Reference-based phasing using the Haplotype Reference Consortium panel

Common variants increase risk for congenital diaphragmatic hernia within the context of de novo variants

Congenital diaphragmatic hernia (CDH) is a severe congenital anomaly often accompanied by other structural anomalies and/or neurobehavioral manifestations. Rare de novo protein-coding variants and copy-number variations contribute to CDH in the population. However, most individuals with CDH remain genetically undiagnosed. Here, we perform integrated de novo and common-variant analyses using 1,469 CDH individuals, including 1,064 child-parent trios and 6,133 ancestry-matched, unaffected controls for the genome-wide association study. We identify candidate CDH variants in 15 genes, including eight novel genes, through deleterious de novo variants. We further identify two genomic loci contributing to CDH risk through common variants with similar effect sizes among Europeans and Latinx. Both loci are in putative transcriptional regulatory regions of developmental patterning genes. Estimated heritability in common variants is ∼19%. Strikingly, there is no significant difference in estimated polygenic risk scores between isolated and complex CDH or between individuals harboring deleterious de novo variants and individuals without these variants. The data support a polygenic model as part of the CDH genetic architecture.

The pleiotropic spectrum of proximal 16p11.2 CNVs

Recurrent genomic rearrangements at 16p11.2 BP4-5 represent one of the most common causes of genomic disorders. Originally associated with increased risk for autism spectrum disorder, schizophrenia, and intellectual disability, as well as adiposity and head circumference, these CNVs have since been associated with a plethora of phenotypic alterations, albeit with high variability in expressivity and incomplete penetrance. Here, we comprehensively review the pleiotropy associated with 16p11.2 BP4-5 rearrangements to shine light on its full phenotypic spectrum. Illustrating this phenotypic heterogeneity, we expose many parallels between findings gathered from clinical versus population-based cohorts, which often point to the same physiological systems, and emphasize the role of the CNV beyond neuropsychiatric and anthropometric traits. Revealing the complex and variable clinical manifestations of this CNV is crucial for accurate diagnosis and personalized treatment strategies for carrier individuals. Furthermore, we discuss areas of research that will be key to identifying factors contributing to phenotypic heterogeneity and gaining mechanistic insights into the molecular pathways underlying observed associations, while demonstrating how diversity in affected individuals, cohorts, experimental models, and analytical approaches can catalyze discoveries.

Polygenic and transcriptional risk scores identify chronic obstructive pulmonary disease subtypes in the COPDGene and ECLIPSE cohort studies

BACKGROUND

Genetic variants and gene expression predict risk of chronic obstructive pulmonary disease (COPD), but their effect on COPD heterogeneity is unclear. We aimed to define high-risk COPD subtypes using genetics (polygenic risk score, PRS) and blood gene expression (transcriptional risk score, TRS) and assess differences in clinical and molecular characteristics.

METHODS

We defined high-risk groups based on PRS and TRS quantiles by maximising differences in protein biomarkers in a COPDGene training set and identified these groups in COPDGene and ECLIPSE test sets. We tested multivariable associations of subgroups with clinical outcomes and compared protein-protein interaction networks and drug repurposing analyses between high-risk groups.

FINDINGS

We examined two high-risk omics-defined groups in non-overlapping test sets (n = 1133 NHW COPDGene, n = 299 African American (AA) COPDGene, n = 468 ECLIPSE). We defined "high activity" (low PRS, high TRS) and "severe risk" (high PRS, high TRS) subgroups. Participants in both subgroups had lower body-mass index (BMI), lower lung function, and alterations in metabolic, growth, and immune signalling processes compared to a low-risk (low PRS, low TRS) subgroup. "High activity" but not "severe risk" participants had greater prospective FEV1 decline (COPDGene: -51 mL/year; ECLIPSE: -40 mL/year) and proteomic profiles were enriched in gene sets perturbed by treatment with 5-lipoxygenase inhibitors and angiotensin-converting enzyme (ACE) inhibitors.

INTERPRETATION

Concomitant use of polygenic and transcriptional risk scores identified clinical and molecular heterogeneity amongst high-risk individuals. Proteomic and drug repurposing analysis identified subtype-specific enrichment for therapies and suggest prior drug repurposing failures may be explained by patient selection.

FUNDING

National Institutes of Health.

High incidence and geographic distribution of cleft palate in Finland are associated with the IRF6 gene

In Finland, the frequency of isolated cleft palate (CP) is higher than that of isolated cleft lip with or without cleft palate (CL/P). This trend contrasts to that in other European countries but its genetic underpinnings are unknown. We conducted a genome-wide association study in the Finnish population and identified rs570516915, a single nucleotide polymorphism highly enriched in Finns, as strongly associated with CP (P = 5.25 × 10-34, OR = 8.65, 95% CI 6.11-12.25), but not with CL/P (P = 7.2 × 10-5), with genome-wide significance. The risk allele frequency of rs570516915 parallels the regional variation of CP prevalence in Finland, and the association was replicated in independent cohorts of CP cases from Finland (P = 8.82 × 10-28) and Estonia (P = 1.25 × 10-5). The risk allele of rs570516915 alters a conserved binding site for the transcription factor IRF6 within an enhancer (MCS-9.7) upstream of the IRF6 gene and diminishes the enhancer activity. Oral epithelial cells derived from CRISPR-Cas9 edited induced pluripotent stem cells demonstrate that the CP-associated allele of rs570516915 concomitantly decreases the binding of IRF6 and the expression level of IRF6, suggesting impaired IRF6 autoregulation as a molecular mechanism underlying the risk for CP.

Effects of reference population size and structure on genomic prediction of maternal traits in two pig lines using whole-genome sequence-, high-density- and combined annotation-dependent depletion genotypes

The aim of this study was to investigate the reference population size required to obtain substantial prediction accuracy within- and across-lines and the effect of using a multi-line reference population for genomic predictions of maternal traits in pigs. The data consisted of two nucleus pig populations, one pure-bred Landrace (L) and one Synthetic (S) Yorkshire/Large White line. All animals were genotyped with up to 30 K animals in each line, and all had records on maternal traits. Prediction accuracy was tested with three different marker data sets: High-density SNP (HD), whole genome sequence (WGS), and markers derived from WGS based on pig combined annotation dependent depletion-score (pCADD). Also, two different genomic prediction methods (GBLUP and Bayes GC) were compared for four maternal traits; total number piglets born (TNB), total number of stillborn piglets (STB), Shoulder Lesion Score and Body Condition Score. The main results from this study showed that a reference population of 3 K-6 K animals for within-line prediction generally was sufficient to achieve high prediction accuracy. However, when the number of animals in the reference population was increased to 30 K, the prediction accuracy significantly increased for the traits TNB and STB. For multi-line prediction accuracy, the accuracy was most dependent on the number of within-line animals in the reference data. The S-line provided a generally higher prediction accuracy compared to the L-line. Using pCADD scores to reduce the number of markers from WGS data in combination with the GBLUP method generally reduced prediction accuracies relative to GBLUP using HD genotypes. The BayesGC method benefited from a large reference population and was less dependent on the different genotype marker datasets to achieve a high prediction accuracy.

Unraveling metabolic stress response in dairy cows: Genetic control of plasma biomarkers throughout lactation and the transition period

Breeding animals able to effectively respond to stress could be a long-term, sustainable, and affordable strategy to improve resilience and welfare in livestock systems. In the present study, the concentrations of 29 plasma biomarkers were used as candidate endophenotypes for metabolic stress response in single-SNP, gene- and haplotype-based GWAS using 739 healthy lactating Italian Holstein cows and 88,271 variants. Significant genetic associations were found in all the 3 GWAS approaches for plasma γ-glutamyl transferase concentration on BTA17, for paraoxonase on BTA4, and for alkaline phosphatase and zinc on BTA2. On these chromosomes, single-SNP and gene-based chromosome-wide association studies were performed, confirming GWAS findings. The signals identified for paraoxonase, γ-glutamyl transferase, and alkaline phosphatase were in proximity to the genes coding for them. The heritability of these 4 biomarkers ranged from moderate to high (from 0.39 to 0.54). Plasma biomarkers are known to undergo large changes in concentration during metabolic stress in the transition period, with an interindividual variability in the rate of change and recovery time. Genetics may account in part for these differences. To assess this, we studied a subset of 139 periparturient cows homozygous at 3 SNPs known to be respectively associated with concentration of plasma ceruloplasmin, paraoxonase, and γ-glutamyl transferase. We compared the immune-metabolic profile measured in plasma at -7, +5, and +30 d relative to calving between groups of opposite homozygotes. A significant effect of the genotype was found on paraoxonase and γ-glutamyl transferase plasma concentration at all the 3 time points. No evidence for genotype effect was detected for ceruloplasmin. Understanding the genetic control underlying metabolic stress response may suggest new approaches to foster resilience in dairy cows.

