Polygenic Contribution Research Articles

Low Penetrance Sarcomere Variants Contribute to Additive Risk in Hypertrophic Cardiomyopathy.

Classically, hypertrophic cardiomyopathy (HCM) has been viewed as a single-gene (monogenic) disease caused by pathogenic variants in sarcomere genes. Pathogenic sarcomere variants are individually rare and convey high risk for developing HCM (highly penetrant). Recently, important polygenic contributions have also been characterized. Low penetrance sarcomere variants (LowSVs) at intermediate frequencies and effect sizes have not been systematically investigated. We hypothesize that LowSVs may be common in HCM with substantial influence on disease risk and severity. Among all sarcomere variants observed in the Sarcomeric Human Cardiomyopathy Registry (SHaRe), we identified putative LowSVs defined by (1) population frequency greater than expected for highly penetrant (monogenic) HCM (allele frequency >5×10-5 in the Genome Aggregation Database, gnomAD) and (2) moderate enrichment (>2×) in patients with HCM compared with gnomAD. LowSVs were examined for their association with disease severity and clinical outcomes. Functional effects of selected LowSVs were assessed using induced pluripotent stem cell-derived cardiomyocytes. Association of LowSVs with HCM-adjacent traits in the general population was tested using UK Biobank cardiac magnetic resonance imaging data. Among 6045 patients and 1159 unique variants in sarcomere genes, 12 LowSVs were identified. LowSVs were collectively common in the general population (1:350) and moderately enriched in HCM (aggregate odds ratio, 14.9 [95% CI, 12.5-17.9]). Isolated LowSVs were associated with an older age of HCM diagnosis and fewer adverse events. However, LowSVs in combination with a pathogenic sarcomere variant conferred higher morbidity (eg, composite adverse event hazard ratio, 5.4 [95% CI, 3.0-9.8] versus single pathogenic sarcomere variant, 2.0 [95% CI, 1.8-2.2]; P<0.001). An intermediate functional impact was validated for 2 specific LowSVs-MYBPC3 c.442G>A (partial splice gain) and TNNT2 c.832C>T (intermediate effect on contractile mechanics). Cardiac magnetic resonance imaging analysis of the general population revealed 5 of 12 LowSVs were significantly associated with HCM-adjacent traits without overt HCM. This study establishes a new class of low penetrance sarcomere variants that are relatively common in the population. When penetrant, isolated LowSVs cause mild HCM. In combination with pathogenic sarcomere variants, LowSVs markedly increase disease severity, supporting a clinically significant additive effect. Last, LowSVs also contribute to age-related remodeling even in the absence of overt HCM.

Abstract 4127792: Age-stratified Monogenic and Polygenic Contributions for Atrial Fibrillation in the All of Us Research Program

Background: Rare and common genetic variation both contribute to atrial fibrillation (AF), but the effects may not be uniform across ages. The All of Us Research Program contains whole-genome sequencing of 100,574 adult participants with electronic health records. Hypothesis: Rare genetic variants are associated with early-onset AF; common genetic variants are associated with late-onset AF. Aims: To quantify the diagnostic yield provided by rare and common genetic variation in AF across age. Methods: The clinical, monogenic, and polygenic contributions to AF were assessed in a cross-sectional group of participants in the NIH-funded All of Us Research Program, stratified by three age groups: &lt;45 years (n=22,290), 45-60 years (n= 26,805), &gt;60 years (n=51,659). Variant discovery was performed for pathogenic or likely pathogenic (P/LP) variants among 145 candidate cardiac genes with dominant inheritance for cardiomyopathy and arrhythmia. A previously established polygenic risk score (PRS) was calculated. After adjusting for known clinical factors, multivariable analysis quantified the associations between monogenic and polygenic factors versus AF status in each age group. Results: There were 100,574 participants: 7,811 with AF and 92,763 without AF. The presence of ≥1 P/LP variant(s) were associated with AF across all age groups, with stronger associations in the age &lt;45 group (OR 2.3 [95% CI 1.4-4.1]) compared older groups (OR 1.5 [95% CI 1.1-2.1] in age 45-60, and OR 1.4 [95% CI 1.2-1.7] in age &gt;60). In contrast, PRS was not associated with AF in participants &lt;45 years (OR 1.02 [95% CI 0.88-1.17]) but was associated with AF in the older groups: OR 1.54 [95% CI 1.31-1.80] in age 45-60 and OR 1.49 [95% CI 1.40-1.59] for age &gt;60. Overall, clinical risk factors are highly associated with AF (AUC 0.84 [0.83-0.85]); adding polygenic and monogenic factors contribute only marginal improvement (AUC 0.86 [0.85-0.87]). Conclusion: In this cross-sectional dataset, monogenic and polygenic factors have opposite associations with AF. Monogenic variants are associated with early-onset AF, whereas PRS has no association with AF at younger ages. Clinical risk factors continue to explain the majority of the variation in AF status.

