Genome-wide Association Studies Findings Research Articles

A multi-trait GWAS identifies novel genes influencing albuminuria.

Albuminuria is common and associated with increased risks of end-stage kidney disease and cardiovascular diseases, yet its underlying mechanism remains obscure. Previous genome-wide association studies (GWAS) for albuminuria did not consider gene pleiotropy and primarily focused on European ancestry populations. This study adopted a multi-trait analysis of GWAS (MTAG) approach to jointly analyze two vital kidney traits, estimated glomerular filtration rate (eGFR) and urine albumin-to-creatinine ratio (UACR) to identify and prioritize the genes associated with UACR. Data from the Taiwan Biobank from 2012 to 2023 were analyzed. GWAS of UACR and eGFR were performed separately and the summary statistics from these GWAS were jointly analyzed using MTAG. The polygenic risk scores (PRS) of UACR were constructed for validation. The UACR-associated loci were further fine-mapped and prioritized based on their deleteriousness, eQTL associations, and relatedness to Mendelian kidney diseases. MTAG analysis of the UACR revealed 15 genetic loci, including 12 novel loci. The PRS for UACR was significantly associated with urinary albumin level (P<0.001) and microalbuminuria (P=0.001 ∼ 0.045). A list of priority genes was generated. Twelve genes with high priority included the albumin endocytic receptor gene LRP2 and ciliary genes IFT172. The findings of this multi-trait GWAS suggest that primary cilia play a role in sensing mechanical stimuli, leading to albumin endocytosis. The priority list of genes warrants further translational investigation to reduce albuminuria.

GENETIC STUDY OF PSORIASIS HIGHLIGHTS ITS CLOSE LINK WITH SOCIO-ECONOMIC STATUS AND AFFECTIVE SYMPTOMS

Psoriasis is an inflammatory skin disease with an estimated heritability of around 70 %. Previous genome-wide association studies (GWASs) have detected several risk loci for psoriasis. To further improve the understanding of the genetic risk factors impacting the disease, we conducted a discovery GWAS in FinnGen and a subsequent replication and meta-analysis with data from the Estonian Biobank and the UK biobank; the study sample included 925 649 individuals (22 659 cases and 902 990 controls), the largest sample for psoriasis yet. In addition, we conducted downstream analyses to find out more about psoriasis’ cross-trait genetic correlations and causal relationships. We report 6 risk loci to our knowledge previously unreported, most of which harbor genes related to nuclear factor kappa-light-chain-enhancer of activated B-cells-signaling pathway and overall immunity. Genetic correlations highlight the relationship between psoriasis and smoking, higher body weight, and lower education level. Additionally, we report causal relationships between psoriasis and mood symptoms, as well as two-directioned causal relationship between psoriasis and lower education level. Our results provide further knowledge on psoriasis risk factors, which may be useful in the development of future treatment strategies.

Technological advancements in functional interpretation of genome-wide association studies (GWAS) findings: bridging the gap to clinical translation.

Genome-wide association studies (GWAS) significantly advanced our understanding of the genetic underpinnings of diseases. However, challenges persist, particularly in interpreting non-coding variants in linkage disequilibrium that affect genes in disease-relevant cells. Addressing key obstacles-identifying causal variants, uncovering target genes, and understanding their network impact-is crucial. This graphical review navigates advanced techniques to fully leverage GWAS for future therapeutic breakthroughs.

Identification of bone mineral density associated genes with shared genetic architectures across multiple tissues: Functional insights for EPDR1, PKDCC, and SPTBN1.

Recent studies suggest a shared genetic architecture between muscle and bone, yet the underlying molecular mechanisms remain elusive. This study aims to identify the functionally annotated genes with shared genetic architecture between muscle and bone using the most up-to-date genome-wide association study (GWAS) summary statistics from bone mineral density (BMD) and fracture-related genetic variants. We employed an advanced statistical functional mapping method to investigate shared genetic architecture between muscle and bone, focusing on genes highly expressed in muscle tissue. Our analysis identified three genes, EPDR1, PKDCC, and SPTBN1, which are highly expressed in muscle tissue and previously unlinked to bone metabolism. About 90% and 85% of filtered Single-Nucleotide Polymorphisms were in the intronic and intergenic regions for the threshold at P≤5×10-8 and P≤5×10-100, respectively. EPDR1 was highly expressed in multiple tissues, including muscles, adrenal glands, blood vessels, and the thyroid. SPTBN1 was highly expressed in all 30 tissue types except blood, while PKDCC was highly expressed in all 30 tissue types except the brain, pancreas, and skin. Our study provides a framework for using GWAS findings to highlight functional evidence of crosstalk between multiple tissues based on shared genetic architecture between muscle and bone. Further research should focus on functional validation, multi-omics data integration, gene-environment interactions, and clinical relevance in musculoskeletal disorders.

