subsets of UK Biobank (comprising 341,449 and 5,335 individuals). The top-performing prediction model was termed "gSOS", and its utility in fracture risk screening was tested in 5 validation cohorts using the National Osteoporosis Guideline Group clinical guidelines (N = 10,522 eligible participants). All individuals were genome-wide genotyped and had measured fracture risk factors. Across the 5 cohorts, the average age ranged from 57 to 75 years, and 54% of studied individuals were women. The main outcomes were the sensitivity and specificity to correctly identify individuals requiring treatment with and without genetic prescreening. The reference standard was a bone mineral density (BMD)-based Fracture Risk Assessment Tool (FRAX) score. The secondary outcomes were the proportions of the screened population requiring clinical-risk-factor-based FRAX (CRF-FRAX) screening and BMD-based FRAX (BMD-FRAX) screening. gSOS was strongly correlated with measured SOS (r2 = 23.2%, 95% CI 22.7% to 23.7%). Without genetic prescreening, guideline recommendations achieved a sensitivity and specificity for correct treatment assignment of 99.6% and 97.1%, respectively, in the validation cohorts. However, 81% of the population required CRF-FRAX tests, and 37% required BMD-FRAX tests to achieve this accuracy. Using gSOS in prescreening and limiting further assessment to those with a low gSOS resulted in small changes to the sensitivity and specificity (93.4% and 98.5%, respectively), but the proportions of individuals requiring CRF-FRAX tests and BMD-FRAX tests were reduced by 37% and 41%, respectively. Study limitations include a reliance on cohorts of predominantly European ethnicity and use of a proxy of fracture risk. CONCLUSIONS: Our results suggest that the use of a polygenic risk score in fracture risk screening could decrease the number of individuals requiring screening tests, including BMD measurement, while maintaining a high sensitivity and specificity to identify individuals who should be recommended an intervention.

An anatomically comprehensive atlas of the adult human brain transcriptome.

Neuroanatomically precise, genome-wide maps of transcript distributions are critical resources to complement genomic sequence data and to correlate functional and genetic brain architecture. Here we describe the generation and analysis of a transcriptional atlas of the adult human brain, comprising extensive histological analysis and comprehensive microarray profiling of ∼900 neuroanatomically precise subdivisions in two individuals. Transcriptional regulation varies enormously by anatomical location, with different regions and their constituent cell types displaying robust molecular signatures that are highly conserved between individuals. Analysis of differential gene expression and gene co-expression relationships demonstrates that brain-wide variation strongly reflects the distributions of major cell classes such as neurons, oligodendrocytes, astrocytes and microglia. Local neighbourhood relationships between fine anatomical subdivisions are associated with discrete neuronal subtypes and genes involved with synaptic transmission. The neocortex displays a relatively homogeneous transcriptional pattern, but with distinct features associated selectively with primary sensorimotor cortices and with enriched frontal lobe expression. Notably, the spatial topography of the neocortex is strongly reflected in its molecular topography-the closer two cortical regions, the more similar their transcriptomes. This freely accessible online data resource forms a high-resolution transcriptional baseline for neurogenetic studies of normal and abnormal human brain function.

Large differences in adiponectin levels have no clear effect on multiple sclerosis risk: A Mendelian randomization study.

BACKGROUND: Mendelian randomization (MR) studies have demonstrated strong support for an association between genetically increased body mass index and risk of multiple sclerosis (MS). The adipokine adiponectin may be a potential mechanism linking body mass to risk of MS. OBJECTIVE: To evaluate whether genetically increased adiponectin levels influence risk of MS. METHODS: Using genome-wide significant single nucleotide polymorphisms (SNPs) for adiponectin, we undertook an MR study to estimate the effect of adiponectin on MS. This method prevents bias due to reverse causation and minimizes bias due to confounding. Sensitivity analyses were performed to evaluate the assumptions of MR. RESULTS: MR analyses did not support a role for genetically elevated adiponectin in risk of MS (odds ratio (OR) = 0.93 per unit increase in natural-log-transformed adiponectin, equivalent to a two-standard deviation increase in adiponectin on the absolute scale; 95% confidence interval (CI) = 0.66-1.33; p = 0.61). Further MR analysis suggested that genetic variation at the adiponectin gene, which influences adiponectin level, does not impact MS risk. Sensitivity analyses, including MR-Egger regression, suggested no bias due to pleiotropy. CONCLUSION: Lifelong genetically increased adiponectin levels in humans have no clear effect on risk of MS. Other biological factors driving the association between body mass and MS should be investigated.

Workforce Development Innovations with Direct Care Workers: Better Jobs, Better Services, Better Business.

This study describes findings from a national search to identify innovative workforce practices designed to improve the lives of direct care workers serving individuals with mental health and substance use conditions, while simultaneously improving client care, and the business vitality of the employer. The search process, conducted by The Annapolis Coalition on the Behavioral Health Workforce, resulted in the selection of five programs to receive the Pacesetter Award from among 51 nominations received. Awardees understood the value of investing in direct care workers, who constitute an essential, but often overlooked, group within the behavioral health workforce. A review of these innovations yielded six cross-cutting principles that should inform future workforce efforts (a) supporting educational and career development (b) increasing wages and benefits

Effects of emotion and emotional valence on the neural correlates of episodic memory search and elaboration.