Effects of polygenic risk score and sodium and potassium intake on hypertension in Asians: A nationwide prospective cohort study

Genetic factors, lifestyle, and diet have been shown to play important roles in the development of hypertension. Increased salt intake is an important risk factor for hypertension. However, research on the involvement of genetic factors in the relationship between salt intake and hypertension in Asians is lacking. We aimed to investigate the risk of hypertension in relation to sodium and potassium intake and the effects of genetic factors on their interactions. We used Korean Genome and Epidemiology Study data and calculated the polygenic risk score (PRS) for the effect of systolic and diastolic blood pressure (SBP and DBP). We also conducted multivariable logistic modeling to evaluate associations among incident hypertension, PRSSBP, PRSDBP, and sodium and potassium intake. In total, 41,351 subjects were included in the test set. The top 10% PRSSBP group was the youngest of the three groups (bottom 10%, middle, top 10%), had the highest proportion of women, and had the highest body mass index, baseline BP, red meat intake, and alcohol consumption. The multivariable logistic regression model revealed the risk of hypertension was significantly associated with higher PRSSBP, higher sodium intake, and lower potassium intake. There was significant interaction between sodium intake and PRSSBP for incident hypertension especially in sodium intake ≥2.0 g/day and PRSSBP top 10% group (OR 1.27 (1.07-1.51), P = 0.007). Among patients at a high risk of incident hypertension due to sodium intake, lifestyle modifications and sodium restriction were especially important to prevent hypertension.

Imputation accuracy and carrier frequency of deleterious recessive defects in Australian dairy cattle

Widespread genotyping has enabled the identification of putative recessive mutations that affect fertility through early embryonic fetal loss, or that compromise neonate or calf viability. The use of artificial insemination in the global dairy population can rapidly spread these harmful mutations, and testing for multiple mutations can become relatively expensive if not all tests are available on the same SNP panel. However, it is possible to provide heifer and cow predicted carrier status to farmers at no additional cost if the animals are genotyped with a standard SNP panel. Additionally, for defects where the causal mutation is unknown but a haplotype of markers has been associated with the defect, the carrier status can be predicted based on that haplotype. The aims of this study were 3-fold: (1) to determine the accuracy of imputation of putative causal mutations for recessive deleterious conditions in Australian dairy cattle, (2) to impute carrier status for known recessive deleterious conditions in all genotyped Australian Holstein, Jersey, and Red breed cows, and (3) to determine the changes in carrier frequencies across time for these recessive deleterious mutations. We used the F1 statistic, combining precision and recall, to assess the accuracy of carrier status prediction. We showed that known deleterious mutations can be accurately imputed in Australian Holstein and Jersey cattle that are not directly genotyped for the causal mutation, with F1 ranging between 0.88 and 0.99. For recessive deleterious conditions not included on the standard Australian SNP panel, carrier status could be predicted using a marker haplotype, with F1 ranging from 0.91 to 0.92. Most putative causals and haplotypes were either stable with a low carrier percentage or had a declining carrier percentage. However, several recessive mutations showed a relatively high or increasing percentage, highlighting the importance of detecting carriers to reduce the number of at-risk matings. Furthermore, the high carrier percentage of the recently identified bovine lymphocyte intestinal retention defect mutation emphasizes the importance of detection of novel mutations.

Response eQTLs, chromatin accessibility, and 3D chromatin structure in chondrocytes provide mechanistic insight into osteoarthritis risk

Osteoarthritis (OA) poses a significant healthcare burden with limited treatment options. While genome-wide association studies (GWAS) have identified over 100 OA-associated loci, translating these findings into therapeutic targets remains challenging. Integrating expression quantitative trait loci (eQTL), 3D chromatin structure, and other genomic approaches with OA GWAS data offers a promising approach to elucidate disease mechanisms; however, comprehensive eQTL maps in OA-relevant tissues and conditions remain scarce. We mapped gene expression, chromatin accessibility, and 3D chromatin structure in primary human articular chondrocytes in both resting and OA-mimicking conditions. We identified thousands of differentially expressed genes, including those associated with differences in sex and age. RNA-seq in chondrocytes from 101 donors across two conditions uncovered 3782 unique eGenes, including 420 that exhibited strong and significant condition-specific effects. Colocalization with OA GWAS signals revealed 13 putative OA risk genes, 10 of which have not been previously identified. Chromatin accessibility and 3D chromatin structure provided insights into the mechanisms and conditional specificity of these variants. Our findings shed light on OA pathogenesis and highlight potential targets for therapeutic development.

Genome-wide association and functional genomic analyses for body conformation traits in North American Holstein cattle

Body conformation traits are directly associated with longevity, fertility, health, and workability in dairy cows and have been under direct genetic selection for many decades in various countries worldwide. The main objectives of this study were to perform genome-wide association studies and functional enrichment analyses for fourteen body conformation traits using imputed high-density single nucleotide polymorphism (SNP) genotypes. The traits analyzed include body condition score (BCS), body depth (BD), bone quality (BQ), chest width (CW), dairy capacity (DC), foot angle (FAN), front legs view (FLV), heel depth (HDe), height at front end (HFE), locomotion (LOC), rear legs rear view (RLRV), rear legs side view (RLSV), stature (ST), and a composite feet and legs score index (FL) of Holstein cows scored in Canada. De-regressed estimated breeding values from a dataset of 39,135 North American Holstein animals were used as pseudo-phenotypes in the genome-wide association analyses. A mixed linear model was used to estimate the SNP effects, which ranged from 239,533 to 242,747 markers depending on the trait analyzed. Genes and quantitative trait loci (QTL) located up to 100 Kb upstream or downstream of the significant SNPs previously cited in the Animal QTLdb were detected, and functional enrichment analyses were performed for the candidate genes identified for each trait. A total of 20, 60, 13, 17, 27, 8, 7, 19, 4, 10, 13, 15, 7, and 13 genome-wide statistically significant SNPs for Bonferroni correction based on independent chromosomal segments were identified for BCS, BD, BQ, CW, DC, FAN, FLV, HDe, HFE, LOC, RLRV, RLSV, ST, and FL, respectively. The significant SNPs were located across the whole genome, except on chromosomes BTA24, BTA27, and BTA29. Four markers (for BCS, BD, HDe, and RLRV) were statistically significant when considering a much stricter threshold for the Bonferroni correction for multiple tests. Moreover, the genomic regions identified overlap with various QTL previously reported for the trait groups of exterior, health, meat and carcass, milk, production, and reproduction. The functional enrichment analyses revealed 27 significant gene ontology terms. These enriched genomic regions harbor various candidate genes previously reported as linked to bone development, metabolism, as well as infectious and immunological diseases.

Longitudinal joint effects of polycyclic aromatic hydrocarbons exposure and genetic susceptibility on fasting plasma glucose: a prospective cohort study of general Chinese urban adults

The effects of environmental polycyclic aromatic hydrocarbons (PAHs) exposure on glycemic regulation and the underlying genetic mechanism were still unclear. This study aimed to analyze the longitudinal joint effects of PAHs exposure and genetic susceptibility on fasting plasma glucose (FPG) through a longitudinal study. We included 4104 observations (2383 baseline participants and 1721 6-year follow-up participants) from Wuhan-Zhuhai cohort. Ten urinary PAHs metabolites and FPG were measured at both baseline and follow-up. We constructed the polygenic risk scores (PRS) of FPG from the corresponding genome-wide association studies. Linear mixed models were used to explore the associations of urinary PAHs metabolites or FPG-PRS on FPG levels in the repeated-measure analysis. Besides, the longitudinal relationships of urinary PAHs metabolites, FPG-PRS, and their joint effects on FPG change over 6 years were evaluated by linear regression models. Compared with participants with persistent low levels of urinary total PAHs metabolites, hydroxynaphthalene, and hydroxyphenanthrene, participants with persistent high levels had average decreases of 0.180, 0.200, and 0.261 mmol/L for FPG change over 6 years, respectively. Each 1-unit increase of FPG-PRS was associated with a 0.521 mmol/L for FPG change over 6 years. Besides, compared with participants with high FPG-PRS and persistent low levels of urinary total hydroxynaphthalene, hydroxyfluorene, and hydroxyphenanthrene, participants with low FPG-PRS and persistent high levels had average decreases of 0.330, 0.557, and 0.421 mmol/L for FPG change over 6 years. Our findings demonstrated that high-level PAHs exposure was longitudinally associated with an average decrease of FPG over 6 years, and low FPG genetic risk can enhance the above associations. Our findings emphasized the hypoglycemic effect of PAHs exposure, shed new light on the complex effects between PAHs exposure and genetic factors in the prevention of high FPG, and might provide some clues for the development of potential hypoglycemic agents.

Interactions of genes with alcohol consumption affect insulin sensitivity and beta cell function

AIMS/HYPOTHESIS

Alcohol consumption has complex effects on diabetes and metabolic disease, but there is widespread heterogeneity within populations and the specific reasons are unclear. Genetic factors may play a role and warrant exploration. The aim of this study was to elucidate genetic variants modulating the impact of alcohol consumption on insulin sensitivity and pancreatic beta cell function within populations presenting normal glucose tolerance (NGT).

METHODS

We recruited 4194 volunteers in Nanjing, 854 in Jurong and an additional 5833 in Nanjing for Discovery cohorts 1 and 2 and a Validation cohort, respectively. We performed an OGTT on all participants, establishing a stringent NGT group, and then assessed insulin sensitivity and beta cell function. Alcohol consumption was categorised as abstinent, light-to-moderate (<210 g per week) or heavy (≥210 g per week). After excluding ineligible individuals, an exploratory genome-wide association study identified potential variants interacting with alcohol consumption in 1862 NGT individuals. These findings were validated in an additional cohort of 2169 NGT individuals. Cox proportional hazard regression was further employed to evaluate the effect of the interaction between the potential variants and alcohol consumption on the risk of type 2 diabetes within the UK Biobank cohort.

