Canalization and Robustness in Human Genetics and Disease.

Canalization refers to the evolution of populations such that the number of individuals who deviate from the optimum trait, or experience disease, is minimized. In the presence of rapid cultural, environmental, or genetic change, the reverse process of decanalization may contribute to observed increases in disease prevalence. This review starts by defining relevant concepts, drawing distinctions between the canalization of populations and robustness of individuals. It then considers evidence pertaining to three continuous traits and six domains of disease. In each case, existing genetic evidence for genotype-by-environment interactions is insufficient to support a strong inference of decanalization, but we argue that the advent of genome-wide polygenic risk assessment now makes an empirical evaluation of the role of canalization in preventing disease possible. Finally, the contributions of both rare and common variants to congenital abnormality and adult onset disease are considered in light of a new kerplunk model of genetic effects.

Dysregulated naive B cells and de novo autoreactivity in severe COVID-19.

Severe SARS-CoV-2 infection1 has been associated with highly inflammatory immune activation since the earliest days of the COVID-19 pandemic2-5. More recently, these responses have been associated with the emergence of self-reactive antibodies with pathologic potential6-10, although their origins and resolution have remained unclear11. Previously, we and others have identified extrafollicular B cell activation, a pathway associated with the formation of new autoreactive antibodies in chronic autoimmunity12,13, as a dominant feature of severe and critical COVID-19 (refs. 14-18). Here, using single-cell B cell repertoire analysis of patients with mild and severe disease, we identify the expansion of a naive-derived, low-mutation IgG1 population of antibody-secreting cells (ASCs) reflecting features of low selective pressure. These features correlate with progressive, broad, clinically relevant autoreactivity, particularly directed against nuclear antigens and carbamylated proteins, emerging 10-15 days after the onset of symptoms. Detailed analysis of the low-selection compartment shows a high frequency of clonotypes specific for both SARS-CoV-2 and autoantigens, including pathogenic autoantibodies against the glomerular basement membrane. We further identify the contraction of this pathway on recovery, re-establishment of tolerance standards and concomitant loss of acute-derived ASCs irrespective of antigen specificity. However, serological autoreactivity persists in a subset of patients with postacute sequelae, raising important questions as to the contribution of emerging autoreactivity to continuing symptomology on recovery. In summary, this study demonstrates the origins, breadth and resolution of autoreactivity in severe COVID-19, with implications for early intervention and the treatment of patients with post-COVID sequelae.

Distinct Effector B Cells Induced by Unregulated Toll-like Receptor 7 Contribute to Pathogenic Responses in Systemic Lupus Erythematosus.

Systemic Lupus Erythematosus (SLE) is characterized by B cells lacking IgD and CD27 (double negative; DN). We show that DN cell expansions reflected a subset of CXCR5- CD11c+ cells (DN2) representing pre-plasma cells (PC). DN2 cells predominated in African-American patients with active disease and nephritis, anti-Smith and anti-RNA autoantibodies. They expressed a T-bet transcriptional network; increased Toll-like receptor-7 (TLR7); lacked the negative TLR regulator TRAF5; and were hyper-responsive to TLR7. DN2 cells shared with activated naive cells (aNAV), phenotypic and functional features, and similar transcriptomes. Their PC differentiation and autoantibody production was driven by TLR7 in an interleukin-21 (IL-21)-mediated fashion. An in vivo developmental link between aNAV, DN2 cells, and PC was demonstrated by clonal sharing. This study defines a distinct differentiation fate of autoreactive naive B cells into PC precursors with hyper-responsiveness to innate stimuli, as well as establishes prominence of extra-follicular B cell activation in SLE, and identifies therapeutic targets.

Genetically transitional disease: a new concept in genomic medicine.

Traditional classification of genetic diseases as monogenic and polygenic has lagged far behind scientific progress. In this opinion article, we propose and define a new terminology, genetically transitional disease (GTD), referring to cases where a large-effect mutation is necessary, but not sufficient, to cause disease. This leads to a working disease nosology based on gradients of four types of genetic architecture: monogenic, polygenic, GTD, and mixed. We present four scenarios under which GTD may occur; namely, subsets of traditionally Mendelian disease, modifiable Tier 1 monogenic conditions, variable penetrance, and situations where a genetic mutational spectrum produces qualitatively divergent pathologies. The implications of the new nosology in precision medicine are discussed, in which therapeutic options may target the molecular cause or the disease phenotype.