Common polygenic variation in the early medication change (EMC) cohort affects disorder risk, but not the antidepressant treatment response

BackgroundGiven the great interest in identifying reliable predictors of the response to antidepressant drugs, the present study investigated whether polygenic scores (PGS) for Major Depressive Disorder (MDD) and antidepressant treatment response (ADR) were related to the complex trait of antidepressant response in the Early Medication Change (EMC) cohort. MethodsIn this secondary analysis of the EMC trial (N = 889), 481 MDD patients were included and compared to controls from a population-based cohort. Patients were treated over eight weeks within a pre-defined treatment-algorithm. We investigated patients' genetic variation associated with MDD and ADR, using PGS and examined the association of PGS with treatment outcomes (early improvement, response, remission). Additionally, the influence of two cytochrome P450 drug-metabolizing enzymes (CYP2C19, CYP2D6) was determined. ResultsPGS for MDD was significantly associated with disorder status (NkR2 = 2.48 %, p < 1*10−12), with higher genetic burden in EMC patients compared to controls. The PGS for ADR did not explain remission status. The PGS for MDD and ADR were also not associated with treatment outcomes. In addition, there were no effects of common CYP450 gene variants on ADR. LimitationsThe study was limited by variability in the outcome parameters due to differences in treatment and insufficient sample size in the used ADR genome-wide association study (GWAS). ConclusionsThe present study confirms a polygenic contribution to MDD burden in the EMC patients. Larger GWAS with homogeneity in antidepressant treatments are needed to explore the genetic variation associated with ADR and realize the potential of PGS to contribute to specific response subtypes.

#1761 Whole-genome sequencing reveals contribution of rare and common variation to structural kidney and urinary tract malformations

Abstract Background and Aims Structural kidney and urinary tract malformations are the commonest cause of kidney failure in children and young adults. Targeted and whole-exome sequencing has identified over 50 monogenic causes for these phenotypically heterogeneous conditions but have largely focused on cohorts enriched for familial, syndromic, or consanguineous disease. We sought to better characterise the genetic architecture of these conditions using whole genome sequencing (WGS) data from the UK's 100 000 Genomes Project. Method 992 unrelated individuals with structural kidney and urinary tract malformations were assessed using the Genomics England clinical interpretation pipeline to determine a genetic diagnosis. Statistically robust case-control association testing was performed using WGS data from a subset of 813 patients and 25 205 ancestry-matched unaffected individuals seeking enrichment of common and rare single-nucleotide and structural variants (SNV/SVs) on a genome-wide, per-gene, and cis-regulatory element basis. Heritability analysis was carried out in 623 cases and 20 060 controls of European ancestry with polygenic risk scores (PRS) derived for each of the six phenotypes. The PUV-PRS was validated in an independent cohort of 77 patients from the AGORA data- and biobank and an additional 2 746 European controls. Results The overall diagnostic yield was 4.3% (43/992; Fig. 1) with age &amp;lt; 18 years (P = 2.0 × 10−4), family history (P = 7.5 × 10−3) and extra-renal features (P = 1.9 × 10−4) all independent predictors of a genetic diagnosis. The diagnostic yield was higher in cases with cystic kidney dysplasia (10.7%) or kidney anomalies (5.9%). HNF1B was the most frequently identified cause. Exome-wide rare variant analysis identified enrichment of SNV/indels affecting AUTS2 (P = 3.7 × 10−6), ARHGAP5 (P=6.0 × 10−6), known kidney malformation gene HNF1B (P = 6.1 × 10−6), and ZNF879 (P=7.0 × 10−6), all of which have been previously implicated in developmental and/or cancer pathways. An increased burden of rare SVs affecting HNF1B (P = 3.1 × 10−4) was observed. There was no evidence of enrichment for cis-regulatory element disrupting SVs. Genome-wide testing of 19 million common and low-frequency variants (minor allele frequency &amp;gt; 0.1%) did not detect any individual variants that were significantly associated in the total cohort, but together these variants were estimated to contribute to 23% (standard error 11%) of the heritability of kidney and urinary tract malformations in cases with European ancestry. Comparison of phenotype-specific PRS showed considerable overlap between kidney anomalies, cystic kidney dysplasia, obstructive uropathy and vesico-ureteric reflux but the polygenic contribution to PUV and bladder exstrophy was distinct (Fig. 2). A PUV-PRS consisting of 36, 106 variants was validated in an independent European cohort of 77 cases and 2 746 controls (empirical P = 1 × 10−4). Conclusion We show that non-Mendelian genomic factors are important for the pathogenesis of structural kidney and urinary tract malformations, supported by the observation that a minority of patients in this large unselected cohort have a monogenic diagnosis. In addition, a significant proportion of heritability can be attributed to common and low-frequency variation and there is overlap in the polygenic contributors to upper urinary tract malformations with distinct polygenic signatures relevant to PUV and bladder exstrophy. Larger cohorts of patients are needed to increase power to detect variants contributing to this heritability and identify biological mechanisms and pathways important for kidney and urinary tract development.