RESULTS

A significant correlation was observed between drinking levels and insulin sensitivity, accompanied by a consequent inverse relationship with insulin resistance and beta cell insulin secretion after adjusting for confounding factors in NGT individuals. However, no significant associations were noted in the disposition indexes. The interaction of variant rs56221195 with alcohol intake exhibited a pronounced effect on the liver insulin resistance index (LIRI) in the discovery set, corroborated in the validation set (combined p=1.32 × 10-11). Alcohol consumption did not significantly affect LIRI in rs56221195 wild-type (TT) carriers, but a strong negative association emerged in heterozygous (TA) and homozygous (AA) individuals. The rs56221195 variant also significantly interacts with alcohol consumption, influencing the total insulin secretion index INSR120 (the ratio of the AUC of insulin to glucose from 0 to 120 min) (p=2.06 × 10-9) but not disposition index. In the UK Biobank, we found a significant interaction between rs56221195 and alcohol consumption, which was linked to the risk of type 2 diabetes (HR 0.897, p=0.008).

CONCLUSIONS/INTERPRETATION

Our findings reveal the effects of the interaction of alcohol and rs56221195 on hepatic insulin sensitivity in NGT individuals. It is imperative to weigh potential benefits and detriments thoughtfully when considering alcohol consumption across diverse genetic backgrounds.

Role of Planetary Health Diet in the association between genetic susceptibility to obesity and anthropometric measures in adults

BACKGROUND/OBJECTIVE

The roles of overall diet quality in linking genetic background with anthropometric measures are unclear, particularly regarding the recently developed Planetary Health Diet (PHD). This study aims to determine if the PHD mediates or moderates the relationship between genetic susceptibility to obesity and anthropometric measures.

SUBJECTS/METHODS

The study involved 2942 individuals from a Finnish population-based cohort (54% women, mean age 53 (SD ± 13) years). Habitual diet was assessed using a validated 130-item food frequency questionnaire, and the PHD Score (total score range 0-13 points) was adapted for Finnish food culture to evaluate diet quality. Genetic susceptibility to obesity was evaluated with a polygenic risk score (PRS) based on one million single nucleotide polymorphisms associated with body mass index (BMI). Baseline anthropometrics included weight, height, waist circumference (WC), and body fat percentage, with changes in these measures tracked over 7 years. A five-step multiple linear regression model and multivariable logistic regression with interaction terms were used to assess the mediating and moderating effects of the PHD. These analyses were also replicated in another Finnish cohort study (2 834 participants).

RESULTS

PRS for BMI was positively associated with baseline BMI and changes in anthropometric measures, except waist circumference (p = 0.12). Significant associations were observed for baseline BMI and WC (p < 0.001), changes in BMI and WC (p = 0.01), and body fat percentage change (p = 0.05). However, the PHD (average score 3.8 points) did not mediate or moderate these relationships. These findings were consistent in the replication cohort.

CONCLUSION

Diet quality assessed with the PHD did not mediate or moderate the associations between genetic susceptibility to obesity and anthropometric measures. This lack of effect may be partly due to low adherence to the PHD and the older age of participants ( > 50 years) at baseline.

Secure discovery of genetic relatives across large-scale and distributed genomic data sets

Finding relatives within a study cohort is a necessary step in many genomic studies. However, when the cohort is distributed across multiple entities subject to data-sharing restrictions, performing this step often becomes infeasible. Developing a privacy-preserving solution for this task is challenging owing to the burden of estimating kinship between all the pairs of individuals across data sets. We introduce SF-Relate, a practical and secure federated algorithm for identifying genetic relatives across data silos. SF-Relate vastly reduces the number of individual pairs to compare while maintaining accurate detection through a novel locality-sensitive hashing (LSH) approach. We assign individuals who are likely to be related together into buckets and then test relationships only between individuals in matching buckets across parties. To this end, we construct an effective hash function that captures identity-by-descent (IBD) segments in genetic sequences, which, along with a new bucketing strategy, enable accurate and practical private relative detection. To guarantee privacy, we introduce an efficient algorithm based on multiparty homomorphic encryption (MHE) to allow data holders to cooperatively compute the relatedness coefficients between individuals and to further classify their degrees of relatedness, all without sharing any private data. We demonstrate the accuracy and practical runtimes of SF-Relate on the UK Biobank and All of Us data sets. On a data set of 200,000 individuals split between two parties, SF-Relate detects 97% of third-degree or closer relatives within 15 h of runtime. Our work enables secure identification of relatives across large-scale genomic data sets.

Somatic mosaicism in schizophrenia brains reveals prenatal mutational processes

Germline mutations modulate the risk of developing schizophrenia (SCZ). Much less is known about the role of mosaic somatic mutations in the context of SCZ. Deep (239×) whole-genome sequencing (WGS) of brain neurons from 61 SCZ cases and 25 controls postmortem identified mutations occurring during prenatal neurogenesis. SCZ cases showed increased somatic variants in open chromatin, with increased mosaic CpG transversions (CpG>GpG) and T>G mutations at transcription factor binding sites (TFBSs) overlapping open chromatin, a result not seen in controls. Some of these variants alter gene expression, including SCZ risk genes and genes involved in neurodevelopment. Although these mutational processes can reflect a difference in factors indirectly involved in disease, increased somatic mutations at developmental TFBSs could also potentially contribute to SCZ.

Genome-wide studies define new genetic mechanisms of IgA vasculitis

IgA vasculitis (IgAV) is a pediatric disease with skin and systemic manifestations. Here, we conducted genome, transcriptome, and proteome-wide association studies in 2,170 IgAV cases and 5,928 controls, generated IgAV-specific maps of gene expression and splicing from blood of 255 pediatric cases, and reconstructed myeloid-specific regulatory networks to define disease master regulators modulated by the newly identified disease driver genes. We observed significant association at the HLA-DRB1 (OR=1.55, P=1.1×10-25) and fine-mapped specific amino-acid risk substitutions in DRβ1. We discovered two novel non-HLA loci: FCAR (OR=1.51, P=1.0×10-20) encoding a myeloid IgA receptor FcαR, and INPP5D (OR=1.34, P=2.2×10-9) encoding a known inhibitor of FcαR signaling. The FCAR risk locus co-localized with a cis-eQTL increasing FCAR expression; the risk alleles disrupted a PRDM1 binding motif within a myeloid enhancer of FCAR. Another risk locus was associated with a higher genetically predicted levels of plasma IL6R. The IL6R risk haplotype carried a missense variant contributing to accelerated cleavage of IL6R into a soluble form. Using systems biology approaches, we prioritized IgAV master regulators co-modulated by FCAR, INPP5D and IL6R in myeloid cells. We additionally identified 21 shared loci in a cross-phenotype analysis of IgAV with IgA nephropathy, including novel loci PAID4, WLS, and ANKRD55.

Multivariable Mendelian randomization with incomplete measurements on the exposure variables in the Hispanic Community Health Study/Study of Latinos

Multivariable Mendelian randomization allows simultaneous estimation of direct causal effects of multiple exposure variables on an outcome. When the exposure variables of interest are quantitative omic features, obtaining complete data can be economically and technically challenging: the measurement cost is high, and the measurement devices may have inherent detection limits. In this paper, we propose a valid and efficient method to handle unmeasured and undetectable values of the exposure variables in a one-sample multivariable Mendelian randomization analysis with individual-level data. We estimate the direct causal effects with maximum likelihood estimation and develop an expectation-maximization algorithm to compute the estimators. We show the advantages of the proposed method through simulation studies and provide an application to the Hispanic Community Health Study/Study of Latinos, which has a large amount of unmeasured exposure data.

Phenome-wide association study in 25,639 pregnant Chinese women reveals loci associated with maternal comorbidities and child health

Phenome-wide association studies (PheWAS) have been less focused on maternal diseases and maternal-newborn comorbidities, especially in the Chinese population. To enhance our understanding of the genetic basis of these related diseases, we conducted a PheWAS on 25,639 pregnant women and 14,151 newborns in the Chinese Han population using ultra-low-coverage whole-genome sequence (ulcWGS). We identified 2,883 maternal trait-associated SNPs associated with 26 phenotypes, among which 99.5% were near established genome-wide association study (GWAS) loci. Further refinement delineated these SNPs to 442 unique trait-associated loci (TALs) predicated on linkage disequilibrium R2 > 0.8, revealing that 75.6% demonstrated pleiotropy and 50.9% were located in genes implicated in analogous phenotypes. Notably, we discovered 21 maternal SNPs associated with 35 neonatal phenotypes, including two SNPs associated with identical complications in both mothers and children. These findings underscore the importance of integrating ulcWGS data to enrich the discoveries derived from traditional PheWAS approaches.

Genome-wide association testing beyond SNPs

Decades of genetic association testing in human cohorts have provided important insights into the genetic architecture and biological underpinnings of complex traits and diseases. However, for certain traits, genome-wide association studies (GWAS) for common SNPs are approaching signal saturation, which underscores the need to explore other types of genetic variation to understand the genetic basis of traits and diseases. Copy number variation (CNV) is an important source of heritability that is well known to functionally affect human traits. Recent technological and computational advances enable the large-scale, genome-wide evaluation of CNVs, with implications for downstream applications such as polygenic risk scoring and drug target identification. Here, we review the current state of CNV-GWAS, discuss current limitations in resource infrastructure that need to be overcome to enable the wider uptake of CNV-GWAS results, highlight emerging opportunities and suggest guidelines and standards for future GWAS for genetic variation beyond SNPs at scale.

