A cross-population atlas of genetic associations for 220 human phenotypes. - Sakaue, Saori; Kanai, Masahiro; Tanigawa, Yosuke; Karjalainen, Juha; Kurki, Mitja; Koshiba, Seizo; Narita, Akira; Konuma, Takahiro; Yamamoto, Kenichi; Akiyama, Masato; Ishigaki, Kazuyoshi; Suzuki, Akari; et al. (Nat Genet, 2021)
Current genome-wide association studies do not yet capture sufficient diversity in populations and scope of phenotypes. To expand an atlas of genetic associations in non-European populations, we conducted 220 deep-phenotype genome-wide association studies (diseases, biomarkers and medication usage) in BioBank Japan (n = 179,000), by incorporating past medical history and text-mining of electronic medical records. Meta-analyses with the UK Biobank and FinnGen (n = 628,000) identified ~5,000 new loci, which improved the resolution of the genomic map of human traits. This atlas elucidated the landscape of pleiotropy as represented by the major histocompatibility complex locus, where we conducted HLA fine-mapping. Finally, we performed statistical decomposition of matrices of phenome-wide summary statistics, and identified latent genetic components, which pinpointed responsible variants and biological mechanisms underlying current disease classifications across populations. The decomposed components enabled genetically informed subtyping of similar diseases (for example, allergic diseases). Our study suggests a potential avenue for hypothesis-free re-investigation of human diseases through genetics.
Keywords: ABO Blood-Group System; Biological Specimen Banks; Genetic Association Studies; Genetic Loci; Genetic Pleiotropy; Genetic Predisposition to Disease; Genome-Wide Association Study; Humans; Major Histocompatibility Complex; Meta-Analysis as Topic; Mutation; Phenotype

Genetics of 35 blood and urine biomarkers in the UK Biobank. - Sinnott-Armstrong, Nasa; Tanigawa, Yosuke; Amar, David; Mars, Nina; Benner, Christian; Aguirre, Matthew; Venkataraman, Guhan Ram; Wainberg, Michael; Ollila, Hanna M; Kiiskinen, Tuomo; Havulinna, Aki S; Pirruccello, James P; et al. (Nat Genet, 2021)
Clinical laboratory tests are a critical component of the continuum of care. We evaluate the genetic basis of 35 blood and urine laboratory measurements in the UK Biobank (n = 363,228 individuals). We identify 1,857 loci associated with at least one trait, containing 3,374 fine-mapped associations and additional sets of large-effect (>0.1 s.d.) protein-altering, human leukocyte antigen (HLA) and copy number variant (CNV) associations. Through Mendelian randomization (MR) analysis, we discover 51 causal relationships, including previously known agonistic effects of urate on gout and cystatin C on stroke. Finally, we develop polygenic risk scores (PRSs) for each biomarker and build 'multi-PRS' models for diseases using 35 PRSs simultaneously, which improved chronic kidney disease, type 2 diabetes, gout and alcoholic cirrhosis genetic risk stratification in an independent dataset (FinnGen; n = 135,500) relative to single-disease PRSs. Together, our results delineate the genetic basis of biomarkers and their causal influences on diseases and improve genetic risk stratification for common diseases.
Keywords: Biological Specimen Banks; Biomarkers; Cardiovascular Diseases; Diabetes Mellitus, Type 2; DNA Copy Number Variations; Genetic Pleiotropy; HLA Antigens; Humans; Linkage Disequilibrium; Liver-Specific Organic Anion Transporter 1; Mendelian Randomization Analysis; Polymorphism, Single Nucleotide; Proteins; Renal Insufficiency, Chronic; Serine Endopeptidases; United Kingdom

Identification of rare and common regulatory variants in pluripotent cells using population-scale transcriptomics. - Bonder, Marc Jan; Smail, Craig; Gloudemans, Michael J; Frésard, Laure; Jakubosky, David; D'Antonio, Matteo; Li, Xin; Ferraro, Nicole M; Carcamo-Orive, Ivan; Mirauta, Bogdan; Seaton, Daniel D; Cai, Na; et al. (Nat Genet, 2021)
Induced pluripotent stem cells (iPSCs) are an established cellular system to study the impact of genetic variants in derived cell types and developmental contexts. However, in their pluripotent state, the disease impact of genetic variants is less well known. Here, we integrate data from 1,367 human iPSC lines to comprehensively map common and rare regulatory variants in human pluripotent cells. Using this population-scale resource, we report hundreds of new colocalization events for human traits specific to iPSCs, and find increased power to identify rare regulatory variants compared with somatic tissues. Finally, we demonstrate how iPSCs enable the identification of causal genes for rare diseases.
Keywords: Bardet-Biedl Syndrome; Calcium Channels; Cell Line; Cerebellar Ataxia; DNA Methylation; Gene Expression; Genetic Variation; Humans; Induced Pluripotent Stem Cells; Polymorphism, Single Nucleotide; Proteins; Quantitative Trait Loci; Rare Diseases; Regulatory Sequences, Nucleic Acid; Sequence Analysis, RNA; Whole Genome Sequencing

Integration of multiomic annotation data to prioritize and characterize inflammation and immune-related risk variants in squamous cell lung cancer. - Sun, Ryan; Xu, Miao; Li, Xihao; Gaynor, Sheila; Zhou, Hufeng; Li, Zilin; Bossé, Yohan; Lam, Stephen; Tsao, Ming-Sound; Tardon, Adonina; Chen, Chu; Doherty, Jennifer; et al. (Genet Epidemiol, 2021)
Clinical trial results have recently demonstrated that inhibiting inflammation by targeting the interleukin-1β pathway can offer a significant reduction in lung cancer incidence and mortality, highlighting a pressing and unmet need to understand the benefits of inflammation-focused lung cancer therapies at the genetic level. While numerous genome-wide association studies (GWAS) have explored the genetic etiology of lung cancer, there remains a large gap between the type of information that may be gleaned from an association study and the depth of understanding necessary to explain and drive translational findings. Thus, in this study we jointly model and integrate extensive multiomics data sources, utilizing a total of 40 genome-wide functional annotations that augment previously published results from the International Lung Cancer Consortium (ILCCO) GWAS, to prioritize and characterize single nucleotide polymorphisms (SNPs) that increase risk of squamous cell lung cancer through the inflammatory and immune responses. Our work bridges the gap between correlative analysis and translational follow-up research, refining GWAS association measures in an interpretable and systematic manner. In particular, reanalysis of the ILCCO data highlights the impact of highly associated SNPs from nuclear factor-κB signaling pathway genes as well as major histocompatibility complex mediated variation in immune responses. One consequence of prioritizing likely functional SNPs is the pruning of variants that might be selected for follow-up work by over an order of magnitude, from potentially tens of thousands to hundreds. The strategies we introduce provide informative and interpretable approaches for incorporating extensive genome-wide annotation data in analysis of genetic association studies.

