Search

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.

A hallmark of fetal alcohol spectrum disorders (FASD) is neurobehavioral deficits that still do not have effective treatment. Here, we present that reduction of Apolipoprotein E (APOE) is critically involved in neurobehavioral deficits in FASD. We show that prenatal alcohol exposure (PAE) changes chromatin accessibility of Apoe locus, and causes reduction of APOE levels in both the brain and peripheral blood in postnatal mice. Of note, postnatal administration of an APOE receptor agonist (APOE-RA) mitigates motor learning deficits and anxiety in those mice. Several molecular and electrophysiological properties essential for learning, which are altered by PAE, are restored by APOE-RA. Our human genome-wide association study further reveals that the interaction of PAE and a single nucleotide polymorphism in the APOE enhancer which chromatin is closed by PAE in mice is associated with lower scores in the delayed matching-to-sample task in children. APOE in the plasma is also reduced in PAE children, and the reduced level is associated with their lower cognitive performance. These findings suggest that controlling the APOE level can serve as an effective treatment for neurobehavioral deficits in FASD.

BACKGROUND AND OBJECTIVES: TMEM106B has been proposed as a modifier of disease risk in FTLD-TDP, particularly in GRN pathogenic variant carriers. Furthermore, TMEM106B has been investigated as a disease modifier in the context of healthy aging and across multiple neurodegenerative diseases. The objective of this study was to evaluate and compare the effect of TMEM106B on gray matter volume and cognition in each of the common genetic FTD groups and in patients with sporadic FTD. METHODS: Participants were enrolled through the ARTFL/LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD) study, which includes symptomatic and presymptomatic individuals with a pathogenic variant in C9orf72, GRN, MAPT, VCP, TBK1, TARDBP, symptomatic nonpathogenic variant carriers, and noncarrier family controls. All participants were genotyped for the TMEM106B rs1990622 SNP. Cross-sectionally, linear mixed-effects models were fitted to assess an association between TMEM106B and genetic group interaction with each outcome measure (gray matter volume and UDS3-EF for cognition), adjusting for education, age, sex, and CDR+NACC-FTLD sum of boxes. Subsequently, associations between TMEM106B and each outcome measure were investigated within the genetic group. For longitudinal modeling, linear mixed-effects models with time by TMEM106B predictor interactions were fitted. RESULTS: The minor allele of TMEM106B rs1990622, linked to a decreased risk of FTD, associated with greater gray matter volume in GRN pathogenic variant carriers under the recessive dosage model (N = 82, beta = 3.25, 95% CI [0.37-6.19], p = 0.034). This was most pronounced in the thalamus in the left hemisphere (beta = 0.03, 95% CI [0.01-0.06], p = 0.006), with a retained association when considering presymptomatic GRN pathogenic variant carriers only (N = 42, beta = 0.03, 95% CI [0.01-0.05], p = 0.003). The minor allele of TMEM106B rs1990622 also associated with greater cognitive scores among all C9orf72 pathogenic variant carriers (N = 229, beta = 0.36, 95% CI [0.05-0.066], p = 0.021) and in presymptomatic C9orf72 pathogenic variant carriers (N = 106, beta = 0.33, 95% CI [0.03-0.63], p = 0.036), under the recessive dosage model. DISCUSSION: We identified associations of TMEM106B with gray matter volume and cognition in the presence of GRN and C9orf72 pathogenic variants. The association of TMEM106B with outcomes of interest in presymptomatic GRN and C9orf72 pathogenic variant carriers could additionally reflect TMEM106Bs effect on divergent pathophysiologic changes before the appearance of clinical symptoms.

Our knowledge of the contribution of genetic interactions (epistasis) to variation in human complex traits remains limited, partly due to the lack of efficient, powerful, and interpretable algorithms to detect interactions. Recently proposed approaches for set-based association tests show promise in improving the power to detect epistasis by examining the aggregated effects of multiple variants. Nevertheless, these methods either do not scale to large Biobank data sets or lack interpretability. We propose QuadKAST, a scalable algorithm focused on testing pairwise interaction effects (quadratic effects) within small to medium-sized sets of genetic variants (window size ≤100) on a trait and provide quantified interpretation of these effects. Comprehensive simulations show that QuadKAST is well-calibrated. Additionally, QuadKAST is highly sensitive in detecting loci with epistatic signals and accurate in its estimation of quadratic effects. We applied QuadKAST to 52 quantitative phenotypes measured in ≈300,000 unrelated white British individuals in the UK Biobank to test for quadratic effects within each of 9515 protein-coding genes. We detect 32 trait-gene pairs across 17 traits and 29 genes that demonstrate statistically significant signals of quadratic effects (accounting for the number of genes and traits tested). Across these trait-gene pairs, the proportion of trait variance explained by quadratic effects is comparable to additive effects, with five pairs having a ratio >1. Our method enables the detailed investigation of epistasis on a large scale, offering new insights into its role and importance.

SNP heritability, the proportion of phenotypic variation explained by genotyped SNPs, is an important parameter in understanding the genetic architecture underlying various diseases and traits. Methods that aim to estimate SNP heritability from individual genotype and phenotype data are limited by their ability to scale to Biobank-scale data sets and by the restrictions in access to individual-level data. These limitations have motivated the development of methods that only require summary statistics. Although the availability of publicly accessible summary statistics makes them widely applicable, these methods lack the accuracy of methods that utilize individual genotypes. Here we present a SUMmary-statistics-based Randomized Haseman-Elston regression (SUM-RHE), a method that can estimate the SNP heritability of complex phenotypes with accuracies comparable to approaches that require individual genotypes, while exclusively relying on summary statistics. SUM-RHE employs Genome-Wide Association Study (GWAS) summary statistics and statistics obtained on a reference population, which can be efficiently estimated and readily shared for public use. Our results demonstrate that SUM-RHE obtains estimates of SNP heritability that are substantially more accurate compared with other summary statistic methods and on par with methods that rely on individual-level data.

Whole genome sequences (WGS) enable discovery of rare variants which may contribute to missing heritability of coronary artery disease (CAD). To measure their contribution, we apply the GREML-LDMS-I approach to WGS of 4949 cases and 17,494 controls of European ancestry from the NHLBI TOPMed program. We estimate CAD heritability at 34.3% assuming a prevalence of 8.2%. Ultra-rare (minor allele frequency ≤ 0.1%) variants with low linkage disequilibrium (LD) score contribute ~50% of the heritability. We also investigate CAD heritability enrichment using a diverse set of functional annotations: i) constraint; ii) predicted protein-altering impact; iii) cis-regulatory elements from a cell-specific chromatin atlas of the human coronary; and iv) annotation principal components representing a wide range of functional processes. We observe marked enrichment of CAD heritability for most functional annotations. These results reveal the predominant role of ultra-rare variants in low LD on the heritability of CAD. Moreover, they highlight several functional processes including cell type-specific regulatory mechanisms as key drivers of CAD genetic risk.