Abstract P491: Functional Annotations for Improvements in Height and Blood Pressure Polygenic Risk Scores

Background: Genome-wide association studies (GWAS) have advanced our understanding of the polygenic basis of common, complex disorders. However, translating GWAS findings into clinical applications remains challenging. Polygenic risk scores (PRS) hold promise for clinical use with recent methodologies enhancing predictive accuracy. This study compared two PRS (LDpred-funct which incorporates functional annotations into the score and a traditional linear scoring system) for traits with varying heritability in European- (EA) and African-ancestry (AA) populations, addressing a need to evaluate novel approaches across diverse conditions and populations. Hypothesis: This study hypothesized that integrating functional annotations into PRS derivation will enhance performance compared to assessing the genetic load for a trait. The addition will provide improvement for (1) traits with high (height) compared to moderate (systolic blood pressure, SBP) heritability and (2) individuals with EA relative to AA. Methods: This study used multi-ancestry summary statistics representing data from 4,080,687 individuals for height (GIANT consortium) and 436,099 individuals for SBP adjusted for antihypertensive medication use (UK Biobank). Two PRS for these traits were constructed using LDpred-funct: PRS funct which incorporates the functional annotation and PRS raw which is a simple linear scoring system. Optimization was performed in 8,916 AA and 1,716 EA participants from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study. PRS predictive performance was evaluated by calculating the proportion of trait variance explained by the PRS (R 2 ) after accounting for age, sex, and genetic ancestry. Results: For height, the PRS funct outperformed PRS raw among both race groups, with a greater improvement among EA (PRS funct R 2 =0.110 versus PRS raw R 2 =0.060, 5% difference) compared to AA (PRS funct R 2 =0.042 versus PRS raw R 2 =0.034, 0.8% difference). Similar findings were observed for medication-adjusted SBP, where PRS funct had better predictive performance than PRS raw , and with greater improvement observed in the EA (PRS funct R 2 =0.042 versus PRS raw R 2 =0.027, 1.5% difference) compared to AA participants (PRS funct R 2 =0.014 versus PRS raw R 2 =0.010, 0.4% difference). Conclusions: Incorporating functional priors into the PRS enhanced the predictive accuracy for both traits. A greater improvement was observed for the higher heritability (height) versus the moderate heritability (SBP) trait, as well as within individuals of EA compared to AA. These findings are currently undergoing validation, using data from the Electronic Medical Records and Genomics (eMERGE) Network, highlighting the potential of incorporating functional annotations into PRS development for broader clinical applications.

GWABLUP: genome-wide association assisted best linear unbiased prediction of genetic values

BackgroundSince the very beginning of genomic selection, researchers investigated methods that improved upon SNP-BLUP (single nucleotide polymorphism best linear unbiased prediction). SNP-BLUP gives equal weight to all SNPs, whereas it is expected that many SNPs are not near causal variants and thus do not have substantial effects. A recent approach to remedy this is to use genome-wide association study (GWAS) findings and increase the weights of GWAS-top-SNPs in genomic predictions. Here, we employ a genome-wide approach to integrate GWAS results into genomic prediction, called GWABLUP.ResultsGWABLUP consists of the following steps: (1) performing a GWAS in the training data which results in likelihood ratios; (2) smoothing the likelihood ratios over the SNPs; (3) combining the smoothed likelihood ratio with the prior probability of SNPs having non-zero effects, which yields the posterior probability of the SNPs; (4) calculating a weighted genomic relationship matrix using the posterior probabilities as weights; and (5) performing genomic prediction using the weighted genomic relationship matrix. Using high-density genotypes and milk, fat, protein and somatic cell count phenotypes on dairy cows, GWABLUP was compared to GBLUP, GBLUP (topSNPs) with extra weights for GWAS top-SNPs, and BayesGC, i.e. a Bayesian variable selection model. The GWAS resulted in six, five, four, and three genome-wide significant peaks for milk, fat and protein yield and somatic cell count, respectively. GWABLUP genomic predictions were 10, 6, 7 and 1% more reliable than those of GBLUP for milk, fat and protein yield and somatic cell count, respectively. It was also more reliable than GBLUP (topSNPs) for all four traits, and more reliable than BayesGC for three of the traits. Although GWABLUP showed a tendency towards inflation bias for three of the traits, this was not statistically significant. In a multitrait analysis, GWABLUP yielded the highest accuracy for two of the traits. However, for SCC, which was relatively unrelated to the yield traits, including yield trait GWAS-results reduced the reliability compared to a single trait analysis.ConclusionsGWABLUP uses GWAS results to differentially weigh all the SNPs in a weighted GBLUP genomic prediction analysis. GWABLUP yielded up to 10% and 13% more reliable genomic predictions than GBLUP for single and multitrait analyses, respectively. Extension of GWABLUP to single-step analyses is straightforward.