Dissecting the polygenic contribution of attention-deficit/hyperactivity disorder and autism spectrum disorder on school performance by their relationship with educational attainment

Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorders (ASD) are strongly associated with educational attainment (EA), but little is known about their genetic relationship with school performance and whether these links are explained, in part, by the genetic liability of EA. Here, we aim to dissect the polygenic contribution of ADHD and ASD to school performance, early manifestation of psychopathology and other psychiatric disorders and related traits by their relationship with EA. To do so, we tested the association of polygenic scores for EA, ADHD and ASD with school performance, assessed whether the contribution of the genetic liability of ADHD and ASD to school performance is influenced by the genetic liability of EA, and evaluated the role of EA in the genetic overlap between ADHD and ASD with early manifestation of psychopathology and other psychiatric disorders and related traits in a sample of 4,278 school-age children. The genetic liability for ADHD and ASD dissected by their relationship with EA show differences in their association with school performance and early manifestation of psychopathology, partly mediated by ADHD and ASD symptoms. Genetic variation with concordant effects in ASD and EA contributes to better school performance, while the genetic variation with discordant effects in ADHD or ASD and EA is associated with poor school performance and higher rates of emotional and behavioral problems. Our results strongly support the usage of the genetic load for EA to dissect the genetic and phenotypic heterogeneity of ADHD and ASD, which could help to fill the gap of knowledge of mechanisms underlying educational outcomes.

Deep learning of left atrial structure and function provides link to atrial fibrillation risk

Increased left atrial volume and decreased left atrial function have long been associated with atrial fibrillation. The availability of large-scale cardiac magnetic resonance imaging data paired with genetic data provides a unique opportunity to assess the genetic contributions to left atrial structure and function, and understand their relationship with risk for atrial fibrillation. Here, we use deep learning and surface reconstruction models to measure left atrial minimum volume, maximum volume, stroke volume, and emptying fraction in 40,558 UK Biobank participants. In a genome-wide association study of 35,049 participants without pre-existing cardiovascular disease, we identify 20 common genetic loci associated with left atrial structure and function. We find that polygenic contributions to increased left atrial volume are associated with atrial fibrillation and its downstream consequences, including stroke. Through Mendelian randomization, we find evidence supporting a causal role for left atrial enlargement and dysfunction on atrial fibrillation risk.

Exposomic and polygenic contributions to allostatic load in early adolescence

Exposomic and polygenic contributions to allostatic load in early adolescence

Exposomic and Polygenic Contributions to Allostatic Load in Early Adolescence

Exposomic and Polygenic Contributions to Allostatic Load in Early Adolescence

What Causes Premature Coronary Artery Disease?

