Fast Principal-Component Analysis Reveals Convergent Evolution of ADH1B in Europe and East Asia

Analysis of Rare Coding Variants in 470,000 UK Biobank Participants Reveals Genetic Associations With Childhood Asthma Predisposition

Previous studies of genetic contributions to risk of childhood asthma have implicated common variants with small effect sizes. Some studies using exome sequence data have reported associations with rare coding variants having larger effects on risk, notably an analysis of 145,000 subjects which found association with loss of function (LOF) variants in FLG, the gene coding for filaggrin. Here, we report the results of an analysis of rare nonsynonymous and LOF variants, carried out on the full UK Biobank cohort of 470,000 exome-sequenced participants. The phenotype of childhood asthma was defined as reporting asthma with onset before 18. Regression analysis was applied to gene-wise tests for association of LOF and nonsynonymous variants. Forty-five tests using different pathogenicity predictors were applied to the first cohort of 200,000 participants. Subsequently, the 100 genes showing strongest evidence for association were analysed in the second cohort of 270,000 participants, using only the best-performing predictor for each gene. For FLG, separate analyses were carried out for participants with atopic dermatitis. Three genes achieved statistical significance after correction for testing these 100 genes: FLG, IL33 and PRKCQ. The effects on asthma risk and frequencies of variants in different functional categories were characterised for these genes. Damaging coding variants were associated with increased risk of asthma in FLG and IL33 but reduced risk in PRKCQ. FLG LOF variants were also associated with the risk of atopic dermatitis, and their effect on asthma risk was higher in people who reported a diagnosis of atopic dermatitis. Rare coding variants in a small number of genes have important effects on asthma risk. Further study of individual variant effects might elucidate mechanisms of pathogenesis. This research has been conducted using the UK Biobank Resource.

Putting Structural Variants Into Practice: The Role of Chromosomal Inversions in the Management of Marine Environments

Major threats to marine species and ecosystems include overfishing, invasive species, pollution and climate change. The changing climate not only imposes direct threats through the impacts of severe marine heatwaves, cyclones and ocean acidification but also complicates fisheries and invasive species management by driving species range shifts. The dynamic nature of these threats means that the future of our oceans will depend on the ability of species to adapt. This has led to calls for genetic interventions focussed on enhancing species' adaptive capacity, including translocations, restocking and selective breeding. Assessing the benefits and risks of such approaches requires an improved understanding of the genetic architecture of adaptive variation, not only in relation to climate-resilient phenotypes but also locally adapted populations and the fitness of hybrids. Large structural genetic variants such as chromosomal inversions play an important role in local adaptation by linking multiple adaptive loci. Consequently, inversions are likely to be particularly important when managing for adaptive capacity. However, under some circumstances, they also accumulate deleterious mutations, potentially increasing the risk of inbreeding depression. Genetic management that takes account of these dual roles on fitness is likely to be more effective at ensuring population persistence. We summarise evolutionary factors influencing adaptive and deleterious variation of inversions, review inversions found in marine taxa, and provide a framework to predict the consequences of ignoring inversions in key management scenarios. We conclude by describing practical methods to bridge the gap between evolutionary theory and practical application of inversions in conservation.

Examining the association between fetal HLA-C, maternal KIR haplotypes and birth weight

Human birth weight is under stabilizing selection, seeking balance between extremes of high and low, thereby reducing fetal and maternal perinatal mortality risk. Certain combinations of maternal killer immunoglobulin-like receptor (KIR) and paternally derived fetal human leuokocyte antigen-C (HLA-C) alleles were previously associated with higher risk of high and low birth weight in a study with limited sample size (n=1,316). Using recently developed methods to impute HLA and KIR haplotypes using single nucleotide polymorphism (SNP) genotype data, we tested associations of fetal HLA and maternal KIR genotypes with offspring birth weight in a large sample. We imputed KIR haplotypes using the KIR*IMP imputation software in 10,602 mother-offspring pairs of European descent from singleton pregnancies from five studies. Using mixed linear regression models to account for mothers with multiple children, we tested associations between maternal KIR A vs B haplotypes (AA, AB/BA, BB genotypes) as well as copy number of activating receptor gene KIR2DS1 (0, 1, 2 copies of the gene) in the presence of fetal HLA C1/C2 alleles, and offspring birth weight. Associations were analyzed in each cohort before performing a meta-analysis to estimate the interaction effects between maternal KIR and fetal HLA-C2 on birth weight across the entire sample. The KIR haplotypes achieved imputation accuracy estimated at >95% in most of the cohorts. No interaction effects were observed between either the maternal A vs. B haplotype or the maternal KIR2DS1 locus and fetal HLA-C. When specifically trying to replicate the previously associated combination of maternal KIR2DS1 and paternally inherited fetal HLA-C2, there was a negligible change in offspring birth weight for each additional KIR2DS1 allele and HLA-C2 of paternal origin (7g lower birth weight per allele [95% CI: -54, 40], P = 0.78). We found little evidence of association between birth weight and maternal KIR haplotypes or fetal HLA-C2 and were unable to replicate previously reported findings. Our observations reinforce the importance of replication and the use of large sample sizes in the validation of genetic associations.

On the origin of an insular hybrid butterfly lineage

A new species can form through hybridization between species. Hybrid speciation in animals has been intensely debated, partly because hard evidence for the process has been difficult to obtain. Here, we report the discovery of a European hybrid butterfly lineage, a finding that can be considered surprising given the intense and long-term study of European butterflies. The lineage we describe is mainly inhabiting an island in the Baltic Sea and was previously designated as a subspecies (horkei) of one of the parental species (Aricia artaxerxes). By analyzing whole-genome resequencing data and developing a novel cluster analysis based on historical recombination events (Fisher junctions), we determine that horkei originated by hybridization between the nonsister species A. artaxerxes and A. agestis. This hybridization event occurred approximately 54,000 years ago, predating the last glaciation of the current distribution range. Horkei must therefore have persisted long enough to be able to colonize its current range, despite that this area lies between the current distributions of the parental species. The hybrid origin, the maintenance of genomic integrity across times of dramatic climate change, and the expression of a combination of parental traits suggest that horkei could be in the process of hybrid speciation.

Parallel and convergent evolution in genes underlying seasonal migration

Seasonal migration has fascinated scientists and natural historians for centuries. While the genetic basis of migration has been widely studied across different taxa, there is little consensus regarding which genomic regions play a role in the ability to migrate and whether they are similar across species. Here, we examine the genetic basis of intraspecific variation within and between distinct migratory phenotypes in a songbird. We focus on the Common Yellowthroat (Geothlypis trichas) as a model system because the polyphyletic origin of eastern and western clades across North America provides a strong framework for understanding the extent to which there has been parallel or convergent evolution in the genes associated with migratory behavior. First, we investigate genome-wide population genetic structure in the Common Yellowthroat in 196 individuals collected from 22 locations across breeding range. Then, to identify candidate genes involved in seasonal migration, we identify signals of putative selection in replicate comparisons between resident and migratory phenotypes within and between eastern and western clades. Overall, we find wide-spread support for parallel evolution at the genic level, particularly in genes that mediate biological timekeeping. However, we find little evidence of parallelism at the individual SNP level, supporting the idea that there are multiple genetic pathways involved in the modulation of migration.

Leveraging large-scale biobank EHRs to enhance pharmacogenetics of cardiometabolic disease medications

Electronic health records (EHRs) coupled with large-scale biobanks offer great promises to unravel the genetic underpinnings of treatment efficacy. However, medication-induced biomarker trajectories stemming from such records remain poorly studied. Here, we extract clinical and medication prescription data from EHRs and conduct GWAS and rare variant burden tests in the UK Biobank (discovery) and the All of Us program (replication) on ten cardiometabolic drug response outcomes including lipid response to statins, HbA1c response to metformin and blood pressure response to antihypertensives (N = 932-28,880). Our discovery analyses in participants of European ancestry recover previously reported pharmacogenetic signals at genome-wide significance level (APOE, LPA and SLCO1B1) and a novel rare variant association in GIMAP5 with HbA1c response to metformin. Importantly, these associations are treatment-specific and not associated with biomarker progression in medication-naive individuals. We also found polygenic risk scores to predict drug response, though they explained less than 2% of the variance. In summary, we present an EHR-based framework to study the genetics of drug response and systematically investigated the common and rare pharmacogenetic contribution to cardiometabolic drug response phenotypes in 41,732 UK Biobank and 14,277 All of Us participants.