Genome-Enabled Analysis of Population Dynamics and Virulence-Associated Loci in the Oat Crown Rust Fungus Puccinia coronata f. sp. avenae.

Puccinia coronata f. sp. avenae (Pca) is an important fungal pathogen causing crown rust that impacts oat production worldwide. Genetic resistance for crop protection against Pca is often overcome by the rapid virulence evolution of the pathogen. This study investigated the factors shaping adaptive evolution of Pca using pathogen populations from distinct geographic regions within the United States and South Africa. Phenotypic and genome-wide sequencing data of these diverse Pca collections, including 217 isolates, uncovered phylogenetic relationships and established distinct genetic composition between populations from northern and southern regions from the United States and South Africa. The population dynamics of Pca involve a bidirectional movement of inoculum between northern and southern regions of the United States and contributions from clonality and sexuality. The population from South Africa is solely clonal. A genome-wide association study (GWAS) employing a haplotype-resolved Pca reference genome was used to define 11 virulence-associated loci corresponding to 25 oat differential lines. These regions were screened to determine candidate Avr effector genes. Overall, the GWAS results allowed us to identify the underlying genetic factors controlling pathogen recognition in an oat differential set used in the United States to assign pathogen races (pathotypes). Key GWAS findings support complex genetic interactions in several oat lines, suggesting allelism among resistance genes or redundancy of genes included in the differential set, multiple resistance genes recognizing genetically linked Avr effector genes, or potentially epistatic relationships. A careful evaluation of the composition of the oat differential set accompanied by the development or implementation of molecular markers is recommended. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

A multi-ancestry genetic study of pain intensity in 598,339 veterans.

Chronic pain is a common problem, with more than one-fifth of adult Americans reporting pain daily or on most days. It adversely affects the quality of life and imposes substantial personal and economic costs. Efforts to treat chronic pain using opioids had a central role in precipitating the opioid crisis. Despite an estimated heritability of 25-50%, the genetic architecture of chronic pain is not well-characterized, in part because studies have largely been limited to samples of European ancestry. To help address this knowledge gap, we conducted a cross-ancestry meta-analysis of pain intensity in 598,339 participants in the Million Veteran Program, which identified 126 independent genetic loci, 69 of which are new. Pain intensity was genetically correlated with other pain phenotypes, level of substance use and substance use disorders, other psychiatric traits, education level and cognitive traits. Integration of the genome-wide association studies findings with functional genomics data shows enrichment for putatively causal genes (n = 142) and proteins (n = 14) expressed in brain tissues, specifically in GABAergic neurons. Drug repurposing analysis identified anticonvulsants, β-blockers and calcium-channel blockers, among other drug groups, as having potential analgesic effects. Our results provide insights into key molecular contributors to the experience of pain and highlight attractive drug targets.

Variant to gene mapping for carpal tunnel syndrome risk loci implicates skeletal muscle regulatory elements

Carpal tunnel syndrome (CTS) is a common disorder caused by compression of the median nerve in the wrist, resulting in pain and numbness throughout the hand and forearm. While multiple behavioural and physiological factors influence CTS risk, a growing body of evidence supports a strong genetic contribution. Recent genome-wide association study (GWAS) efforts have reported 53 independent signals associated with CTS. While GWAS can identify genetic loci conferring risk, it does not determine which cell types drive the genetic aetiology of the trait, which variants are "causal" at a given signal, and which effector genes correspond to these non-coding variants. These obstacles limit interpretation of potential disease mechanisms. We analysed CTS GWAS findings in the context of chromatin conformation between gene promoters and accessible chromatin regions across cellular models of bone, skeletal muscle, adipocytes and neurons. We identified proxy variants in high LD with the lead CTS sentinel SNPs residing in promoter connected open chromatin in the skeletal muscle and bone contexts. We detected significant enrichment for heritability in skeletal muscle myotubes, as well as a weaker correlation in human mesenchymal stem cell-derived osteoblasts. In myotubes, our approach implicated 117 genes contacting 60 proxy variants corresponding to 20 of the 53 GWAS signals. In the osteoblast context we implicated 30 genes contacting 24 proxy variants coinciding with 12 signals, of which 19 genes shared. We subsequently prioritized BZW2 as a candidate effector gene in CTS and implicated it as novel gene that perturbs myocyte differentiation invitro. Taken together our results suggest that the CTS genetic component influences the size, integrity, and organization of multiple tissues surrounding the carpal tunnel, in particular muscle and bone, to predispose the nerve to being compressed in this disease setting. This work was supported by NIH Grant UM1 DK126194 (SFAG and WY), R01AG072705 (SFAG & KDH) and the Center for Spatial and Functional Genomics at CHOP (SFAG & ADW). SFAG is supported by the Daniel B. Burke Endowed Chair for Diabetes Research. WY is supported by the Perelman School of Medicine of the University of Pennsylvania.