A genotype imputation reference panel specific for native Southeast Asian populations

We report the development of a "Southeast Asian Specific (SEA-specific) Reference Panel" through a "Cross-panel Imputation" approach, consisting of 2550 samples derived from the GA100K, SG10K, and the Peninsular Malaysia Orang Asli (OA) datasets, covering 113,851,450 variants. The SEA-specific panel produced more high confidence variants than 1000 Genomes Project (1KGP) when imputing the OA (8.9 million SEA-specific vs 8.1 million 1KGP) and the Singapore Genome Variation Project (SGVP) (12.5 million SEA-specific vs 11.8 million 1KGP) genotyping datasets. Further, the SEA-specific panel imputed SNPs with better estimated quality scores (INFO, DR2 and R2) on the OA genotyping dataset when comparing with TOPMED and the Human Genome Diversity Project, but performed similarly on SGVP dataset. This panel also exhibited higher recall and non-reference disconcordance rates, indicating the influence of ancestry closeness of the reference panel. However, we note that the imputation accuracy may be compromised by the size of the reference panel.

Multi-ancestry GWAS meta-analyses of lung cancer reveal susceptibility loci and elucidate smoking-independent genetic risk

Lung cancer remains the leading cause of cancer mortality, despite declining smoking rates. Previous lung cancer GWAS have identified numerous loci, but separating the genetic risks of lung cancer and smoking behavioral susceptibility remains challenging. Here, we perform multi-ancestry GWAS meta-analyses of lung cancer using the Million Veteran Program cohort (approximately 95% male cases) and a previous study of European-ancestry individuals, jointly comprising 42,102 cases and 181,270 controls, followed by replication in an independent cohort of 19,404 cases and 17,378 controls. We then carry out conditional meta-analyses on cigarettes per day and identify two novel, replicated loci, including the 19p13.11 pleiotropic cancer locus in squamous cell lung carcinoma. Overall, we report twelve novel risk loci for overall lung cancer, lung adenocarcinoma, and squamous cell lung carcinoma, nine of which are externally replicated. Finally, we perform PheWAS on polygenic risk scores for lung cancer, with and without conditioning on smoking. The unconditioned lung cancer polygenic risk score is associated with smoking status in controls, illustrating a reduced predictive utility in non-smokers. Additionally, our polygenic risk score demonstrates smoking-independent pleiotropy of lung cancer risk across neoplasms and metabolic traits.

Genetic modifiers of body mass index in individuals with cystic fibrosis

To identify modifier loci underlying variation in body mass index (BMI) in persons with cystic fibrosis (pwCF), we performed a genome-wide association study (GWAS). Utilizing longitudinal height and weight data, along with demographic information and covariates from 4,393 pwCF, we calculated AvgBMIz representing the average of per-quarter BMI Z scores. The GWAS incorporated 9.8M single nucleotide polymorphisms (SNPs) with a minor allele frequency (MAF) > 0.005 extracted from whole-genome sequencing (WGS) of each study subject. We observed genome-wide significant association with a variant in FTO (FaT mass and Obesity-associated gene; rs28567725; p value = 1.21e-08; MAF = 0.41, β = 0.106; n = 4,393 individuals) and a variant within ADAMTS5 (A Disintegrin And Metalloproteinase with ThromboSpondin motifs 5; rs162500; p value = 2.11e-10; MAF = 0.005, β = -0.768; n = 4,085 pancreatic-insufficient individuals). Notably, BMI-associated variants in ADAMTS5 occur on a haplotype that is much more common in African (AFR, MAF = 0.183) than European (EUR, MAF = 0.006) populations (1000 Genomes project). A polygenic risk score (PRS) calculated using 924 SNPs (excluding 17 in FTO) showed significant association with AvgBMIz (p value = 2.2e-16; r2 = 0.03). Association between variants in FTO and the PRS correlation reveals similarities in the genetic architecture of BMI in CF and the general population. Inclusion of Black individuals in whom the single-gene disorder CF is much less common but genomic diversity is greater facilitated detection of association with variants that are in LD with functional SNPs in ADAMTS5. Our results illustrate the importance of population diversity, particularly when attempting to identify variants that manifest only under certain physiologic conditions.

A genetic basis for sex differences in Xp11 translocation renal cell carcinoma

Xp11 translocation renal cell carcinoma (tRCC) is a rare, female-predominant cancer driven by a fusion between the transcription factor binding to IGHM enhancer 3 (TFE3) gene on chromosome Xp11.2 and a partner gene on either chromosome X (chrX) or an autosome. It remains unknown what types of rearrangements underlie TFE3 fusions, whether fusions can arise from both the active (chrXa) and inactive X (chrXi) chromosomes, and whether TFE3 fusions from chrXi translocations account for the female predominance of tRCC. To address these questions, we performed haplotype-specific analyses of chrX rearrangements in tRCC whole genomes. We show that TFE3 fusions universally arise as reciprocal translocations and that oncogenic TFE3 fusions can arise from chrXi:autosomal translocations. Female-specific chrXi:autosomal translocations result in a 2:1 female-to-male ratio of TFE3 fusions involving autosomal partner genes and account for the female predominance of tRCC. Our results highlight how X chromosome genetics constrains somatic chrX alterations and underlies cancer sex differences.

A genome-wide association study identified PTPN2 as a population-specific susceptibility gene locus for primary biliary cholangitis

BACKGROUND AND AIMS

Previous genome-wide association studies (GWAS) have indicated the involvement of shared (population-nonspecific) and nonshared (population-specific) susceptibility genes in the pathogenesis of primary biliary cholangitis (PBC) among European and East-Asian populations. Although a meta-analysis of these distinct populations has recently identified more than 20 novel PBC susceptibility loci, analyses of population-specific genetic architecture are still needed for a more comprehensive search for genetic factors in PBC.

APPROACH AND RESULTS

Protein tyrosine phosphatase nonreceptor type 2 ( PTPN2) was identified as a novel PBC susceptibility gene locus through GWAS and subsequent genome-wide meta-analysis involving 2181 cases and 2699 controls from the Japanese population (GWAS-lead variant: rs8098858, p = 2.6 × 10 -8 ). In silico and in vitro functional analyses indicated that the risk allele of rs2292758, which is a primary functional variant, decreases PTPN2 expression by disrupting Sp1 binding to the PTPN2 promoter in T follicular helper cells and plasmacytoid dendritic cells. Infiltration of PTPN2-positive T-cells and plasmacytoid dendritic cells was confirmed in the portal area of the PBC liver by immunohistochemistry. Furthermore, transcriptomic analysis of PBC-liver samples indicated the presence of a compromised negative feedback loop in vivo between PTPN2 and IFNG in patients carrying the risk allele of rs2292758.

CONCLUSIONS

PTPN2 , a novel susceptibility gene for PBC in the Japanese population, may be involved in the pathogenesis of PBC through an insufficient negative feedback loop caused by the risk allele of rs2292758 in IFN-γ signaling. This suggests that PTPN2 could be a potential molecular target for PBC treatment.

Identification of susceptibility loci and relevant cell type for IgA nephropathy in Han Chinese by integrative genome-wide analysis

Although many susceptibility loci for IgA nephropathy (IgAN) have been identified, they only account for 11.0% of the overall IgAN variance. We performed a large genome-wide meta-analysis of IgAN in Han Chinese with 3616 cases and 10 417 controls to identify additional genetic loci of IgAN. Considering that inflammatory bowel disease (IBD) and asthma might share an etiology of dysregulated mucosal immunity with IgAN, we performed cross-trait integrative analysis by leveraging functional annotations of relevant cell type and the pleiotropic information from IBD and asthma. Among 8 669 456 imputed variants, we identified a novel locus at 4p14 containing the long noncoding RNA LOC101060498. Cell type enrichment analysis based on annotations suggested that PMA-I-stimulated CD4+CD25-IL17+ Th17 cell was the most relevant cell type for IgAN, which highlights the essential role of Th17 pathway in the pathogenesis of IgAN. Furthermore, we identified six more novel loci associated with IgAN, which included three loci showing pleiotropic effects with IBD or asthma (2q35/PNKD, 6q25.2/SCAF8, and 22q11.21/UBE2L3) and three loci specific to IgAN (14q32.32/TRAF3, 16q22.2/TXNL4B, and 21q21.3/LINC00113) in the pleiotropic analysis. Our findings support the involvement of mucosal immunity, especially T cell immune response and IL-17 signal pathway, in the development of IgAN and shed light on further investigation of IgAN.

Genetic architecture of oral glucose-stimulated insulin release provides biological insights into type 2 diabetes aetiology

The genetics of β-cell function (BCF) offer valuable insights into the aetiology of type 2 diabetes (T2D)1,2. Previous studies have expanded the catalogue of BCF genetic associations through candidate gene studies3-7, large-scale genome-wide association studies (GWAS) of fasting BCF8,9 or functional islet studies on T2D risk variants10-14. Nonetheless, GWAS focused on BCF traits derived from oral glucose tolerance test (OGTT) data have been limited in sample size15,16 and have often overlooked the potential for related traits to capture distinct genetic features of insulin-producing β-cells17,18. We reasoned that investigating the genetic basis of multiple BCF estimates could provide a broader understanding of β-cell physiology. Here, we aggregate GWAS data of eight OGTT-based BCF traits from ~26,000 individuals of European descent, identifying 55 independent genetic associations at 44 loci. By examining the effects of BCF genetic signals on related phenotypes, we uncover diverse disease mechanisms whereby genetic regulation of BCF may influence T2D risk. Integrating BCF-GWAS data with pancreatic islet transcriptomic and epigenomic datasets reveals 92 candidate effector genes. Gene silencing in β-cell models highlights ACSL1 and FAM46C as key regulators of insulin secretion. Overall, our findings yield insights into the biology of insulin release and the molecular processes linking BCF to T2D risk, shedding light on the heterogeneity of T2D pathophysiology.