Whole genome sequences (WGS) of 185 North American Thoroughbred horses were compared to quantify the number and frequency of variants, diversity of mitotypes, and autosomal runs of homozygosity (ROH). Of the samples, 82 horses were born between 1965 and 1986 (Group 1); the remaining 103, selected to maximize pedigree diversity, were born between 2000 and 2020 (Group 2). Over 14.3 million autosomal variants were identified with 4.5-5.0 million found per horse. Mitochondrial sequences associated the North American Thoroughbreds with 9 of 17 clades previously identified among diverse breeds. Individual coefficients of inbreeding, estimated from ROH, averaged 0.266 (Group 1) and 0.283 (Group 2). When SNP arrays were simulated using subsets of WGS markers, the arrays over-estimated lengths of ROH. WGS-based estimates of inbreeding were highly correlated (r > 0.98) with SNP array-based estimates, but only moderately correlated (r = 0.40) with inbreeding based on 5-generation pedigrees. On average, Group 1 horses had more heterozygous variants (P

The adoption of agriculture triggered a rapid shift towards starch-rich diets in human populations1. Amylase genes facilitate starch digestion, and increased amylase copy number has been observed in some modern human populations with high-starch intake2, although evidence of recent selection is lacking3,4. Here, using 94 long-read haplotype-resolved assemblies and short-read data from approximately 5,600 contemporary and ancient humans, we resolve the diversity and evolutionary history of structural variation at the amylase locus. We find that amylase genes have higher copy numbers in agricultural populations than in fishing, hunting and pastoral populations. We identify 28 distinct amylase structural architectures and demonstrate that nearly identical structures have arisen recurrently on different haplotype backgrounds throughout recent human history. AMY1 and AMY2A genes each underwent multiple duplication/deletion events with mutation rates up to more than 10,000-fold the single-nucleotide polymorphism mutation rate, whereas AMY2B gene duplications share a single origin. Using a pangenome-based approach, we infer structural haplotypes across thousands of humans identifying extensively duplicated haplotypes at higher frequency in modern agricultural populations. Leveraging 533 ancient human genomes, we find that duplication-containing haplotypes (with more gene copies than the ancestral haplotype) have rapidly increased in frequency over the past 12,000 years in West Eurasians, suggestive of positive selection. Together, our study highlights the potential effects of the agricultural revolution on human genomes and the importance of structural variation in human adaptation.

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.

Psoriasis is a chronic, immune-mediated inflammatory skin disease associated with a polygenic mode of inheritance. There are few studies that explore the association of a psoriasis Polygenic Risk Score (PRS) with patient clinical characteristics, and to our knowledge there are no studies examining psoriasis PRS associations across different ethnicities. In this study, we used a multi-racial psoriasis cohort to investigate PRS associations with clinical phenotypes including age of onset, psoriatic arthritis, other comorbidities, psoriasis body location, psoriasis subtype, environmental triggers, and response to therapies. We collected patient data and Affymetrix genome-wide SNP data from a cohort of 607 psoriasis patients and calculated an 88-loci PRS (PRS-ALL), also partitioned between genetic loci within the HLA region (PRS-HLA; 11 SNPS) and loci outside the HLA region (PRS-NoHLA; 77 SNPS). We used t-test and logistic regression to analyze the association of PRS with clinical phenotypes. We found that PRS-HLA and PRS-noHLA had differing effects on psoriasis age of onset, psoriatic arthritis, psoriasis located on the ears, genitals, nails, soles of feet, skin folds, and palms, skin injury as an environmental trigger, cardiovascular comorbidities, and response to phototherapy. In some cases these PRS associations were ethnicity specific. Overall, these results show that the genetic basis for clinical manifestations of psoriasis are driven by distinct HLA and non-HLA effects, and that these PRS associations can be dependent on ethnicity.

BackgroundPrenatal folate supplementation has been consistently associated with a reduced risk of childhood acute lymphoblastic leukemia (ALL). Previous germline genetic studies examining the one carbon (folate) metabolism pathway were limited in sample size, scope, and population diversity and led to inconclusive results.MethodsWe evaluated whether ∼2,900 single-nucleotide polymorphisms (SNP) within 46 candidate genes involved in the folate metabolism pathway influence the risk of childhood ALL, using genome-wide data from nine case-control studies in the Childhood Cancer and Leukemia International Consortium (n = 9,058 cases including 4,510 children of European ancestry, 3,018 Latinx, and 1,406 Asians, and 92,364 controls). Each study followed a standardized protocol for quality control and imputation of genome-wide data and summary statistics were meta-analyzed for all children combined and by major ancestry group using METAL software.ResultsNone of the selected SNPs reached statistical significance, overall and for major ancestry groups (using adjusted Bonferroni P-value of 5 × 10-6 and less-stringent P-value of 3.5 × 10-5 accounting for the number of "independent" SNPs). None of the 10 top (nonsignificant) SNPs and corresponding genes overlapped across ancestry groups.ConclusionsThis large meta-analysis of original data does not reveal associations between many common genetic variants in the folate metabolism pathway and childhood ALL in various ancestry groups.ImpactGenetic variants in the folate pathway alone do not appear to substantially influence childhood acute lymphoblastic leukemia risk. Other mechanisms such as gene-folate interaction, DNA methylation, or maternal genetic effects may explain the observed associations with self-reported prenatal folate intake.

INTRODUCTION: We conducted admixture mapping and fine-mapping analyses to identify ancestry-of-origin loci influencing cognitive abilities. METHODS: We estimated the association of local ancestry intervals across the genome with five neurocognitive measures in 7140 diverse Hispanic and Latino adults (mean age 55 years). We prioritized genetic variants in associated loci and tested them for replication in four independent cohorts. RESULTS: We identified nine local ancestry-associated regions for the five neurocognitive measures. There was strong biological support for the observed associations to cognitive function at all loci and there was statistical evidence of independent replication at 4q12, 9p22.1, and 13q12.13. DISCUSSION: Our study identified multiple novel loci harboring genes implicated in cognitive functioning and dementia, and uncovered ancestry-relevant genetic variants. It adds to our understanding of the genetic architecture of cognitive function in Hispanic and Latino adults and demonstrates the power of admixture mapping to discover unique haplotypes influencing cognitive function, complementing genome-wide association studies. HIGHLIGHTS: We identified nine ancestry-of-origin chromosomal regions associated with five neurocognitive traits. In each associated region, we identified single nucleotide polymorphisms (SNPs) that explained, at least in part, the admixture signal and were tested for replication in independent samples of Black, non-Hispanic White, and Hispanic/Latino adults with the same or similar neurocognitive tests. Statistical evidence of independent replication of the prioritized SNPs was observed for three of the nine associations, at chr4q12, chr9p22.1, and chr13q12.13. At all loci, there was strong biological support for the observed associations to cognitive function and dementia, prioritizing genes such as KIT, implicated in autophagic clearance of neurotoxic proteins and on mast cell and microglial-mediated inflammation; SLC24A2, implicated in synaptic plasticity associated with learning and memory; and MTMR6, implicated in phosphoinositide lipids metabolism.

