Prior Genome-wide Association Studies Research Articles

Drinking motives and alcohol sensitivity mediate multi-dimensional genetic influences on alcohol use behaviors.

Genetic influences account for a substantial proportion of individual differences in alcohol use behaviors (AUBs). However, multiple distinct sets of genes are linked to different AUBs, which may explain their dramatic variability in risk factors and manifestations. In this study, we explore whether intermediate neurobiological traits and alcohol-related cognitions mediate the relationship between polygenic scores (PGS) and multiple AUBs, with the aim to better understand processes captured by different genetic profiles. Using results from prior genome-wide association studies, we derived PGS for 6 AUBs in participants from Spit for Science, a longitudinal study of college students in the U.S. (n=4,549). Self-report measures included personality traits, alcohol expectancies, drinking motivations, and alcohol sensitivity measures as well as drinking frequency, drinking quantity, alcohol use disorder (AUD) symptoms, and maximum drinks in 24 hours. Using linear regression and multiple mediation models, we investigated the direct and indirect effects of PGS on AUBs. In univariable regression results, PGSs indexing broad AUB dimensions such as drinks per week (DPW) and AUD predicted higher levels of sensation-seeking and multiple drinking motives, while BeerPref PGSs (indexing a variable pattern of alcohol problems associated with a preference for beer) predicted higher negative urgency and lower alcohol sensitivity. Mediational models indicated strong direct and indirect effects of DPW PGSs on multiple AUBs via social/enhancement drinking motives and alcohol sensitivity, indirect effects of AUD PGSs on AUD symptoms via coping motives, and indirect effects of BeerPref PGS on all AUBs via the joint effect of mediators including alcohol sensitivity. These findings provide initial evidence that the genetic influences on different AUBs are associated with and partially mediated by intermediate neurobiological and cognitive factors, which may be more amenable to intervention. Greater focus on drinking motives and alcohol sensitivity is warranted in genetic research, as well as attention to the heterogeneous pathways linking genes to alcohol use outcomes.

G protein–coupled receptor kinase 5 regulates thrombin signaling in platelets

BackgroundOur prior genome-wide association study of thrombin-induced platelet aggregation identified a G protein–coupled receptor kinase 5 (GRK5) noncoding variant (rs10886430-G) that is strongly associated with increased platelet reactivity to thrombin. This variant predisposes to increased risk of stroke, pulmonary embolism, and venous thromboembolism. ObjectivesTo determine role of platelet specific GRK5 in platelet responses to agonists and injury. MethodsPlatelets from GRK5 mutant mice have been shown to have increased thrombin sensitivity, indicating that GRK5 may be a negative regulator of platelet activation. However, this has not been studied in a platelet-specific manner. We therefore used platelet-specific GRK5 mutant mice and models of thrombosis and pulmonary embolism. ResultsWe now demonstrate that mice lacking GRK5 specifically in platelets had a mild increase in thrombin responses in vitro and a shortened time to arterial thrombosis in vivo. In addition, platelet GRK5 mutant mice had increased thrombin but not collagen-induced thrombus burden in a mouse model of pulmonary embolism. ConclusionThese data indicate that platelet GRK5 has a significant role in limiting platelet responses to thrombin.

3D genomic features across >50 diverse cell types reveal insights into the genomic architecture of childhood obesity.

The prevalence of childhood obesity is increasing worldwide, along with the associated common comorbidities of type 2 diabetes and cardiovascular disease in later life. Motivated by evidence for a strong genetic component, our prior genome-wide association study (GWAS) efforts for childhood obesity revealed 19 independent signals for the trait; however, the mechanism of action of these loci remains to be elucidated. To molecularly characterize these childhood obesity loci we sought to determine the underlying causal variants and the corresponding effector genes within diverse cellular contexts. Integrating childhood obesity GWAS summary statistics with our existing 3D genomic datasets for 57 human cell types, consisting of high-resolution promoter-focused Capture-C/Hi-C, ATAC-seq, and RNA-seq, we applied stratified LD score regression and calculated the proportion of genome-wide SNP heritability attributable to cell type-specific features, revealing pancreatic alpha cell enrichment as the most statistically significant. Subsequent chromatin contact-based fine-mapping was carried out for genome-wide significant childhood obesity loci and their linkage disequilibrium proxies to implicate effector genes, yielded the most abundant number of candidate variants and target genes at the BDNF, ADCY3, TMEM18 and FTO loci in skeletal muscle myotubes and the pancreatic beta-cell line, EndoC-BH1. One novel implicated effector gene, ALKAL2 - an inflammation-responsive gene in nerve nociceptors - was observed at the key TMEM18 locus across multiple immune cell types. Interestingly, this observation was also supported through colocalization analysis using expression quantitative trait loci (eQTL) derived from the Genotype-Tissue Expression (GTEx) dataset, supporting an inflammatory and neurologic component to the pathogenesis of childhood obesity. Our comprehensive appraisal of 3D genomic datasets generated in a myriad of different cell types provides genomic insights into pediatric obesity pathogenesis.