This review provides an overview of genetic and non-genetic causes of premature coronary artery disease (pCAD). pCAD refers to coronary artery disease (CAD) occurring before the age of 65years in women and 55years in men. Both genetic and non-genetic risk factors may contribute to the onset of pCAD. Recent advances in the genetic epidemiology of pCAD have revealed the importance of both monogenic and polygenic contributions to pCAD. Familial hypercholesterolemia (FH) is the most common monogenic disorder associated with atherosclerotic pCAD. However, clinical overreliance on monogenic genes can result in overlooked genetic causes of pCAD, especially polygenic contributions. Non-genetic factors, notably smoking and drug use, are also important contributors to pCAD. Cigarette smoking has been observed in 25.5% of pCAD patients relative to 12.2% of non-pCAD patients. Finally, myocardial infarction (MI) associated with spontaneous coronary artery dissection (SCAD) may result in similar clinical presentations as atherosclerotic pCAD. Recognizing the genetic and non-genetic causes underlying pCAD is important for appropriate prevention and treatment. Despite recent progress, pCAD remains incompletely understood, highlighting the need for both awareness and research.

(379) - Monogenic and Polygenic Contributions to Early Onset Advanced Heart Failure Based on Whole Genome Sequencing

(379) - Monogenic and Polygenic Contributions to Early Onset Advanced Heart Failure Based on Whole Genome Sequencing

Genome-Wide Association Study of Obsessive-Compulsive Symptoms including 33,943 individuals from the general population.

While 1-2% of individuals meet the criteria for a clinical diagnosis of obsessive-compulsive disorder (OCD), many more (~13-38%) experience subclinical obsessive-compulsive symptoms (OCS) during their life. To characterize the genetic underpinnings of OCS and its genetic relationship to OCD, we conducted the largest genome-wide association study (GWAS) meta-analysis of parent- or self-reported OCS to date (N = 33,943 with complete phenotypic and genome-wide data), combining the results from seven large-scale population-based cohorts from Sweden, the Netherlands, England, and Canada (including six twin cohorts and one cohort of unrelated individuals). We found no genome-wide significant associations at the single-nucleotide polymorphism (SNP) or gene-level, but a polygenic risk score (PRS) based on the OCD GWAS previously published by the Psychiatric Genetics Consortium (PGC-OCD) was significantly associated with OCS (Pfixed = 3.06 × 10-5). Also, one curated gene set (Mootha Gluconeogenesis) reached Bonferroni-corrected significance (Ngenes = 28, Beta = 0.79, SE = 0.16, Pbon = 0.008). Expression of genes in this set is high at sites of insulin mediated glucose disposal. Dysregulated insulin signaling in the etiology of OCS has been suggested by a previous study describing a genetic overlap of OCS with insulin signaling-related traits in children and adolescents. We report a SNP heritability of 4.1% (P = 0.0044) in the meta-analyzed GWAS, and heritability estimates based on the twin cohorts of 33-43%. Genetic correlation analysis showed that OCS were most strongly associated with OCD (rG = 0.72, p = 0.0007) among all tested psychiatric disorders (N = 11). Of all 97 tested phenotypes, 24 showed a significant genetic correlation with OCS, and 66 traits showed concordant directions of effect with OCS and OCD. OCS have a significant polygenic contribution and share genetic risk with diagnosed OCD, supporting the hypothesis that OCD represents the extreme end of widely distributed OCS in the population.

Two polygenic mouse models of major depressive disorders identify TMEM161B as a potential biomarker of disease in humans.