East and South Asian-Specific Blood Pressure Trajectories and Cardiovascular Disease

BACKGROUND

Cardiovascular disease (CVD) risk differs across Asian subgroups, possibly due to differences in hypertension burden. We characterized lifetime blood pressure (BP) trajectories for East and South Asian individuals and compared their associations with CVD risk.

METHODS

Among 148 872 UK Biobank participants with primary care utilization data, life course BP trajectories were fitted as a function of age by sex according to self-identified ethnicity. We determined associations of time-averaged young adulthood (18-39 years), middle age (40-64 years), and later life (≥65 years) systolic BP (SBP) and diastolic BP with incident atherosclerotic CVD risk.

RESULTS

The predicted SBP/diastolic BP (95% CI) at age 30 years was 108 (103-114)/68 (65-71) mm Hg for East Asian and 114 (110-118)/72 (71-73) mm Hg for South Asian individuals. By age 40, South Asian individuals were projected to reach an SBP of 130.0 mm Hg, whereas East Asian individuals reached the equivalent SBP by age 49 years. Among South Asian individuals, each SD increase in young adulthood SBP was associated with a higher atherosclerotic CVD risk with an odds ratio (95% CI) of 1.41 (1.12-1.75), but not among East Asians (Pinteraction=0.01). Midlife SBP was associated with peripheral artery disease among South Asian individuals (odds ratio, 2.08 [95% CI, 1.51-2.88]) and with ischemic stroke among East Asian individuals (odds ratio, 3.84 [95% CI, 1.08-5.07]). Later-life SBP was associated with myocardial infarction risk by 1.52 (1.15-1.92)-fold among South Asians and ischemic stroke by 2.50 (1.06-3.80)-fold among East Asian individuals.

CONCLUSIONS

East and South Asian individuals exhibit distinct BP trajectories that age-differentially associate with incident CVD. Disaggregating Asian subgroups may inform tailored hypertension screening and management.

Neuropsychiatric polygenic scores are weak predictors of professional categories

Polygenic scores (PGS) enable the exploration of pleiotropic effects and genomic dissection of complex traits. Here, in 421,889 individuals with European ancestry from the Million Veteran Program and UK Biobank, we examine how PGS of 17 neuropsychiatric traits are related to membership in 22 broad professional categories. Overall, we find statistically significant but weak (the highest odds ratio is 1.1 per PGS standard deviation) associations between most professional categories and genetic predisposition for at least one neuropsychiatric trait. Secondary analyses in UK Biobank revealed independence of these associations from observed fluid intelligence and sex-specific effects. By leveraging aggregate population trends, we identified patterns in the public interest, such as the mediating effect of education attainment on the association of attention-deficit/hyperactivity disorder PGS with multiple professional categories. However, at the individual level, PGS explained less than 0.5% of the variance of professional membership, and almost none after we adjusted for education and socio-economic status.

Sequence-based GWAS in 180,000 German Holstein cattle reveals new candidate variants for milk production traits

BACKGROUND

Milk production traits are complex and influenced by many genetic and environmental factors. Although extensive research has been performed for these traits, with many associations unveiled thus far, due to their crucial economic importance, complex genetic architecture, and the fact that causal variants in cattle are still scarce, there is a need for a better understanding of their genetic background. In this study, we aimed to identify new candidate loci associated with milk production traits in German Holstein cattle, the most important dairy breed in Germany and worldwide. For that purpose, 180,217 cattle were imputed to the sequence level and large-scale genome-wide association study (GWAS) followed by fine-mapping and evolutionary and functional annotation were carried out to identify and prioritize new association signals.

RESULTS

Using the imputed sequence data of a large cattle dataset, we identified 50,876 significant variants, confirming many known and identifying previously unreported candidate variants for milk (MY), fat (FY), and protein yield (PY). Genome-wide significant signals were fine-mapped with the Bayesian approach that determines the credible variant sets and generates the probability of causality for each signal. The variants with the highest probabilities of being causal were further classified using external information about the function and evolution, making the prioritization for subsequent validation experiments easier. The top potential causal variants determined with fine-mapping explained a large percentage of genetic variance compared to random ones; 178 variants explained 11.5%, 104 explained 7.7%, and 68 variants explained 3.9% of the variance for MY, FY, and PY, respectively, demonstrating the potential for causality.

CONCLUSIONS

Our findings proved the power of large samples and sequence-based GWAS in detecting new association signals. In order to fully exploit the power of GWAS, one should aim at very large samples combined with whole-genome sequence data. These can also come with both computational and time burdens, as presented in our study. Although milk production traits in cattle are comprehensively investigated, the genetic background of these traits is still not fully understood, with the potential for many new associations to be revealed, as shown. With constantly growing sample sizes, we expect more insights into the genetic architecture of milk production traits in the future.

Investigating the Contribution of Coding Variants in Alcohol Use Disorder Using Whole-Exome Sequencing Across Ancestries

BACKGROUND

Alcohol use disorder (AUD) is a leading cause of death and disability worldwide. There has been substantial progress in identifying genetic variants that underlie AUD. However, whole-exome sequencing studies of AUD have been hampered by the lack of available samples.

METHODS

We analyzed whole-exome sequencing data of 4530 samples from the Yale-Penn cohort and 469,835 samples from the UK Biobank, which represent an unprecedented resource for exploring the contribution of coding variants in AUD. After quality control, 1750 African-ancestry (1142 cases) and 2039 European-ancestry (1420 cases) samples from the Yale-Penn and 6142 African-ancestry (130 cases), 415,617 European-ancestry (12,861‬ cases), and 4607 South Asian (130 cases) samples from the UK Biobank cohorts were included in the analyses.

RESULTS

We confirmed the well-known functional variant rs1229984 in ADH1B (p = 4.88 × 10-31) and several other variants in ADH1C. Gene-based collapsing tests that considered the high allelic heterogeneity revealed the previously unreported genes CNST (p = 1.19 × 10-6), attributable to rare variants with allele frequency < 0.001, and IFIT5 (p = 3.74 × 10-6), driven by the burden of both common and rare loss-of-function and missense variants.

CONCLUSIONS

This study extends our understanding of the genetic architecture of AUD by providing insights into the contribution of rare coding variants, separately and convergently with common variants in AUD.

A genealogy-based approach for revealing ancestry-specific structures in admixed populations

Elucidating ancestry-specific structures in admixed populations is crucial for comprehending population history and mitigating confounding effects in genome-wide association studies. Existing methods for elucidating the ancestry-specific structures generally rely on frequency-based estimates of genetic relationship matrix (GRM) among admixed individuals after masking segments from ancestry components not being targeted for investigation. However, these approaches disregard linkage information between markers, potentially limiting their resolution in revealing structure within an ancestry component. We introduce ancestry-specific expected GRM (as-eGRM), a novel framework for elucidating the relatedness within ancestry components between admixed individuals. The key design of as-eGRM consists of defining ancestry-specific pairwise relatedness between individuals based on genealogical trees encoded in the Ancestral Recombination Graph (ARG) and local ancestry calls and computing the expectation of the ancestry-specific relatedness across the genome. Comprehensive evaluations using both simulated stepping-stone models of population structure and empirical datasets based on three-way admixed Latino cohorts showed that analysis based on as-eGRM robustly outperforms existing methods in revealing the structure in admixed populations with diverse demographic histories. Taken together, as-eGRM has the promise to better reveal the fine-scale structure within an ancestry component of admixed individuals, which can help improve the robustness and interpretation of findings from association studies of disease or complex traits for these understudied populations.