Regulation of MicroRNA-4697-3p by Parkinson's disease-associated SNP rs329648 and its impact on SNCA112 mRNA.

Parkinson's disease (PD) is a common neurodegenerative disorder characterized by a multifaceted genetic foundation. Genome-Wide Association Studies (GWAS) have played a crucial role in pinpointing genetic variants linked to PD susceptibility. Current study aims to delve into the mechanistic aspects through which the PD-associated Single Nucleotide Polymorphism (SNP) rs329648, identified in prior GWAS, influences the pathogenesis of PD. Employing the CRISPR/Cas9-mediated genome editing mechanism, we demonstrated the association of the disease-associated allele of rs329648 with increased expression of miR-4697-3p in differentiated SH-SY5Y cells. We revealed that miR-4697-3p contributes to the formation of high molecular weight complexes of α-Synuclein (α-Syn), indicative of α-Syn aggregate formation, as evidenced by Western blot analysis. Furthermore, our study unveiled that miR-4697-3p elevates SNCA112 mRNA levels. The resultant protein product, α-Syn 112, a variant of α-Syn with 112 amino acids, is recognized for augmenting α-Syn aggregation. Notably, this regulatory effect minimally impacts the levels of full-length SNCA140 mRNA, as evidenced by qRT-PCR. Additionally, we observed a correlation between the disease-associated allele and miR-4697-3p with increased cell death, substantiated by assessments including cell viability assays, alterations in cell morphology, and TUNEL assays. Our research reveals that the disease-associated allele of rs329648 is linked to higher levels of miR-4697-3p. This increase in miR-4697-3p leads to elevated SNCA112 mRNA levels, consequently promoting the formation of α-Syn aggregates. Furthermore, miR-4697-3p appears to play a role in increased cell death, potentially contributing to the pathogenesis of PD.

Meta-Analysis of Genome-Wide Association Studies Reveals Genetic Mechanisms of Supraventricular Arrhythmias.

Substantial data support a heritable basis for supraventricular tachycardias, but the genetic determinants and molecular mechanisms of these arrhythmias are poorly understood. We sought to identify genetic loci associated with atrioventricular nodal reentrant tachycardia (AVNRT) and atrioventricular accessory pathways or atrioventricular reciprocating tachycardia (AVAPs/AVRT). We performed multiancestry meta-analyses of genome-wide association studies to identify genetic loci for AVNRT (4 studies) and AVAP/AVRT (7 studies). We assessed evidence supporting the potential causal effects of candidate genes by analyzing relations between associated variants and cardiac gene expression, performing transcriptome-wide analyses, and examining prior genome-wide association studies. Analyses comprised 2384 AVNRT cases and 106 489 referents, and 2811 AVAP/AVRT cases and 1,483 093 referents. We identified 2 significant loci for AVNRT, which implicate NKX2-5 and TTN as disease susceptibility genes. A transcriptome-wide association analysis supported an association between reduced predicted cardiac expression of NKX2-5 and AVNRT. We identified 3 significant loci for AVAP/AVRT, which implicate SCN5A, SCN10A, and TTN/CCDC141. Variant associations at several loci have been previously reported for cardiac phenotypes, including atrial fibrillation, stroke, Brugada syndrome, and electrocardiographic intervals. Our findings highlight gene regions associated with ion channel function (AVAP/AVRT), as well as cardiac development and the sarcomere (AVAP/AVRT and AVNRT) as important potential effectors of supraventricular tachycardia susceptibility.

Pooled DNA sequencing in hairy vetch (Vicia villosa Roth) reveals QTL for seed dormancy but not pod dehiscence.