Treatments are only partially effective in major depressive disorders (MDD) but no biomarker exists to predict symptom improvement in patients. Animal models are essential tools in the development of antidepressant medications, but while recent genetic studies have demonstrated the polygenic contribution to MDD, current models are limited to either mimic the effect of a single gene or environmental factor. We developed in the past a model of depressive-like behaviors in mice (H/Rouen), using selective breeding based on behavioral reaction after an acute mild stress in the tail suspension test. Here, we propose a new mouse model of depression (H-TST) generated from a more complex genetic background and based on the same selection process. We first demonstrated that H/Rouen and H-TST mice had similar phenotypes and were more sensitive to glutamate-related antidepressant medications than selective serotonin reuptake inhibitors. We then conducted an exome sequencing on the two mouse models and showed that they had damaging variants in 174 identical genes, which have also been associated with MDD in humans. Among these genes, we showed a higher expression level of Tmem161b in brain and blood of our two mouse models. Changes in TMEM161B expression level was also observed in blood of MDD patients when compared with controls, and after 8-week treatment with duloxetine, mainly in good responders to treatment. Altogether, our results introduce H/Rouen and H-TST as the two first polygenic animal models of MDD and demonstrate their ability to identify biomarkers of the disease and to develop rapid and effective antidepressant medications.

Whole exome sequencing and polygenic assessment of a Swedish cohort with severe developmental language disorder

Developmental language disorder (DLD) overlaps clinically, genetically, and pathologically with other neurodevelopmental disorders (NDD), corroborating the concept of the NDD continuum. There is a lack of studies to understand the whole genetic spectrum in individuals with DLD. Previously, we recruited 61 probands with severe DLD from 59 families and examined 59 of them and their families using microarray genotyping with a 6.8% diagnostic yield. Herein, we investigated 53 of those probands using whole exome sequencing (WES). Additionally, we used polygenic risk scores (PRS) to understand the within family enrichment of neurodevelopmental difficulties and examine the associations between the results of language-related tests in the probands and language-related PRS. We identified clinically significant variants in four probands, resulting in a 7.5% (4/53) molecular diagnostic yield. Those variants were in PAK2, MED13, PLCB4, and TNRC6B. We also prioritized additional variants for future studies for their role in DLD, including high-impact variants in PARD3 and DIP2C. PRS did not explain the aggregation of neurodevelopmental difficulties in these families. We did not detect significant associations between the language-related tests and language-related PRS. Our results support using WES as the first-tier genetic test for DLD as it can identify monogenic DLD forms. Large-scale sequencing studies for DLD are needed to identify new genes and investigate the polygenic contribution to the condition.

The polygenic implication of clopidogrel responsiveness: Insights from platelet reactivity analysis and next-generation sequencing.

Clopidogrel is widely used worldwide as an antiplatelet therapy in patients with acute coronary disease. Genetic factors influence interindividual variability in response. Some studies have explored the polygenic contributions in the drug response, generating pharmacogenomic risk scores (PgxPRS). Importantly, these factors are less explored in underrepresented populations, such as Latin-American countries. Identifying patients at risk of high-on-treatment platelet reactivity (HTPR) is highly valuable in translational medicine. In this study we used a custom next-generation sequencing (NGS) panel composed of 91 single nucleotide polymorphisms (SNPs) and 28 genes related to clopidogrel metabolism, to analyze 70 patients with platelet reactivity values, assessed through closure time (CT). Our results demonstrated the association of SNPs with HTPR and non-HTPR, revealing the strongest associations with rs2286823 (OR: 5,0; 95% CI: 1,02-24,48; p: 0,03), rs2032582 (OR: 4,41; 95% CI: 1,20-16,12; p: 0,019), and rs1045642 (OR: 3,38; 95% CI: 0,96-11,9; p: 0,05). Bivariate regression analysis demonstrated the significant association of several SNPs with the CT value, a "surrogate" biomarker of clopidogrel response. Exploratory results from the LASSO regression model showed a high discriminatory capacity between HTPR and non-HTPR patients (AUC: 0,955), and the generated PgxPRS demonstrated a significant negative association between the risk score, CT value, and the condition of HTPR and non-HTPR. To our knowledge, our study addresses for the first time the analysis of the polygenic contribution in platelet reactivity using NGS and establishes PgxPRS derived from the LASSO model. Our results demonstrate the polygenic implication of clopidogrel response and offer insights applicable to the translational medicine of antiplatelet therapy in an understudied population.