Population sequencing data reveal a compendium of mutational processes in the human germ line. - Seplyarskiy, Vladimir B; Soldatov, Ruslan A; Koch, Evan; McGinty, Ryan J; Goldmann, Jakob M; Hernandez, Ryan D; Barnes, Kathleen; Correa, Adolfo; Burchard, Esteban G; Ellinor, Patrick T; McGarvey, Stephen T; Mitchell, Braxton D; et al. (Science, 2021)
Biological mechanisms underlying human germline mutations remain largely unknown. We statistically decompose variation in the rate and spectra of mutations along the genome using volume-regularized nonnegative matrix factorization. The analysis of a sequencing dataset (TOPMed) reveals nine processes that explain the variation in mutation properties between loci. We provide a biological interpretation for seven of these processes. We associate one process with bulky DNA lesions that are resolved asymmetrically with respect to transcription and replication. Two processes track direction of replication fork and replication timing, respectively. We identify a mutagenic effect of active demethylation primarily acting in regulatory regions and a mutagenic effect of long interspersed nuclear elements. We localize a mutagenic process specific to oocytes from population sequencing data. This process appears transcriptionally asymmetric.
Keywords: Algorithms; CpG Islands; DNA Damage; DNA Demethylation; DNA Mutational Analysis; DNA Replication; Genetic Variation; Genome, Human; Germ Cells; Germ-Line Mutation; Humans; Long Interspersed Nucleotide Elements; Mutagenesis; Oocytes; Transcription, Genetic

Population-scale tissue transcriptomics maps long non-coding RNAs to complex disease. - de Goede, Olivia M; Nachun, Daniel C; Ferraro, Nicole M; Gloudemans, Michael J; Rao, Abhiram S; Smail, Craig; Eulalio, Tiffany Y; Aguet, Francois; Ng, Bernard; Xu, Jishu; Barbeira, Alvaro N; Castel, Stephane E; et al. (Cell, 2021)
Long non-coding RNA (lncRNA) genes have well-established and important impacts on molecular and cellular functions. However, among the thousands of lncRNA genes, it is still a major challenge to identify the subset with disease or trait relevance. To systematically characterize these lncRNA genes, we used Genotype Tissue Expression (GTEx) project v8 genetic and multi-tissue transcriptomic data to profile the expression, genetic regulation, cellular contexts, and trait associations of 14,100 lncRNA genes across 49 tissues for 101 distinct complex genetic traits. Using these approaches, we identified 1,432 lncRNA gene-trait associations, 800 of which were not explained by stronger effects of neighboring protein-coding genes. This included associations between lncRNA quantitative trait loci and inflammatory bowel disease, type 1 and type 2 diabetes, and coronary artery disease, as well as rare variant associations to body mass index.
Keywords: Coronary Artery Disease; Diabetes Mellitus, Type 1; Diabetes Mellitus, Type 2; Disease; Gene Expression Profiling; Genetic Variation; Humans; Inflammatory Bowel Diseases; Multifactorial Inheritance; Organ Specificity; Population; Quantitative Trait Loci; RNA, Long Noncoding; Transcriptome

Sex-specific genetic effects across biomarkers. - Flynn, Emily; Tanigawa, Yosuke; Rodriguez, Fatima; Altman, Russ B; Sinnott-Armstrong, Nasa; Rivas, Manuel A (Eur J Hum Genet, 2021)
Sex differences have been shown in laboratory biomarkers; however, the extent to which this is due to genetics is unknown. In this study, we infer sex-specific genetic parameters (heritability and genetic correlation) across 33 quantitative biomarker traits in 181,064 females and 156,135 males from the UK Biobank study. We apply a Bayesian Mixture Model, Sex Effects Mixture Model (SEMM), to Genome-wide Association Study summary statistics in order to (1) estimate the contributions of sex to the genetic variance of these biomarkers and (2) identify variants whose statistical association with these traits is sex-specific. We find that the genetics of most biomarker traits are shared between males and females, with the notable exception of testosterone, where we identify 119 female and 445 male-specific variants. These include protein-altering variants in steroid hormone production genes (POR, UGT2B7). Using the sex-specific variants as genetic instruments for Mendelian randomization, we find evidence for causal links between testosterone levels and height, body mass index, waist and hip circumference, and type 2 diabetes. We also show that sex-specific polygenic risk score models for testosterone outperform a combined model. Overall, these results demonstrate that while sex has a limited role in the genetics of most biomarker traits, sex plays an important role in testosterone genetics.

Synaptic processes and immune-related pathways implicated in Tourette syndrome. - Tsetsos, Fotis; Yu, Dongmei; Sul, Jae Hoon; Huang, Alden Y; Illmann, Cornelia; Osiecki, Lisa; Darrow, Sabrina M; Hirschtritt, Matthew E; Greenberg, Erica; Muller-Vahl, Kirsten R; Stuhrmann, Manfred; Dion, Yves; et al. (Transl Psychiatry, 2021)
Tourette syndrome (TS) is a neuropsychiatric disorder of complex genetic architecture involving multiple interacting genes. Here, we sought to elucidate the pathways that underlie the neurobiology of the disorder through genome-wide analysis. We analyzed genome-wide genotypic data of 3581 individuals with TS and 7682 ancestry-matched controls and investigated associations of TS with sets of genes that are expressed in particular cell types and operate in specific neuronal and glial functions. We employed a self-contained, set-based association method (SBA) as well as a competitive gene set method (MAGMA) using individual-level genotype data to perform a comprehensive investigation of the biological background of TS. Our SBA analysis identified three significant gene sets after Bonferroni correction, implicating ligand-gated ion channel signaling, lymphocytic, and cell adhesion and transsynaptic signaling processes. MAGMA analysis further supported the involvement of the cell adhesion and trans-synaptic signaling gene set. The lymphocytic gene set was driven by variants in FLT3, raising an intriguing hypothesis for the involvement of a neuroinflammatory element in TS pathogenesis. The indications of involvement of ligand-gated ion channel signaling reinforce the role of GABA in TS, while the association of cell adhesion and trans-synaptic signaling gene set provides additional support for the role of adhesion molecules in neuropsychiatric disorders. This study reinforces previous findings but also provides new insights into the neurobiology of TS.