Hairy vetch (Vicia villosa Roth) is a promising legume cover crop, but its use is limited by high rates of pod dehiscence and seed dormancy. We used phenotypically contrasting pooled DNA samples (n=24 with 29-74 individuals per sample) from an ongoing cover crop breeding program across four environments (site-year combinations: Maryland 2020, Maryland 2022, Wisconsin 2021, Wisconsin 2022) to find genetic associations and genomic prediction accuracies for pod dehiscence and seed dormancy. We also combined pooled DNA sample genetic association results with the results of a prior genome-wide association study. Genomic prediction resulted in positive predictive abilities for both traits between environments and with an independent dataset (0.34-0.50), but reduced predictive ability for DNA pools with divergent seed dormancy in the Maryland environments (0.07-0.15). The pooled DNA samples found six significant (false discovery rate q-value<0.01) quantitative trait loci (QTL) for seed dormancy and four significant QTL for pod dehiscence. Unfortunately, the minor alleles of the pod dehiscence QTL increased the rate of pod dehiscence and are not useful for marker-assisted selection. When combined with a prior association study, sixteen seed dormancy QTL and zero pod dehiscence QTL were significant. Combining the association studies did not increase the detection of useful QTL.

Investigating the Association of Polygenic Risk Scores With Thyroid Cancer Susceptibility in a Han Chinese Population.

Thyroid cancer, the leading endocrine tumor with a rising global incidence, especially in women, is influenced by both genetic and environmental factors. This study examines the relationship between polygenic risk scores (PRS) and thyroid cancer susceptibility in the Han Chinese population, as well as the impact of genetic variants on clinical outcomes. Analyzing data from 57 257 participants in the Taiwan Precision Medicine Initiative, the study employed the Affymetrix Genome-Wide TWB 2.0 SNP Array for genotyping. PRS were calculated using single nucleotide polymorphisms (SNPs) from prior genome-wide association studies, specifically PGS000087 and PGS000797, and correlated with clinical parameters like age, sex, comorbidities, and treatment methods. Among 4063 participants with thyroid tumors (839 malignant, 3224 benign), higher PRS quartiles correlated significantly with increased thyroid cancer incidence. The highest quartile showed a 1.15-fold (PGS000797) and 1.14-fold (PGS000087) greater risk than the lowest quartile. Key findings included an association between higher PRS quartiles and younger onset age, along with a notable link to chronic kidney disease and thyroid hormone levels in specific SNPs. The study demonstrates PRS's utility in predicting thyroid cancer risk in the Han Chinese population, with higher PRS associated with increased risk and distinct clinical features. While this study focuses on the Han Chinese population, we recognize the importance of comparing PRS performance across different ancestries to fully understand ethnic genetic diversity in cancer risk assessment. Future studies should aim to include such comparative analysis.

Investigating the association between genetically proxied circulating levels of immune checkpoint proteins and cancer survival: protocol for a Mendelian randomisation analysis

IntroductionCompared with the traditional drug development pathway, investigating alternative uses for existing drugs (ie, drug repurposing) requires substantially less time, cost and resources. Immune checkpoint inhibitors are licensed for the...

Distinct and shared genetic architectures of gestational diabetes mellitus and type 2 diabetes

Gestational diabetes mellitus (GDM) is a common metabolic disorder affecting more than 16 million pregnancies annually worldwide1,2. GDM is related to an increased lifetime risk of type 2 diabetes (T2D)1–3, with over a third of women developing T2D within 15 years of their GDM diagnosis. The diseases are hypothesized to share a genetic predisposition1–7, but few studies have sought to uncover the genetic underpinnings of GDM. Most studies have evaluated the impact of T2D loci only8–10, and the three prior genome-wide association studies of GDM11–13 have identified only five loci, limiting the power to assess to what extent variants or biological pathways are specific to GDM. We conducted the largest genome-wide association study of GDM to date in 12,332 cases and 131,109 parous female controls in the FinnGen study and identified 13 GDM-associated loci, including nine new loci. Genetic features distinct from T2D were identified both at the locus and genomic scale. Our results suggest that the genetics of GDM risk falls into the following two distinct categories: one part conventional T2D polygenic risk and one part predominantly influencing mechanisms disrupted in pregnancy. Loci with GDM-predominant effects map to genes related to islet cells, central glucose homeostasis, steroidogenesis and placental expression.

Causality of Blood Metabolites on Proliferative Diabetic Retinopathy: Insights From a Genetic Perspective.