Genetic evidence for T-wave area from 12-lead electrocardiograms to monitor cardiovascular diseases in patients taking diabetes medications

Aims Many studies indicated use of diabetes medications can influence the electrocardiogram (ECG), which remains the simplest and fastest tool for assessing cardiac functions. However, few studies have explored the role of genetic factors in determining the relationship between the use of diabetes medications and ECG trace characteristics (ETC). Methods Genome-wide association studies (GWAS) were performed for 168 ETCs extracted from the 12-lead ECGs of 42,340 Europeans in the UK Biobank. The genetic correlations, causal relationships, and phenotypic relationships of these ETCs with medication usage, as well as the risk of cardiovascular diseases (CVDs), were estimated by linkage disequilibrium score regression (LDSC), Mendelian randomization (MR), and regression model, respectively. Results The GWAS identified 124 independent single nucleotide polymorphisms (SNPs) that were study-wise and genome-wide significantly associated with at least one ETC. Regression model and LDSC identified significant phenotypic and genetic correlations of T-wave area in lead aVR (aVR_T-area) with usage of diabetes medications (ATC code: A10 drugs, and metformin), and the risks of ischemic heart disease (IHD) and coronary atherosclerosis (CA). MR analyses support a putative causal effect of the use of diabetes medications on decreasing aVR_T-area, and on increasing risk of IHD and CA. ConclusionPatients taking diabetes medications are prone to have decreased aVR_T-area and an increased risk of IHD and CA. The aVR_T-area is therefore a potential ECG marker for pre-clinical prediction of IHD and CA in patients taking diabetes medications.

Polygenic Scoring for Detection of Ascending Thoracic Aortic Dilation

BACKGROUND

Ascending thoracic aortic dilation is a complex heritable trait that involves modifiable and nonmodifiable risk factors. Polygenic scores (PGS) are increasingly used to assess risk for complex diseases. The degree to which a PGS can improve aortic diameter prediction in diverse populations is unknown. Presently, we tested whether adding a PGS to clinical prediction algorithms improves performance in a diverse biobank.

METHODS

The analytic cohort comprised 6235 Penn Medicine Biobank participants with available echocardiography and clinical data linked to genome-wide genotype data. Linear regression models were used to integrate PGS weights derived from a genome-wide association study of thoracic aortic diameter performed in the UK Biobank and were compared with the performance of the previously published aorta optimized regression for thoracic aneurysm (AORTA) score.

RESULTS

Cohort participants had a median age of 61 years (IQR, 53-70) and a mean ascending aortic diameter of 3.36 cm (SD, 0.49). Fifty-five percent were male, and 33% were genetically similar to an African reference population. Compared with the AORTA score, which explained 30.6% (95% CI, 29.9%-31.4%) of the variance in aortic diameter, AORTA score+UK Biobank-derived PGS explained 33.1%, (95% CI, 32.3%-33.8%), the reweighted AORTA score explained 32.5% (95% CI, 31.8%-33.2%), and the reweighted AORTA score+UK Biobank-derived PGS explained 34.9% (95% CI, 34.2%-35.6%). When stratified by population, models including the UK Biobank-derived PGS consistently improved upon the clinical AORTA score among individuals genetically similar to a European reference population but conferred minimal improvement among individuals genetically similar to an African reference population. Comparable performance disparities were observed in models developed to discriminate cases/noncases of thoracic aortic dilation (≥4.0 cm).

CONCLUSIONS

We demonstrated that inclusion of a UK Biobank-derived PGS to the AORTA score confers a clinically meaningful improvement in model performance only among individuals genetically similar to European reference populations and may exacerbate existing health care disparities.

Genotype imputation in human genomic studies

Imputation is a method that supplies missing information about genetic variants that could not be directly genotyped with DNA microarrays or low-coverage sequencing. Imputation plays a critical role in genome-wide association studies (GWAS). It leads to a significant increase in the number of studied variants, which improves the resolution of the method and enhances the comparability of data obtained in different cohorts and/or by using different technologies, which is important for conducting meta-analyses. When performing imputation, genotype information from the study sample, in which only part of the genetic variants are known, is complemented using the standard (reference) sample, which has more complete genotype data (most often the results of whole-genome sequencing). Imputation has become an integral part of human genomic research due to the benefits it provides and the increasing availability of imputation tools and reference sample data. This review focuses on imputation in human genomic research. The first section of the review provides a description of technologies for obtaining information about human genotypes and characteristics of these types of data. The second section describes the imputation methodology, lists the stages of its implementation and the corresponding programs, provides a description of the most popular reference panels and methods for assessing the quality of imputation. The review concludes with examples of the use of imputation in genomic studies of samples from Russia. This review shows the importance of imputation, provides information on how to carry it out, and systematizes the results of its application using Russian samples.

Genome-wide association studies for pelvic organ prolapse in the Japanese population

Pelvic organ prolapse (POP) affects approximately 40% of elderly women, characterized by the descent of the pelvic organs into the vaginal cavity. Here we present the results of a genome-wide association study (GWAS) for susceptibility to POP comprising 771 cases and 76,625 controls in the Japanese population. We identified a significant association of WT1 locus with POP in the Japanese population; rs10742277; odds ratio (OR) = 1.48, 95% confidence interval (CI), 1.29-1.68, P = 6.72 × 10-9. Subsequent cross-ancestry GWAS meta-analysis combining the Japanese data and previously reported European data, including 28,857 cases and 622,916 controls, identified FGFR2 locus as a novel susceptibility locus to POP (rs7072877; OR = 1.06, 95% CI, 1.04-1.08, P = 4.11 × 10-8). We also observed consistent directions of the effects for 21 out of 24 European GWAS derived loci (binomial test P = 2.8 × 10-4), indicating that most of susceptibility loci for POP are shared across the Japanese and European populations.

Association of autosomal mosaic chromosomal alterations with risk of bladder cancer in Chinese adults: a prospective cohort study

Little is known about the prospective association between autosomal mosaic chromosomal alterations (mCAs), a group of large-scale somatic mutations on autosomes, and bladder cancer. Here we utilized data from 99,877 participants who were free of physician-diagnosed cancer at baseline (2004-2008) of the China Kadoorie Biobank to estimate the associations between autosomal mCAs and bladder cancer (ICD-10: C67). A total of 2874 autosomal mCAs events among 2612 carriers (2.6%) were detected. After a median follow-up of 12.4 years, we discovered that participants with all autosomal mCAs exhibited higher risks of bladder cancer, with a multivariable-adjusted hazard ratio (HR) (95% confidence interval [CI]) of 2.60 (1.44, 4.70). The estimate of such association was even stronger for mosaic loss events (HR [95% CI]: 6.68 [2.92, 15.30]), while it was not significant for CN-LOH events. Both expanded (cell fraction ≥10%) and non-expanded autosomal mCAs, as well as mosaic loss, were associated with increased risks of bladder cancer. Of interest, physical activity (PA) significantly modified the associations of autosomal mCAs and mosaic loss (Pinteraction = 0.038 and 0.012, respectively) with bladder cancer. The increased risks of bladder cancer were only observed with mCAs and mosaic loss among participants with a lower level of PA (HR [95% CI]: 5.11 [2.36, 11.09] and 16.30 [6.06, 43.81]), but not among participants with a higher level of PA. Our findings suggest that peripheral leukocyte autosomal mCAs may represent a novel risk factor for bladder cancer, and PA may serve as a potential intervention target for mCAs carriers.

Genome-wide association analysis of treatment resistant schizophrenia for variant discovery and polygenic assessment

BACKGROUND

Treatment resistant schizophrenia (TRS) is broadly defined as inadequate response to adequate treatment and is associated with a substantial increase in disease burden. Clozapine is the only approved treatment for TRS, showing superior clinical effect on overall symptomatology compared to other drugs, and is the prototype of atypical antipsychotics. Risperidone, another atypical antipsychotic with a more distinctive dopamine 2 antagonism, is commonly used in treatment of schizophrenia. Here, we conducted a genome-wide association study on patients treated with clozapine (TRS) vs. risperidone (non-TRS) and investigated whether single variants and/or polygenic risk score for schizophrenia are associated with TRS status. We hypothesized that patients who are treated with clozapine and risperidone might exhibit distinct neurobiological phenotypes that match pharmacological profiles of these drugs and can be explained by genetic differences. The study population (n = 1286) was recruited from a routine therapeutic drug monitoring (TDM) service between 2005 and 2022. History of a detectable serum concentration of clozapine and risperidone (without TDM history of clozapine) defined the TRS (n = 478) and non-TRS (n = 808) group, respectively.

RESULTS

We identified a suggestive association between TRS and a common variant within the LINC00523 gene with a significance just below the genome-wide threshold (rs79229764 C > T, OR = 4.89; p = 1.8 × 10-7). Polygenic risk score for schizophrenia was significantly associated with TRS (OR = 1.4, p = 2.1 × 10-6). In a large post-mortem brain sample from schizophrenia donors (n = 214; CommonMind Consortium), gene expression analysis indicated that the rs79229764 variant allele might be involved in the regulation of GPR88 and PUDP, which plays a role in striatal neurotransmission and intellectual disability, respectively.