Whole exome sequencing analyses reveal gene-microbiota interactions in the context of IBD. - Hu, Shixian; Vich Vila, Arnau; Gacesa, Ranko; Collij, Valerie; Stevens, Christine; Fu, Jack M; Wong, Isaac; Talkowski, Michael E; Rivas, Manuel A; Imhann, Floris; Bolte, Laura; van Dullemen, Hendrik; et al. (Gut, 2021)
OBJECTIVE: Both the gut microbiome and host genetics are known to play significant roles in the pathogenesis of IBD. However, the interaction between these two factors and its implications in the aetiology of IBD remain underexplored. Here, we report on the influence of host genetics on the gut microbiome in IBD. DESIGN: To evaluate the impact of host genetics on the gut microbiota of patients with IBD, we combined whole exome sequencing of the host genome and whole genome shotgun sequencing of 1464 faecal samples from 525 patients with IBD and 939 population-based controls. We followed a four-step analysis: (1) exome-wide microbial quantitative trait loci (mbQTL) analyses, (2) a targeted approach focusing on IBD-associated genomic regions and protein truncating variants (PTVs, minor allele frequency (MAF) >5%), (3) gene-based burden tests on PTVs with MAF <5% and exome copy number variations (CNVs) with site frequency <1%, (4) joint analysis of both cohorts to identify the interactions between disease and host genetics. RESULTS: We identified 12 mbQTLs, including variants in the IBD-associated genes , , and . For example, the decrease of the pathway acetyl-coenzyme A biosynthesis, which is involved in short chain fatty acids production, was associated with variants in the gene (false discovery rate <0.05). Changes in functional pathways involved in the metabolic potential were also observed in participants carrying rare PTVs or CNVs in , and genes. These genes are known for their function in the immune system. Moreover, interaction analyses confirmed previously known IBD disease-specific mbQTLs in . CONCLUSION: This study highlights that both common and rare genetic variants affecting the immune system are key factors in shaping the gut microbiota in the context of IBD and pinpoints towards potential mechanisms for disease treatment.

Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale. - Li, Xihao; Li, Zilin; Zhou, Hufeng; Gaynor, Sheila M; Liu, Yaowu; Chen, Han; Sun, Ryan; Dey, Rounak; Arnett, Donna K; Aslibekyan, Stella; Ballantyne, Christie M; Bielak, Lawrence F; et al. (Nat Genet, 2020)
Large-scale whole-genome sequencing studies have enabled the analysis of rare variants (RVs) associated with complex phenotypes. Commonly used RV association tests have limited scope to leverage variant functions. We propose STAAR (variant-set test for association using annotation information), a scalable and powerful RV association test method that effectively incorporates both variant categories and multiple complementary annotations using a dynamic weighting scheme. For the latter, we introduce 'annotation principal components', multidimensional summaries of in silico variant annotations. STAAR accounts for population structure and relatedness and is scalable for analyzing very large cohort and biobank whole-genome sequencing studies of continuous and dichotomous traits. We applied STAAR to identify RVs associated with four lipid traits in 12,316 discovery and 17,822 replication samples from the Trans-Omics for Precision Medicine Program. We discovered and replicated new RV associations, including disruptive missense RVs of NPC1L1 and an intergenic region near APOC1P1 associated with low-density lipoprotein cholesterol.
Keywords: Cholesterol, LDL; Computer Simulation; Genetic Predisposition to Disease; Genetic Variation; Genome; Genome-Wide Association Study; Humans; Models, Genetic; Molecular Sequence Annotation; Phenotype; Whole Genome Sequencing

Electronic health record phenotypes associated with genetically regulated expression of CFTR and application to cystic fibrosis. - Zhong, Xue; Yin, Zhijun; Jia, Gengjie; Zhou, Dan; Wei, Qiang; Faucon, Annika; Evans, Patrick; Gamazon, Eric R; Li, Bingshan; Tao, Ran; Rzhetsky, Andrey; Bastarache, Lisa; et al. (Genet Med, 2020)
PURPOSE: The increasing use of electronic health records (EHRs) and biobanks offers unique opportunities to study Mendelian diseases. We described a novel approach to summarize clinical manifestations from patient EHRs into phenotypic evidence for cystic fibrosis (CF) with potential to alert unrecognized patients of the disease. METHODS: We estimated genetically predicted expression (GReX) of cystic fibrosis transmembrane conductance regulator (CFTR) and tested for association with clinical diagnoses in the Vanderbilt University biobank (N = 9142 persons of European descent with 71 cases of CF). The top associated EHR phenotypes were assessed in combination as a phenotype risk score (PheRS) for discriminating CF case status in an additional 2.8 million patients from Vanderbilt University Medical Center (VUMC) and 125,305 adult patients including 25,314 CF cases from MarketScan, an independent external cohort. RESULTS: GReX of CFTR was associated with EHR phenotypes consistent with CF. PheRS constructed using the EHR phenotypes and weights discovered by the genetic associations improved discriminative power for CF over the initially proposed PheRS in both VUMC and MarketScan. CONCLUSION: Our study demonstrates the power of EHRs for clinical description of CF and the benefits of using a genetics-informed weighing scheme in construction of a phenotype risk score. This research may find broad applications for phenomic studies of Mendelian disease genes.
Keywords: Adult; Cystic Fibrosis; Cystic Fibrosis Transmembrane Conductance Regulator; Electronic Health Records; Humans; Mutation; Phenotype