Cannabis use disorder (CanUD) has increased with the legalization of the use of cannabis. Around 20% of individuals using cannabis develop CanUD, and the number of users has grown with increasing ease of access. CanUD and other substance use disorders (SUDs) are associated phenotypically and genetically. We leveraged new CanUD genomics data to undertake genetically-informed analyses with unprecedented power, to investigate the genetic architecture and causal relationships between CanUD and lifetime cannabis use with risk for developing SUDs and substance use traits. Analyses included calculating local and global genetic correlations, genomic structural equation modeling (genomicSEM), and Mendelian Randomization (MR). Results from the genetic correlation and genomicSEM analyses demonstrated that CanUD and cannabis use differ in their relationships with SUDs and substance use traits. We found significant causal effects of CanUD influencing all the analyzed traits: opioid use disorder (OUD) (Inverse variant weighted, IVW β = 0.925 ± 0.082), problematic alcohol use (PAU) (IVW β = 0.443 ± 0.030), drinks per week (DPW) (IVW β = 0.182 ± 0.025), Fagerström Test for Nicotine Dependence (FTND) (IVW β = 0.183 ± 0.052), cigarettes per day (IVW β = 0.150 ± 0.045), current versus former smokers (IVW β = 0.178 ± 0.052), and smoking initiation (IVW β = 0.405 ± 0.042). We also found evidence of bidirectionality showing that OUD, PAU, smoking initiation, smoking cessation, and DPW all increase risk of developing CanUD. For cannabis use, bidirectional relationships were inferred with PAU, smoking initiation, and DPW; cannabis use was also associated with a higher risk of developing OUD (IVW β = 0.785 ± 0.266). GenomicSEM confirmed that CanUD and cannabis use load onto different genetic factors. We conclude that CanUD and cannabis use can increase the risk of developing other SUDs. This has substantial public health implications; the move towards legalization of cannabis use may be expected to increase other kinds of problematic substance use. These harmful outcomes are in addition to the medical harms associated directly with CanUD.

The insights into interactions between host genetics and gut microbiome (GM) in colorectal tumor susceptibility (CTS) remains lacking. We used Collaborative Cross mouse population model to identify genetic and microbial determinants of Azoxymethane-induced CTS. We identified 4417 CTS-associated single nucleotide polymorphisms (SNPs) containing 334 genes that were transcriptionally altered in human colorectal cancers (CRCs) and consistently clustered independent human CRC cohorts into two subgroups with different prognosis. We discovered a set of genera in early-life associated with CTS and defined a 16-genus signature that accurately predicted CTS, the majority of which were correlated with human CRCs. We identified 547 SNPs associated with abundances of these genera. Mediation analysis revealed GM as mediators partially exerting the effect of SNP UNC3869242 within Duox2 on CTS. Intestine cell-specific depletion of Duox2 altered GM composition and contribution of Duox2 depletion to CTS was significantly influenced by GM. Our findings provide potential novel targets for personalized CRC prevention and treatment.

Chordoma is a rare bone cancer with variable clinical outcomes. Here, we recruited 184 sporadic chordoma patients from the US and Canada and collected their clinical and treatment data. The average age at diagnosis was 45.5 years (Range 5-78) and the chordoma site distribution was 49.2% clivus, 26.2% spinal, and 24.0% sacral. Most patients (97.5%) received surgery as the primary treatment, among whom 85.3% also received additional treatment. Except for the most prevalent cancers like prostate, lung, breast, and skin cancer, there was no discernible enrichment for any specific cancer type among patients or their family members. Among a subset of patients (N = 70) with tumor materials, we conducted omics analyses and obtained targeted panel sequencing and SNP array genotyping data for 51 and 49 patients, respectively. The most recurrent somatic driver mutations included PIK3CA (12%), followed by chromatin remodeling genes PBRM1 and SETD2. Amplification of the 6q27 region, containing the chordoma susceptibility gene TBXT, was detected in eight patients (16.3%). Clival patients appeared to be less likely to carry driver gene mutations, chromosome arm level deletion events (e.g., 5p, 5p, and 9p), or 6q27 amplification compared to sacral patients. After adjusting for age, sex, tumor site, and additional treatment, patients with somatic deletions of 14q (OR = 13.73, 95% CI 1.96-96.02, P = 0.008) and 18p (OR = 13.68, 95% CI 1.77-105.89, P = 0.012) were more likely to have persistent chordoma. The study highlights genomic heterogeneity in chordoma, potentially linked to location and clinical progression.

SummaryHarmonizing variant indexing and allele assignments across datasets is crucial for data integrity in cross-dataset studies such as multi-cohort genome-wide association studies, meta-analyses, and the development, validation, and application of polygenic risk scores. Ensuring this indexing and allele consistency is a laborious, time-consuming, and error-prone process requiring a certain degree of computational proficiency. Here, we introduce GRIEVOUS, a command-line tool for cross-dataset variant homogenization. By means of an internal database and a custom indexing methodology, GRIEVOUS identifies, formats, and aligns all biallelic single nucleotide polymorphisms (SNPs) across all summary statistic and genotype files of interest. Upon completion of dataset harmonization, GRIEVOUS can also be used to extract the maximal set of biallelic SNPs common to all datasets.Availability and implementationGRIEVOUS and all supporting documentation and tutorials can be found at https://github.com/jvtalwar/GRIEVOUS. It is freely and publicly available under the MIT license and can be installed via pip.

Genome-wide association studies (GWAS) implicate broad genomic loci containing clusters of highly correlated genetic variants. Finemapping techniques can select and prioritize variants within each GWAS locus which are more likely to have a functional influence on the trait. Here, we present a novel method, Finemap-MiXeR, for finemapping causal variants from GWAS summary statistics, controlling for correlation among variants due to linkage disequilibrium. Our method is based on a variational Bayesian approach and direct optimization of the Evidence Lower Bound (ELBO) of the likelihood function derived from the MiXeR model. After obtaining the analytical expression for ELBOs gradient, we apply Adaptive Moment Estimation (ADAM) algorithm for optimization, allowing us to obtain the posterior causal probability of each variant. Using these posterior causal probabilities, we validated Finemap-MiXeR across a wide range of scenarios using both synthetic data, and real data on height from the UK Biobank. Comparison of Finemap-MiXeR with two existing methods, FINEMAP and SuSiE RSS, demonstrated similar or improved accuracy. Furthermore, our method is computationally efficient in several aspects. For example, unlike many other methods in the literature, its computational complexity does not increase with the number of true causal variants in a locus and it does not require any matrix inversion operation. The mathematical framework of Finemap-MiXeR is flexible and may also be applied to other problems including cross-trait and cross-ancestry finemapping.

BACKGROUND: Deeper insights into ERBB2-driven cancers are essential to develop new treatment approaches for ERBB2+ breast cancers (BCs). We employed the Collaborative Cross (CC) mouse model to unearth genetic factors underpinning Erbb2-driven mammary tumour development and metastasis. METHODS: 732 F1 hybrid female mice between FVB/N MMTV-Erbb2 and 30 CC strains were monitored for mammary tumour phenotypes. GWAS pinpointed SNPs that influence various tumour phenotypes. Multivariate analyses and models were used to construct the polygenic score and to develop a mouse tumour susceptibility gene signature (mTSGS), where the corresponding human ortholog was identified and designated as hTSGS. The importance and clinical value of hTSGS in human BC was evaluated using public datasets, encompassing TCGA, METABRIC, GSE96058, and I-SPY2 cohorts. The predictive power of mTSGS for response to chemotherapy was validated in vivo using genetically diverse MMTV-Erbb2 mice. FINDINGS: Distinct variances in tumour onset, multiplicity, and metastatic patterns were observed in F1-hybrid female mice between FVB/N MMTV-Erbb2 and 30 CC strains. Besides lung metastasis, liver and kidney metastases emerged in specific CC strains. GWAS identified specific SNPs significantly associated with tumour onset, multiplicity, lung metastasis, and liver metastasis. Multivariate analyses flagged SNPs in 20 genes (Stx6, Ramp1, Traf3ip1, Nckap5, Pfkfb2, Trmt1l, Rprd1b, Rer1, Sepsecs, Rhobtb1, Tsen15, Abcc3, Arid5b, Tnr, Dock2, Tti1, Fam81a, Oxr1, Plxna2, and Tbc1d31) independently tied to various tumour characteristics, designated as a mTSGS. hTSGS scores (hTSGSS) based on their transcriptional level showed prognostic values, superseding clinical factors and PAM50 subtype across multiple human BC cohorts, and predicted pathological complete response independent of and superior to MammaPrint score in I-SPY2 study. The power of mTSGS score for predicting chemotherapy response was further validated in an in vivo mouse MMTV-Erbb2 model, showing that, like findings in human patients, mouse tumours with low mTSGS scores were most likely to respond to treatment. INTERPRETATION: Our investigation has unveiled many new genes predisposing individuals to ERBB2-driven cancer. Translational findings indicate that hTSGS holds promise as a biomarker for refining treatment strategies for patients with BC. FUNDING: The U.S. Department of Defense (DoD) Breast Cancer Research Program (BCRP) (BC190820), United States; MCIN/AEI/10.13039/501100011039 (PID2020-118527RB-I00, PDC2021-121735-I00), the European Union Next Generation EU/PRTR, the Regional Government of Castile and León (CSI144P20), European Union.