Abstract 15706: Common- and Rare-Variant Genetic Architecture of Heart Failure Across the Allele Frequency Spectrum

Background: Heart failure (HF) is a complex trait influenced by environmental and genetic factors. Genome-wide association studies (GWAS) have found common genetic variants associated with HF risk, but the extent that common and rare variants explain risk and implicate similar genes and pathways in HF remains less understood. Methods: For common variants, we meta-analyze existing GWAS of all-cause HF with data from the Million Veteran Program, including 207,346 individuals with HF and 2,151,210 without in diverse populations. We examine rare coding variants in the Penn Medicine BioBank (PMBB) using gene-collapsing association studies and burden heritability regression. We test for an interaction between a polygenic risk score (PRS) based on our GWAS meta-analysis and truncating variants in TTN (TTNtv). Results: GWAS meta-analysis identified 176 risk loci (146 previously unreported), implicating known risk factors for HF and genes involved in cardiac development. New signals at GIPR/ GLP1R highlight potential contributions of dysregulated glucose homeostasis and metabolism in HF. Gene collapsing studies identified associations between HF and rare loss-of-function variants in TTN (OR 2.94, 95% CI 2.43-3.56) and MYBPC3 (OR 7.71, 95% CI 3.97-14.97) at exome-wide significance. HF heritability mediated through common variants (4.5%) was significantly higher than for rare variants (1.8%), but rare variant heritability was further enriched in cardiomyopathy genes compared to common variants (27-fold vs. 3.4-fold). We found a significant interaction between a new multi-ancestry HF-associated PRS (AUC 0.72, 95% CI 0.72-0.73) and TTNtv carrier status (interaction OR 1.32, 95% CI 1.06-1.64). Conclusions: Common and rare variants contribute to HF heritability. Common variant HF heritability is highly polygenic, while rare variant burden heritability appears more concentrated in core cardiomyopathy genes. HF risk conferred by TTNtv carrier status is further increased by an individual’s polygenic contribution. Our results support the continued inclusion of cardiomyopathy genes in rare-variant genetic testing panels for HF but suggest a meaningful polygenic component to HF exists that is not currently captured by clinical genetic testing.

Polygenic contributions to performance on the Balloon Analogue Risk Task

Risky decision-making is a common, heritable endophenotype seen across many psychiatric disorders. Its underlying genetic architecture is incompletely explored. We examined behavior in the Balloon Analogue Risk Task (BART), which tests risky decision-making, in two independent samples of European ancestry. One sample (n = 1138) comprised healthy participants and some psychiatric patients (53 schizophrenia, 42 bipolar disorder, 47 ADHD); the other (n = 911) excluded for recent treatment of various psychiatric disorders but not ADHD. Participants provided DNA and performed the BART, indexed by mean adjusted pumps. We constructed a polygenic risk score (PRS) for discovery in each dataset and tested it in the other as replication. Subsequently, a genome-wide MEGA-analysis, combining both samples, tested genetic correlation with risk-taking self-report in the UK Biobank sample and psychiatric phenotypes characterized by risk-taking (ADHD, Bipolar Disorder, Alcohol Use Disorder, prior cannabis use) in the Psychiatric Genomics Consortium. The PRS for BART performance in one dataset predicted task performance in the replication sample (r = 0.13, p = 0.000012, pFDR = 0.000052), as did the reciprocal analysis (r = 0.09, p = 0.0083, pFDR=0.04). Excluding participants with psychiatric diagnoses produced similar results. The MEGA-GWAS identified a single SNP (rs12023073; p = 3.24 × 10−8) near IGSF21, a protein involved in inhibitory brain synapses; replication samples are needed to validate this result. A PRS for self-reported cannabis use (p = 0.00047, pFDR = 0.0053), but not self-reported risk-taking or psychiatric disorder status, predicted behavior on the BART in our MEGA-GWAS sample. The findings reveal polygenic architecture of risky decision-making as measured by the BART and highlight its overlap with cannabis use.

Variant-based heritability assessment of dexmedetomidine and fentanyl clearance in pediatric patients.