Background: Our goal was to examine the causal link between blood metabolites, their ratios, and the risk of developing proliferative diabetic retinopathy (PDR) from a genetic insight. Methods: Summary-level data about 1400 blood metabolites and their ratios, as well as PDR, were sourced from prior genome-wide association studies (GWAS). A two-sample univariate and multivariate Mendelian randomization (MR) approach was utilized. Additionally, metabolic pathway analysis and sensitivity analysis were also conducted. Results: After adjusting for multiple tests, four blood metabolites significantly correlated with PDR risk. Two ceramides, including glycosyl-N-palmitoyl-sphingosine (d18:1/16:0) (odds ratio [OR] = 1.12, 95% confidence interval (CI): 1.06-1.17, p < 0.001, false discovery rate (FDR) = 0.005) and glycosyl-N-behenoyl-sphingadienine (d18:2/22:0) (OR = 1.11, 95% CI: 1.06-1.16, p < 0.001, FDR = 0.017), were linked to increased risk. Additionally, 3-methylcytidine (OR = 1.05, 95% CI: 1.03-1.08, p < 0.001, FDR = 0.021) also posed a risk, whereas (N(1)+N(8))-acetylspermidine (OR = 0.91, 95% CI: 0.87-0.94, p < 0.001, FDR = 0.002) appeared protective. Multivariable MR analysis further confirmed a direct, protective effect of (N(1)+N(8))-acetylspermidine on PDR risk (OR = 0.94, 95% CI: 0.89-1.00, p = 0.040). The sensitivity analysis results indicated that evidence for heterogeneity and pleiotropy was absent. Conclusion: These metabolites have the potential to be used as biomarkers and are promising for future research into the mechanisms and drug targets for PDR.

Multivariate genome-wide association study of sleep health demonstrates unity and diversity.

There has been a recent push to focus sleep research less on disordered sleep and more on the dimensional sleep health. Sleep health incorporates several dimensions of sleep: chronotype, efficiency, daytime alertness, duration, regularity, and satisfaction with sleep. A previous study demonstrated sleep health domains correlate only moderately with each other at the genomic level (|rGs| = 0.11-0.51) and show unique relationships with psychiatric domains (controlling for shared variances, duration, alertness, and non-insomnia independently related to a factor for internalizing psychopathology). Of the domains assessed, circadian preference was the least genetically correlated with all other facets of sleep health. This pattern is important because it suggests sleep health should be considered a multifaceted construct rather than a unitary construct. Prior genome-wide association studies (GWASs) have vastly increased our knowledge of the biological underpinnings of specific sleep traits but have only focused on univariate analyses. We present the first multivariate GWAS of sleep and circadian health (multivariate circadian preference, efficiency, and alertness factors, and three single-indicator factors of insomnia, duration, and regularity) using genomic structural equation modeling. We replicated loci found in prior sleep GWASs, but also discovered "novel" loci for each factor and found little evidence for genomic heterogeneity. While we saw overlapping genomic enrichment in subcortical brain regions and shared associations with external traits, much of the genetic architecture (loci, mapped genes, and enriched pathways) was diverse among sleep domains. These results confirm sleep health as a family of correlated but genetically distinct domains, which has important health implications.

Large scale genome-wide association analyses identify novel genetic loci and mechanisms in hypertrophic cardiomyopathy