Phenotypic and Genomic Signatures of Latitudinal Local Adaptation Along With Prevailing Ocean Current in a Coastal Goby

In the marine realm, unidirectional ocean currents often lead to high migration rates of marine organisms and, therefore, inhibit the formation of their latitudinal genetic structure. In contrast, cryptic latitudinal structures associated with local adaptation may frequently exist in widespread species generally exposed to a strong environmental heterogeneity. However, our understanding of the evolvability of locally adapted populations in open marine environments still needs to be completed. The coastal area along the Sea of Japan, where the Tsushima Warm Current flows from south to north in the Japanese Archipelago, provides a good model system for exploring this question. This study explored evidence for latitudinal local adaptation along with the prevailing ocean current in the ice goby Leucopsarion petersii at the phenotypic and genomic levels. Common garden experiments clearly showed genetically based clinal variation in growth rate, strongly suggesting local adaptation through conutergradient selection of this fitness-related trait. Analyses based on reduced-representation sequencing revealed a slight signal of genetic differentiation between the southern and northern populations, although continuous historical gene flow between them was supported by demographic modelling. Also, whole-genome resequencing showed their independent demographic history during the last glacial period. Thus, these results suggest that gene flow along with the prevailing ocean current is somewhat limited, and the populations are not completely panmictic. Furthermore, the selection scan based on low-coverage genome-wide sequencing detected putative genomic signatures of latitudinal adaptation of growth-related genes. Thus, our integrative study provided a novel example of marine local adaptation under a large ocean current.

Analysis of rare coding variants in 470,000 exome-sequenced subjects characterises contributions to risk of type 2 diabetes

AIMS

To follow up results from an earlier study using an extended sample of 470,000 exome-sequenced subjects to identify genes associated with type 2 diabetes (T2D) and to characterise the distribution of rare variants in these genes.

MATERIALS AND METHODS

Exome sequence data for 470,000 UK Biobank participants was analysed using a combined phenotype for T2D obtained from diagnostic and prescription data. Gene-wise weighted burden analysis of rare coding variants in the new cohort of 270,000 samples was carried out for the 32 genes previously significant with uncorrected p < 0.001 along with 7 other genes previously implicated in T2D. Follow-up studies of GCK, GIGYF1, HNF1A and HNF4A used the full sample of 470,000 to investigate the effects of different categories of variant.

RESULTS

No novel genes were identified as exome wide significant. Rare loss of function (LOF) variants in GCK exerted a very large effect on T2D risk but more common (though still very rare) nonsynonymous variants classified as probably damaging by PolyPhen on average approximately doubled risk. Rare variants in the other three genes also had large effects on risk.

CONCLUSIONS

In spite of the very large sample size, no novel genes are implicated. Coding variants with an identifiable effect are collectively too rare be generally useful for guiding treatment choices for most patients. The finding that some nonsynonymous variants in GCK affect T2D risk is novel but not unexpected and does not have obvious practical implications. This research has been conducted using the UK Biobank Resource.

Adjusting for principal components can induce collider bias in genome-wide association studies

Principal component analysis (PCA) is widely used to control for population structure in genome-wide association studies (GWAS). Top principal components (PCs) typically reflect population structure, but challenges arise in deciding how many PCs are needed and ensuring that PCs do not capture other artifacts such as regions with atypical linkage disequilibrium (LD). In response to the latter, many groups suggest performing LD pruning or excluding known high LD regions prior to PCA. However, these suggestions are not universally implemented and the implications for GWAS are not fully understood, especially in the context of admixed populations. In this paper, we investigate the impact of pre-processing and the number of PCs included in GWAS models in African American samples from the Women's Health Initiative SNP Health Association Resource and two Trans-Omics for Precision Medicine Whole Genome Sequencing Project contributing studies (Jackson Heart Study and Genetic Epidemiology of Chronic Obstructive Pulmonary Disease Study). In all three samples, we find the first PC is highly correlated with genome-wide ancestry whereas later PCs often capture local genomic features. The pattern of which, and how many, genetic variants are highly correlated with individual PCs differs from what has been observed in prior studies focused on European populations and leads to distinct downstream consequences: adjusting for such PCs yields biased effect size estimates and elevated rates of spurious associations due to the phenomenon of collider bias. Excluding high LD regions identified in previous studies does not resolve these issues. LD pruning proves more effective, but the optimal choice of thresholds varies across datasets. Altogether, our work highlights unique issues that arise when using PCA to control for ancestral heterogeneity in admixed populations and demonstrates the importance of careful pre-processing and diagnostics to ensure that PCs capturing multiple local genomic features are not included in GWAS models.

Scalable analysis of large multi-ancestry biobanks by leveraging sparse ancestry-adjusted sample-relatedness

Linear mixed-effects models (LMMs) and ridge regression are commonly applied in genetic association studies to control for population structure and sample-relatedness. To control for sample-relatedness, the existing methods use empirical genetic relatedness matrices (GRM) either explicitly or conceptually. This works well with mostly homogeneous populations, however, in multi-ancestry heterogeneous populations, GRMs are confounded with population structure which leads to inflated type I error rates, massively increased computation, and reduced power. Here, we propose FastSparseGRM, a scalable pipeline for multi-ancestry Genome-Wide Association studies (GWAS) and Whole Genome Sequencing (WGS) studies. It utilizes a block-diagonal sparse ancestry-adjusted (BDSA) GRM to model sample-relatedness, and ancestry PCs as fixed effects to control for population structure. It is ~ 2540/4100/54 times faster than BOLT-LMM/fast-GWA/REGENIE for fitting the null LMM on 50,000 heterogeneous subjects. Through numerical simulations and both single-variant GWAS and rare variant WGS analyses of five biomarkers (Triglycerides, HDL, LDL, BMI, Total Bilirubin) on the entire UK Biobank data, we demonstrate that our approach scales to nearly half-a-million subjects and provides accurate p-value calibration and improved power compared to the existing methods.

Hypometric genetics: Improved power in genetic discovery by incorporating quality control flags

Balancing the tradeoff between quantity and quality of phenotypic data is critical in omics studies. Measurements below the limit of quantification (BLQ) are often tagged in quality control fields, but these flags are currently underutilized in human genetics studies. Extreme phenotype sampling is advantageous for mapping rare variant effects. We hypothesize that genetic drivers, along with environmental and technical factors, contribute to the presence of BLQ flags. Here, we introduce "hypometric genetics" (hMG) analysis and uncover a genetic basis for BLQ flags, indicating an additional source of genetic signal for genetic discovery, especially from phenotypic extremes. Applying our hMG approach to n = 227,469 UK Biobank individuals with metabolomic profiles, we reveal more than 5% heritability for BLQ flags and report biologically relevant associations, for example, at APOC3, APOA5, and PDE3B loci. For common variants, polygenic scores trained only for BLQ flags predict the corresponding quantitative traits with 91% accuracy, validating the genetic basis. For rare coding variant associations, we find an asymmetric 65.4% higher enrichment of metabolite-lowering associations for BLQ flags, highlighting the impact of putative loss-of-function variants with large effects on phenotypic extremes. Joint analysis of binarized BLQ flags and the corresponding quantitative metabolite measurements improves power in Bayesian rare variant aggregation tests, resulting in an average of 181% more prioritized genes. Our approach is broadly applicable to omics profiling. Overall, our results underscore the benefit of integrating quality control flags and quantitative measurements and highlight the advantage of joint analysis of population-based samples and phenotypic extremes in human genetics studies.

Assessment of ability of AlphaMissense to identify variants affecting susceptibility to common disease

An important issue in the analysis of rare variant association studies is the ability to annotate nonsynonymous variants in terms of their likely importance as affecting protein function. To address this, AlphaMissense was recently released and was shown to have good performance using benchmarks based on variants causing severe disease and on functional assays. Here, we assess the performance of AlphaMissense across 18 genes which had previously demonstrated association between rare coding variants and hyperlipidaemia, hypertension or type 2 diabetes. The strength of evidence in favour of association, expressed as the signed log p value (SLP), was compared between AlphaMissense and 43 other annotation methods. The results demonstrated marked variability between genes regarding the extent to which nonsynonymous variants contributed to evidence for association and also between the performance of different methods of annotating the nonsynonymous variants. Although AlphaMissense produced the highest SLP on average across genes, it produced the maximum SLP for only 4 genes. For some genes, other methods produced a considerably higher SLP and there were examples of genes where AlphaMissense produced no evidence for association while another method performed well. The marked inconsistency across genes means that it is difficult to decide on an optimal method of analysis of sequence data. The fact that different methods perform well for different genes suggests that if one wished to use sequence data for individual risk prediction then gene-specific annotation methods should be used.

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.