Recent studies have highlighted the essential role of RNA splicing, a key mechanism of alternative RNA processing, in establishing connections between genetic variations and disease. Genetic loci influencing RNA splicing variations show considerable influence on complex traits, possibly surpassing those affecting total gene expression. Dysregulated RNA splicing has emerged as a major potential contributor to neurological and psychiatric disorders, likely due to the exceptionally high prevalence of alternatively spliced genes in the human brain. Nevertheless, establishing direct associations between genetically altered splicing and complex traits has remained an enduring challenge. We introduce Spliced-Transcriptome-Wide Associations (SpliTWAS) to integrate alternative splicing information with genome-wide association studies to pinpoint genes linked to traits through exon splicing events. We applied SpliTWAS to two schizophrenia (SCZ) RNA-sequencing datasets, BrainGVEX and CommonMind, revealing 137 and 88 trait-associated exons (in 84 and 67 genes), respectively. Enriched biological functions in the associated gene sets converged on neuronal function and development, immune cell activation, and cellular transport, which are highly relevant to SCZ. SpliTWAS variants impacted RNA-binding protein binding sites, revealing potential disruption of RNA-protein interactions affecting splicing. We extended the probabilistic fine-mapping method FOCUS to the exon level, identifying 36 genes and 48 exons as putatively causal for SCZ. We highlight VPS45 and APOPT1, where splicing of specific exons was associated with disease risk, eluding detection by conventional gene expression analysis. Collectively, this study supports the substantial role of alternative splicing in shaping the genetic basis of SCZ, providing a valuable approach for future investigations in this area.

One of the justifiable criticisms of human genetic studies is the underrepresentation of participants from diverse populations. Lack of inclusion must be addressed at-scale to identify causal disease factors and understand the genetic causes of health disparities. We present genome-wide associations for 2068 traits from 635,969 participants in the Department of Veterans Affairs Million Veteran Program, a longitudinal study of diverse United States Veterans. Systematic analysis revealed 13,672 genomic risk loci; 1608 were only significant after including non-European populations. Fine-mapping identified causal variants at 6318 signals across 613 traits. One-third (n = 2069) were identified in participants from non-European populations. This reveals a broadly similar genetic architecture across populations, highlights genetic insights gained from underrepresented groups, and presents an extensive atlas of genetic associations.

Deciphering the genetic basis of prostate-specific antigen (PSA) levels may improve their utility for prostate cancer (PCa) screening. Using genome-wide association study (GWAS) summary statistics from 95,768 PCa-free men, we conducted a transcriptome-wide association study (TWAS) to examine impacts of genetically predicted gene expression on PSA. Analyses identified 41 statistically significant (p 0.5: CCNA2 and HIST1H2BN. Six of the 20 identified genes are not known to impact PCa risk. Fine-mapping based on whole blood and prostate tissue revealed five protein-coding genes with evidence of causal relationships with PSA levels. Of these five genes, four exhibited evidence of colocalization and one was conditionally independent of previous GWAS findings. These results yield hypotheses that should be further explored to improve understanding of genetic factors underlying PSA levels.

BACKGROUND: The pleiotropic effects of the melanocortin system show promise in overcoming limitations associated with large variations in opioid analgesic effectiveness observed in equine practice. Of particular interest is variation in the melanocortin-1-receptor (MC1R) gene, which dictates pigment type expression through its epistatic interaction with the agouti signalling protein (ASIP) gene. MC1R has previously been implicated in opioid efficacy in other species; however, this relationship is yet to be explored in horses. In this study, analgesic effectiveness was scored (1-3) based on noted response to dura penetration during the performance of cerebrospinal fluid centisis after sedation and tested for association with known genetic regions responsible for pigmentation variation in horses. RESULTS: The chestnut phenotype was statistically significant (P < 0.05) in lowering analgesic effectiveness when compared to the bay base coat colour. The 11bp indel in ASIP known to cause the black base coat colour was not significant (P>0.05); however, six single nucleotide polymorphisms (SNPs) within the genomic region encoding the ASIP gene and one within MC1R were identified as being nominally significant (P

Frontotemporal dementia (FTD) is the second most common cause of early-onset dementia after Alzheimer disease (AD). Efforts in the field mainly focus on familial forms of disease (fFTDs), while studies of the genetic etiology of sporadic FTD (sFTD) have been less common. In the current work, we analyzed 4,685 sFTD cases and 15,308 controls looking for common genetic determinants for sFTD. We found a cluster of variants at the MAPT (rs199443; p = 2.5 × 10-12, OR = 1.27) and APOE (rs6857; p = 1.31 × 10-12, OR = 1.27) loci and a candidate locus on chromosome 3 (rs1009966; p = 2.41 × 10-8, OR = 1.16) in the intergenic region between RPSA and MOBP, contributing to increased risk for sFTD through effects on expression and/or splicing in brain cortex of functionally relevant in-cis genes at the MAPT and RPSA-MOBP loci. The association with the MAPT (H1c clade) and RPSA-MOBP loci may suggest common genetic pleiotropy across FTD and progressive supranuclear palsy (PSP) (MAPT and RPSA-MOBP loci) and across FTD, AD, Parkinson disease (PD), and cortico-basal degeneration (CBD) (MAPT locus). Our data also suggest population specificity of the risk signals, with MAPT and APOE loci associations mainly driven by Central/Nordic and Mediterranean Europeans, respectively. This study lays the foundations for future work aimed at further characterizing population-specific features of potential FTD-discriminant APOE haplotype(s) and the functional involvement and contribution of the MAPT H1c haplotype and RPSA-MOBP loci to pathogenesis of sporadic forms of FTD in brain cortex.