Abstract Background Hypertrophic cardiomyopathy (HCM) is an important cause of morbidity and mortality with both monogenic and polygenic components. Prior genome-wide association studies (GWAS) identified few genomic loci and disease genes due to limited sample size. Purpose To discover novel genetic loci, genes and mechanisms implicated in HCM using a large scale GWAS and multi-trait analysis of GWAS (MTAG). Methods and results We performed the largest HCM GWAS meta-analysis and MTAG to date including 5,900 HCM cases, 68,359 controls, and 36,083 UK Biobank (UKB) participants with cardiac magnetic resonance (CMR) imaging. We estimated the heritability of HCM attributable to common genetic variation (h2SNP) to be 0.25±0.02 using genome-based restricted maximum likelihood (GREML), with higher h2SNP in non-sarcomeric (0.29±0.02) compared to sarcomeric HCM (0.16±0.04). We identified a total of 70 loci (50 novel) associated with HCM (Figure 1), and 62 loci (32 novel) associated with relevant left ventricular (LV) structural or functional traits. Amongst the common variant HCM loci, we identify a novel HCM disease gene, SVIL, which encodes the actin-binding protein supervillin. We performed rare variant burden analysis including 1,845 clinically-diagnosed unrelated HCM cases and 37,481 controls and demonstrated a 10.5-fold (95% CI: 4.1-26.8; P=0.0000002) excess burden of SVIL loss of function (LoF) variants in HCM cases. Two-sample mendelian randomization analyses using LV contractility as exposure and obstructive (oHCM) and non-obstructive HCM (nHCM) as outcomes support a causal role of increased LV contractility in both oHCM and nHCM (Figure 2), suggesting common disease mechanisms and anticipating shared response to therapy. Conclusion We identify 50 novel genomic loci associated with HCM. Our data suggest that LoF variants in SVIL are a cause of HCM, and that increased contractility mediate both nHCM and oHCM. Taken together, the findings significantly increase our understanding of the genetic basis and molecular mechanisms of HCM, with potential implications for disease management.Figure 1Figure 2

Abstract 18382: Clinical and Genetic Associations of Deep-Learning Estimated Peak Oxygen Consumption From the Resting 12-Lead Electrocardiogram

Introduction: Oxygen consumption at peak exercise (VO2 peak ) is the gold standard for cardiorespiratory fitness, but prior genome-wide association studies (GWAS) have been limited by the availability of cardiopulmonary exercise testing (CPET). Recent deep learning methods to estimate VO2 peak from the resting 12-lead electrocardiogram (ECG) may enhance genetic studies of cardiorespiratory fitness. Methods: We applied a validated deep learning model (Deep ECG-VO2) to estimate VO2 peak among UK Biobank participants with a 12-lead ECG. We assessed for associations between estimated VO2 peak and incident hypertension, diabetes, and atrial fibrillation (AF) using Cox proportional hazards models adjusted for age and sex, and plotted cumulative risk of each outcome stratified by tertile of estimated VO2 peak . We then performed a multi-ancestry GWAS of estimated VO2 peak using BOLT-LMM, adjusted for age, sex, array, and the first five principal components of ancestry. Candidate genes were prioritized based on proximity to the lead variant. Results: We applied Deep ECG-VO2 to estimate VO2 peak using the resting 12-lead ECG of 40,801 UK Biobank participants (age 65±8, 52% women). Greater estimated VO2 peak was associated with lower risks of hypertension (hazard ratio per 1-standard deviation 0.76, 95% CI 0.70-0.83), diabetes (0.60, 95% CI 0.53-0.67) and AF (0.82, 95% CI 0.74-0.90). Cumulative risk of each outcome was higher with decreasing estimated VO2 peak ( Figure ). In a GWAS of estimated VO2 peak within 39,716 participants with genetic data (age 65±8, 52% women, 90% European), we identified 10 novel genome-wide significant loci, including variants near genes involved in cardiac structure ( CCDC141/TTN, BAG3) , cardiac conduction ( SCN5A ), and adiposity ( FTO ). Conclusions: Leveraging artificial intelligence-enabled estimation of VO2 peak from the resting 12-lead ECG, we identify 10 novel common genetic variants associated with cardiorespiratory fitness.

European and multi-ancestry genome-wide association meta-analysis of atopic dermatitis highlights importance of systemic immune regulation

Atopic dermatitis (AD) is a common inflammatory skin condition and prior genome-wide association studies (GWAS) have identified 71 associated loci. In the current study we conducted the largest AD GWAS to date (discovery N = 1,086,394, replication N = 3,604,027), combining previously reported cohorts with additional available data. We identified 81 loci (29 novel) in the European-only analysis (which all replicated in a separate European analysis) and 10 additional loci in the multi-ancestry analysis (3 novel). Eight variants from the multi-ancestry analysis replicated in at least one of the populations tested (European, Latino or African), while two may be specific to individuals of Japanese ancestry. AD loci showed enrichment for DNAse I hypersensitivity and eQTL associations in blood. At each locus we prioritised candidate genes by integrating multi-omic data. The implicated genes are predominantly in immune pathways of relevance to atopic inflammation and some offer drug repurposing opportunities.