Genome-Wide Association Analysis Identifies LILRB2 Gene for Pathological Myopia

Pathological myopia (PM) is one of the leading causes of blindness, especially in Asia. To identify the genetic risk factors of PM, a two-stage genome-wide association study (GWAS) and replication analysis in East Asian populations is conducted. The analysis identified LILRB2 in 19q13.42 as a new candidate locus for PM. The increased protein expression of LILRB2/Pirb (mouse orthologous protein) in PM patients and myopia mouse models is validated. It is further revealed that the increase in LILRB2/Pirb promoted fatty acid synthesis and lipid accumulation, leading to the destruction of choroidal function and the development of PM. This study revealed the association between LILRB2 and PM, uncovering the molecular mechanism of lipid metabolism disorders leading to the pathogenesis of PM due to LILRB2 upregulation.

Whole-exome sequencing study of opioid dependence offers novel insights into the contributions of exome variants

Opioid dependence (OD) is epidemic in the United States and it is associated with a variety of adverse health effects. Its estimated heritability is ∼50%, and recent genome-wide association studies have identified more than a dozen common risk variants. However, there are no published studies of rare OD risk variants. In this study, we analyzed whole-exome sequencing data from the Yale-Penn cohort, comprising 2,100 participants of European ancestry (EUR; 1,321 OD cases) and 1,790 of African ancestry (AFR; 864 cases). A novel low-frequency variant (rs746301110) in the RUVBL2 gene was identified in EUR ( p =6.59×10 -10 ). Suggestive associations ( p <1×10 -5 ) were observed in TMCO3 in EUR, in NEIL2 and CFAP44 in AFR, and in FAM210B in the cross-ancestry meta-analysis. Gene-based collapsing tests identified SLC22A10 , TMCO3 , FAM90A1 , DHX58 , CHRND , GLDN , PLAT , H1-4 , COL3A1 , GPHB5 and QPCTL as top genes ( p <1×10 -4 ) with most associations attributable to rare variants and driven by the burden of predicted loss-of-function and missense variants. This study begins to fill the gap in our understanding of the genetic architecture of OD, providing insights into the contribution of rare coding variants and potential targets for future functional studies and drug development.

Sex chromosome turnover in hybridizing stickleback lineages

Recent discoveries of sex chromosome diversity across the tree of life have challenged the canonical model of conserved sex chromosome evolution and evoked new theories on labile sex chromosomes that maintain less differentiation and undergo frequent turnover. However, theories of labile sex chromosome evolution lack direct empirical support due to the paucity of case studies demonstrating ongoing sex chromosome turnover in nature. Two divergent lineages (viz. WL & EL) of nine-spined sticklebacks (Pungitius pungitius) with different sex chromosomes (linkage group [LG] 12 in the EL, unknown in the WL) hybridize in a natural secondary contact zone in the Baltic Sea, providing an opportunity to study ongoing turnover between coexisting sex chromosomes. In this study, we first identify an 80 kbp genomic region on LG3 as the sex-determining region (SDR) using whole-genome resequencing data of family crosses of a WL population. We then verify this region as the SDR in most other WL populations and demonstrate a potentially ongoing sex chromosome turnover in admixed marine populations where the evolutionarily younger and homomorphic LG3 sex chromosome replaces the older and heteromorphic LG12 sex chromosome. The results provide a rare glimpse of sex chromosome turnover in the wild and indicate the possible existence of additional yet undiscovered sex chromosome diversity in Pungitius sticklebacks.

Recurrent hybridization and gene flow shaped Norway and Siberian spruce evolutionary history over multiple glacial cycles

Most tree species underwent cycles of contraction and expansion during the Quaternary. These cycles led to an ancient and complex genetic structure that has since been affected by extensive gene flow and by strong local adaptation. The extent to which hybridization played a role in this multi-layered genetic structure is important to be investigated. To study the effect of hybridization on the joint population genetic structure of two dominant species of the Eurasian boreal forest, Picea abies and P. obovata, we used targeted resequencing and obtained around 480 K nuclear SNPs and 87 chloroplast SNPs in 542 individuals sampled across most of their distribution ranges. Despite extensive gene flow and a clear pattern of Isolation-by-Distance, distinct genetic clusters emerged, indicating the presence of barriers and corridors to migration. Two cryptic refugia located in the large hybrid zone between the two species played a critical role in shaping their current distributions. The two species repeatedly hybridized during the Pleistocene and the direction of introgression depended on latitude. Our study suggests that hybridization helped both species to overcome main shifts in their distribution ranges during glacial cycles and highlights the importance of considering whole species complex instead of separate entities to retrieve complex demographic histories.

Systematic rare variant analyses identify RAB32 as a susceptibility gene for familial Parkinson's disease

Despite substantial progress, causal variants are identified only for a minority of familial Parkinson's disease (PD) cases, leaving high-risk pathogenic variants unidentified1,2. To identify such variants, we uniformly processed exome sequencing data of 2,184 index familial PD cases and 69,775 controls. Exome-wide analyses converged on RAB32 as a novel PD gene identifying c.213C > G/p.S71R as a high-risk variant presenting in ~0.7% of familial PD cases while observed in only 0.004% of controls (odds ratio of 65.5). This variant was confirmed in all cases via Sanger sequencing and segregated with PD in three families. RAB32 encodes a small GTPase known to interact with LRRK2 (refs. 3,4). Functional analyses showed that RAB32 S71R increases LRRK2 kinase activity, as indicated by increased autophosphorylation of LRRK2 S1292. Here our results implicate mutant RAB32 in a key pathological mechanism in PD-LRRK2 kinase activity5-7-and thus provide novel insights into the mechanistic connections between RAB family biology, LRRK2 and PD risk.

Microglial function interacts with the environment to affect sex-specific depression risk

There is a two-fold higher incidence of depression in females compared to men with recent studies suggesting a role for microglia in conferring this sex-dependent depression risk. In this study we investigated the nature of this relation. Using GWAS enrichment, gene-set enrichment analysis and Mendelian randomization, we found minimal evidence for a direct relation between genes functionally related to microglia and sex-dependent genetic risk for depression. We then used expression quantitative trait loci and single nucleus RNA-sequencing resources to generate polygenic scores (PGS) representative of individual variation in microglial function in the adult (UK Biobank; N = 54753-72682) and fetal (ALSPAC; N = 1452) periods. The adult microglial PGS moderated the association between BMI (UK Biobank; beta = 0.001, 95 %CI 0.0009 to 0.003, P = 7.74E-6) and financial insecurity (UK Biobank; beta = 0.001, 95 %CI 0.005 to 0.015, P = 2E-4) with depressive symptoms in females. The fetal microglia PGS moderated the association between maternal prenatal depressive symptoms and offspring depressive symptoms at 24 years in females (ALSPAC; beta = 0.04, 95 %CI 0.004 to 0.07, P = 0.03). We found no evidence for an interaction between the microglial PGS and depression risk factors in males. Our results illustrate a role for microglial function in the conferral of sex-dependent depression risk following exposure to a depression risk factor.

Weighted burden analysis of rare coding variants in 470,000 exome-sequenced UK Biobank participants characterises effects on hyperlipidaemia risk

A previous study of 200,000 exome-sequenced UK Biobank participants investigating the association between rare coding variants and hyperlipidaemia had implicated four genes, LDLR, PCSK9, APOC3 and IFITM5, at exome-wide significance. In addition, a further 43 protein-coding genes were significant with an uncorrected p value of <0.001. Exome sequence data has become available for a further 270,000 participants and weighted burden analysis to test for association with hyperlipidaemia was carried out in this sample for the 47 genes highlighted by the previous study. There was no evidence to implicate IFITM5 but LDLR, PCSK9, APOC3, ANGPTL3, ABCG5 and NPC1L1 were all statistically significant after correction for multiple testing. These six genes were also all exome-wide significant in the combined sample of 470,000 participants. Variants impairing function of LDLR and ABCG5 were associated with increased risk whereas variants in the other genes were protective. Variant categories associated with large effect sizes are cumulatively very rare and the main benefit of this kind of study seems to be to throw light on the molecular mechanisms impacting hyperlipidaemia risk, hopefully supporting attempts to develop improved therapies.