CONCLUSIONS

We report a suggestive genetic association at the rs79229764 locus with TRS and show that genetic liability for schizophrenia is positively associated with TRS. These results suggest a candidate locus for future follow-up studies to elucidate the molecular underpinnings of TRS. Our findings further demonstrate the value of both single variant and polygenic association analyses for TRS prediction.

Germline Polymorphisms Associated with Overall Survival in Lung Adenocarcinoma: Genome-Wide Analysis

BACKGROUND/OBJECTIVES

Lung cancer remains a global health concern, with substantial variation in patient survival. Despite advances in detection and treatment, the genetic basis for the divergent outcomes is not understood. We investigated germline polymorphisms that modulate overall survival in 1464 surgically resected lung adenocarcinoma patients.

METHODS

A multivariable Cox proportional hazard model was used to assess the association of more than seven million polymorphisms with overall survival at the 60-month follow-up, considering age, sex, pathological stage, decade of surgery and principal components as covariates. Genes in which variants were identified were studied in silico to investigate functional roles.

RESULTS

Six germline variants passed the genome-wide significance threshold. These single nucleotide polymorphisms were mapped to non-coding (intronic) regions on chromosomes 2, 3, and 5. The minor alleles of rs13000315, rs151212827, and rs190923216 (chr. 2, 3 and 5, respectively) were found to be independent negative prognostic factors. All six variants have been reported to regulate the expression of nine genes, seven of which are protein-coding, in different tissues. Survival-associated variants on chromosomes 2 and 3 were already reported to regulate the expression of NT5DC2 and NAGK, with high expression associated with the minor alleles. High NT5DC2 and NAGK expression in lung adenocarcinoma tissue was already shown to correlate with poor overall survival.

CONCLUSIONS

This study highlights a potential regulatory role of the identified polymorphisms in influencing outcome and suggests a mechanistic link between these variants, gene expression regulation, and lung adenocarcinoma prognosis. Validation and functional studies are warranted to elucidate the mechanisms underlying these associations.

Characterization of non-coding variants associated with transcription factor binding through ATAC-seq-defined footprint QTLs in liver

Non-coding variants discovered by genome-wide association studies (GWAS) are enriched in regulatory elements harboring transcription factor (TF) binding motifs, strongly suggesting a connection between disease association and the disruption of cis-regulatory sequences. Occupancy of a TF inside a region of open chromatin can be detected in ATAC-seq where bound TFs block the transposase Tn5, leaving a pattern of relatively depleted Tn5 insertions known as a "footprint". Here, we sought to identify variants associated with TF-binding, or "footprint quantitative trait loci" (fpQTLs) in ATAC-seq data generated from 170 human liver samples. We used computational tools to scan the ATAC-seq reads to quantify TF binding likelihood as "footprint scores" at variants derived from whole genome sequencing generated in the same samples. We tested for association between genotype and footprint score and observed 693 fpQTLs associated with footprint-inferred TF binding (FDR < 5%). Given that Tn5 insertion sites are measured with base-pair resolution, we show that fpQTLs can aid GWAS and QTL fine-mapping by precisely pinpointing TF activity within broad trait-associated loci where the underlying causal variant is unknown. Liver fpQTLs were strongly enriched across ChIP-seq peaks, liver expression QTLs (eQTLs), and liver-related GWAS loci, and their inferred effect on TF binding was concordant with their effect on underlying sequence motifs in 80% of cases. We conclude that fpQTLs can reveal causal GWAS variants, define the role of TF binding site disruption in disease and provide functional insights into non-coding variants, ultimately informing novel treatments for common diseases.

Integrated clinical risk prediction of type 2 diabetes with a multifactorial polygenic risk score

Combining information from multiple GWASs for a disease and its risk factors has proven a powerful approach for development of polygenic risk scores (PRSs). This may be particularly useful for type 2 diabetes (T2D), a highly polygenic and heterogeneous disease where the additional predictive value of a PRS is unclear. Here, we use a meta-scoring approach to develop a metaPRS for T2D that incorporated genome-wide associations from both European and non-European genetic ancestries and T2D risk factors. We evaluated the performance of this metaPRS and benchmarked it against existing genome-wide PRS in 620,059 participants and 50,572 T2D cases amongst six diverse genetic ancestries from UK Biobank, INTERVAL, the All of Us Research Program, and the Singapore Multi-Ethnic Cohort. We show that our metaPRS was the most powerful PRS for predicting T2D in European population-based cohorts and had comparable performance to the top ancestry-specific PRS, highlighting its transferability. In UK Biobank, we show the metaPRS had stronger predictive power for 10-year risk than all individual risk factors apart from BMI and biomarkers of dysglycemia. The metaPRS modestly improved T2D risk stratification of QDiabetes risk scores for 10-year risk prediction, particularly when prioritising individuals for blood tests of dysglycemia. Overall, we present a highly predictive and transferrable PRS for T2D and demonstrate that the potential for PRS to incrementally improve T2D risk prediction when incorporated into UK guideline-recommended screening and risk prediction with a clinical risk score.

gsQTL: Associating genetic risk variants with gene sets by exploiting their shared variability

To investigate the functional significance of genetic risk loci identified through genome-wide association studies (GWASs), genetic loci are linked to genes based on their capacity to account for variation in gene expression, resulting in expression quantitative trait loci (eQTL). Following this, gene set analyses are commonly used to gain insights into functionality. However, the efficacy of this approach is hampered by small effect sizes and the burden of multiple testing. We propose an alternative approach: instead of examining the cumulative associations of individual genes within a gene set, we consider the collective variation of the entire gene set. We introduce the concept of gene set QTL (gsQTL), and show it to be more adept at identifying links between genetic risk variants and specific gene sets. Notably, gsQTL experiences less susceptibility to inflation or deflation of significant enrichments compared with conventional methods. Furthermore, we demonstrate the broader applicability of shared variability within gene sets. This is evident in scenarios such as the coordinated regulation of genes by a transcription factor or coordinated differential expression.

MethylGenotyper: Accurate Estimation of SNP Genotypes and Genetic Relatedness from DNA Methylation Data

Epigenome-wide association studies (EWAS) are susceptible to widespread confounding caused by population structure and genetic relatedness. Nevertheless, kinship estimation is challenging in EWAS without genotyping data. Here, we proposed MethylGenotyper, a method that for the first time enables accurate genotyping at thousands of single nucleotide polymorphisms (SNPs) directly from commercial DNA methylation microarrays. We modeled the intensities of methylation probes near SNPs with a mixture of three beta distributions corresponding to different genotypes and estimated parameters with an expectation-maximization algorithm. We conducted extensive simulations to demonstrate the performance of the method. When applying MethylGenotyper to the Infinium EPIC array data of 4662 Chinese samples, we obtained genotypes at 4319 SNPs with a concordance rate of 98.26%, enabling the identification of 255 pairs of close relatedness. Furthermore, we showed that MethylGenotyper allows for the estimation of both population structure and cryptic relatedness among 702 Australians of diverse ancestry. We also implemented MethylGenotyper in a publicly available R package (https://github.com/Yi-Jiang/MethylGenotyper) to facilitate future large-scale EWAS.

Commonly used genomic arrays may lose information due to imperfect coverage of discovered variants for autism spectrum disorder

BACKGROUND

Common genetic variation has been shown to account for a large proportion of ASD heritability. Polygenic scores generated for autism spectrum disorder (ASD-PGS) using the most recent discovery data, however, explain less variance than expected, despite reporting significant associations with ASD and other ASD-related traits. Here, we investigate the extent to which information loss on the target study genome-wide microarray weakens the predictive power of the ASD-PGS.

METHODS

We studied genotype data from three cohorts of individuals with high familial liability for ASD: The Early Autism Risk Longitudinal Investigation (EARLI), Markers of Autism Risk in Babies-Learning Early Signs (MARBLES), and the Infant Brain Imaging Study (IBIS), and one population-based sample, Study to Explore Early Development Phase I (SEED I). Individuals were genotyped on different microarrays ranging from 1 to 5 million sites. Coverage of the top 88 genome-wide suggestive variants implicated in the discovery was evaluated in all four studies before quality control (QC), after QC, and after imputation. We then created a novel method to assess coverage on the resulting ASD-PGS by correlating a PGS informed by a comprehensive list of variants to a PGS informed with only the available variants.

RESULTS

Prior to imputations, None of the four cohorts directly or indirectly covered all 88 variants among the measured genotype data. After imputation, the two cohorts genotyped on 5-million arrays reached full coverage. Analysis of our novel metric showed generally high genome-wide coverage across all four studies, but a greater number of SNPs informing the ASD-PGS did not result in improved coverage according to our metric.

LIMITATIONS

The studies we analyzed contained modest sample sizes. Our analyses included microarrays with more than 1-million sites, so smaller arrays such as Global Diversity and the PsychArray were not included. Our PGS metric for ASD is only generalizable to samples of European ancestries, though the coverage metric can be computed for traits that have sufficiently large-sized discovery findings in other ancestries.

CONCLUSIONS

We show that commonly used genotyping microarrays have incomplete coverage for common ASD variants, and imputation cannot always recover lost information. Our novel metric provides an intuitive approach to reporting information loss in PGS and an alternative to reporting the total number of SNPs included in the PGS. While applied only to ASD here, this metric can easily be used with other traits.