Going to the negative: genomics for optimized medical prescription.

Personalized medicine promises to advance and improve health by targeting the right medication to the right person at the right time, thus maximizing the proportion of treated patients who achieve an effective response to therapy. This Comment article makes the complementary argument that equally important benefits will derive from negative prediction, namely by identifying those individuals who are either not actually in need of, or unlikely to respond to, a drug. Reduction of unnecessary prescription could conceivably save health-care systems many billions of dollars with very little detrimental impact on outcomes.

Stratification of risk of progression to colectomy in ulcerative colitis via measured and predicted gene expression.

An important goal of clinical genomics is to be able to estimate the risk of adverse disease outcomes. Between 5% and 10% of individuals with ulcerative colitis (UC) require colectomy within 5 years of diagnosis, but polygenic risk scores (PRSs) utilizing findings from genome-wide association studies (GWASs) are unable to provide meaningful prediction of this adverse status. By contrast, in Crohn disease, gene expression profiling of GWAS-significant genes does provide some stratification of risk of progression to complicated disease in the form of a transcriptional risk score (TRS). Here, we demonstrate that a measured TRS based on bulk rectal gene expression in the PROTECT inception cohort study has a positive predictive value approaching 50% for colectomy. Single-cell profiling demonstrates that the genes are active in multiple diverse cell types from both the epithelial and immune compartments. Expression quantitative trait locus (QTL) analysis identifies genes with differential effects at baseline and week 52 follow-up, but for the most part, differential expression associated with colectomy risk is independent of local genetic regulation. Nevertheless, a predicted polygenic transcriptional risk score (PPTRS) derived by summation of transcriptome-wide association study (TWAS) effects identifies UC-affected individuals at 5-fold elevated risk of colectomy with data from the UK Biobank population cohort studies, independently replicated in an NIDDK-IBDGC dataset. Prediction of gene expression from relatively small transcriptome datasets can thus be used in conjunction with TWASs for stratification of risk of disease complications.

Canalization of the Polygenic Risk for Common Diseases and Traits in the UK Biobank Cohort.

Since organisms develop and thrive in the face of constant perturbations due to environmental and genetic variation, species may evolve resilient genetic architectures. We sought evidence for this process, known as canalization, through a comparison of the prevalence of phenotypes as a function of the polygenic score (PGS) across environments in the UK Biobank cohort study. Contrasting seven diseases and three categorical phenotypes with respect to 151 exposures in 408,925 people, the deviation between the prevalence-risk curves was observed to increase monotonically with the PGS percentile in one-fifth of the comparisons, suggesting extensive PGS-by-Environment (PGS×E) interaction. After adjustment for the dependency of allelic effect sizes on increased prevalence in the perturbing environment, cases where polygenic influences are greater or lesser than expected are seen to be particularly pervasive for educational attainment, obesity, and metabolic condition type-2 diabetes. Inflammatory bowel disease analysis shows fewer interactions but confirms that smoking and some aspects of diet influence risk. Notably, body mass index has more evidence for decanalization (increased genetic influence at the extremes of polygenic risk), whereas the waist-to-hip ratio shows canalization, reflecting different evolutionary pressures on the architectures of these weight-related traits. An additional 10 % of comparisons showed evidence for an additive shift of prevalence independent of PGS between exposures. These results provide the first widespread evidence for canalization protecting against disease in humans and have implications for personalized medicine as well as understanding the evolution of complex traits. The findings can be explored through an R shiny app at https://canalization-gibsonlab.shinyapps.io/rshiny/.

Differential response of mesenchymal stromal cells (MSCs) to type 1 ex vivo cytokine priming: implications for MSC therapy.