Combining Transdiagnostic and Disorder-Level GWAS Enhances Precision of Psychiatric Genetic Risk Profiles in a Multi-Ancestry Sample

The etiology of substance use disorders (SUDs) and psychiatric disorders reflects a combination of both transdiagnostic (i.e., common) and disorder-level (i.e., independent) genetic risk factors. We applied genomic structural equation modeling to examine these genetic factors across SUDs, psychotic, mood, and anxiety disorders using genome-wide association studies (GWAS) of European- (EUR) and African-ancestry (AFR) individuals. In EUR individuals, transdiagnostic genetic factors represented SUDs (143 lead single nucleotide polymorphisms [SNPs]), psychotic (162 lead SNPs), and mood/anxiety disorders (112 lead SNPs). We identified two novel SNPs for mood/anxiety disorders that have probable regulatory roles on FOXP1, NECTIN3, and BTLA genes. In AFR individuals, genetic factors represented SUDs (1 lead SNP) and psychiatric disorders (no significant SNPs). The SUD factor lead SNP, although previously significant in EUR- and cross-ancestry GWAS, is a novel finding in AFR individuals. Shared genetic variance accounted for overlap between SUDs and their psychiatric comorbidities, with second-order GWAS identifying up to 12 SNPs not significantly associated with either first-order factor in EUR individuals. Finally, common and independent genetic effects showed different associations with psychiatric, sociodemographic, and medical phenotypes. For example, the independent components of schizophrenia and bipolar disorder had distinct associations with affective and risk-taking behaviors, and phenome-wide association studies identified medical conditions associated with tobacco use disorder independent of the broader SUDs factor. Thus, combining transdiagnostic and disorder-level genetic approaches can improve our understanding of co-occurring conditions and increase the specificity of genetic discovery, which is critical for psychiatric disorders that demonstrate considerable symptom and etiological overlap.

NRDE2 deficiency impairs homologous recombination repair and sensitizes hepatocellular carcinoma to PARP inhibitors

To identify novel susceptibility genes for hepatocellular carcinoma (HCC), we performed a rare-variant association study in Chinese populations consisting of 2,750 cases and 4,153 controls. We identified four HCC-associated genes, including NRDE2, RANBP17, RTEL1, and STEAP3. Using NRDE2 (index rs199890497 [p.N377I], p = 1.19 × 10-9) as an exemplary candidate, we demonstrated that it promotes homologous recombination (HR) repair and suppresses HCC. Mechanistically, NRDE2 binds to the subunits of casein kinase 2 (CK2) and facilitates the assembly and activity of the CK2 holoenzyme. This NRDE2-mediated enhancement of CK2 activity increases the phosphorylation of MDC1 and then facilitates the HR repair. These functions are eliminated almost completely by the NRDE2-p.N377I variant, which sensitizes the HCC cells to poly(ADP-ribose) polymerase (PARP) inhibitors, especially when combined with chemotherapy. Collectively, our findings highlight the relevance of the rare variants to genetic susceptibility to HCC, which would be helpful for the precise treatment of this malignancy.

Large-scale cross-ancestry genome-wide meta-analysis of serum urate

Hyperuricemia is an essential causal risk factor for gout and is associated with cardiometabolic diseases. Given the limited contribution of East Asian ancestry to genome-wide association studies of serum urate, the genetic architecture of serum urate requires exploration. A large-scale cross-ancestry genome-wide association meta-analysis of 1,029,323 individuals and ancestry-specific meta-analysis identifies a total of 351 loci, including 17 previously unreported loci. The genetic architecture of serum urate control is similar between European and East Asian populations. A transcriptome-wide association study, enrichment analysis, and colocalization analysis in relevant tissues identify candidate serum urate-associated genes, including CTBP1, SKIV2L, and WWP2. A phenome-wide association study using polygenic risk scores identifies serum urate-correlated diseases including heart failure and hypertension. Mendelian randomization and mediation analyses show that serum urate-associated genes might have a causal relationship with serum urate-correlated diseases via mediation effects. This study elucidates our understanding of the genetic architecture of serum urate control.

Olfactory genes affect major depression in highly educated, emotionally stable, lean women: a bridge between animal models and precision medicine

Most current approaches to establish subgroups of depressed patients for precision medicine aim to rely on biomarkers that require highly specialized assessment. Our present aim was to stratify participants of the UK Biobank cohort based on three readily measurable common independent risk factors, and to investigate depression genomics in each group to discover common and separate biological etiology. Two-step cluster analysis was run separately in males (n = 149,879) and females (n = 174,572), with neuroticism (a tendency to experience negative emotions), body fat percentage, and years spent in education as input variables. Genome-wide association analyses were implemented within each of the resulting clusters, for the lifetime occurrence of either a depressive episode or recurrent depressive disorder as the outcome. Variant-based, gene-based, gene set-based, and tissue-specific gene expression test were applied. Phenotypically distinct clusters with high genetic intercorrelations in depression genomics were found. A two-cluster solution was the best model in each sex with some differences including the less important role of neuroticism in males. In females, in case of a protective pattern of low neuroticism, low body fat percentage, and high level of education, depression was associated with pathways related to olfactory function. While also in females but in a risk pattern of high neuroticism, high body fat percentage, and less years spent in education, depression showed association with complement system genes. Our results, on one hand, indicate that alteration of olfactory pathways, that can be paralleled to the well-known rodent depression models of olfactory bulbectomy, might be a novel target towards precision psychiatry in females with less other risk factors for depression. On the other hand, our results in multi-risk females may provide a special case of immunometabolic depression.

Leveraging large-scale biobank EHRs to enhance pharmacogenetics of cardiometabolic disease medications

Electronic health records (EHRs) coupled with large-scale biobanks offer great promises to unravel the genetic underpinnings of treatment efficacy. However, medication-induced biomarker trajectories stemming from such records remain poorly studied. Here, we extract clinical and medication prescription data from EHRs and conduct GWAS and rare variant burden tests in the UK Biobank (discovery) and the All of Us program (replication) on ten cardiometabolic drug response outcomes including lipid response to statins, HbA1c response to metformin and blood pressure response to antihypertensives (N = 740-26,669). Our findings at genome-wide significance level recover previously reported pharmacogenetic signals and also include novel associations for lipid response to statins (N = 26,669) near LDLR and ZNF800. Importantly, these associations are treatment-specific and not associated with biomarker progression in medication-naive individuals. Furthermore, we demonstrate that individuals with higher genetically determined low-density and total cholesterol baseline levels experience increased absolute, albeit lower relative biomarker reduction following statin treatment. In summary, we systematically investigated the common and rare pharmacogenetic contribution to cardiometabolic drug response phenotypes in over 50,000 UK Biobank and All of Us participants with EHR and identified clinically relevant genetic predictors for improved personalized treatment strategies.

Adjusting for principal components can induce spurious associations in genome-wide association studies in admixed populations

Principal component analysis (PCA) is widely used to control for population structure in genome-wide association studies (GWAS). Top principal components (PCs) typically reflect population structure, but challenges arise in deciding how many PCs are needed and ensuring that PCs do not capture other artifacts such as regions with atypical linkage disequilibrium (LD). In response to the latter, many groups suggest performing LD pruning or excluding known high LD regions prior to PCA. However, these suggestions are not universally implemented and the implications for GWAS are not fully understood, especially in the context of admixed populations. In this paper, we investigate the impact of pre-processing and the number of PCs included in GWAS models in African American samples from the Women's Women's Health Initiative SNP Health Association Resource and two Trans-Omics for Precision Medicine Whole Genome Sequencing Project contributing studies (Jackson Heart Study and Genetic Epidemiology of Chronic Obstructive Pulmonary Disease Study). In all three samples, we find the first PC is highly correlated with genome-wide ancestry whereas later PCs often capture local genomic features. The pattern of which, and how many, genetic variants are highly correlated with individual PCs differs from what has been observed in prior studies focused on European populations and leads to distinct downstream consequences: adjusting for such PCs yields biased effect size estimates and elevated rates of spurious associations due to the phenomenon of collider bias. Excluding high LD regions identified in previous studies does not resolve these issues. LD pruning proves more effective, but the optimal choice of thresholds varies across datasets. Altogether, our work highlights unique issues that arise when using PCA to control for ancestral heterogeneity in admixed populations and demonstrates the importance of careful pre-processing and diagnostics to ensure that PCs capturing multiple local genomic features are not included in GWAS models.