Neurophysiological and Genetic Findings in Patients With Juvenile Myoclonic Epilepsy. - Stefani, Stefani; Kousiappa, Ioanna; Nicolaou, Nicoletta; Papathanasiou, Eleftherios S; Oulas, Anastasis; Fanis, Pavlos; Neocleous, Vassos; Phylactou, Leonidas A; Spyrou, George M; Papacostas, Savvas S (Front Integr Neurosci, 2020)
Objective: Transcranial magnetic stimulation (TMS), a non-invasive procedure, stimulates the cortex evaluating the central motor pathways. The response is called motor evoked potential (MEP). Polyphasia results when the response crosses the baseline more than twice (zero crossing). Recent research shows MEP polyphasia in patients with generalized genetic epilepsy (GGE) and their first-degree relatives compared with controls. Juvenile Myoclonic Epilepsy (JME), a GGE type, is not well studied regarding polyphasia. In our study, we assessed polyphasia appearance probability with TMS in JME patients, their healthy first-degree relatives and controls. Two genetic approaches were applied to uncover genetic association with polyphasia. Methods: 20 JME patients, 23 first-degree relatives and 30 controls underwent TMS, obtaining 10-15 MEPs per participant. We evaluated MEP mean number of phases, proportion of MEP trials displaying polyphasia for each subject and variability between groups. Participants underwent whole exome sequencing (WES) via trio-based analysis and two-case scenario. Extensive bioinformatics analysis was applied. Results: We identified increased polyphasia in patients (85%) and relatives (70%) compared to controls (47%) and significantly higher mean number of zero crossings (i.e., occurrence of phases) (patients 1.49, relatives 1.46, controls 1.22; < 0.05). Trio-based analysis revealed a candidate polymorphism, p.Glu270del,in , in JME patients and their relatives presenting polyphasia. Sanger sequencing analysis in remaining participants showed no significant association. In two-case scenario, a machine learning approach was applied in variants identified from odds ratio analysis and risk prediction scores were obtained for polyphasia. The results revealed 61 variants of which none was associated with polyphasia. Risk prediction scores indeed showed lower probability for non-polyphasic subjects on having polyphasia and higher probability for polyphasic subjects on having polyphasia. Conclusion: Polyphasia was present in JME patients and relatives in contrast to controls. Although no known clinical symptoms are linked to polyphasia this neurophysiological phenomenon is likely due to common cerebral electrophysiological abnormality. We did not discover direct association between genetic variants obtained and polyphasia. It is likely these genetic traits alone cannot provoke polyphasia, however, this predisposition combined with disturbed brain-electrical activity and tendency to generate seizures may increase the risk of developing polyphasia, mainly in patients and relatives.

A positively selected FBN1 missense variant reduces height in Peruvian individuals. - Asgari, Samira; Luo, Yang; Akbari, Ali; Belbin, Gillian M; Li, Xinyi; Harris, Daniel N; Selig, Martin; Bartell, Eric; Calderon, Roger; Slowikowski, Kamil; Contreras, Carmen; Yataco, Rosa; et al. (Nature, 2020)
On average, Peruvian individuals are among the shortest in the world. Here we show that Native American ancestry is associated with reduced height in an ethnically diverse group of Peruvian individuals, and identify a population-specific, missense variant in the FBN1 gene (E1297G) that is significantly associated with lower height. Each copy of the minor allele (frequency of 4.7%) reduces height by 2.2 cm (4.4 cm in homozygous individuals). To our knowledge, this is the largest effect size known for a common height-associated variant. FBN1 encodes the extracellular matrix protein fibrillin 1, which is a major structural component of microfibrils. We observed less densely packed fibrillin-1-rich microfibrils with irregular edges in the skin of individuals who were homozygous for G1297 compared with individuals who were homozygous for E1297. Moreover, we show that the E1297G locus is under positive selection in non-African populations, and that the E1297 variant shows subtle evidence of positive selection specifically within the Peruvian population. This variant is also significantly more frequent in coastal Peruvian populations than in populations from the Andes or the Amazon, which suggests that short stature might be the result of adaptation to factors that are associated with the coastal environment in Peru.
Keywords: Body Height; Female; Fibrillin-1; Gene Frequency; Genome-Wide Association Study; Heredity; Humans; Indians, South American; Male; Microfibrils; Mutation, Missense; Peru; Selection, Genetic

Rare protein-altering variants in ANGPTL7 lower intraocular pressure and protect against glaucoma. - Tanigawa, Yosuke; Wainberg, Michael; Karjalainen, Juha; Kiiskinen, Tuomo; Venkataraman, Guhan; Lemmelä, Susanna; Turunen, Joni A; Graham, Robert R; Havulinna, Aki S; Perola, Markus; Palotie, Aarno; Daly, Mark J; et al. (PLoS Genet, 2020)
Protein-altering variants that are protective against human disease provide in vivo validation of therapeutic targets. Here we use genotyping data from UK Biobank (n = 337,151 unrelated White British individuals) and FinnGen (n = 176,899) to conduct a search for protein-altering variants conferring lower intraocular pressure (IOP) and protection against glaucoma. Through rare protein-altering variant association analysis, we find a missense variant in ANGPTL7 in UK Biobank (rs28991009, p.Gln175His, MAF = 0.8%, genotyped in 82,253 individuals with measured IOP and an independent set of 4,238 glaucoma patients and 250,660 controls) that significantly lowers IOP (β = -0.53 and -0.67 mmHg for heterozygotes, -3.40 and -2.37 mmHg for homozygotes, P = 5.96 x 10-9 and 1.07 x 10-13 for corneal compensated and Goldman-correlated IOP, respectively) and is associated with 34% reduced risk of glaucoma (P = 0.0062). In FinnGen, we identify an ANGPTL7 missense variant at a greater than 50-fold increased frequency in Finland compared with other populations (rs147660927, p.Arg220Cys, MAF Finland = 4.3%), which was genotyped in 6,537 glaucoma patients and 170,362 controls and is associated with a 29% lower glaucoma risk (P = 1.9 x 10-12 for all glaucoma types and also protection against its subtypes including exfoliation, primary open-angle, and primary angle-closure). We further find three rarer variants in UK Biobank, including a protein-truncating variant, which confer a strong composite lowering of IOP (P = 0.0012 and 0.24 for Goldman-correlated and corneal compensated IOP, respectively), suggesting the protective mechanism likely resides in the loss of interaction or function. Our results support inhibition or down-regulation of ANGPTL7 as a therapeutic strategy for glaucoma.
Keywords: Adult; Aged; Aged, 80 and over; Angiopoietin-like Proteins; Biological Specimen Banks; Case-Control Studies; Cohort Studies; Female; Finland; Gene Frequency; Genetic Predisposition to Disease; Genetics, Population; Genome-Wide Association Study; Glaucoma; Humans; Intraocular Pressure; Loss of Function Mutation; Male; Middle Aged; Mutation, Missense; Polymorphism, Single Nucleotide; United Kingdom