BACKGROUND AIMS: Mesenchymal stromal cells (MSCs) are polymorphic, adherent cells with the capability to stimulate tissue regeneration and modulate immunity. MSCs have been broadly investigated for potential therapeutic applications, particularly immunomodulatory properties, wound healing and tissue regeneration. The exact physiologic role of MSCs, however, remains poorly understood, and this gap in knowledge significantly impedes the rational development of therapeutic cells. Here, we considered interferon γ (IFN-γ) and tumor necrosis factor alpha (TNF-α), two cytokines likely encountered physiologically and commonly used in cell manufacturing. For comparison, we studied interleukin-10 (IL-10) (anti-inflammatory) and interleukin-4 (IL-4) (type 2 cytokine). METHODS: We directly assessed the effects of these cytokines on bone marrow MSCs by comparing RNA Seq transcriptional profiles. Western blotting and flow cytometry were also used to evaluate effects of cytokine priming. RESULTS: The type 1 cytokines (IFN-γ and TNF-α) induced striking changes in gene expression and remarkably different profiles from one another. Importantly, priming MSCs with either of these cytokines did not increase variability among multiple donors beyond what is intrinsic to non-primed MSCs from different donors. IFN-γ-primed MSCs expressed IDO1 and chemokines that recruit activated T cells. In contrast, TNF-α-primed MSCs expressed genes in alternate pathways, namely PGE2 and matrix metalloproteinases synthesis, and chemokines that recruit neutrophils. IL-10 and IL-4 priming had little to no effect. CONCLUSIONS: Our data suggest that IFN-γ-primed MSCs may be a more efficacious immunosuppressive therapy aimed at diseases that target T cells (ie, graft-versus-host disease) compared with TNF-α-primed or non-primed MSCs, which may be better suited for therapies in other disease settings. These results contribute to our understanding of MSC bioactivity and suggest rational ex vivo cytokine priming approaches for MSC manufacturing and therapeutic applications.

TIGAR: An Improved Bayesian Tool for Transcriptomic Data Imputation Enhances Gene Mapping of Complex Traits.

The transcriptome-wide association studies (TWASs) that test for association between the study trait and the imputed gene expression levels from cis-acting expression quantitative trait loci (cis-eQTL) genotypes have successfully enhanced the discovery of genetic risk loci for complex traits. By using the gene expression imputation models fitted from reference datasets that have both genetic and transcriptomic data, TWASs facilitate gene-based tests with GWAS data while accounting for the reference transcriptomic data. The existing TWAS tools like PrediXcan and FUSION use parametric imputation models that have limitations for modeling the complex genetic architecture of transcriptomic data. Therefore, to improve on this, we employ a nonparametric Bayesian method that was originally proposed for genetic prediction of complex traits, which assumes a data-driven nonparametric prior for cis-eQTL effect sizes. The nonparametric Bayesian method is flexible and general because it includes both of the parametric imputation models used by PrediXcan and FUSION as special cases. Our simulation studies showed that the nonparametric Bayesian model improved both imputation R2 for transcriptomic data and the TWAS power over PrediXcan when ≥1% cis-SNPs co-regulate gene expression and gene expression heritability ≤0.2. In real applications, the nonparametric Bayesian method fitted transcriptomic imputation models for 57.8% more genes over PrediXcan, thus improving the power of follow-up TWASs. We implement both parametric PrediXcan and nonparametric Bayesian methods in a convenient software tool "TIGAR" (Transcriptome-Integrated Genetic Association Resource), which imputes transcriptomic data and performs subsequent TWASs using individual-level or summary-level GWAS data.

TreeMap: a structured approach to fine mapping of eQTL variants.