Sex-dependent placental methylation quantitative trait loci provide insight into the prenatal origins of childhood onset traits and conditions

Molecular quantitative trait loci (QTLs) allow us to understand the biology captured in genome-wide association studies (GWASs). The placenta regulates fetal development and shows sex differences in DNA methylation. We therefore hypothesized that placental methylation QTL (mQTL) explain variation in genetic risk for childhood onset traits, and that effects differ by sex. We analyzed 411 term placentas from two studies and found 49,252 methylation (CpG) sites with mQTL and 2,489 CpG sites with sex-dependent mQTL. All mQTL were enriched in regions that typically affect gene expression in prenatal tissues. All mQTL were also enriched in GWAS results for growth- and immune-related traits, but male- and female-specific mQTL were more enriched than cross-sex mQTL. mQTL colocalized with trait loci at 777 CpG sites, with 216 (28%) specific to males or females. Overall, mQTL specific to male and female placenta capture otherwise overlooked variation in childhood traits.

Human adaptations to diet: Biological and cultural coevolution

Modern humans evolved in Africa some 200,000 years ago, and since then, human populations have expanded and diversified to occupy a broad range of habitats and use different subsistence modes. This has resulted in different adaptations, such as differential responses to diseases and different abilities to digest or tolerate certain foods. The shift from a subsistence strategy based on hunting and gathering during the Palaeolithic to a lifestyle based on the consumption of domesticated animals and plants in the Neolithic can be considered one of the most important dietary transitions of Homo sapiens. In this text, we review four examples of gene-culture coevolution: (i) the persistence of the enzyme lactase after weaning, which allows the digestion of milk in adulthood, related to the emergence of dairy farming during the Neolithic; (ii) the population differences in alcohol susceptibility, in particular the ethanol intolerance of Asian populations due to the increased accumulation of the toxic acetaldehyde, related to the spread of rice domestication; (iii) the maintenance of gluten intolerance (celiac disease) with the subsequent reduced fitness of its sufferers, related to the emergence of agriculture and (iv) the considerable variation in the biosynthetic pathway of long-chain polyunsaturated fatty acids in native populations with extreme diets.

Investigation of Recessive Effects of Coding Variants on Common Clinical Phenotypes in Exome-Sequenced UK Biobank Participants

INTRODUCTION

Previous studies have demonstrated effects of rare coding variants on common, clinically relevant phenotypes although the additive burden of these variants makes only a small contribution to overall trait variance. Although recessive effects of individual homozygous variants have been studied, little work has been done to elucidate the impact of rare coding variants occurring together as compound heterozygotes.

METHODS

In this study, attempts were made to identify pairs of variants likely to be occurring as compound heterozygotes using 200,000 exome-sequenced subjects from the UK Biobank. Pairs of variants, which were seen together in the same subject more often than would be expected by chance, were excluded as it was assumed that these might be present in the same haplotype. Attention was restricted to variants with minor allele frequency ≤0.05 and to those predicted to alter amino acid sequence or prevent normal gene expression. For each gene, compound heterozygotes were assigned scores based on the rarity and predicted functional consequences of the constituent variants and the scores were used in a logistic regression analysis to test for association with hypertension, hyperlipidaemia, and type 2 diabetes.

RESULTS

No statistically significant associations were observed and the results conformed to the distribution, which would be expected under the null hypothesis. The average number of apparently compound heterozygous subjects for each gene was only 282.2.

CONCLUSION

It seems difficult to detect an effect of compound heterozygotes on the risk of these phenotypes. Even if recessive effects from compound heterozygotes do occur, they would only affect a small number of people and overall would not make a substantial contribution to phenotypic variance. This research has been conducted using the UK Biobank Resource.

The Impact of Patterns in Linkage Disequilibrium and Sequencing Quality on the Imprint of Balancing Selection

Regions under balancing selection are characterized by dense polymorphisms and multiple persistent haplotypes, along with other sequence complexities. Successful identification of these patterns depends on both the statistical approach and the quality of sequencing. To address this challenge, at first, a new statistical method called LD-ABF was developed, employing efficient Bayesian techniques to effectively test for balancing selection. LD-ABF demonstrated the most robust detection of selection in a variety of simulation scenarios, compared against a range of existing tests/tools (Tajima's D, HKA, Dng, BetaScan, and BalLerMix). Furthermore, the impact of the quality of sequencing on detection of balancing selection was explored, as well, using: (i) SNP genotyping and exome data, (ii) targeted high-resolution HLA genotyping (IHIW), and (iii) whole-genome long-read sequencing data (Pangenome). In the analysis of SNP genotyping and exome data, we identified known targets and 38 new selection signatures in genes not previously linked to balancing selection. To further investigate the impact of sequencing quality on detection of balancing selection, a detailed investigation of the MHC was performed with high-resolution HLA typing data. Higher quality sequencing revealed the HLA-DQ genes consistently demonstrated strong selection signatures otherwise not observed from the sparser SNP array and exome data. The HLA-DQ selection signature was also replicated in the Pangenome samples using considerably less samples but, with high-quality long-read sequence data. The improved statistical method, coupled with higher quality sequencing, leads to more consistent identification of selection and enhanced localization of variants under selection, particularly in complex regions.

Pleistocene diversification of unifoliolate-leaved Lupinus (Leguminosae: Papilionoideae) in Florida

The importance and prevalence of recent ice-age and post-glacial speciation and species diversification during the Pleistocene across many organismal groups and physiographic settings are well established. However, the extent to which Pleistocene diversification can be attributed to climatic oscillations and their effects on distribution ranges and population structure remains debatable. In this study, we use morphologic, geographic and genetic (RADseq) data to document Pleistocene speciation and intra-specific diversification of the unifoliolate-leaved clade of Florida Lupinus, a small group of species largely restricted to inland and coastal sand ridges across the Florida peninsula and panhandle. Phylogenetic and demographic analyses alongside morphological and geographic evidence suggest that recent speciation and intra-specific divergence within this clade were driven by a combination of non-adaptive allopatric divergence caused by edaphic niche conservatism and opportunities presented by the emergence of new post-glacial sand ridge habitats. These results highlight the central importance of even modest geographic isolation and short periods of allopatric divergence following range expansion in the emergence of new taxa and add to the growing evidence that Pleistocene climatic oscillations may contribute to rapid diversification in a myriad of physiographic settings. Furthermore, our results shed new light on long-standing taxonomic debate surrounding the number of species in the Florida unifoliate Lupinus clade providing support for recognition of five species and a set of intra-specific variants. The important conservation implications for the narrowly restricted, highly endangered species Lupinus aridorum, which we show to be genetically distinct from its sister species Lupinus westianus, are discussed.

A multi-cohort genome-wide association study in African ancestry individuals reveals risk loci for primary open-angle glaucoma

Primary open-angle glaucoma (POAG), the leading cause of irreversible blindness worldwide, disproportionately affects individuals of African ancestry. We conducted a genome-wide association study (GWAS) for POAG in 11,275 individuals of African ancestry (6,003 cases; 5,272 controls). We detected 46 risk loci associated with POAG at genome-wide significance. Replication and post-GWAS analyses, including functionally informed fine-mapping, multiple trait co-localization, and in silico validation, implicated two previously undescribed variants (rs1666698 mapping to DBF4P2; rs34957764 mapping to ROCK1P1) and one previously associated variant (rs11824032 mapping to ARHGEF12) as likely causal. For individuals of African ancestry, a polygenic risk score (PRS) for POAG from our mega-analysis (African ancestry individuals) outperformed a PRS from summary statistics of a much larger GWAS derived from European ancestry individuals. This study quantifies the genetic architecture similarities and differences between African and non-African ancestry populations for this blinding disease.

A Fast, Reproducible, High-throughput Variant Calling Workflow for Population Genomics

The increasing availability of genomic resequencing data sets and high-quality reference genomes across the tree of life present exciting opportunities for comparative population genomic studies. However, substantial challenges prevent the simple reuse of data across different studies and species, arising from variability in variant calling pipelines, data quality, and the need for computationally intensive reanalysis. Here, we present snpArcher, a flexible and highly efficient workflow designed for the analysis of genomic resequencing data in nonmodel organisms. snpArcher provides a standardized variant calling pipeline and includes modules for variant quality control, data visualization, variant filtering, and other downstream analyses. Implemented in Snakemake, snpArcher is user-friendly, reproducible, and designed to be compatible with high-performance computing clusters and cloud environments. To demonstrate the flexibility of this pipeline, we applied snpArcher to 26 public resequencing data sets from nonmammalian vertebrates. These variant data sets are hosted publicly to enable future comparative population genomic analyses. With its extensibility and the availability of public data sets, snpArcher will contribute to a broader understanding of genetic variation across species by facilitating the rapid use and reuse of large genomic data sets.