Understanding the contribution of gene-environment interactions (GxE) to complex trait variation can provide insights into disease mechanisms, explain sources of heritability, and improve genetic risk prediction. While large biobanks with genetic and deep phenotypic data hold promise for obtaining novel insights into GxE, our understanding of GxE architecture in complex traits remains limited. We introduce a method to estimate the proportion of trait variance explained by GxE (GxE heritability) and additive genetic effects (additive heritability) across the genome and within specific genomic annotations. We show that our method is accurate in simulations and computationally efficient for biobank-scale datasets. We applied our method to common array SNPs (MAF ≥1%), fifty quantitative traits, and four environmental variables (smoking, sex, age, and statin usage) in unrelated white British individuals in the UK Biobank. We found 68 trait-E pairs with significant genome-wide GxE heritability (p

Polygenic scores (PGS) have emerged as the tool of choice for genomic prediction in a wide range of fields. We show that PGS performance varies broadly across contexts and biobanks. Contexts such as age, sex and income can impact PGS accuracy with similar magnitudes as genetic ancestry. Here we introduce an approach (CalPred) that models all contexts jointly to produce prediction intervals that vary across contexts to achieve calibration (include the trait with 90% probability), whereas existing methods are miscalibrated. In analyses of 72 traits across large and diverse biobanks (All of Us and UK Biobank), we find that prediction intervals required adjustment by up to 80% for quantitative traits. For disease traits, PGS-based predictions were miscalibrated across socioeconomic contexts such as annual household income levels, further highlighting the need of accounting for context information in PGS-based prediction across diverse populations.

Pubertal timing varies considerably and is associated with later health outcomes. We performed multi-ancestry genetic analyses on ~800,000 women, identifying 1,080 signals for age at menarche. Collectively, these explained 11% of trait variance in an independent sample. Women at the top and bottom 1% of polygenic risk exhibited ~11 and ~14-fold higher risks of delayed and precocious puberty, respectively. We identified several genes harboring rare loss-of-function variants in ~200,000 women, including variants in ZNF483, which abolished the impact of polygenic risk. Variant-to-gene mapping approaches and mouse gonadotropin-releasing hormone neuron RNA sequencing implicated 665 genes, including an uncharacterized G-protein-coupled receptor, GPR83, which amplified the signaling of MC3R, a key nutritional sensor. Shared signals with menopause timing at genes involved in DNA damage response suggest that the ovarian reserve might signal centrally to trigger puberty. We also highlight body size-dependent and independent mechanisms that potentially link reproductive timing to later life disease.

Ninu (greater bilby, Macrotis lagotis) are desert-dwelling, culturally and ecologically important marsupials. In collaboration with Indigenous rangers and conservation managers, we generated the Ninu chromosome-level genome assembly (3.66 Gbp) and genome sequences for the extinct Yallara (lesser bilby, Macrotis leucura). We developed and tested a scat single-nucleotide polymorphism panel to inform current and future conservation actions, undertake ecological assessments and improve our understanding of Ninu genetic diversity in managed and wild populations. We also assessed the beneficial impact of translocations in the metapopulation (N = 363 Ninu). Resequenced genomes (temperate Ninu, 6; semi-arid Ninu, 6; and Yallara, 4) revealed two major population crashes during global cooling events for both species and differences in Ninu genes involved in anatomical and metabolic pathways. Despite their 45-year captive history, Ninu have fewer long runs of homozygosity than other larger mammals, which may be attributable to their boom-bust life history. Here we investigated the unique Ninu biology using 12 tissue transcriptomes revealing expression of all 115 conserved eutherian chorioallantoic placentation genes in the uterus, an XY1Y2 sex chromosome system and olfactory receptor gene expansions. Together, we demonstrate the holistic value of genomics in improving key conservation actions, understanding unique biological traits and developing tools for Indigenous rangers to monitor remote wild populations.

BACKGROUND AND AIMS: Despite the substantial impact of environmental factors, individuals with a family history of liver cancer have an increased risk for HCC. However, genetic factors have not been studied systematically by genome-wide approaches in large numbers of individuals from European descent populations (EDP). APPROACH AND RESULTS: We conducted a 2-stage genome-wide association study (GWAS) on HCC not affected by HBV infections. A total of 1872 HCC cases and 2907 controls were included in the discovery stage, and 1200 HCC cases and 1832 controls in the validation. We analyzed the discovery and validation samples separately and then conducted a meta-analysis. All analyses were conducted in the presence and absence of HCV. The liability-scale heritability was 24.4% for overall HCC. Five regions with significant ORs (95% CI) were identified for nonviral HCC: 3p22.1, MOBP , rs9842969, (0.51, [0.40-0.65]); 5p15.33, TERT , rs2242652, (0.70, (0.62-0.79]); 19q13.11, TM6SF2 , rs58542926, (1.49, [1.29-1.72]); 19p13.11 MAU2 , rs58489806, (1.53, (1.33-1.75]); and 22q13.31, PNPLA3 , rs738409, (1.66, [1.51-1.83]). One region was identified for HCV-induced HCC: 6p21.31, human leukocyte antigen DQ beta 1, rs9275224, (0.79, [0.74-0.84]). A combination of homozygous variants of PNPLA3 and TERT showing a 6.5-fold higher risk for nonviral-related HCC compared to individuals lacking these genotypes. This observation suggests that gene-gene interactions may identify individuals at elevated risk for developing HCC. CONCLUSIONS: Our GWAS highlights novel genetic susceptibility of nonviral HCC among European descent populations from North America with substantial heritability. Selected genetic influences were observed for HCV-positive HCC. Our findings indicate the importance of genetic susceptibility to HCC development.

Polygenic scores (PGSs) summarize the combined effect of common risk variants and are associated with breast cancer risk in patients without identifiable monogenic risk factors. One of the most well-validated PGSs in breast cancer to date is PGS313, which was developed from a Northern European biobank but has shown attenuated performance in non-European ancestries. We further investigate the generalizability of the PGS313 for American women of European (EA), African (AFR), Asian (EAA), and Latinx (HL) ancestry within one institution with a singular electronic health record (EHR) system, genotyping platform, and quality control process. We found that the PGS313 achieved overlapping areas under the receiver operator characteristic (ROC) curve (AUCs) in females of HL (AUC = 0.68, 95% confidence interval [CI] = 0.65-0.71) and EA ancestry (AUC = 0.70, 95% CI = 0.69-0.71) but lower AUCs for the AFR and EAA populations (AFR: AUC = 0.61, 95% CI = 0.56-0.65; EAA: AUC = 0.64, 95% CI = 0.60-0.680). While PGS313 is associated with hormone-receptor-positive (HR+) disease in EA Americans (odds ratio [OR] = 1.42, 95% CI = 1.16-1.64), this association is lost in African, Latinx, and Asian Americans. In summary, we found that PGS313 was significantly associated with breast cancer but with attenuated accuracy in women of AFR and EAA descent within a singular health system in Los Angeles. Our work further highlights the need for additional validation in diverse cohorts prior to the clinical implementation of PGSs.

Cowpea is a highly drought-adapted leguminous crop with great promise for improving agricultural sustainability and food security. Here, we report analyses derived from array-based genotyping of 2,021 accessions constituting a core subset of the worlds largest cowpea collection, held at the International Institute of Tropical Agriculture (IITA) in Ibadan, Nigeria. We used this dataset to examine genetic variation and population structure in worldwide cowpea. We confirm that the primary pattern of population structure is two geographically defined subpopulations originating in West and East Africa, respectively, and that population structure is associated with shifts in phenotypic distribution. Furthermore, we establish the cowpea core collection as a resource for genome-wide association studies by mapping the genetic basis of several phenotypes, with a focus on seed coat pigmentation patterning and color. We anticipate that the genotyped IITA Cowpea Core Collection will serve as a powerful tool for mapping complex traits, facilitating the acceleration of breeding programs to enhance the resilience of this crop in the face of rapid global climate change.