MOTIVATION: Expression quantitative trait loci (eQTL) harbor genetic variants modulating gene transcription. Fine mapping of regulatory variants at these loci is a daunting task due to the juxtaposition of causal and linked variants at a locus as well as the likelihood of interactions among multiple variants. This problem is exacerbated in genes with multiple cis-acting eQTL, where superimposed effects of adjacent loci further distort the association signals. RESULTS: We developed a novel algorithm, TreeMap, that identifies putative causal variants in cis-eQTL accounting for multisite effects and genetic linkage at a locus. Guided by the hierarchical structure of linkage disequilibrium, TreeMap performs an organized search for individual and multiple causal variants. Via extensive simulations, we show that TreeMap detects co-regulating variants more accurately than current methods. Furthermore, its high computational efficiency enables genome-wide analysis of long-range eQTL. We applied TreeMap to GTEx data of brain hippocampus samples and transverse colon samples to search for eQTL in gene bodies and in 4 Mbps gene-flanking regions, discovering numerous distal eQTL. Furthermore, we found concordant distal eQTL that were present in both brain and colon samples, implying long-range regulation of gene expression. AVAILABILITY AND IMPLEMENTATION: TreeMap is available as an R package enabled for parallel processing at https://github.com/liliulab/treemap. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Surveillance-to-Diagnostic Testing Program for Asymptomatic SARS-CoV-2 Infections on a Large, Urban Campus in Fall 2020.

BACKGROUND: Six months into the COVID-19 pandemic, college campuses faced uncertainty regarding the likely prevalence and spread of disease, necessitating large-scale testing to help guide policy following re-entry. METHODS: A SARS-CoV-2 testing program combining pooled saliva sample surveillance leading to diagnosis and intervention surveyed over 112,000 samples from 18,029 students, staff and faculty, as part of integrative efforts to mitigate transmission at the Georgia Institute of Technology in Fall 2020. RESULTS: Cumulatively, we confirmed 1,508 individuals diagnostically, 62% of these through the surveillance program and the remainder through diagnostic tests of symptomatic individuals administered on or off campus. The total strategy, including intensification of testing given case clusters early in the semester, was associated with reduced transmission following rapid case increases upon entry in Fall semester in August 2020, again in early November 2020, and upon re-entry for Spring semester in January 2021. During the Fall semester daily asymptomatic test positivity initially peaked at 4.1% but fell below 0.5% by mid-semester, averaging 0.84% across the Fall semester, with similar levels of control in Spring 2021. CONCLUSIONS: Owing to broad adoption by the campus community, we estimate that the program protected higher risk staff and faculty while allowing some normalization of education and research activities.

Altered splicing associated with the pathology of inflammatory bowel disease.

BACKGROUND: Aberrant splicing of individual genes is a well-known mechanism promoting pathology for a wide range of conditions, but disease is less commonly attributed to global disruption of exon usage. To explore the possible association of aberrant splicing with inflammatory bowel disease, we developed a pipeline for quantifying transcript abundance and exon inclusion transcriptome-wide and applied it to a dataset of ileal and rectal biopsies, both obtained in duplicate from 34 pediatric or young adult cases of ulcerative colitis and Crohn's disease. RESULTS: Expression and splicing covary to some extent, and eight individuals exhibited aberrant profiles that can be explained by altered ratios of epithelial to stromal and immune cells. Ancestry-related biases in alternative splicing accounting for 5% of the variance were also observed, in part also related to cell-type proportions. In addition, two individuals were identified who had 284 exons with significantly divergent percent spliced in exons, including in the established IBD risk gene CEACAM1, which caused their ileal samples to resemble the rectum. CONCLUSIONS: These results imply that quantitative differences in splice usage contribute to the pathology of inflammatory bowel disease in a previously unrecognized manner.

On the utilization of polygenic risk scores for therapeutic targeting.

The promise of personalized genomic medicine is that knowledge of a person's gene sequences and activity will facilitate more appropriate medical interventions, particularly drug prescriptions, to reduce the burden of disease. Early successes in oncology and pediatrics have affirmed the power of positive diagnosis and are mostly based on detection of one or a few mutations that drive the specific pathology. However, genetically more complex diseases require the development of polygenic risk scores (PRSs) that have variable accuracy. The rarity of events often means that they have necessarily low precision: many called positives are actually not at risk, and only a fraction of cases are prevented by targeted therapy. In some situations, negative prediction may better define the population at low risk. Here, I review five conditions across a broad spectrum of chronic disease (opioid pain medication, hypertension, type 2 diabetes, major depression, and osteoporotic bone fracture), considering in each case how genetic prediction might be used to target drug prescription. This leads to a call for more research designed to evaluate genetic likelihood of response to therapy and a call for evaluation of PRS, not just in terms of sensitivity and specificity but also with respect to potential clinical efficacy.