A Robust Method Uncovers Significant Context-Specific Heritability in Diverse Complex Traits. - Dahl, Andy; Nguyen, Khiem; Cai, Na; Gandal, Michael J; Flint, Jonathan; Zaitlen, Noah (Am J Hum Genet, 2020)
Gene-environment interactions (GxE) can be fundamental in applications ranging from functional genomics to precision medicine and is a conjectured source of substantial heritability. However, unbiased methods to profile GxE genome-wide are nascent and, as we show, cannot accommodate general environment variables, modest sample sizes, heterogeneous noise, and binary traits. To address this gap, we propose a simple, unifying mixed model for gene-environment interaction (GxEMM). In simulations and theory, we show that GxEMM can dramatically improve estimates and eliminate false positives when the assumptions of existing methods fail. We apply GxEMM to a range of human and model organism datasets and find broad evidence of context-specific genetic effects, including GxSex, GxAdversity, and GxDisease interactions across thousands of clinical and molecular phenotypes. Overall, GxEMM is broadly applicable for testing and quantifying polygenic interactions, which can be useful for explaining heritability and invaluable for determining biologically relevant environments.
Keywords: Adult; Animals; Computer Simulation; Female; Gene-Environment Interaction; Genetic Markers; Genome-Wide Association Study; Humans; Male; Mental Disorders; Middle Aged; Models, Genetic; Multifactorial Inheritance; Phenomics; Phenotype; Rats

Transcriptomic signatures across human tissues identify functional rare genetic variation. - Ferraro, Nicole M; Strober, Benjamin J; Einson, Jonah; Abell, Nathan S; Aguet, Francois; Barbeira, Alvaro N; Brandt, Margot; Bucan, Maja; Castel, Stephane E; Davis, Joe R; Greenwald, Emily; Hess, Gaelen T; et al. (Science, 2020)
Rare genetic variants are abundant across the human genome, and identifying their function and phenotypic impact is a major challenge. Measuring aberrant gene expression has aided in identifying functional, large-effect rare variants (RVs). Here, we expanded detection of genetically driven transcriptome abnormalities by analyzing gene expression, allele-specific expression, and alternative splicing from multitissue RNA-sequencing data, and demonstrate that each signal informs unique classes of RVs. We developed Watershed, a probabilistic model that integrates multiple genomic and transcriptomic signals to predict variant function, validated these predictions in additional cohorts and through experimental assays, and used them to assess RVs in the UK Biobank, the Million Veterans Program, and the Jackson Heart Study. Our results link thousands of RVs to diverse molecular effects and provide evidence to associate RVs affecting the transcriptome with human traits.
Keywords: Genetic Variation; Genome, Human; Humans; Multifactorial Inheritance; Organ Specificity; Transcriptome

Differential NOVA2-Mediated Splicing in Excitatory and Inhibitory Neurons Regulates Cortical Development and Cerebellar Function. - Saito, Yuhki; Yuan, Yuan; Zucker-Scharff, Ilana; Fak, John J; Jereb, Saša; Tajima, Yoko; Licatalosi, Donny D; Darnell, Robert B (Neuron, 2019)
RNA-binding proteins (RBPs) regulate genetic diversity, but the degree to which they do so in individual cell types in vivo is unknown. We developed NOVA2 cTag-crosslinking and immunoprecipitation (CLIP) to generate functional RBP-RNA maps from different neuronal populations in the mouse brain. Combining cell type datasets from Nova2-cTag and Nova2 conditional knockout mice revealed differential NOVA2 regulatory actions on alternative splicing (AS) on the same transcripts expressed in different neurons. This includes functional differences in transcripts expressed in cortical and cerebellar excitatory versus inhibitory neurons, where we find NOVA2 is required for, respectively, development of laminar structure, motor coordination, and synapse formation. We also find that NOVA2-regulated AS is coupled to NOVA2 regulation of intron retention in hundreds of transcripts, which can sequester the trans-acting splicing factor PTBP2. In summary, cTag-CLIP complements single-cell RNA sequencing (RNA-seq) studies by providing a means for understanding RNA regulation of functional cell diversity.
Keywords: Alternative Splicing; Animals; Antigens, Neoplasm; Cells, Cultured; Cerebellum; Cerebral Cortex; Excitatory Postsynaptic Potentials; Female; Inhibitory Postsynaptic Potentials; Male; Mice; Mice, Inbred C57BL; Nerve Tissue Proteins; Neuro-Oncological Ventral Antigen; Neurogenesis; Neurons; Polypyrimidine Tract-Binding Protein; RNA-Binding Proteins

Genome sequencing analysis identifies Epstein-Barr virus subtypes associated with high risk of nasopharyngeal carcinoma. - Xu, Miao; Yao, Youyuan; Chen, Hui; Zhang, Shanshan; Cao, Su-Mei; Zhang, Zhe; Luo, Bing; Liu, Zhiwei; Li, Zilin; Xiang, Tong; He, Guiping; Feng, Qi-Sheng; et al. (Nat Genet, 2019)
Epstein-Barr virus (EBV) infection is ubiquitous worldwide and is associated with multiple cancers, including nasopharyngeal carcinoma (NPC). The importance of EBV viral genomic variation in NPC development and its striking epidemic in southern China has been poorly explored. Through large-scale genome sequencing of 270 EBV isolates and two-stage association study of EBV isolates from China, we identify two non-synonymous EBV variants within BALF2 that are strongly associated with the risk of NPC (odds ratio (OR) = 8.69, P = 9.69 × 10 for SNP 162476_C; OR = 6.14, P = 2.40 × 10 for SNP 163364_T). The cumulative effects of these variants contribute to 83% of the overall risk of NPC in southern China. Phylogenetic analysis of the risk variants reveals a unique origin in Asia, followed by clonal expansion in NPC-endemic regions. Our results provide novel insights into the NPC endemic in southern China and also enable the identification of high-risk individuals for NPC prevention.

Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts. - Frésard, Laure; Smail, Craig; Ferraro, Nicole M; Teran, Nicole A; Li, Xin; Smith, Kevin S; Bonner, Devon; Kernohan, Kristin D; Marwaha, Shruti; Zappala, Zachary; Balliu, Brunilda; Davis, Joe R; et al. (Nat Med, 2019)
It is estimated that 350 million individuals worldwide suffer from rare diseases, which are predominantly caused by mutation in a single gene. The current molecular diagnostic rate is estimated at 50%, with whole-exome sequencing (WES) among the most successful approaches. For patients in whom WES is uninformative, RNA sequencing (RNA-seq) has shown diagnostic utility in specific tissues and diseases. This includes muscle biopsies from patients with undiagnosed rare muscle disorders, and cultured fibroblasts from patients with mitochondrial disorders. However, for many individuals, biopsies are not performed for clinical care, and tissues are difficult to access. We sought to assess the utility of RNA-seq from blood as a diagnostic tool for rare diseases of different pathophysiologies. We generated whole-blood RNA-seq from 94 individuals with undiagnosed rare diseases spanning 16 diverse disease categories. We developed a robust approach to compare data from these individuals with large sets of RNA-seq data for controls (n = 1,594 unrelated controls and n = 49 family members) and demonstrated the impacts of expression, splicing, gene and variant filtering strategies on disease gene identification. Across our cohort, we observed that RNA-seq yields a 7.5% diagnostic rate, and an additional 16.7% with improved candidate gene resolution.
Keywords: Acid Ceramidase; Case-Control Studies; Child; Child, Preschool; Cohort Studies; Female; Genetic Variation; Humans; Male; Models, Genetic; Mutation; Oxidoreductases Acting on CH-CH Group Donors; Potassium Channels; Rare Diseases; RNA; RNA Splicing; Sequence Analysis, RNA; Whole Exome Sequencing

Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection. - Schoech, Armin P; Jordan, Daniel M; Loh, Po-Ru; Gazal, Steven; O'Connor, Luke J; Balick, Daniel J; Palamara, Pier F; Finucane, Hilary K; Sunyaev, Shamil R; Price, Alkes L (Nat Commun, 2019)
Understanding the role of rare variants is important in elucidating the genetic basis of human disease. Negative selection can cause rare variants to have larger per-allele effect sizes than common variants. Here, we develop a method to estimate the minor allele frequency (MAF) dependence of SNP effect sizes. We use a model in which per-allele effect sizes have variance proportional to [p(1 - p)], where p is the MAF and negative values of α imply larger effect sizes for rare variants. We estimate α for 25 UK Biobank diseases and complex traits. All traits produce negative α estimates, with best-fit mean of -0.38 (s.e. 0.02) across traits. Despite larger rare variant effect sizes, rare variants (MAF < 1%) explain less than 10% of total SNP-heritability for most traits analyzed. Using evolutionary modeling and forward simulations, we validate the α model of MAF-dependent trait effects and assess plausible values of relevant evolutionary parameters.
Keywords: Algorithms; Alleles; Biological Specimen Banks; Gene Frequency; Genome-Wide Association Study; Genotype; Humans; Models, Genetic; Polymorphism, Single Nucleotide; Quantitative Trait, Heritable; Selection, Genetic; United Kingdom

Functional architecture of low-frequency variants highlights strength of negative selection across coding and non-coding annotations. - Gazal, Steven; Loh, Po-Ru; Finucane, Hilary K; Ganna, Andrea; Schoech, Armin; Sunyaev, Shamil; Price, Alkes L (Nat Genet, 2018)
Common variant heritability has been widely reported to be concentrated in variants within cell-type-specific non-coding functional annotations, but little is known about low-frequency variant functional architectures. We partitioned the heritability of both low-frequency (0.5%≤ minor allele frequency <5%) and common (minor allele frequency ≥5%) variants in 40 UK Biobank traits across a broad set of functional annotations. We determined that non-synonymous coding variants explain 17 ± 1% of low-frequency variant heritability ([Formula: see text]) versus 2.1 ± 0.2% of common variant heritability ([Formula: see text]). Cell-type-specific non-coding annotations that were significantly enriched for [Formula: see text] of corresponding traits were similarly enriched for [Formula: see text] for most traits, but more enriched for brain-related annotations and traits. For example, H3K4me3 marks in brain dorsolateral prefrontal cortex explain 57 ± 12% of [Formula: see text] versus 12 ± 2% of [Formula: see text] for neuroticism. Forward simulations confirmed that low-frequency variant enrichment depends on the mean selection coefficient of causal variants in the annotation, and can be used to predict effect size variance of causal rare variants (minor allele frequency <0.5%).
Keywords: Alleles; Biological Specimen Banks; Gene Frequency; Genetic Variation; Genetics, Population; Genome-Wide Association Study; Humans; Linkage Disequilibrium; Molecular Sequence Annotation; Open Reading Frames; Polymorphism, Single Nucleotide; Selection, Genetic; United Kingdom; White People

Functional equivalence of genome sequencing analysis pipelines enables harmonized variant calling across human genetics projects. - Regier, Allison A; Farjoun, Yossi; Larson, David E; Krasheninina, Olga; Kang, Hyun Min; Howrigan, Daniel P; Chen, Bo-Juen; Kher, Manisha; Banks, Eric; Ames, Darren C; English, Adam C; Li, Heng; et al. (Nat Commun, 2018)
Hundreds of thousands of human whole genome sequencing (WGS) datasets will be generated over the next few years. These data are more valuable in aggregate: joint analysis of genomes from many sources increases sample size and statistical power. A central challenge for joint analysis is that different WGS data processing pipelines cause substantial differences in variant calling in combined datasets, necessitating computationally expensive reprocessing. This approach is no longer tenable given the scale of current studies and data volumes. Here, we define WGS data processing standards that allow different groups to produce functionally equivalent (FE) results, yet still innovate on data processing pipelines. We present initial FE pipelines developed at five genome centers and show that they yield similar variant calling results and produce significantly less variability than sequencing replicates. This work alleviates a key technical bottleneck for genome aggregation and helps lay the foundation for community-wide human genetics studies.
Keywords: Genome, Human; Human Genetics; Humans; Whole Genome Sequencing