The causal effect of two occupational factors on osteoarthritis and rheumatoid arthritis: a Mendelian randomization study.

Osteoarthritis (OA) and rheumatoid arthritis (RA) are two common types of arthritis. We conducted a two-sample Mendelian randomization (MR) study to estimate the causal effects of two common occupational factors-job involves heavy manual or physical work and job involves mainly walking or standing-on OA and RA in individuals of European ancestry. Instruments were chosen from genome-wide association studies (GWASs) that identified independent single nucleotide polymorphisms (SNPs) robustly linked to job involves heavy manual or physical work (N = 263,615) as well as job involves mainly walking or standing (N = 263,556). Summary statistics for OA and RA were taken from the Integrative Epidemiology Unit (IEU) GWAS database; both discovery and replication GWAS datasets were considered. The primary analysis utilized the inverse variance weighted (IVW) MR method supplemented by various sensitivity MR analyses. In the IVW model, we found that genetically predicted job involves heavy manual or physical work was significantly associated with OA in both the discovery [odds ratio (OR) = 1.034, 95% confidence interval (CI): 1.016-1.053, P = 2.257 × 10-4] and replication (OR = 1.857, 95% CI: 1.223-2.822, P = 0.004) analyses. The causal associations were supported in diverse sensitivity analyses. MR analyses suggested no causal effect of genetically predicted job involves heavy manual or physical work on RA. Similarly, our data provided no evidence that genetically predicted job involves mainly walking or standing was related to OA and RA. Our MR study suggests that job involves heavy manual or physical work is a risk factor for OA. It is of utmost importance to create preventive strategies aimed at reducing its impact on OA at such work sites.

Polymorphisms in transcription factor binding sites and enhancer regions and pancreatic ductal adenocarcinoma risk

Genome-wide association studies (GWAS) are a powerful tool for detecting variants associated with complex traits and can help risk stratification and prevention strategies against pancreatic ductal adenocarcinoma (PDAC). However, the strict significance threshold commonly used makes it likely that many true risk loci are missed. Functional annotation of GWAS polymorphisms is a proven strategy to identify additional risk loci. We aimed to investigate single-nucleotide polymorphisms (SNP) in regulatory regions [transcription factor binding sites (TFBSs) and enhancers] that could change the expression profile of multiple genes they act upon and thereby modify PDAC risk. We analyzed a total of 12,636 PDAC cases and 43,443 controls from PanScan/PanC4 and the East Asian GWAS (discovery populations), and the PANDoRA consortium (replication population). We identified four associations that reached study-wide statistical significance in the overall meta-analysis: rs2472632(A) (enhancer variant, OR 1.10, 95%CI 1.06,1.13, p = 5.5 × 10−8), rs17358295(G) (enhancer variant, OR 1.16, 95%CI 1.10,1.22, p = 6.1 × 10−7), rs2232079(T) (TFBS variant, OR 0.88, 95%CI 0.83,0.93, p = 6.4 × 10−6) and rs10025845(A) (TFBS variant, OR 1.88, 95%CI 1.50,1.12, p = 1.32 × 10−5). The SNP with the most significant association, rs2472632, is located in an enhancer predicted to target the coiled-coil domain containing 34 oncogene. Our results provide new insights into genetic risk factors for PDAC by a focused analysis of polymorphisms in regulatory regions and demonstrating the usefulness of functional prioritization to identify loci associated with PDAC risk.

Neuropsychiatric disorders, chronotype and sleep: A narrative review of GWAS findings and the application of Mendelian randomization to investigate causal relationships.

Genome-wide association studies (GWAS) have been important for characterizing the genetic component and enhancing our understanding of the biological aetiology of both neuropsychiatric disorders and sleep-related phenotypes such as chronotype, which is our preference for morning or evening time. Mendelian randomization (MR) is a post-GWAS analysis that is used to infer causal relationships between potential risk factors and outcomes. MR uses genetic variants as instrumental variants for exposures to study the effect on outcomes. This review details the main results from GWAS of neuropsychiatric disorders and sleep-related phenotypes, and the application of MR to investigate their bidirectional relationship. The main results from MR studies of neuropsychiatric disorders and sleep-related phenotypes are summarized. These MR studies have identified 37 causal relationships between neuropsychiatric disorders and sleep-related phenotypes. MR studies identified evidence of a causal role for five neuropsychiatric disorders and symptoms (attention deficit hyperactivity disorder, bipolar disorder, depressive symptoms, major depressive disorder and schizophrenia) on sleep-related phenotypes and evidence of a causal role for five sleep-related phenotypes (daytime napping, insomnia, morning person, long sleep duration and sleep duration) on risk for neuropsychiatric disorders. These MR results show a bidirectional relationship between neuropsychiatric disorders and sleep-related phenotypes and identify potential risk factors for follow-up studies.