The Importance of Regulatory Network Structure for Complex Trait Heritability and Evolution

Complex traits are determined by many loci-mostly regulatory elements-that, through combinatorial interactions, can affect multiple traits. Such high levels of epistasis and pleiotropy have been proposed in the omnigenic model and may explain why such a large part of complex trait heritability is usually missed by genome-wide association studies while raising questions about the possibility for such traits to evolve in response to environmental constraints. To explore the molecular bases of complex traits and understand how they can adapt, we systematically analyzed the distribution of SNP heritability for ten traits across 29 tissue-specific Expression Quantitative Trait Locus (eQTL) networks. We find that heritability is clustered in a small number of tissue-specific, functionally relevant SNP-gene modules and that the greatest heritability occurs in local "hubs" that are both the cornerstone of the network's modules and tissue-specific regulatory elements. The network structure could thus both amplify the genotype-phenotype connection and buffer the deleterious effect of the genetic variations on other traits. We confirm that this structure has allowed complex traits to evolve in response to environmental constraints, with the local "hubs" being the preferential targets of past and ongoing directional selection. Together, these results provide a conceptual framework for understanding complex trait architecture and evolution.

Genetic, transcriptomic, histological, and biochemical analysis of progressive supranuclear palsy implicates glial activation and novel risk genes

Progressive supranuclear palsy (PSP), a rare Parkinsonian disorder, is characterized by problems with movement, balance, and cognition. PSP differs from Alzheimer's disease (AD) and other diseases, displaying abnormal microtubule-associated protein tau by both neuronal and glial cell pathologies. Genetic contributors may mediate these differences; however, the genetics of PSP remain underexplored. Here we conduct the largest genome-wide association study (GWAS) of PSP which includes 2779 cases (2595 neuropathologically-confirmed) and 5584 controls and identify six independent PSP susceptibility loci with genome-wide significant (P < 5 × 10-8) associations, including five known (MAPT, MOBP, STX6, RUNX2, SLCO1A2) and one novel locus (C4A). Integration with cell type-specific epigenomic annotations reveal an oligodendrocytic signature that might distinguish PSP from AD and Parkinson's disease in subsequent studies. Candidate PSP risk gene prioritization using expression quantitative trait loci (eQTLs) identifies oligodendrocyte-specific effects on gene expression in half of the genome-wide significant loci, and an association with C4A expression in brain tissue, which may be driven by increased C4A copy number. Finally, histological studies demonstrate tau aggregates in oligodendrocytes that colocalize with C4 (complement) deposition. Integrating GWAS with functional studies, epigenomic and eQTL analyses, we identify potential causal roles for variation in MOBP, STX6, RUNX2, SLCO1A2, and C4A in PSP pathogenesis.

Smoking and alcohol by HPV status in head and neck cancer: a Mendelian randomization study

HPV-positive and HPV-negative head and neck squamous cell carcinoma (HNSCC) are recognized as distinct entities. There remains uncertainty surrounding the causal effects of smoking and alcohol on the development of these two cancer types. Here we perform multivariable Mendelian randomization (MR) to evaluate the causal effects of smoking and alcohol on the risk of HPV-positive and HPV-negative HNSCC in 3431 cases and 3469 controls. Lifetime smoking exposure, as measured by the Comprehensive Smoking Index (CSI), is associated with increased risk of both HPV-negative HNSCC (OR = 3.03, 95%CI:1.75-5.24, P = 7.00E-05) and HPV-positive HNSCC (OR = 2.73, 95%CI:1.39-5.36, P = 0.003). Drinks Per Week is also linked with increased risk of both HPV-negative HNSCC (OR = 7.72, 95%CI:3.63-16.4, P = 1.00E-07) and HPV-positive HNSCC (OR = 2.66, 95%CI:1.06-6.68, P = 0.038). Smoking and alcohol independently increase the risk of both HPV-positive and HPV-negative HNSCC. These findings have important implications for understanding the modifying risk factors between HNSCC subtypes.

Associations of dinitroaniline herbicide exposure, genetic susceptibility, and lifestyle with glucose dysregulation: A gene-environment interaction study from the Wuhan-Zhuhai cohort

OBJECTIVE

To assess the association of dinitroaniline herbicides as well as their interactions with genetic susceptibility and lifestyle with glucose dysregulation.

METHODS

A total of 4310 Chinese urban adults from the baseline of the Wuhan-Zhuhai Cohort were included in the cross-sectional study. A follow-up panel from the cohort was included in the longitudinal study, including 158 participants with 432 observations. Glucose dysregulation, including fasting plasma glucose (FPG), homeostasis model assessment of insulin resistance (HOMA-IR), type 2 diabetes mellitus (T2DM), and impaired fasting glucose (IFG) were assessed. Serum dinitroaniline herbicides including benfluralin, trifluralin, and pendimethalin were measured. T2DM-related polygenic risk score (PRS) and healthy life scores were constructed.

RESULTS

Cross-sectionally, each 2-fold increase in serum benfluralin was associated with a 1.12%, 2.03%, and 9% increase in FPG, HOMA-IR, and IFG risk, respectively. Each 2-fold increase in serum trifluralin was associated with a 0.70% increase in FPG. Each 2-fold increase in serum pendimethalin was associated with a 2.53% and 24% increase in FPG and IFG risk, respectively (all P < 0.05). Positive associations were found between the dinitroaniline herbicide mixture and glucose dysregulation. Longitudinally, serum benfluralin and pendimethalin were associated with the annual increases in FPG and HOMA-IR (P < 0.05). Joint and interaction effect analysis showed that compared with participants with high benfluralin/trifluralin/pendimethalin, high PRS, and unhealthy lifestyle, those with low benfluralin/trifluralin/pendimethalin, low PRS, and healthy lifestyle showed the greatest declines in FPG, i.e., -15.46%, -13.58%, and -10.51% changes, respectively; and the greatest reductions in IFG risks, i.e., 75%, 61%, and 73% reductions, respectively (all P < 0.05).

CONCLUSIONS

This study highlighted the importance of controlling dinitroaniline herbicide exposure and following healthy lifestyles in glucose dysregulation prevention, especially among individuals with high genetic risk of T2DM.

Genetic analysis of asymptomatic antinuclear antibody production

Objective

Antinuclear antibodies (ANA) are detected in up to 14% of the population and the majority of individuals with ANA are asymptomatic. The literature on the genetic contribution to asymptomatic ANA positivity in the population is limited. In this study, we aimed to perform a multi-ancestry genome-wide association study (GWAS) of asymptomatic ANA positivity.

Methods

Asymptomatic ANA positive and negative individuals from the All of Us Research Program were included in this study, selecting those with an ANA test by immunofluorescence and no evidence of autoimmune disease. Imputation was performed and a multi-ancestry meta-analysis including approximately 6 million single-nucleotide polymorphisms (SNPs) was conducted. Genome-wide SNP based heritability was estimated using the GCTA software. A cumulative genetic risk score for lupus was constructed using previously reported genome-wide significant loci.

Results

1,955 asymptomatic ANA positive and 3,634 asymptomatic ANA negative individuals were included across three genetic ancestries. The multi-ancestry meta-analysis revealed SNPs with a suggestive association (p-value < 1×10 -5 ) across 8 different loci, but no genome-wide significant loci were identified. A gene variant upstream of HLA-DQB1 (rs17211748, P = 1.4×10 -6 , OR = 0.82, 95% CI 0.76-0.89) showed the most significant association. The heritability of asymptomatic ANA positivity was estimated to be 24.9%. Asymptomatic ANA positive individuals did not exhibit increased cumulative genetic risk for lupus compared to ANA negative individuals.

Conclusion

ANA production is not associated with significant genetic risk and is primarily determined by non-genetic, likely environmental, factors.

A genome-wide meta-analysis of palmoplantar pustulosis implicates TH2 responses and cigarette smoking in disease pathogenesis

BACKGROUND

Palmoplantar pustulosis (PPP) is an inflammatory skin disorder that mostly affects smokers and manifests with painful pustular eruptions on the palms and soles. Although the disease can present with concurrent plaque psoriasis, TNF and IL-17/IL-23 inhibitors show limited efficacy. There is therefore a pressing need to uncover PPP disease drivers and therapeutic targets.

OBJECTIVES

We sought to identify genetic determinants of PPP and investigate whether cigarette smoking contributes to disease pathogenesis.

METHODS

We performed a genome-wide association meta-analysis of 3 North-European cohorts (n = 1,456 PPP cases and 402,050 controls). We then used the scGWAS program to investigate the cell-type specificity of the association signals. We also undertook genetic correlation analyses to examine the similarities between PPP and other immune-mediated diseases. Finally, we applied Mendelian randomization to analyze the causal relationship between cigarette smoking and PPP.

RESULTS

We found that PPP is not associated with the main genetic determinants of plaque psoriasis. Conversely, we identified genome-wide significant associations with the FCGR3A/FCGR3B and CCHCR1 loci. We also observed 13 suggestive (P < 5 × 10-6) susceptibility regions, including the IL4/IL13 interval. Accordingly, we demonstrated a significant genetic correlation between PPP and TH2-mediated diseases such as atopic dermatitis and ulcerative colitis. We also found that genes mapping to PPP-associated intervals were preferentially expressed in dendritic cells and often implicated in T-cell activation pathways. Finally, we undertook a Mendelian randomization analysis, which supported a causal role of cigarette smoking in PPP.

CONCLUSIONS

The first genome-wide association study of PPP points to a pathogenic role for deregulated TH2 responses and cigarette smoking.