Imputation-Aware Tag SNP Selection To Improve Power for Large-Scale, Multi-ethnic Association Studies. - Wojcik, Genevieve L; Fuchsberger, Christian; Taliun, Daniel; Welch, Ryan; Martin, Alicia R; Shringarpure, Suyash; Carlson, Christopher S; Abecasis, Goncalo; Kang, Hyun Min; Boehnke, Michael; Bustamante, Carlos D; Gignoux, Christopher R; et al. (G3 (Bethesda), 2018)
The emergence of very large cohorts in genomic research has facilitated a focus on genotype-imputation strategies to power rare variant association. These strategies have benefited from improvements in imputation methods and association tests, however little attention has been paid to ways in which array design can increase rare variant association power. Therefore, we developed a novel framework to select tag SNPs using the reference panel of 26 populations from Phase 3 of the 1000 Genomes Project. We evaluate tag SNP performance mean imputed r at untyped sites using leave-one-out internal validation and standard imputation methods, rather than pairwise linkage disequilibrium. Moving beyond pairwise metrics allows us to account for haplotype diversity across the genome for improve imputation accuracy and demonstrates population-specific biases from pairwise estimates. We also examine array design strategies that contrast multi-ethnic cohorts single populations, and show a boost in performance for the former can be obtained by prioritizing tag SNPs that contribute information across multiple populations simultaneously. Using our framework, we demonstrate increased imputation accuracy for rare variants (frequency < 1%) by 0.5-3.1% for an array of one million sites and 0.7-7.1% for an array of 500,000 sites, depending on the population. Finally, we show how recent explosive growth in non-African populations means tag SNPs capture on average 30% fewer other variants than in African populations. The unified framework presented here will enable investigators to make informed decisions for the design of new arrays, and help empower the next phase of rare variant association for global health.
Keywords: Computational Biology; Databases, Nucleic Acid; Ethnicity; Genetic Association Studies; Genetics, Population; Genome-Wide Association Study; Humans; Linkage Disequilibrium; Models, Genetic; Polymorphism, Single Nucleotide; Reproducibility of Results; Selection, Genetic

Phenotype risk scores identify patients with unrecognized Mendelian disease patterns. - Bastarache, Lisa; Hughey, Jacob J; Hebbring, Scott; Marlo, Joy; Zhao, Wanke; Ho, Wanting T; Van Driest, Sara L; McGregor, Tracy L; Mosley, Jonathan D; Wells, Quinn S; Temple, Michael; Ramirez, Andrea H; et al. (Science, 2018)
Genetic association studies often examine features independently, potentially missing subpopulations with multiple phenotypes that share a single cause. We describe an approach that aggregates phenotypes on the basis of patterns described by Mendelian diseases. We mapped the clinical features of 1204 Mendelian diseases into phenotypes captured from the electronic health record (EHR) and summarized this evidence as phenotype risk scores (PheRSs). In an initial validation, PheRS distinguished cases and controls of five Mendelian diseases. Applying PheRS to 21,701 genotyped individuals uncovered 18 associations between rare variants and phenotypes consistent with Mendelian diseases. In 16 patients, the rare genetic variants were associated with severe outcomes such as organ transplants. PheRS can augment rare-variant interpretation and may identify subsets of patients with distinct genetic causes for common diseases.
Keywords: Databases, Genetic; DNA Mutational Analysis; Electronic Health Records; Exome; Genetic Association Studies; Genetic Diseases, Inborn; Genetic Predisposition to Disease; Genetic Variation; Humans; Phenotype; Risk Factors

A synthetic-diploid benchmark for accurate variant-calling evaluation. - Li, Heng; Bloom, Jonathan M; Farjoun, Yossi; Fleharty, Mark; Gauthier, Laura; Neale, Benjamin; MacArthur, Daniel (Nat Methods, 2018)
Existing benchmark datasets for use in evaluating variant-calling accuracy are constructed from a consensus of known short-variant callers, and they are thus biased toward easy regions that are accessible by these algorithms. We derived a new benchmark dataset from the de novo PacBio assemblies of two fully homozygous human cell lines, which provides a relatively more accurate and less biased estimate of small-variant-calling error rates in a realistic context.
Keywords: Algorithms; Benchmarking; Cell Line, Tumor; Databases, Genetic; Diploidy; Female; Genetic Variation; Genome, Human; Homozygote; Humans; Hydatidiform Mole; Pregnancy; Synthetic Biology; Uterine Neoplasms; Whole Genome Sequencing

Incorporation of Biological Knowledge Into the Study of Gene-Environment Interactions. - Ritchie, Marylyn D; Davis, Joe R; Aschard, Hugues; Battle, Alexis; Conti, David; Du, Mengmeng; Eskin, Eleazar; Fallin, M Daniele; Hsu, Li; Kraft, Peter; Moore, Jason H; Pierce, Brandon L; et al. (Am J Epidemiol, 2017)
A growing knowledge base of genetic and environmental information has greatly enabled the study of disease risk factors. However, the computational complexity and statistical burden of testing all variants by all environments has required novel study designs and hypothesis-driven approaches. We discuss how incorporating biological knowledge from model organisms, functional genomics, and integrative approaches can empower the discovery of novel gene-environment interactions and discuss specific methodological considerations with each approach. We consider specific examples where the application of these approaches has uncovered effects of gene-environment interactions relevant to drug response and immunity, and we highlight how such improvements enable a greater understanding of the pathogenesis of disease and the realization of precision medicine.
Keywords: Animals; Disease; Gene-Environment Interaction; Genome-Wide Association Study; Genomics; Humans; Models, Animal; Sequence Analysis, RNA