Genome, HLA and polygenic risk score analyses for prevalent and persistent cervical human papillomavirus (HPV) infections.

Genetic variants that underlie susceptibility to cervicalhigh-risk human papillomavirus (hrHPV) infections are largely unknown. We conducted discovery genome-wide association studies (GWAS), replication, meta-analysis and colocalization,generated polygenic risk scores (PRS) and examined the association of classical HLA alleles and cervical hrHPVinfections in a cohort of over 10,000 women. We identified genome-wide significant variants for prevalent hrHPV around LDB2 and for persistent hrHPV near TPTE2, SMAD2, and CDH12, which code for proteins that are significantly expressed in the human endocervix. Genetic variants associated with persistent hrHPV are in genes enriched for the antigen processing and presentation gene set. HLA-DRB1*13:02, HLA-DQB1*05:02 and HLA-DRB1*03:01 were associated with increased risk, and HLA-DRB1*15:03 was associated with decreased risk of persistent hrHPV. The analyses of peptide binding predictions showed that HLA-DRB1 alleles that were positively associated with persistent hrHPV showed weaker binding with peptides derived from hrHPV proteins and vice versa. The PRS for persistent hrHPV with the best model fit, had a P-value threshold (PT) of 0.001 and a p-value of 0.06 (-log10(0.06) = 1.22). The findings of this study expand our understanding of genetic risk factors for hrHPV infection and persistence and highlight the roles of MHC class II molecules in hrHPV infection.

Genetic effects of sequence-conserved enhancer-like elements on human complex traits.

The vast majority of findings from human genome-wide association studies (GWAS) map to non-coding sequences, complicating their mechanistic interpretations and clinical translations. Non-coding sequences that are evolutionarily conserved and biochemically active could offer clues to the mechanisms underpinning GWAS discoveries. However, genetic effects of such sequences have not been systematically examined across a wide range of human tissues and traits, hampering progress to fully understand regulatory causes of human complex traits. Here we develop a simple yet effective strategy to identify functional elements exhibiting high levels of human-mouse sequence conservation and enhancer-like biochemical activity, which scales well to 313 epigenomic datasets across 106 human tissues and cell types. Combined with 468 GWAS of European (EUR) and East Asian (EAS) ancestries, these elements show tissue-specific enrichments of heritability and causal variants for many traits, which are significantly stronger than enrichments based on enhancers without sequence conservation. These elements also help prioritize candidate genes that are functionally relevant to body mass index (BMI) and schizophrenia but were not reported in previous GWAS with large sample sizes. Our findings provide a comprehensive assessment of how sequence-conserved enhancer-like elements affect complex traits in diverse tissues and demonstrate a generalizable strategy of integrating evolutionary and biochemical data to elucidate human disease genetics.

COL11A1 is associated with developmental dysplasia of the hip and secondary osteoarthritis in the HUNT study

ObjectiveDevelopmental dysplasia of the hip (DDH) is a congenital condition affecting 2–3% of all infants. DDH increases the risk of osteoarthritis, is the cause of 30 ​% of all total hip arthroplasties (THAs) in adults <40 years of age and can result in loss of life quality. Our aim was to explore the genetic background of DDH in order to improve diagnosis, management and longterm outcome. DesignWe used the large, ongoing, longitudinal Trøndelag Health Study (HUNT) database. Case definition was based on ICD-9/-10 diagnoses of DDH, or osteoarthritis secondary to DDH. Analyses were performed using SAIGE software, with covariates including sex, batch, birth year and principal components. We included only single nucleotide polymorphisms (SNPs) with minor allele frequency (MAF) ≥ 0.01, R2≥ 0.8 and Hardy-Weinberg equilibrium (HWE) P-value ≥ 0.0001. Significance level was set at p ​< ​5 ​× ​10−8. Meta-analysis using data from DDH and primary osteoarthritis genome-wide association studies (GWASs) was done using METAL software. The study was approved by the regional ethical committee. ResultsAnalysis included 69,500 individuals, of which 408 cases, and 8,531,386 SNPs. Two SNPs near COL11A1 were significantly associated with DDH; rs713162 (β ​= ​−0.43, SE ​= ​0.07, p ​= ​8.4 ​× ​10−9) and rs6577334 (β ​= ​−0.43, SE ​= ​0.08, p ​= ​8.9 ​× ​10−9). COL11A1 has previously been associated with acetabular dysplasia and osteoarthritis. Meta-analysis supported previous GWAS findings of both DDH and primary osteoarthritis. ConclusionsThis large, genome-wide case-control study indicates an association between COL11A1 and DDH and is an important contribution to investigating the etiology of DDH, with further research needed.