Despite complex pathways of drug disposition, clinical pharmacogenetic predictors currently rely on only a few high effect variants. Quantification of the polygenic contribution to variability in drug disposition is necessary to prioritize target drugs for pharmacogenomic approaches and guide analytic methods. Dexmedetomidine and fentanyl, often used in postoperative care of pediatric patients, have high rates of inter-individual variability in dosing requirements. Analyzing previously generated population pharmacokinetic parameters, we used Bayesian hierarchical mixed modeling to measure narrow-sense (additive) heritability ( ) of dexmedetomidine and fentanyl clearance in children and identify relative contributions of small, moderate, and large effect-size variants to . We used genome-wide association studies (GWAS) to identify variants contributing to variation in dexmedetomidine and fentanyl clearance, followed by functional analyses to identify associated pathways. For dexmedetomidine, median clearance was 33.0 L/h (interquartile range [IQR] 23.8-47.9 L/h) and was estimated to be 0.35 (90% credible interval 0.00-0.90), with 45% of attributed to large-, 32% to moderate-, and 23% to small-effect variants. The fentanyl cohort had median clearance of 8.2 L/h (IQR 4.7-16.7 L/h), with estimated of 0.30 (90% credible interval 0.00-0.84). Large-effect variants accounted for 30% of , whereas moderate- and small-effect variants accounted for 37% and 33%, respectively. As expected, given small sample sizes, no individual variants or pathways were significantly associated with dexmedetomidine or fentanyl clearance by GWAS. We conclude that clearance of both drugs is highly polygenic, motivating the future use of polygenic risk scores to guide appropriate dosing of dexmedetomidine and fentanyl.

Discovering cellular programs of intrinsic and extrinsic drivers of metabolic traits using LipocyteProfiler

A primary obstacle in translating genetic associations with disease into therapeutic strategies is elucidating the cellular programs affected by genetic risk variants and effector genes. Here, we introduce LipocyteProfiler, a cardiometabolic-disease-oriented high-content image-based profiling tool that enables evaluation of thousands of morphological and cellular profiles that can be systematically linked to genes and genetic variants relevant to cardiometabolic disease. We show that LipocyteProfiler allows surveillance of diverse cellular programs by generating rich context- and process-specific cellular profiles across hepatocyte and adipocyte cell-state transitions. We use LipocyteProfiler to identify known and novel cellular mechanisms altered by polygenic risk of metabolic disease, including insulin resistance, fat distribution, and the polygenic contribution to lipodystrophy. LipocyteProfiler paves the way for large-scale forward and reverse deep phenotypic profiling in lipocytes and provides a framework for the unbiased identification of causal relationships between genetic variants and cellular programs relevant to human disease.

The genetic contribution to the comorbidity of depression and anxiety: a multi-site electronic health records study of almost 178 000 people.

Depression and anxiety are common and highly comorbid, and their comorbidity is associated with poorer outcomes posing clinical and public health concerns. We evaluated the polygenic contribution to comorbid depression and anxiety, and to each in isolation. Diagnostic codes were extracted from electronic health records for four biobanks [N = 177 865 including 138 632 European (77.9%), 25 612 African (14.4%), and 13 621 Hispanic (7.7%) ancestry participants]. The outcome was a four-level variable representing the depression/anxiety diagnosis group: neither, depression-only, anxiety-only, and comorbid. Multinomial regression was used to test for association of depression and anxiety polygenic risk scores (PRSs) with the outcome while adjusting for principal components of ancestry. In total, 132 960 patients had neither diagnosis (74.8%), 16 092 depression-only (9.0%), 13 098 anxiety-only (7.4%), and 16 584 comorbid (9.3%). In the European meta-analysis across biobanks, both PRSs were higher in each diagnosis group compared to controls. Notably, depression-PRS (OR 1.20 per s.d. increase in PRS; 95% CI 1.18-1.23) and anxiety-PRS (OR 1.07; 95% CI 1.05-1.09) had the largest effect when the comorbid group was compared with controls. Furthermore, the depression-PRS was significantly higher in the comorbid group than the depression-only group (OR 1.09; 95% CI 1.06-1.12) and the anxiety-only group (OR 1.15; 95% CI 1.11-1.19) and was significantly higher in the depression-only group than the anxiety-only group (OR 1.06; 95% CI 1.02-1.09), showing a genetic risk gradient across the conditions and the comorbidity. This study suggests that depression and anxiety have partially independent genetic liabilities and the genetic vulnerabilities to depression and anxiety make distinct contributions to comorbid depression and anxiety.

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.