Successful retrieval of an event includes an initial search phase in which the information is accessed and a subsequent elaboration phase in which an individual expands on event details. Traditionally, functional neuroimaging studies examining episodic memory retrieval either have not made a distinction between these two phases or have focused on the initial search process. The current study used an extended retrieval trial to compare the neural correlates of search and elaboration and to examine the effects of emotion on each phase. Before scanning, participants encoded positive, negative, and neutral images paired with neutral titles. After a 30-min delay, participants engaged in a scanned recognition task in which they viewed the neutral titles and indicated whether the title had been presented with an image during the study phase. Retrieval was divided into an initial memory search and a subsequent 5-sec elaboration phase. The current study identified neural differences between the search and elaboration phases, with search being associated with widespread bilateral activations across the entire cortex and elaboration primarily being associated with increased activity in the medial pFC. The emotionality of the retrieval target was more influential during search relative to elaboration. However, valence influenced when the effect of emotion was greatest, with search engaging many more regions for positive events than negative ones, but elaboration engaging the dorsomedial pFC more for negative events than positive events.

Non-linear transcriptional responses to gradual modulation of transcription factor dosage.

Genomic loci associated with common traits and diseases are typically non-coding and likely impact gene expression, sometimes coinciding with rare loss-of-function variants in the target gene. However, our understanding of how gradual changes in gene dosage affect molecular, cellular, and organismal traits is currently limited. To address this gap, we induced gradual changes in gene expression of four genes using CRISPR activation and inactivation. Downstream transcriptional consequences of dosage modulation of three master trans-regulators associated with blood cell traits (GFI1B, NFE2, and MYB) were examined using targeted single-cell multimodal sequencing. We showed that guide tiling around the TSS is the most effective way to modulate cis gene expression across a wide range of fold-changes, with further effects from chromatin accessibility and histone marks that differ between the inhibition and activation systems. Our single-cell data allowed us to precisely detect subtle to large gene expression changes in dozens of trans genes, revealing that many responses to dosage changes of these three TFs are non-linear, including non-monotonic behaviours, even when constraining the fold-changes of the master regulators to a copy number gain or loss. We found that the dosage properties are linked to gene constraint and that some of these non-linear responses are enriched for disease and GWAS genes. Overall, our study provides a straightforward and scalable method to precisely modulate gene expression and gain insights into its downstream consequences at high resolution.

Divergent and nonuniform gene expression patterns in mouse brain.

Considerable progress has been made in understanding variations in gene sequence and expression level associated with phenotype, yet how genetic diversity translates into complex phenotypic differences remains poorly understood. Here, we examine the relationship between genetic background and spatial patterns of gene expression across seven strains of mice, providing the most extensive cellular-resolution comparative analysis of gene expression in the mammalian brain to date. Using comprehensive brainwide anatomic coverage (more than 200 brain regions), we applied in situ hybridization to analyze the spatial expression patterns of 49 genes encoding well-known pharmaceutical drug targets. Remarkably, over 50% of the genes examined showed interstrain expression variation. In addition, the variability was nonuniformly distributed across strain and neuroanatomic region, suggesting certain organizing principles. First, the degree of expression variance among strains mirrors genealogic relationships. Second, expression pattern differences were concentrated in higher-order brain regions such as the cortex and hippocampus. Divergence in gene expression patterns across the brain could contribute significantly to variations in behavior and responses to neuroactive drugs in laboratory mouse strains and may help to explain individual differences in human responsiveness to neuroactive drugs.

Large-scale causal discovery using interventional data sheds light on the regulatory network architecture of blood traits.

Inference of directed biological networks is an important but notoriously challenging problem. We introduce inverse sparse regression (inspre), an approach to learning causal networks that leverages large-scale intervention-response data. Applied to 788 genes from the genome-wide perturb-seq dataset, inspre helps elucidate the network architecture of blood traits.

Discovery of target genes and pathways at GWAS loci by pooled single-cell CRISPR screens.

Most variants associated with complex traits and diseases identified by genome-wide association studies (GWAS) map to noncoding regions of the genome with unknown effects. Using ancestrally diverse, biobank-scale GWAS data, massively parallel CRISPR screens, and single-cell transcriptomic and proteomic sequencing, we discovered 124 cis-target genes of 91 noncoding blood trait GWAS loci. Using precise variant insertion through base editing, we connected specific variants with gene expression changes. We also identified trans-effect networks of noncoding loci when cis target genes encoded transcription factors or microRNAs. Networks were themselves enriched for GWAS variants and demonstrated polygenic contributions to complex traits. This platform enables massively parallel characterization of the target genes and mechanisms of human noncoding variants in both cis and trans.

Converging evidence from exome sequencing and common variants implicates target genes for osteoporosis.

In this study, we leveraged the combined evidence of rare coding variants and common alleles to identify therapeutic targets for osteoporosis. We undertook a large-scale multiancestry exome-wide association study for estimated bone mineral density, which showed that the burden of rare coding alleles in 19 genes was associated with estimated bone mineral density (P < 3.6 × 10-7). These genes were highly enriched for a set of known causal genes for osteoporosis (65-fold; P = 2.5 × 10-5). Exome-wide significant genes had 96-fold increased odds of being the top ranked effector gene at a given GWAS locus (P = 1.8 × 10-10). By integrating proteomics Mendelian randomization evidence, we prioritized CD109 (cluster of differentiation 109) as a gene for which heterozygous loss of function is associated with higher bone density. CRISPR-Cas9 editing of CD109 in SaOS-2 osteoblast-like cell lines showed that partial CD109 knockdown led to increased mineralization. This study demonstrates that the convergence of common and rare variants, proteomics and CRISPR can highlight new bone biology to guide therapeutic development.

Anatomy of the Ventricles, Subarachnoid Spaces, and Meninges.

The ventricular system, subarachnoid spaces, and meninges are structures that lend structure, support, and protection to the brain and spinal cord. This article provides a detailed look at the anatomy of the intracranial portions of these structures with a particular focus on neuroimaging methods.