Expanded Assessments of Germline Genetic Variants Identify Additional Risk Loci for Langerhans Cell Histiocytosis

Introduction: Langerhans cell histiocytosis (LCH) is an inflammatory myeloid neoplasia characterized by lesions including pathogenic CD207+ dendritic cells among an inflammatory infiltrate. Sequencing studies have identified recurrent, mutually exclusive somatic activating mutations in MAPK pathway genes in ~85% of LCH lesions, including BRAF V600E in 50-65%. Despite advances to elucidate the somatic mutational landscape underlying LCH pathogenesis, germline risk factors remain largely unknown. We previously conducted the first genome-wide association study (GWAS) of LCH and identified and validated a risk variant in SMAD6 (rs12438941, G-&amp;gt;A) associated with a 3-fold increase in LCH risk. Our current objective is to further elucidate the role of SMAD6 variation on LCH risk and identify novel LCH susceptibility loci. Methods: Independent of our discovery GWAS, we sequenced SMAD6 in 466 additional LCH cases and compared them to aggregate-level SMAD6 data from ~15,694 non-cancer controls in gnomAD v2.1.1. Targeted sequencing of SMAD6 was conducted among these cases with ~200x coverage at the Avera Institute of Human Genetics. In parallel, we conducted a GWAS of 319 of those cases and leveraged controlled-access data from 9,921 controls in the ADDHealth study. Genotyping of the 319 cases was also performed at the Avera Institute for Human Genetics on the Illumina Infinium Global Screening Array. We evaluated the role of common variants (minor allele frequency &amp;gt;5%) on LCH risk and applied principal components analysis to account for potential population stratification. A genome-wide threshold of significance was applied at P-value&amp;lt;5.0x10 -8, and threshold of suggestive significance at P-value&amp;lt;1.0x10 -6. Analyses were conducted in Plink and STATAv17.1. Results: The case-control study of targeted SMAD6 identified novel SMAD6 variants associated with LCH risk ( P-values ranging from 4.54x10 -28 to 2.9x10 -4), including our original GWAS locus. All cases with two copies of the alternate alleles in the top 2 SNPs had BRAF V600E + lesions. In terms of the new GWAS, 31 novel loci were associated with LCH at P-value=5x10 -8, including 2 separate loci on Chr 9, with the top hit being intergenic between KCNV2 and VLDLR on Chr 9 and the second being intergenic between OLFM1 and LOC401557. Other identified top hits suggest putative biologic significance in terms of LCH pathogenesis. Conclusion: We identified additional support that inherited genetic variation impacts LCH risk. We are concurrently assessing the role of ancestry-specific loci on LCH risk and analyzing newly generated SMAD6 targeted sequence and GWAS data in an independent set of case-parent trios (n=185) to integrate with the findings reported here. Next steps include a meta-analysis of our discovery GWAS, the new GWAS reported here, and the recently genotyped new set of 185 case-parent trios. We also aim to determine the role of variants on clinical characteristics (e.g., ancestry, age at onset, BRAF V600E). Our work suggests an important and complex role of germline variants and ancestry in LCH pathogenesis.

Ancestry-Specific Genetic Determinants of Clonal Haematopoiesis: A Comparative Analysis of 136,401 Admixed Americans and 419,228 Europeans