AimTo develop a non-invasive prenatal test for beta-hemoglobinopathies based on analyzing maternal plasma by using next generation sequencing.MethodsWe applied next generation sequencing (NGS) of maternal plasma to the non-invasive prenatal testing (NIPT) of autosomal recessive diseases, sickle cell disease and beta-thalassemia. Using the Illumina MiSeq, we sequenced plasma libraries obtained via a Twist Bioscience probe capture panel covering 4 Kb of chromosome 11, including the beta-globin (HBB) gene and >450 genomic single-nucleotide polymorphisms (SNPs) used to estimate the fetal fraction (FF). The FF is estimated by counting paternally transmitted allelic sequence reads present in the plasma but absent in the mother. We inferred fetal beta-globin genotypes by comparing the observed mutation (Mut) and reference (Ref) read ratios to those expected for the three possible fetal genotypes (Mut/Mut; Mut/Ref; Ref/Ref), based on the FF.ResultsWe bioinformatically enriched the FF by excluding reads over a specified length via in-silico size selection (ISS), favoring the shorter fetal reads, which increased fetal genotype prediction accuracy. Finally, we determined the parental HBB haplotypes, which allowed us to use the read ratios observed at linked SNPs to help predict the fetal genotype at the mutation site(s). We determined HBB haplotypes via Oxford Nanopore MinION sequencing of a 2.2 kb amplicon and aligned these sequences using Soft Genetics' NextGENe LR software.ConclusionThe combined use of ISS and HBB haplotypes enabled us to correctly predict fetal genotypes in cases where the prediction based on variant read ratios alone was incorrect.

BACKGROUND: Polygenic Risk Scores (PRS) based on results from genome-wide association studies offer the prospect of risk stratification for many common and complex diseases. We developed a PRS for alcohol-associated cirrhosis by comparing single-nucleotide polymorphisms among patients with alcohol-associated cirrhosis (ALC) versus drinkers who did not have evidence of liver fibrosis/cirrhosis. METHODS: Using a data-driven approach, a PRS for ALC was generated using a meta-genome-wide association study of ALC (N=4305) and an independent cohort of heavy drinkers with ALC and without significant liver disease (N=3037). It was validated in 2 additional independent cohorts from the UK Biobank with diagnosed ALC (N=467) and high-risk drinking controls (N=8981) and participants in the Indiana Biobank Liver cohort with alcohol-associated liver disease (N=121) and controls without liver disease (N=3239). RESULTS: A 20-single-nucleotide polymorphisms PRS for ALC (PRSALC) was generated that stratified risk for ALC comparing the top and bottom deciles of PRS in the 2 validation cohorts (ORs: 2.83 [95% CI: 1.82 -4.39] in UK Biobank; 4.40 [1.56 -12.44] in Indiana Biobank Liver cohort). Furthermore, PRSALC improved the prediction of ALC risk when added to the models of clinically known predictors of ALC risk. It also stratified the risk for metabolic dysfunction -associated steatotic liver disease -cirrhosis (3.94 [2.23 -6.95]) in the Indiana Biobank Liver cohort -based exploratory analysis. CONCLUSIONS: PRSALC incorporates 20 single-nucleotide polymorphisms, predicts increased risk for ALC, and improves risk stratification for ALC compared with the models that only include clinical risk factors. This new score has the potential for early detection of heavy drinking patients who are at high risk for ALC.

A quarter of humanity is estimated to have been exposed to Mycobacterium tuberculosis (Mtb) with a 5-10% risk of developing tuberculosis (TB) disease. Variability in responses to Mtb infection could be due to host or pathogen heterogeneity. Here, we focused on host genetic variation in a Peruvian population and its associations with gene regulation in monocyte-derived macrophages and dendritic cells (DCs). We recruited former household contacts of TB patients who previously progressed to TB (cases, n = 63) or did not progress to TB (controls, n = 63). Transcriptomic profiling of monocyte-derived DCs and macrophages measured the impact of genetic variants on gene expression by identifying expression quantitative trait loci (eQTL). We identified 330 and 257 eQTL genes in DCs and macrophages (False Discovery Rate (FDR) < 0.05), respectively. Four genes in DCs showed interaction between eQTL variants and TB progression status. The top eQTL interaction for a protein-coding gene was with FAH, the gene encoding fumarylacetoacetate hydrolase, which mediates the last step in mammalian tyrosine catabolism. FAH expression was associated with genetic regulatory variation in cases but not controls. Using public transcriptomic and epigenomic data of Mtb-infected monocyte-derived dendritic cells, we found that Mtb infection results in FAH downregulation and DNA methylation changes in the locus. Overall, this study demonstrates effects of genetic variation on gene expression levels that are dependent on history of infectious disease and highlights a candidate pathogenic mechanism through pathogen-response genes. Furthermore, our results point to tyrosine metabolism and related candidate TB progression pathways for further investigation.

Based on emerging evidence on the role for specific single-nucleotide variants (SNVs) in EIF2AK3 encoding the integrated stress response kinase PERK, in neurodegeneration, we assessed the association of EIF2AK3 SNVs with neurocognitive performance in people with HIV (PWH) using a candidate gene approach. This retrospective study included the CHARTER cohort participants, excluding those with severe neuropsychiatric comorbidities. Genome-wide data previously obtained for 1047 participants and targeted sequencing of 992 participants with available genomic DNA were utilized to interrogate the association of three noncoding and three coding EIF2AK3 SNVs with the continuous global deficit score (GDS) and global neurocognitive impairment (NCI; GDS ≥ 0.5) using univariable and multivariable methods, with demographic, disease-associated, and treatment characteristics as covariates. The cohort characteristics were as follows: median age, 43.1 years; females, 22.8%; European ancestry, 41%; median CD4 + T cell counts, 175/µL (nadir) and 428/µL (current). At first assessment, 70.5% used ART and 68.3% of these had plasma HIV RNA levels ≤ 200 copies/mL. All three noncoding EIF2AK3 SNVs were associated with GDS and NCI (all p  13 were independently associated with GDS and NCI (p

Tanoak (Notholithocarpus densiflorus) is an evergreen tree in the Fagaceae family found in California and southern Oregon. Historically, tanoak acorns were an important food source for Native American tribes, and the bark was used extensively in the leather tanning process. Long considered a disjunct relictual element of the Asian stone oaks (Lithocarpus spp.), phylogenetic analysis has determined that the tanoak is an example of convergent evolution. Tanoaks are deeply divergent from oaks (Quercus) of the Pacific Northwest and comprise a new genus with a single species. These trees are highly susceptible to sudden oak death (SOD), a plant pathogen (Phytophthora ramorum) that has caused widespread deaths of tanoaks. In this study, we set out to assemble the genome and perform comparative studies among a number of individuals that demonstrated varying levels of susceptibility to SOD. First, we sequenced and de novo assembled a draft reference genome of N. densiflorus using cobarcoded library processing methods and an MGI DNBSEQ-G400 sequencer. To increase the contiguity of the final assembly, we also sequenced Oxford Nanopore long reads to 30× coverage. To our knowledge, the draft genome reported here is one of the more contiguous and complete genomes of a tree species published to date, with a contig N50 of ∼1.2 Mb, a scaffold N50 of ∼2.1 Mb, and a complete gene score of 95.5% through BUSCO analysis. In addition, we sequenced 11 genetically distinct individuals and mapped these onto the draft reference genome, enabling the discovery of almost 25 million single nucleotide polymorphisms and ∼4.4 million small insertions and deletions. Finally, using cobarcoded data, we were able to generate a complete haplotype coverage of all 11 genomes.