Genome-wide association studies and fine-mapping identify genomic loci for n-3 and n-6 polyunsaturated fatty acids in Hispanic American and African American cohorts

Omega-3 (n-3) and omega-6 (n-6) polyunsaturated fatty acids (PUFAs) play critical roles in human health. Prior genome-wide association studies (GWAS) of n-3 and n-6 PUFAs in European Americans from the CHARGE Consortium have documented strong genetic signals in/near the FADS locus on chromosome 11. We performed a GWAS of four n-3 and four n-6 PUFAs in Hispanic American (n = 1454) and African American (n = 2278) participants from three CHARGE cohorts. Applying a genome-wide significance threshold of P < 5 × 10−8, we confirmed association of the FADS signal and found evidence of two additional signals (in DAGLA and BEST1) within 200 kb of the originally reported FADS signal. Outside of the FADS region, we identified novel signals for arachidonic acid (AA) in Hispanic Americans located in/near genes including TMX2, SLC29A2, ANKRD13D and POLD4, and spanning a > 9 Mb region on chromosome 11 (57.5 Mb ~ 67.1 Mb). Among these novel signals, we found associations unique to Hispanic Americans, including rs28364240, a POLD4 missense variant for AA that is common in CHARGE Hispanic Americans but absent in other race/ancestry groups. Our study sheds light on the genetics of PUFAs and the value of investigating complex trait genetics across diverse ancestry populations.

Exploring genetic risk for catatonia in a genome wide association study and polygenic risk score analysis

BackgroundCatatonia is an under-recognized disorder characterized by psychomotor (increased, decreased, or abnormal) changes, affective symptoms, and disturbance of volition, which may arise in the setting of decompensated psychiatric or non-psychiatric medical disorders. Genetic studies of catatonia are limited, and to the best of our knowledge no prior genome wide association studies of catatonia have been performed to date. MethodsFirst we performed a genome wide association study of catatonia regardless of etiology (psychiatric or non-psychiatric). Secondarily we evaluated whether there was an elevated genetic risk profile for predisposing psychiatric disorders (schizophrenia spectrum disorder, bipolar affective disorder, etc.) in patients with catatonia. We used a matched case control design and applied polygenic risk scores to evaluate for a shared polygenetic contribution to catatonia from common psychiatric phenotypes that show a high prevalence of catatonia in their decompensated states. ResultsAnxiety, bipolar affective disorder, schizophrenia spectrum disorder and cross disorder polygenic risk scores were significantly associated with catatonia case status in both unadjusted and adjusted logistic regression models for the European Ancestry set even after correcting for multiple comparisons. Depression, Alzheimer's, Autism Spectrum Disorder and Obsessive Disorder polygenic risk scores were not significantly associated with catatonia status in participants of European Ancestry. In the African Ancestry set, no psychiatric polygenic risk scores were significantly associated with catatonia status in either the unadjusted or adjusted regression models. ConclusionsEven after controlling for relevant covariates, anxiety, bipolar affective disorder, schizophrenia spectrum disorder and cross disorders were significantly associated with catatonia status suggesting that there might be a shared genetic risk for those disorders amongst patients with catatonia.

Abstract 1181: Etiologic heterogeneity of genetic risk for DLBCL cell-of origin molecular subtypes