Introduction: Somatic mutations in blood stem cells can drive clonal expansion and result in clonal haematopoiesis (CH). CH is a precursor to myeloid malignancies, and is increasingly also recognised as a risk factor for non-malignant diseases. CH has been investigated in Europeans, but remains understudied in non-European populations. Here, we investigate the causes and consequences of CH in two large prospective cohort studies, specifically the Mexico City Prospective Study (MCPS) and UK Biobank (UKB). MCPS represents the largest CH study in a non-European population to date. Methods: Admixed Americans were identified from MCPS (n=136,401) while Europeans were identified from the UKB (n=419,228) participants. Somatic variant calling was performed using Mutect2 on whole exome sequencing (WES) data across a selected panel of genes to identify putative CH driver mutations. WES was performed at an average depth of 55x, and CH was defined using a variant allele frequency of ≥3%. Genome-wide association studies (GWAS) for CH were performed using imputed array data, and exome-wide association studies (ExWAS) and gene-level association analyses using WES data. Global/Continental-level ancestry was assigned based on peddy score ≥95% while local ancestry was inferred using RFMix (Ziyatdinov et al., 2022). Results: The most recurrently mutated genes in MCPS and UKB were DNMT3A, TET2, ASXL1, PPM1D, TP53, SF3B1 and SRSF2. The prevalence of CH increased progressively with age to approximately 8/22 (36%) detected as carriers at age 100 and above. CH was 40% more prevalent in age-matched Europeans (4.96%) compared to Admixed Americans (3.10%). Inter-population comparison revealed overall CH, DNMT3A-, TET2-, ASXL1-, PPM1D-, TP53-, JAK2-, and SRSF2-mutant CH to be more prevalent in UKB relative to MCPS (Figure A). Intra-population analysis of the Admixed American cohort further revealed that individuals with a higher fraction of European ancestry were at higher risk of overall CH, DNMT3A-, ASXL1-, and SRSF2-mutant CH, but not TET2-, PPM1D-, TP53-, and JAK2-mutant CH. These suggest differences in relative contribution of genetic, lifestyle or environment factors to specific CH genes. CH GWAS performed in Admixed Americans recapitulated previously reported variants in Europeans, and also identified novel, ancestry-specific variants associated with CH risk, including SNPs upstream of TCL1B (rs968294563: OR=1.79, P=2.01x10 -9; rs187319135: OR=1.85, P=2.69x10 -9). Notably, TCL1B variants were associated with an increased risk of TET2- and ASXL1-mutant CH (rs968294563: OR=3.17, P=3.82x10 -16 for TET2; OR=2.36, P=2.40x10 -3 for ASXL1), but a decreased risk of DNMT3A-mutantCH (rs968294563: OR=0.51, P=6.32x10 -4) (Figure B). The minor allele frequency (MAF) of the most common TCL1B variant in Admixed Americans was 1.23% but was virtually absent in Europeans. CH ExWAS can identify rare causal variants not captured by genotyping or imputation, and these variants may be in linkage disequilibrium with common variants detectable via GWAS. Indeed, ExWAS in Admixed Americans identified one rare SNP on the TCL1B promoter (rs774615666: OR=2.24, P=1.94x10 -8) that was associated with an increased risk of TET2-mutantCH (OR=4.19, P=2.77x10 -10) and a decreased risk of DNMT3A-mutantCH (OR=0.13, P=1.65x10 -4), mirroring our GWAS findings. The rs774615666 risk allele was &amp;gt;200-fold more common in Admixed Americans (MAF: 0.33%) compared to Europeans (MAF: 0.0011%) and was not in linkage disequilibrium with the previously reported TCL1A promoter CH risk SNP in Europeans (Weinstock et al., 2023). Meta-analyses were performed using 555,629 individuals, from both MCPS Admixed American CH GWAS and UKB European CH GWAS. Of the 11 loci reported for overall CH, one was novel, namely GACAT3/ CYRIA. Lastly, we investigated the phenotypic associations of CH in Admixed Americans. Gene-specific CH was associated with increased risk of death from haematological malignancies ( TET2, TP53, SF3B1, and SRSF2), other cancer types ( ASXL1, DNMT3A, and SRSF2) and cardiovascular diseases( DNMT3A, TP53). Conclusions: The substantial difference in CH prevalence between populations and the ancestry-specific genetic associations, demonstrate how the analysis of non-European cohorts can generate novel insights and highlights the importance of such analyses in advancing health equality amongst different human populations.

Assessment of multi-trait analysis of GWAS (MTAG) for discovery of novel genetic variants and mechanistic insight in common cardiovascular diseases