Adverse pregnancy outcomes (APOs) affect a large proportion of pregnancies and represent an important cause of morbidity and mortality worldwide. Yet the pathophysiology of APOs is poorly understood, limiting our ability to prevent and treat these conditions. To search for genetic markers of maternal risk for four APOs, we performed multi-ancestry genome-wide association studies (GWAS) for pregnancy loss, gestational length, gestational diabetes, and preeclampsia. We clustered participants by their genetic ancestry and focused our analyses on three sub-cohorts with the largest sample sizes: European, African, and Admixed American. Association tests were carried out separately for each sub-cohort and then meta-analyzed together. Two novel loci were significantly associated with an increased risk of pregnancy loss: a cluster of SNPs located downstream of the TRMU gene (top SNP: rs142795512), and the SNP rs62021480 near RGMA. In the GWAS of gestational length we identified two new variants, rs2550487 and rs58548906 near WFDC1 and AC005052.1, respectively. Lastly, three new loci were significantly associated with gestational diabetes (top SNPs: rs72956265, rs10890563, rs79596863), located on or near ZBTB20, GUCY1A2, and RPL7P20, respectively. Fourteen loci previously correlated with preterm birth, gestational diabetes, and preeclampsia were found to be associated with these outcomes as well.

Clonal hematopoiesis (CH) is characterized by the acquisition of a somatic mutation in a hematopoietic stem cell that results in a clonal expansion. These driver mutations can be single nucleotide variants in cancer driver genes or larger structural rearrangements called mosaic chromosomal alterations (mCAs). The factors that influence the variations in mCA fitness and ultimately result in different clonal expansion rates are not well understood. We used the Passenger-Approximated Clonal Expansion Rate (PACER) method to estimate clonal expansion rate as PACER scores for 6,381 individuals in the NHLBI TOPMed cohort with gain, loss, and copy-neutral loss of heterozygosity mCAs. Our mCA fitness estimates, derived by aggregating per-individual PACER scores, were correlated (R2 = 0.49) with an alternative approach that estimated fitness of mCAs in the UK Biobank using population-level distributions of clonal fraction. Among individuals with JAK2 V617F clonal hematopoiesis of indeterminate potential or mCAs affecting the JAK2 gene on chromosome 9, PACER score was strongly correlated with erythrocyte count. In a cross-sectional analysis, genome-wide association study of estimates of mCA expansion rate identified a TCL1A locus variant associated with mCA clonal expansion rate, with suggestive variants in NRIP1 and TERT.

The genetic influence on human vocal pitch in tonal and non-tonal languages remains largely unknown. In tonal languages, such as Mandarin Chinese, pitch changes differentiate word meanings, whereas in non-tonal languages, such as Icelandic, pitch is used to convey intonation. We addressed this question by searching for genetic associations with interindividual variation in median pitch in a Chinese major depression case-control cohort and compared our results with a genome-wide association study from Iceland. The same genetic variant, rs11046212-T in an intron of the ABCC9 gene, was one of the most strongly associated loci with median pitch in both samples. Our meta-analysis revealed four genome-wide significant hits, including two novel associations. The discovery of genetic variants influencing vocal pitch across both tonal and non-tonal languages suggests the possibility of a common genetic contribution to the human vocal system shared in two distinct populations with languages that differ in tonality (Icelandic and Mandarin).

Vitamin A deficiency remains prevalent on a global scale, including in regions where maize constitutes a high percentage of human diets. One solution for alleviating this deficiency has been to increase grain concentrations of provitamin A carotenoids in maize (Zea mays ssp. mays L.)-an example of biofortification. The International Maize and Wheat Improvement Center (CIMMYT) developed a Carotenoid Association Mapping panel of 380 inbred lines adapted to tropical and subtropical environments that have varying grain concentrations of provitamin A and other health-beneficial carotenoids. Several major genes have been identified for these traits, 2 of which have particularly been leveraged in marker-assisted selection. This project assesses the predictive ability of several genomic prediction strategies for maize grain carotenoid traits within and between 4 environments in Mexico. Ridge Regression-Best Linear Unbiased Prediction, Elastic Net, and Reproducing Kernel Hilbert Spaces had high predictive abilities for all tested traits (β-carotene, β-cryptoxanthin, provitamin A, lutein, and zeaxanthin) and outperformed Least Absolute Shrinkage and Selection Operator. Furthermore, predictive abilities were higher when using genome-wide markers rather than only the markers proximal to 2 or 13 genes. These findings suggest that genomic prediction models using genome-wide markers (and assuming equal variance of marker effects) are worthwhile for these traits even though key genes have already been identified, especially if breeding for additional grain carotenoid traits alongside β-carotene. Predictive ability was maintained for all traits except lutein in between-environment prediction. The TASSEL (Trait Analysis by aSSociation, Evolution, and Linkage) Genomic Selection plugin performed as well as other more computationally intensive methods for within-environment prediction. The findings observed herein indicate the utility of genomic prediction methods for these traits and could inform their resource-efficient implementation in biofortification breeding programs.

Post-traumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 new). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (for example, GRIA1, GRM8 and CACNA1E), developmental, axon guidance and transcription factors (for example, FOXP2, EFNA5 and DCC), synaptic structure and function genes (for example, PCLO, NCAM1 and PDE4B) and endocrine or immune regulators (for example, ESR1, TRAF3 and TANK). Additional top genes influence stress, immune, fear and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation.

The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We perform a genome-wide association study on head size (N = 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimaging studies show that 17 variants affect specific brain areas, but most have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer.

We report a multi-ancestry genome-wide association study on liver cirrhosis and its associated endophenotypes, alanine aminotransferase (ALT) and γ-glutamyl transferase. Using data from 12 cohorts, including 18,265 cases with cirrhosis, 1,782,047 controls, up to 1 million individuals with liver function tests and a validation cohort of 21,689 cases and 617,729 controls, we identify and validate 14 risk associations for cirrhosis. Many variants are located near genes involved in hepatic lipid metabolism. One of these, PNPLA3 p.Ile148Met, interacts with alcohol intake, obesity and diabetes on the risk of cirrhosis and hepatocellular carcinoma (HCC). We develop a polygenic risk score that associates with the progression from cirrhosis to HCC. By focusing on prioritized genes from common variant analyses, we find that rare coding variants in GPAM associate with lower ALT, supporting GPAM as a potential target for therapeutic inhibition. In conclusion, this study provides insights into the genetic underpinnings of cirrhosis.

Hypertension affects more than one billion people worldwide. Here we identify 113 novel loci, reporting a total of 2,103 independent genetic signals (P

The Phenome-Wide Association Study (PheWAS) is increasingly used to broadly screen for potential treatment effects, e.g., IL6R variant as a proxy for IL6R antagonists. This approach offers an opportunity to address the limited power in clinical trials to study differential treatment effects across patient subgroups. However, limited methods exist to efficiently test for differences across subgroups in the thousands of multiple comparisons generated as part of a PheWAS. In this study, we developed an approach that maximizes the power to test for heterogeneous genotype-phenotype associations and applied this approach to an IL6R PheWAS among individuals of African (AFR) and European (EUR) ancestries. We identified 29 traits with differences in IL6R variant-phenotype associations, including a lower risk of type 2 diabetes in AFR (OR 0.96) vs EUR (OR 1.0, p-value for heterogeneity = 8.5 × 10-3), and higher white blood cell count (p-value for heterogeneity = 8.5 × 10-131). These data suggest a more salutary effect of IL6R blockade for T2D among individuals of AFR vs EUR ancestry and provide data to inform ongoing clinical trials targeting IL6 for an expanding number of conditions. Moreover, the method to test for heterogeneity of associations can be applied broadly to other large-scale genotype-phenotype screens in diverse populations.