Abstract Diffuse large B-cell lymphoma (DLBCL) is clinically and biologically heterogenous. Based on gene expression profiling of the tumor, DLBCL is classified into two major molecular subtypes linked to cell-of-origin (COO): germinal center (GCB) and activated B-Cell (ABC). The GCB subtype is characterized by a high prevalence of somatic mutations, particularly in apoptosis genes (e.g., BCL2) which is characteristic of follicular lymphoma (FL, another GCB lymphoma). The development of the validated NanoString gene expression test as well as immunohistochemistry markers that work in formalin-fixed, paraffin-embedded tissue allows for the classification of DLBCL by COO in epidemiological studies. We hypothesized that integration of COO with germline genetics could provide insight into the underlying biology driving this heterogeneity, as well as insight into putative function of germline risk variants. Prior genome wide association studies (GWAS) have identified 7 SNPs in 6 susceptibility loci for DLBCL, including: 2p23.3 (rs79480871 NCOA1), 3q13.33 (rs9831894 CD86), 3p24.1 (rs6773363 EOMES), 6p21.33 (rs2523607 HLA-B), 6p25.3 (rs116446171 EXOC2), and 8q24.21 (rs13255292 and rs4733601 PVT1 and MYC). Two of these loci were also identified in FL GWAS (different lead SNPs): 6p21.33 (rs3130437) and 8q24.21 (rs13254990 PVT1). Additional published FL susceptibility loci include: 3q28 (rs6444305 LPP), 6p21.32 (rs9268839), 11q23.3 (rs4938573 CXCR5), 11q24.3 (rs4937362 ETS1), and 18q21.33 (rs17749561 BCL2). Here we evaluated whether the published DLBCL/FL loci differ by COO molecular subtypes. We evaluated each of the 14 DLBCL/FL SNPs by case-case (GCB vs. nonGCB DLBCL) and polytomous case-control (GCB, nonGCB, and FL vs. controls) analyses. DLBCL cases were classified into GCB vs. nonGCB based on best available data from NanoString, RNAseq, followed by the Hans algorithm. A total of 778 DLBCL cases (470 GCB and 308 nonGCB), 1,050 FL cases, and 1,383 controls were analyzed. Odds ratios (OR) based on ordinal encoding of each SNP and 95% CI were calculated for each of the comparison groups. The ORs for four GWAS SNPs were significantly elevated in GCB vs. nonGCB DLBCL as well as in FL; two were FL GWAS SNPs from the HLA region (6p21.32 and 6p21.33) and the other two (BCL2 and ETS1) are important in the germinal center program. In contrast, one SNP (EXOC2) was significantly elevated in nonGCB-DLBCL and was not associated with GCB-DLBCL or FL; this SNP is also near IRF4 (MUM1), a gene important in the ABC program. For the remaining SNPs, there were suggestive associations for GCB-DLBCL and FL versus nonGCB DLBCL (CD86, CXCR5); nonGCB-DLBCL vs. GCB-DLBCL and FL (NCOA1, PVT1); and associations that showed no pattern with COO (EOMES, LPP, HLA-B and MYC). These findings provide insight into the shared pathogenesis of FL and GCB-DLBCL to inform etiologic mechanisms and risk assessment. Citation Format: Rosalie Griffin Waller, Dennis P. Robinson, Anne J. Novak, Lisa M. Rimsza, Kerstin Wenzl, Rebecca L. King, Andrew L. Feldman, Matthew J. Maurer, Grzegorz S. Nowakowski, Brian K. Link, Thomas M. Habermann, Susan L. Slager, James R. Cerhan. Etiologic heterogeneity of genetic risk for DLBCL cell-of origin molecular subtypes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1181.

163 Integrative Genomics Analysis Implicates Decreased FGD6 Expression Underlying Risk of Intracranial Aneurysm Rupture

INTRODUCTION: The genetic determinants of intracranial aneurysm rupture (rIA) are largely unknown. To identify and characterize genetic risk factors for rIA, we perform a genome-wide association study (GWAS) containing 84,353 individuals (7,843 rIA cases and 76,510 controls). We then use functional genomics approaches to delineate the mechanistic consequences of rIA risk loci. METHODS: We perform a meta-analysis across 24 published GWAS of rIA. Logistic regression was used to identify rIA-associated single nucleotide polymorphisms (SNPs). Gene-burden, expression quantitative trait loci (eQTL) mapping, and analysis of publicly-available single-cell RNA sequencing (scRNA-seq) data from normal human brain endothelial and perivascular cells was used to delineate cell-lineage expression of rIA-associated genes. RESULTS: We identify 5 independent genetic loci reaching genome-wide significance (p &lt; 5.0 x 10-8) for rIA: rs73392700 (CDKN2B, OR = 1.12), rs6841581 (EDNRA, OR = 0.77), rs11661542 (RBBP8, OR=0.84), rs62516550 (RP1, OR = 1.20), and rs12310399 (FGD6, OR = 1.16). FGD6, to our knowledge, has not been implicated in prior GWAS of (r)IA. We then quantified gene-level mutation-burden across ∼20,000 genes, and only FGD6 (containing 21 rIA-associated SNPs) reached transcriptome-wide significance. Functional eQTL mapping indicates that rs12310399 causes decreased FGD6 gene expression in arterial tissue. scRNA-seq identified high expression of FGD6 in 1 of 3 arterial lineages, but absent in perivascular cells, identifying the likely cell-lineage underlying FGD6-mediated rIA risk. CONCLUSIONS: We perform the largest genetic study of rIA to date. We identify and characterize a previously unknown risk loci for rIA containing FGD6. Elucidation of high-risk genetic loci may instruct population-genetic screening and clinical-genetic testing strategies to identify patients predisposed to rIA enabling early treatment and improved patient outcomes.