Abstract Background Variability in cardiovascular conditions is partly explained by common genomic variation identifiable by genome-wide association studies (GWAS). Genetic substrate may overlap in certain entities, this being quantified by genetic correlation. We aimed to leverage multi-trait analysis of GWAS (MTAG), (1) which boosts statistical power by joint analysis of genetically correlated traits, to improve genetic loci discovery in 3 common cardiovascular diseases: atrial fibrillation (AF), coronary artery disease (CAD), and heart failure (HF). Methods and Results Cardiovascular phenotypes with available GWAS summary statistics most correlated with the disease of interest were analysed jointly by MTAG (workflow depicted in Figure 1). These included body mass index and HF for AF (2); HF, LDL-cholesterol, and systolic blood pressure for CAD (3); and AF, CAD, and dilated cardiomyopathy for HF (4). MTAG increased statistical power for all 3 disease GWAS and allowed the identification of 19 new genomic loci for AF, 89 for CAD and 52 for HF (at a GWAS significance level P&amp;lt;5x10-8) (Figure 2). New loci were defined as not previously identified in the single trait original GWAS. Consistently, 19/19, 85/89 and 48/52 of new loci reached nominal significance (P&amp;lt;0.05) in the original studies; and 37%, 44% and 36% of new loci have been associated with AF, CAD and HF in GWAS and phenome wide association studies (PheWAS) in independent cohorts. MTAG summary statistics annotation and functional analysis integrated the distance to the canonical transcriptional start site, chromatin interaction experiments, quantitative molecular phenotype trait experiments and in silico functional prediction through OpenTargets Genetics. MAGMA gene-set functional analysis of the new MTAG results showed 87, 27 and 24 significant associated pathways to AF, CAD and HF respectively. Among the top associations, cardiac depolarization, repolarization, and muscle contraction in AF; macromolecular complex remodeling, triglyceride, chylomicron and LDL metabolism in CAD; and muscle structure, tissue development and RNA transcription initiation in HF. Among novel relevant genes in AF, SRR on chromosome 16 is involved in central nervous system development through regulation of NMDA receptors. This locus has been previously associated with QRS in another GWAS and SRR is related to reduction in heart rate variability and AF enhancement in rats. In CAD, RSPO3 and JAG1 genes, on chromosomes 6 and 20 respectively, have a relevant role in angiogenesis, where RSPO3 is a crucial regulator of coronary artery formation in the developing heart. Conclusions MTAG allows the discovery of new trait-specific loci involved in the pathogenesis of AF, CAD, and HF congruent with the mechanisms of each disease and consistent with independent external cohort PheWAS and GWAS. Thus, MTAG is an interesting tool to unravel relevant mechanisms and potential therapeutic targets in common cardiovascular diseases.

MTHFR, NR3C1, FKBP5, and CRHR1 gene polymorphisms are strongly associated with depressive disorder susceptibility: A meta-analysis and power analysis

Depression is a polygenic and complex condition; however, most genetic analyses have yielded insignificant associations between candidate genes and depressive disorder. This is primarily due to the lack of reproducible findings in genome-wide association studies (GWAS). In this meta-analysis, we extensively investigated the implications of genetic polymorphisms in seven candidate genes for depression. We conducted a thorough search of electronic databases, including Google Scholar, Cochrane, PubMed, Medline, Embase, and PsycINFO, covering data from January 1997 to 2022. Our search identified approximately 3,500 published research papers related to this study. Among these, 81 studies met our eligibility criteria and focused on the six genes under study. These selected candidate genes for our meta-analysis included NR3C1, MTHFR, FKBP5, CRHR1, COMT, and TNF-α. The results of our meta-analysis on genetic polymorphisms indicate a significant association with depression at the 95% confidence interval (CI). When categorizing outcomes by different ethnic groups, our findings reveal significant results (p=<0.05) for Asian and Caucasian populations. This current meta-analysis provides valuable insights that can facilitate the use of these significantly associated genes for diagnosing the severity of depression or as indicators for treatment modalities in depression conditions.

Regulome-wide association study identifies genetically driven accessible regions associated with pancreatic cancer risk.

Genome-wide association studies (GWAS) have identified two dozen genetic variants that are associated with the risk of pancreatic ductal adenocarcinoma (PDAC), a deadly malignancy. However, a majority of these variants are located in noncoding regions of the genome, which limits the translation of GWAS findings into clinical applications. The regulome-wide association study (RWAS) is a recently developed method for identifying TF binding-induced accessibility regions for diseases. However, their potential connection to PDAC has yet to be fully explored. We evaluated the associations between genetically predicted levels of chromatin accessibility and risk of PDAC by using pan-cancer chromatin accessibility genetic prediction models. Our analysis included 8275 cases and 6723 controls from the PanScan (I, II, and III) and PanC4 consortia. To further refine our results, we also integrated genes associated to allele-specific accessibility quantitative trait loci (as-aQTL) and TF motifs located in the as-aQTL. We found that 50 chromatin accessibility features were associated with PDAC risk at a false discovery rate (FDR) of less than 0.05. A total of 28 RWAS peaks were identified as conditionally significant. By integrating the results from as-aQTL, motif analysis, and RWAS, we identified candidate causal regulatory elements for two potential chromatin accessibility regions (THCA_89956 and ESCA_89167) that are associated with PDAC risk. Our study identified chromatin accessibility features in noncoding genomic regions that are associated with PDAC risk. We also predicted the associated genes and disrupt motifs. Our findings provide new insights into the regulatory mechanisms of noncoding regions for pancreatic tumorigenesis.