Mendelian Randomization Indicates a Causal Role for Omega-3 Fatty Acids in Inflammatory Bowel Disease.

Inflammatory bowel disease (IBD) is characterized by chronic inflammation of the gastrointestinal system. Omega-3 (ω3) fatty acids are polyunsaturated fatty acids (PUFAs) that are largely obtained from diet and have been speculated to decrease the inflammatory response that is involved in IBD; however, the causality of this association has not been established. A two-sample Mendelian randomization (MR) was used to assess genetic associations between 249 circulating metabolites measured in the UK Biobank as exposures and IBD as the outcome. The genome-wide association study summary level data for metabolite measurements and IBD were derived from large European ancestry cohorts. We observed ω3 fatty acids as a significant protective association with IBD, with multiple modes of MR evidence replicated in three IBD summary genetic datasets. The instrumental variables that were involved in the causal association of ω3 fatty acids with IBD highlighted an intronic SNP, rs174564, in FADS2, a protein engaged in the first step of alpha-linolenic acid desaturation leading to anti-inflammatory EPA and thence DHA production. A low ratio of ω3 to ω6 fatty acids was observed to be a causal risk factor, particularly for Crohn's disease. ω3 fatty acid supplementation may provide anti-inflammatory responses that are required to attenuate inflammation that is involved in IBD.

Replicability and Prediction: Lessons and Challenges from GWAS.

Since the publication of the Wellcome Trust Case Control Consortium (WTCCC) landmark study a decade ago, genome-wide association studies (GWAS) have led to the discovery of thousands of risk variants involved in disease etiology. This success story has two angles that are often overlooked. First, GWAS findings are highly replicable. This is an unprecedented phenomenon in complex trait genetics, and indeed in many areas of science, which in past decades have been plagued by false positives. At a time of increasing concerns about the lack of reproducibility, we examine the biological and methodological reasons that account for the replicability of GWAS and identify the challenges ahead. In contrast to the exemplary success of disease gene discovery, at present GWAS findings are not useful for predicting phenotypes. We close with an overview of the prospects for individualized prediction of disease risk and its foreseeable impact in clinical practice.

Population genetics and GWAS: A primer.

This primer provides some background to help non-specialists understand a new theoretical evolutionary genetics study that helps explain why thousands of variants of small effect contribute to complex traits.

Derivation of notochordal cells from human embryonic stem cells reveals unique regulatory networks by single cell-transcriptomics.

Intervertebral disc degeneration (IDD) is a public health dilemma as it is associated with low back and neck pain, a frequent reason for patients to visit the physician. During IDD, nucleus pulposus (NP), the central compartment of intervertebral disc (IVD) undergo degeneration. Stem cells have been adopted as a promising biological source to regenerate the IVD and restore its function. Here, we describe a simple, two-step differentiation strategy using a cocktail of four factors (LDN, AGN, FGF, and CHIR) for efficient derivation of notochordal cells from human embryonic stem cells (hESCs). We employed a CRISPR/Cas9 based genome-editing approach to knock-in the mCherry reporter vector upstream of the 3' untranslated region of the Noto gene in H9-hESCs and monitored notochordal cell differentiation. Our data show that treatment of H9-hESCs with the above-mentioned four factors for 6 days successfully resulted in notochordal cells. These cells were characterized by morphology, immunostaining, and gene and protein expression analyses for established notochordal cell markers including FoxA2, SHH, and Brachyury. Additionally, pan-genomic high-throughput single cell RNA-sequencing revealed an efficient and robust notochordal differentiation. We further identified a key regulatory network consisting of eight candidate genes encoding transcription factors including PAX6, GDF3, FOXD3, TDGF1, and SOX5, which are considered as potential drivers of notochordal differentiation. This is the first single cell transcriptomic analysis of notochordal cells derived from hESCs. The ability to efficiently obtain notochordal cells from pluripotent stem cells provides an additional tool to develop new cell-based therapies for the treatment of IDD.