Abstract P424: Associations of Taste-Related Genes With Empirical Dietary Patterns Among Community-Dwelling Adults - The Framingham Heart Study

Background: Understanding the genetic contribution to food choices and intake is critical for the development of effective precision nutrition guidance. Recent findings by our lab suggest that genetic variants (SNPs) related to bitter and umami taste perception are differentially associated with food group intakes. The aim of this study was to examine the associations of bitter- and umami-related SNPs, combined as polygenic taste scores, with overall dietary patterns. Methods: Cross-sectional analyses were conducted in 5,817 Framingham Heart Study Offspring (1998-2001) and Third Generation (2002-05) participants (mean age ± SD: 50 ± 14 years; 54% female). Weighed polygenic taste scores were derived using SNPs identified from prior genome-wide association studies for taste perception (11 SNPs: 9 bitter and 2 umami). Higher scores indicated more alleles for higher taste perception. Empirical dietary patterns were derived using Principal Component (PC) analysis with food groups tabulated from food frequency questionnaires. Associations were assessed using linear mixed effects models with FDR adjustment. Results: Three dietary patterns were identified, explaining 32% of total variance in dietary intake: a vegetables, fruits, legumes, and fish pattern (Prudent); a refined grains, sweets, salty foods, and pizza pattern (Western); and a liquor, beer, and wine pattern (Alcohol). On average, after adjusting for age, sex, genetic PCs and energy intake, higher umami polygenic taste scores were associated with lower adherence to the Prudent dietary pattern (OR [95% CI] for upper vs. lower tertial of dietary pattern adherence scores per additional allele for higher umami perception: 0.87 [0.79, 0.97]; P = 0.01). Subsequent analysis at the SNP-level identified one umami-related SNP (rs7691456_T) independently associated with lower Prudent dietary pattern adherence ( P = 0.009), potentially driving the observed association. Both associations remained significant after additional adjustment for smoking, physical activity, and BMI. No significant associations were identified for bitter-related genes and dietary patterns. Conclusions: Among community dwelling adults, higher genetic predisposition to perceive umami was associated with lower adherence to a Prudent dietary pattern, suggesting the potential benefit of leveraging knowledge of taste-related genes in precision nutrition.

Bitter- and Umami-Related Genes are Differentially Associated with Food Group Intakes: the Framingham Heart Study

BackgroundAs suboptimal diet quality remains the leading modifiable contributor to chronic disease risk, it is important to better understand the individual-level drivers of food choices. Recently, a genetic component of food choices was proposed based on variants (SNPs) in genes related to taste perception (taste-related SNPs). ObjectivesThis study aimed to determine the cumulative contribution of taste-related SNPs for basic tastes (bitter, sweet, umami, salt, and sour), summarized as “polygenic taste scores,” to food group intakes among adults. MethodsCross-sectional analyses were performed on 6230 Framingham Heart Study participants (mean age ± SD: 50 ± 14 y; 54% female). Polygenic taste scores were derived for tastes with ≥2 related SNPs identified in prior genome-wide association studies, and food group intakes (servings per week [sev/wk]) were tabulated from food frequency questionnaires. Associations were determined via linear mixed-effects models, using false discovery rates and bootstrap resampling to determine statistical significance. ResultsThirty-three taste-related SNPs (9 bitter, 19 sweet, 2 umami, 2 sour, 1 salt) were identified and used to derive polygenic taste scores for bitter, sweet, umami, and sour. Per additional allele for higher bitter perception, whole grain intakes were lower by 0.17 (95% CI: −0.28, −0.06) sev/wk, and for higher umami perception, total and red/orange vegetable intakes were lower by 0.73 (95% CI: −1.12, −0.34) and 0.25 (95% CI: −0.40, −0.10) sev/wk, respectively. Subsequent analyses at the SNP level identified four novel SNP-diet associations—two bitter-related SNPs with whole grains (rs10960174 and rs6782149) and one umami-related SNP with total and red/orange vegetables (rs7691456)—which may have been driving the identified associations. ConclusionsTaste-related genes for bitter and umami were differentially associated with food choices that may impact diet quality. Hence, a benefit could be derived from leveraging knowledge of taste-related genes when developing personalized risk reduction dietary guidance.