Polygenic scores for complex traits are associated with changes in concentration of circulating lipid species

Understanding perturbations in circulating lipid levels that often occur years or decades before clinical symptoms may enhance our understanding of disease mechanisms and provide novel intervention opportunities. Here, we assessed if polygenic scores (PGSs) for complex traits could detect lipid dysfunctions related to the traits and provide new biological insights. We constructed genome-wide PGSs (approximately 1 million genetic variants) for 50 complex traits in 7,169 Finnish individuals with routine clinical lipid profiles and lipidomics measurements (179 lipid species). We identified 678 associations (P < 9.0 × 10-5) involving 26 traits and 142 lipids. Most of these associations were also validated with the actual phenotype measurements where available (89.5% of 181 associations where the trait was available), suggesting that these associations represent early signs of physiological changes of the traits. We detected many known relationships (e.g., PGS for body mass index (BMI) and lysophospholipids, PGS for type 2 diabetes and triacyglycerols) and those that suggested potential target for prevention strategies (e.g., PGS for venous thromboembolism and arachidonic acid). We also found association of PGS for favorable adiposity with increased sphingomyelins levels, suggesting a probable role of sphingomyelins in increased risk for certain disease, e.g., venous thromboembolism as reported previously, in favorable adiposity despite its favorable metabolic effect. Altogether, our study provides a comprehensive characterization of lipidomic alterations in genetic predisposition for a wide range of complex traits. The study also demonstrates potential of PGSs for complex traits to capture early, presymptomatic lipid alterations, highlighting its utility in understanding disease mechanisms and early disease detection.

Fine-mapping the CYP2A6 regional association with nicotine metabolism among African American smokers

The nicotine metabolite ratio (NMR; 3'hydroxycotinine/cotinine) is a stable biomarker for CYP2A6 enzyme activity and nicotine clearance, with demonstrated clinical utility in personalizing smoking cessation treatment. Common genetic variation in the CYP2A6 region is strongly associated with NMR in smokers. Here, we investigated this regional association in more detail. We evaluated the association of CYP2A6 single-nucleotide polymorphisms (SNPs) and * alleles with NMR among African American smokers (N = 953) from two clinical trials of smoking cessation. Stepwise conditional analysis and Bayesian fine-mapping were undertaken. Putative causal variants were incorporated into an existing African ancestry-specific genetic risk score (GRS) for NMR, and the performance of the updated GRS was evaluated in both African American (n = 953) and European ancestry smokers (n = 933) from these clinical trials. Five independent associations with NMR in the CYP2A6 region were identified using stepwise conditional analysis, including the deletion variant CYP2A6*4 (beta = -0.90, p = 1.55 × 10-11). Six putative causal variants were identified using Bayesian fine-mapping (posterior probability, PP = 0.67), with the top causal configuration including CYP2A6*4, rs116670633, CYP2A6*9, rs28399451, rs8192720, and rs10853742 (PP = 0.09). Incorporating these putative causal variants into an existing ancestry-specific GRS resulted in comparable prediction of NMR within African American smokers, and improved trans-ancestry portability of the GRS to European smokers. Our findings suggest that both * alleles and SNPs underlie the association of the CYP2A6 region with NMR among African American smokers, identify a shortlist of variants that may causally influence nicotine clearance, and suggest that portability of GRSs across populations can be improved through inclusion of putative causal variants.

Exploring causal effects of sarcopenia on risk and progression of Parkinson disease by Mendelian randomization

Previous observational studies suggested that sarcopenia is associated with Parkinson disease (PD), but it is unclear whether this association is causal. The objective of this study was to examine causal associations between sarcopenia-related traits and the risk or progression of PD using a Mendelian randomization (MR) approach. Two-sample bidirectional MR analyses were conducted to evaluate causal relationships. Genome-wide association study (GWAS) summary statistics for sarcopenia-related traits, including right handgrip strength (n = 461,089), left handgrip strength (n = 461,026), and appendicular lean mass (n = 450,243), were retrieved from the IEU OpenGWAS database. GWAS data for the risk of PD were derived from the FinnGen database (4235 cases; 373,042 controls). Summary-level data for progression of PD, including progression to Hoehn and Yahr stage 3, progression to dementia, and development of levodopa-induced dyskinesia, were obtained from a recent GWAS publication on progression of PD in 4093 patients from 12 longitudinal cohorts. Significant causal associations identified in MR analysis were verified through a polygenic score (PGS)-based approach and pathway enrichment analysis using genotype data from the Parkinson's Progression Markers Initiative. MR results supported a significant causal influence of right handgrip strength (odds ratio [OR] = 0.152, 95% confidence interval [CI] = 0.055-0.423, adjusted P = 0.0036) and appendicular lean mass (OR = 0.597, 95% CI = 0.440-0.810, adjusted P = 0.0111) on development of levodopa-induced dyskinesia. In Cox proportional hazard analysis, higher PGSs for right handgrip strength (hazard ratio [HR] = 0.225, 95% CI = 0.095-0.530, adjusted P = 0.0019) and left handgrip strength (HR = 0.303, 95% CI = 0.121-0.59, adjusted P = 0.0323) were significantly associated with a lower risk of developing levodopa-induced dyskinesia, after adjusting for covariates. Pathway enrichment analysis revealed that genome-wide significant single-nucleotide polymorphisms for right handgrip strength were substantially enriched in biological pathways involved in the control of synaptic plasticity. This study provides genetic evidence of the protective role of handgrip strength or appendicular lean mass on the development of levodopa-induced dyskinesia in PD. Sarcopenia-related traits can be promising prognostic markers for levodopa-induced dyskinesia and potential therapeutic targets for preventing levodopa-induced dyskinesia in patients with PD.

Genome-wide association meta-analysis identifies two novel loci associated with dental caries

BACKGROUND

Tooth loss significantly impacts oral function and overall health deterioration. Dental caries and periodontal disease are major contributors to tooth loss, emphasizing the critical need to prevent these conditions. Genetic studies have played a crucial role in deepening our understanding of the underlying mechanisms of these diseases. While large-scale genome-wide association studies (GWAS) on dental caries and periodontal disease have been conducted extensively, research focusing on Asian populations remains limited. Given substantial genetic and lifestyle variations across ethnicities, conducting studies across diverse populations is imperative. This study aimed to uncover new insights into the genetic mechanisms of these diseases, contributing to broader knowledge and potential targeted interventions.

METHODS

We conducted a GWAS using genome data from 45,525 Japanese individuals, assessing their self-reported history of dental caries and periodontal disease. Additionally, we performed a meta-analysis by integrating our results with those from a previous large-scale GWAS predominantly involving European populations.

RESULTS

While no new loci associated with periodontal disease were identified, we discovered two novel loci associated with dental caries. The lead variants of these loci were intron variant rs10974056 in GLIS3 and intron variant rs4801882 in SIGLEC5.

CONCLUSION

Our study findings are anticipated to advance understanding of the underlying mechanisms of dental caries and periodontal disease. Thes insights may inform better management strategies for patients affected by these conditions.

Multimodal analysis of disease onset in Alzheimer's disease using Connectome, Molecular, and genetics data

Alzheimer's disease (AD) and its related age at onset (AAO) are highly heterogeneous, due to the inherent complexity of the disease. They are affected by multiple factors, such as neuroimaging and genetic predisposition. Multimodal integration of various data types is necessary; however, it has been nontrivial due to the high dimensionality of each modality. We aimed to identify multimodal biomarkers of AAO in AD using an extended version of sparse canonical correlation analysis, in which we integrated two imaging modalities, functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), and genetic data in the form of single-nucleotide polymorphisms (SNPs) obtained from the Alzheimer's disease neuroimaging initiative database. These three modalities cover low-to-high-level complementary information and offer multiscale insights into the AAO. We identified multivariate markers of AAO in AD using fMRI, PET, and SNP. Furthermore, the markers identified were largely consistent with those reported in the existing literature. In particular, our serial mediation analysis suggests that genetic variants influence the AAO in AD by indirectly affecting brain connectivity by mediation of amyloid-beta protein accumulation, supporting a plausible path in existing research. Our approach provides comprehensive biomarkers related to AAO in AD and offers novel multimodal insights into AD.

Genome-wide Association Study of Susceptibility to Respiratory Syncytial Virus Hospitalization in Young Children <5 Years of age

BACKGROUND

Worldwide, respiratory syncytial virus (RSV) infections are among the most common causes of infant hospitalization. Host genetic factors influencing the risk and severity of RSV infection are not well known.

METHODS

We conducted a genome-wide association study (GWAS) to investigate single-nucleotide polymorphisms (SNPs) associated with severe RSV infections using a nested case-control design based on 2 Danish cohorts. We compared SNPs from 1786 children hospitalized with RSV to 45 060 controls without an RSV-coded hospitalization. We performed gene-based testing, tissue enrichment, gene-set enrichment, and a meta-analysis of the 2 cohorts. Finally, an analysis of potential associations between the severity of RSV infection and genetic markers was performed.

RESULTS

We did not detect any significant genome-wide associations between SNPs and RSV infection or the severity of RSV. We did find potential loci associated with RSV infections on chromosome 5 in 1 cohort but failed to replicate any signals in both cohorts.

CONCLUSIONS

Despite being the largest GWAS of severe RSV infection, we did not detect any genome-wide significant loci. This may be an indication of a lack of power or an absence of signal. Future studies might include mild illness and need to be larger to detect any significant associations.