The correlates of neonatal complement component 3 and 4 protein concentrations with a focus on psychiatric and autoimmune disorders

Complement components have been linked to schizophrenia and autoimmune disorders. We examined the association between neonatal circulating C3 and C4 protein concentrations in 68,768 neonates and the risk of six mental disorders. We completed genome-wide association studies (GWASs) for C3 and C4 and applied the summary statistics in Mendelian randomization and phenome-wide association studies related to mental and autoimmune disorders. The GWASs for C3 and C4 protein concentrations identified 15 and 36 independent loci, respectively. We found no associations between neonatal C3 and C4 concentrations and mental disorders in the total sample (both sexes combined); however, post-hoc analyses found that a higher C3 concentration was associated with a reduced risk of schizophrenia in females. Mendelian randomization based on C4 summary statistics found an altered risk of five types of autoimmune disorders. Our study adds to our understanding of the associations between C3 and C4 concentrations and subsequent mental and autoimmune disorders.

Positive personality traits moderate persistent high alcohol consumption, determined by polygenic risk in U.S. military veterans: results from a 10-year, population-based, observational cohort study

BACKGROUND

Understanding the interplay between psychosocial factors and polygenic risk scores (PRS) may help elucidate the biopsychosocial etiology of high alcohol consumption (HAC). This study examined the psychosocial moderators of HAC, determined by polygenic risk in a 10-year longitudinal study of US military veterans. We hypothesized that positive psychosocial traits (e.g. social support, personality traits, optimism, gratitude) may buffer risk of HAC in veterans with greater polygenic liability for alcohol consumption (AC).

METHODS

Data were analyzed from 1323 European-American US veterans who participated in the National Health and Resilience in Veterans Study, a 10-year, nationally representative longitudinal study of US military veterans. PRS reflecting genome-wide risk for AC (AUDIT-C) was derived from a Million Veteran Program genome-wide association study (N = 200 680).

RESULTS

Among the total sample, 328 (weighted 24.8%) had persistent HAC, 131 (weighted 9.9%) had new-onset HAC, 44 (weighted 3.3%) had remitted HAC, and 820 (weighted 62.0%) had no/low AC over the 10-year study period. AUDIT-C PRS was positively associated with persistent HAC relative to no/low AC [relative risk ratio (RRR) = 1.43, 95% confidence interval (CI) = 1.23-1.67] and remitted HAC (RRR = 1.63, 95% CI = 1.07-2.50). Among veterans with higher AUDIT-C PRS, greater baseline levels of agreeableness and greater dispositional gratitude were inversely associated with persistent HAC.

CONCLUSIONS

AUDIT-C PRS was prospectively associated with persistent HAC over a 10-year period, and agreeableness and dispositional gratitude moderated this association. Clinical interventions designed to target these modifiable psychological traits may help mitigate risk of persistent HAC in veterans with greater polygenic liability for persistent HAC.

FiMAP: A fast identity-by-descent mapping test for biobank-scale cohorts

Although genome-wide association studies (GWAS) have identified tens of thousands of genetic loci, the genetic architecture is still not fully understood for many complex traits. Most GWAS and sequencing association studies have focused on single nucleotide polymorphisms or copy number variations, including common and rare genetic variants. However, phased haplotype information is often ignored in GWAS or variant set tests for rare variants. Here we leverage the identity-by-descent (IBD) segments inferred from a random projection-based IBD detection algorithm in the mapping of genetic associations with complex traits, to develop a computationally efficient statistical test for IBD mapping in biobank-scale cohorts. We used sparse linear algebra and random matrix algorithms to speed up the computation, and a genome-wide IBD mapping scan of more than 400,000 samples finished within a few hours. Simulation studies showed that our new method had well-controlled type I error rates under the null hypothesis of no genetic association in large biobank-scale cohorts, and outperformed traditional GWAS single-variant tests when the causal variants were untyped and rare, or in the presence of haplotype effects. We also applied our method to IBD mapping of six anthropometric traits using the UK Biobank data and identified a total of 3,442 associations, 2,131 (62%) of which remained significant after conditioning on suggestive tag variants in the ± 3 centimorgan flanking regions from GWAS.

Multi-ancestry study of the genetics of problematic alcohol use in over 1 million individuals

Problematic alcohol use (PAU), a trait that combines alcohol use disorder and alcohol-related problems assessed with a questionnaire, is a leading cause of death and morbidity worldwide. Here we conducted a large cross-ancestry meta-analysis of PAU in 1,079,947 individuals (European, N = 903,147; African, N = 122,571; Latin American, N = 38,962; East Asian, N = 13,551; and South Asian, N = 1,716 ancestries). We observed a high degree of cross-ancestral similarity in the genetic architecture of PAU and identified 110 independent risk variants in within- and cross-ancestry analyses. Cross-ancestry fine mapping improved the identification of likely causal variants. Prioritizing genes through gene expression and chromatin interaction in brain tissues identified multiple genes associated with PAU. We identified existing medications for potential pharmacological studies by a computational drug repurposing analysis. Cross-ancestry polygenic risk scores showed better performance of association in independent samples than single-ancestry polygenic risk scores. Genetic correlations between PAU and other traits were observed in multiple ancestries, with other substance use traits having the highest correlations. This study advances our knowledge of the genetic etiology of PAU, and these findings may bring possible clinical applicability of genetics insights-together with neuroscience, biology and data science-closer.

A Polygenic Risk Score for Predicting Racial and Genetic Susceptibility to Prurigo Nodularis

Prurigo nodularis (PN) is an understudied inflammatory skin disease characterized by pruritic, hyperkeratotic nodules. Identifying the genetic factors underlying PN could help to better understand its etiology and guide the development of therapies. In this study, we developed a polygenic risk score that predicts a diagnosis of PN (OR = 1.41, P = 1.6 × 10-5) in two independent and continentally distinct populations. We also performed GWASs, which uncovered genetic variants associated with PN, including one near PLCB4 (rs6039266: OR = 3.15, P = 4.8 × 10-8) and others near TXNRD1 (rs34217906: OR = 1.71, P = 6.4 × 10-7; rs7134193: OR = 1.57, P = 1.1 × 10-6). Finally, we discovered that Black patients have over a two-times greater genetic risk of developing PN (OR = 2.63, P = 7.8 × 10-4). Combining the polygenic risk score and self-reported race together was significantly predictive of PN (OR = 1.32, P = 4.7 × 10-3). Strikingly, this association was more significant with race than after adjusting for genetic ancestry. Because race is a sociocultural construct and not a genetically bound category, our findings suggest that genetics, environmental influence, and social determinants of health likely affect the development of PN and may contribute to clinically observed racial disparities.

Panmixia in the American eel extends to its tropical range of distribution: Biological implications and policymaking challenges

The American eel (Anguilla rostrata) has long been regarded as a panmictic fish and has been confirmed as such in the northern part of its range. In this paper, we tested for the first time whether panmixia extends to the tropical range of the species. To do so, we first assembled a reference genome (975 Mbp, 19 chromosomes) combining long (PacBio and Nanopore and short (Illumina paired-end) reads technologies to support both this study and future research. To test for population structure, we estimated genotype likelihoods from low-coverage whole-genome sequencing of 460 American eels, collected at 21 sampling sites (in seven geographic regions) ranging from Canada to Trinidad and Tobago. We estimated genetic distance between regions, performed ADMIXTURE-like clustering analysis and multivariate analysis, and found no evidence of population structure, thus confirming that panmixia extends to the tropical range of the species. In addition, two genomic regions with putative inversions were observed, both geographically widespread and present at similar frequencies in all regions. We discuss the implications of lack of genetic population structure for the species. Our results are key for the future genomic research in the American eel and the implementation of conservation measures throughout its geographic range. Additionally, our results can be applied to fisheries management and aquaculture of the species.