IntroductionLate-onset Alzheimer's disease (LOAD) has a strong genetic component. Participants in Long-Life Family Study (LLFS) exhibit delayed onset of dementia, offering a unique opportunity to investigate LOAD genetics.MethodsWe conducted a whole genome sequence analysis of 3475 LLFS members. Genetic associations were examined in six independent studies (N = 14,260) with a wide range of LOAD risk. Association analysis in a sub-sample of the LLFS cohort (N = 1739) evaluated the association of LOAD variants with beta amyloid (Aβ) levels.ResultsWe identified several single nucleotide polymorphisms (SNPs) in tight linkage disequilibrium within the MTUS2 gene associated with LOAD (rs73154407, p = 7.6 × 10-9). Association of MTUS2 variants with LOAD was observed in the five independent studies and was significantly stronger within high levels of Aβ42/40 ratio compared to lower amyloid.DiscussionMTUS2 encodes a microtubule associated protein implicated in the development and function of the nervous system, making it a plausible candidate to investigate LOAD biology.HighlightsLong-Life Family Study (LLFS) families may harbor late onset Alzheimer's dementia (LOAD) variants. LLFS whole genome sequence analysis identified MTUS2 gene variants associated with LOAD. The observed LLFS variants generalized to cohorts with wide range of LOAD risk. The association of MTUS2 with LOAD was stronger within high levels of beta amyloid. Our results provide evidence for MTUS2 gene as a novel LOAD candidate locus.

Hispanic/Latino children have the highest risk of acute lymphoblastic leukemia (ALL) in the US compared to other racial/ethnic groups, yet the basis of this remains incompletely understood. Through genetic fine-mapping analyses, we identified a new independent childhood ALL risk signal near IKZF1 in self-reported Hispanic/Latino individuals, but not in non-Hispanic White individuals, with an effect size of ∼1.44 (95% confidence interval = 1.33-1.55) and a risk allele frequency of ∼18% in Hispanic/Latino populations and

We previously demonstrated that a genetic single-nucleotide polymorphism (SNP, rs2304297) in the 3 untranslated region (UTR) of the human CHRNA6 gene has sex- and genotype-dependent effects on nicotine-induced locomotion, anxiety, and nicotine + cue-induced reinstatement in adolescent rats. This study aims to investigate how the CHRNA6 3-UTR SNP influences dopaminergic and noradrenergic tissue levels in brain reward regions during baseline and after the reinstatement of drug-seeking behavior. Naïve adolescent and adult rats, along with those undergoing nicotine + cue reinstatement and carrying the CHRNA6 3-UTR SNP, were assessed for dopamine (DA), norepinephrine (NE), and metabolites in reward pathway regions. The results reveal age-, sex-, and genotype-dependent baseline DA, NE, and DA turnover levels. Post-reinstatement, male α6GG rats show suppressed DA levels in the Nucleus Accumbens (NAc) Shell compared to the baseline, while nicotine+ cue-induced reinstatement behavior correlates with neurotransmitter levels in specific brain regions. This study emphasizes the role of CHRNA6 3-UTR SNP in the developmental maturation of the dopaminergic and noradrenergic system in the adolescent rat brain, with tissue levels acting as predictors of nicotine + cue-induced reinstatement.

Genetic diversity is critical to crop breeding and improvement, and dissection of the genomic variation underlying agronomic traits can both assist breeding and give insight into basic biological mechanisms. Although recent genome analyses in plants reveal many structural variants (SVs), most current studies of crop genetic variation are dominated by single-nucleotide polymorphisms (SNPs). The extent of the impact of SVs on global trait variation, as well as their utility in genome-wide selection, is not yet understood. In this study, we built an SV data set based on whole-genome resequencing of diverse sorghum lines (n = 363), validated the correlation of photoperiod sensitivity and variety type, and identified SV hotspots underlying the divergent evolution of cellulosic and sweet sorghum. In addition, we showed the complementary contribution of SVs for heritability of traits related to sorghum adaptation. Importantly, inclusion of SV polymorphisms in association studies revealed genotype-phenotype associations not observed with SNPs alone. Three-way genome-wide association studies (GWAS) based on whole-genome SNP, SV, and integrated SNP + SV data sets showed substantial associations between SVs and sorghum traits. The addition of SVs to GWAS substantially increased heritability estimates for some traits, indicating their important contribution to functional allelic variation at the genome level. Our discovery of the widespread impacts of SVs on heritable gene expression variation could render a plausible mechanism for their disproportionate impact on phenotypic variation. This study expands our knowledge of SVs and emphasizes the extensive impacts of SVs on sorghum.

Regulation of transcription and translation are mechanisms through which genetic variants affect complex traits. Expression quantitative trait locus (eQTL) studies have been more successful at identifying cis-eQTL (within 1 Mb of the transcription start site) than trans-eQTL. Here, we tested the cis component of gene expression for association with observed plasma protein levels to identify cis- and trans-acting genes that regulate protein levels. We used transcriptome prediction models from 49 Genotype-Tissue Expression (GTEx) Project tissues to predict the cis component of gene expression and tested the predicted expression of every gene in every tissue for association with the observed abundance of 3,622 plasma proteins measured in 3,301 individuals from the INTERVAL study. We tested significant results for replication in 971 individuals from the Trans-omics for Precision Medicine (TOPMed) Multi-Ethnic Study of Atherosclerosis (MESA). We found 1,168 and 1,210 cis- and trans-acting associations that replicated in TOPMed (FDR

Heat stress results in significant economic losses to the poultry industry. Genetics plays an important role in chickens adapting to the warm environment. Physiological parameters such as hematochemical parameters change in response to heat stress in chickens. To explore the genetics of heat stress resilience in chickens, a genome-wide association study (GWAS) was conducted using Hy-Line Brown layer chicks subjected to either high ambient temperature or combined high temperature and Newcastle disease virus infection. Hematochemical parameters were measured during three treatment phases: acute heat stress, chronic heat stress, and chronic heat stress combined with NDV infection. Significant changes in blood parameters were recorded for 11 parameters (sodium (Na+, potassium (K+), ionized calcium (iCa2+), glucose (Glu), pH, carbon dioxide partial pressure (PCO2), oxygen partial pressure (PO2), total carbon dioxide (TCO2), bicarbonate (HCO3), base excess (BE), and oxygen saturation (sO2)) across the three treatments. The GWAS revealed 39 significant SNPs (p < 0.05) for seven parameters, located on Gallus gallus chromosomes (GGA) 1, 3, 4, 6, 11, and 12. The significant genomic regions were further investigated to examine if the genes within the regions were associated with the corresponding traits under heat stress. A candidate gene list including genes in the identified genomic regions that were also differentially expressed in chicken tissues under heat stress was generated. Understanding the correlation between genetic variants and resilience to heat stress is an important step towards improving heat tolerance in poultry.