HLA allele-calling using multi-ancestry whole-exome sequencing from the UK Biobank identifies 129 novel associations in 11 autoimmune diseases

The human leukocyte antigen (HLA) region on chromosome 6 is strongly associated with many immune-mediated and infection-related diseases. Due to its highly polymorphic nature and complex linkage disequilibrium patterns, traditional genetic association studies of single nucleotide polymorphisms do not perform well in this region. Instead, the field has adopted the assessment of the association of HLA alleles (i.e., entire HLA gene haplotypes) with disease. Often based on genotyping arrays, these association studies impute HLA alleles, decreasing accuracy and thus statistical power for rare alleles and in non-European ancestries. Here, we use whole-exome sequencing (WES) from 454,824 UK Biobank (UKB) participants to directly call HLA alleles using the HLA-HD algorithm. We show this method is more accurate than imputing HLA alleles and harness the improved statistical power to identify 360 associations for 11 auto-immune phenotypes (at least 129 likely novel), leading to better insights into the specific coding polymorphisms that underlie these diseases. We show that HLA alleles with synonymous variants, often overlooked in HLA studies, can significantly influence these phenotypes. Lastly, we show that HLA sequencing may improve polygenic risk scores accuracy across ancestries. These findings allow better characterization of the role of the HLA region in human disease.

Power of inclusion: Enhancing polygenic prediction with admixed individuals

Admixed individuals offer unique opportunities for addressing limited transferability in polygenic scores (PGSs), given the substantial trans-ancestry genetic correlation in many complex traits. However, they are rarely considered in PGS training, given the challenges in representing ancestry-matched linkage-disequilibrium reference panels for admixed individuals. Here we present inclusive PGS (iPGS), which captures ancestry-shared genetic effects by finding the exact solution for penalized regression on individual-level data and is thus naturally applicable to admixed individuals. We validate our approach in a simulation study across 33 configurations with varying heritability, polygenicity, and ancestry composition in the training set. When iPGS is applied to n = 237,055 ancestry-diverse individuals in the UK Biobank, it shows the greatest improvements in Africans by 48.9% on average across 60 quantitative traits and up to 50-fold improvements for some traits (neutrophil count, R2 = 0.058) over the baseline model trained on the same number of European individuals. When we allowed iPGS to use n = 284,661 individuals, we observed an average improvement of 60.8% for African, 11.6% for South Asian, 7.3% for non-British White, 4.8% for White British, and 17.8% for the other individuals. We further developed iPGS+refit to jointly model the ancestry-shared and -dependent genetic effects when heterogeneous genetic associations were present. For neutrophil count, for example, iPGS+refit showed the highest predictive performance in the African group (R2 = 0.115), which exceeds the best predictive performance for the White British group (R2 = 0.090 in the iPGS model), even though only 1.49% of individuals used in the iPGS training are of African ancestry. Our results indicate the power of including diverse individuals for developing more equitable PGS models.

Genetic correlation for alcohol consumption between Europeans and East Asians

Genome-wide association studies (GWAS) have identified many genetic variants associated with alcohol consumption in Europeans and East Asians, as well as other populations. However, the genetic homogeneity and heterogeneity between these populations have not been thoroughly investigated, despite evidence of varying effect sizes of variants between ethnicities and the presence of population-specific strong signals of selection on loci associated with alcohol consumption. In order to better understand the relationship between Europeans and East Asians in the genetic architecture of alcohol consumption, we compared their heritability and evaluated their genetic correlation using GWAS results from UK Biobank (UKB) and Biobank Japan (BBJ). We found that these two populations have low genetic correlation due to the large difference on chromosome 12. After excluding this chromosome, the genetic correlation was moderately high ([Formula: see text] = 0.544, p = 1.12e-4) and 44.31% of the genome-wide causal variants were inferred to be shared between Europeans and East Asians. Given those observations, we conducted a meta-analysis on UKB and BBJ and identified new signals, including the CADM2 gene on chromosome 3, which has been associated with various behavioral and metabolic traits. Overall, our findings suggest that the genetic architecture of alcohol consumption is largely shared between Europeans and East Asians, but there are exceptions such as the enrichment of heritability on chromosome 12 in East Asians.

Uncovering the genetic architecture of parallel evolution

Identifying the genetic architecture underlying adaptive traits is exceptionally challenging in natural populations. This is because associations between traits not only mask the targets of selection but also create correlated patterns of genomic divergence that hinder our ability to isolate causal genetic effects. Here, we examine the repeated evolution of components of the auxin pathway that have contributed to the replicated loss of gravitropism (i.e. the ability of a plant to bend in response to gravity) in multiple populations of the Senecio lautus species complex in Australia. We use a powerful approach which combines parallel population genomics with association mapping in a Multiparent Advanced Generation Inter-Cross (MAGIC) population to break down genetic and trait correlations to reveal how adaptive traits evolve during replicated evolution. We sequenced auxin and shoot gravitropism-related gene regions in 80 individuals from six natural populations (three parallel divergence events) and 133 individuals from a MAGIC population derived from two of the recently diverged natural populations. We show that artificial tail selection on gravitropism in the MAGIC population recreates patterns of parallel divergence in the auxin pathway in the natural populations. We reveal a set of 55 auxin gene regions that have evolved repeatedly during the evolution of the species, of which 50 are directly associated with gravitropism divergence in the MAGIC population. Our work creates a strong link between patterns of genomic divergence and trait variation contributing to replicated evolution by natural selection, paving the way to understand the origin and maintenance of adaptations in natural populations.

Genetic, sociodemographic, lifestyle, and clinical risk factors of recurrent coronary artery disease events: a population-based cohort study

AIMS

Complications of coronary artery disease (CAD) represent the leading cause of death among adults globally. This study examined the associations and clinical utilities of genetic, sociodemographic, lifestyle, and clinical risk factors on CAD recurrence.

METHODS AND RESULTS

Data were from 7024 UK Biobank middle-aged adults with established CAD at enrolment. Cox proportional hazards regressions modelled associations of age at enrolment, age at first CAD diagnosis, sex, cigarette smoking, physical activity, diet, sleep, Townsend Deprivation Index, body mass index, blood pressure, blood lipids, glucose, lipoprotein(a), C reactive protein, estimated glomerular filtration rate (eGFR), statin prescription, and CAD polygenic risk score (PRS) with first post-enrolment CAD recurrence. Over a median [interquartile range] follow-up of 11.6 [7.2-12.7] years, 2003 (28.5%) recurrent CAD events occurred. The hazard ratio (95% confidence interval [CI]) for CAD recurrence was the most pronounced with current smoking (1.35, 1.13-1.61) and per standard deviation increase in age at first CAD (0.74, 0.67-0.82). Additionally, age at enrolment, CAD PRS, C-reactive protein, lipoprotein(a), glucose, low-density lipoprotein cholesterol, deprivation, sleep quality, eGFR, and high-density lipoprotein (HDL) cholesterol also significantly associated with recurrence risk. Based on C indices (95% CI), the strongest predictors were CAD PRS (0.58, 0.57-0.59), HDL cholesterol (0.57, 0.57-0.58), and age at initial CAD event (0.57, 0.56-0.57). In addition to traditional risk factors, a comprehensive model improved the C index from 0.644 (0.632-0.654) to 0.676 (0.667-0.686).

CONCLUSION

Sociodemographic, clinical, and laboratory factors are each associated with CAD recurrence with genetic risk, age at first CAD event, and HDL cholesterol concentration explaining the most.

Genetic modification of inflammation- and clonal hematopoiesis-associated cardiovascular risk

Clonal hematopoiesis of indeterminate potential (CHIP) is associated with an increased risk of cardiovascular diseases (CVDs), putatively via inflammasome activation. We pursued an inflammatory gene modifier scan for CHIP-associated CVD risk among 424,651 UK Biobank participants. We identified CHIP using whole-exome sequencing data of blood DNA and modeled as a composite, considering all driver genes together, as well as separately for common drivers (DNMT3A, TET2, ASXL1, and JAK2). We developed predicted gene expression scores for 26 inflammasome-related genes and assessed how they modify CHIP-associated CVD risk. We identified IL1RAP as a potential key molecule for CHIP-associated CVD risk across genes and increased AIM2 gene expression leading to heightened JAK2- and ASXL1-associated CVD risk. We show that CRISPR-induced Asxl1-mutated murine macrophages had a particularly heightened inflammatory response to AIM2 agonism, associated with an increased DNA damage response, as well as increased IL-10 secretion, mirroring a CVD-protective effect of IL10 expression in ASXL1 CHIP. Our study supports the role of inflammasomes in CHIP-associated CVD and provides evidence to support gene-specific strategies to address CHIP-associated CVD risk.