Leveraging blood and tissue CD4+ T cell heterogeneity at the single cell level to identify mechanisms of disease in rheumatoid arthritis. - Fonseka, Chamith Y; Rao, Deepak A; Raychaudhuri, Soumya (Curr Opin Immunol, 2017)
CD4+ T cells have been long known to play an important role in the pathogenesis of rheumatoid arthritis (RA), but the specific cell populations and states that drive the disease have been challenging to identify with low dimensional single cell data and bulk assays. The advent of high dimensional single cell technologies-like single cell RNA-seq or mass cytometry-has offered promise to defining key populations, but brings new methodological and statistical challenges. Recent single cell profiling studies have revealed a broad diversity of cell types among CD4+ T cells, identifying novel populations that are expanded or altered in RA. Here, we will review recent findings on CD4+ T cell heterogeneity and RA that have come from single cell profiling studies and discuss the best practices for conducting these studies.
Keywords: Animals; Arthritis, Rheumatoid; Blood Cells; CD4-Positive T-Lymphocytes; Datasets as Topic; Flow Cytometry; Humans; Immunophenotyping; Organ Specificity; Single-Cell Analysis; T-Lymphocyte Subsets

Linkage disequilibrium-dependent architecture of human complex traits shows action of negative selection. - Gazal, Steven; Finucane, Hilary K; Furlotte, Nicholas A; Loh, Po-Ru; Palamara, Pier Francesco; Liu, Xuanyao; Schoech, Armin; Bulik-Sullivan, Brendan; Neale, Benjamin M; Gusev, Alexander; Price, Alkes L (Nat Genet, 2017)
Recent work has hinted at the linkage disequilibrium (LD)-dependent architecture of human complex traits, where SNPs with low levels of LD (LLD) have larger per-SNP heritability. Here we analyzed summary statistics from 56 complex traits (average N = 101,401) by extending stratified LD score regression to continuous annotations. We determined that SNPs with low LLD have significantly larger per-SNP heritability and that roughly half of this effect can be explained by functional annotations negatively correlated with LLD, such as DNase I hypersensitivity sites (DHSs). The remaining signal is largely driven by our finding that more recent common variants tend to have lower LLD and to explain more heritability (P = 2.38 × 10); the youngest 20% of common SNPs explain 3.9 times more heritability than the oldest 20%, consistent with the action of negative selection. We also inferred jointly significant effects of other LD-related annotations and confirmed via forward simulations that they jointly predict deleterious effects.
Keywords: Alleles; Chi-Square Distribution; Datasets as Topic; Genetic Fitness; Genetic Variation; Humans; Linkage Disequilibrium; Models, Genetic; Molecular Sequence Annotation; Multifactorial Inheritance; Polymorphism, Single Nucleotide; Selection, Genetic

Negative selection in humans and fruit flies involves synergistic epistasis. - Sohail, Mashaal; Vakhrusheva, Olga A; Sul, Jae Hoon; Pulit, Sara L; Francioli, Laurent C; van den Berg, Leonard H; Veldink, Jan H; de Bakker, Paul I W; Bazykin, Georgii A; Kondrashov, Alexey S; Sunyaev, Shamil R (Science, 2017)
Negative selection against deleterious alleles produced by mutation influences within-population variation as the most pervasive form of natural selection. However, it is not known whether deleterious alleles affect fitness independently, so that cumulative fitness loss depends exponentially on the number of deleterious alleles, or synergistically, so that each additional deleterious allele results in a larger decrease in relative fitness. Negative selection with synergistic epistasis should produce negative linkage disequilibrium between deleterious alleles and, therefore, an underdispersed distribution of the number of deleterious alleles in the genome. Indeed, we detected underdispersion of the number of rare loss-of-function alleles in eight independent data sets from human and fly populations. Thus, selection against rare protein-disrupting alleles is characterized by synergistic epistasis, which may explain how human and fly populations persist despite high genomic mutation rates.
Keywords: Alleles; Animals; Drosophila melanogaster; Epistasis, Genetic; Genetic Fitness; Genome, Human; Genome, Insect; Humans; Linkage Disequilibrium; Mutation Rate; Mutation, Missense; Selection, Genetic

Population- and individual-specific regulatory variation in Sardinia. - Pala, Mauro; Zappala, Zachary; Marongiu, Mara; Li, Xin; Davis, Joe R; Cusano, Roberto; Crobu, Francesca; Kukurba, Kimberly R; Gloudemans, Michael J; Reinier, Frederic; Berutti, Riccardo; Piras, Maria G; et al. (Nat Genet, 2017)
Genetic studies of complex traits have mainly identified associations with noncoding variants. To further determine the contribution of regulatory variation, we combined whole-genome and transcriptome data for 624 individuals from Sardinia to identify common and rare variants that influence gene expression and splicing. We identified 21,183 expression quantitative trait loci (eQTLs) and 6,768 splicing quantitative trait loci (sQTLs), including 619 new QTLs. We identified high-frequency QTLs and found evidence of selection near genes involved in malarial resistance and increased multiple sclerosis risk, reflecting the epidemiological history of Sardinia. Using family relationships, we identified 809 segregating expression outliers (median z score of 2.97), averaging 13.3 genes per individual. Outlier genes were enriched for proximal rare variants, providing a new approach to study large-effect regulatory variants and their relevance to traits. Our results provide insight into the effects of regulatory variants and their relationship to population history and individual genetic risk.
Keywords: Alternative Splicing; Chromosome Mapping; Family Health; Female; Gene Expression Profiling; Genetic Predisposition to Disease; Genetic Variation; Genetics, Population; Genome-Wide Association Study; Genotype; Humans; Italy; Male; Polymorphism, Single Nucleotide; Quantitative Trait Loci; Transcription Initiation Site

Whole-transcriptome sequencing in blood provides a diagnosis of spinal muscular atrophy with progressive myoclonic epilepsy. - Kernohan, Kristin D; Frésard, Laure; Zappala, Zachary; Hartley, Taila; Smith, Kevin S; Wagner, Justin; Xu, Hongbin; McBride, Arran; Bourque, Pierre R; Consortium, Care Rare Canada; Bennett, Steffany A L; Dyment, David A; et al. (Hum Mutat, 2017)
At least 15% of the disease-causing mutations affect mRNA splicing. Many splicing mutations are missed in a clinical setting due to limitations of in silico prediction algorithms or their location in noncoding regions. Whole-transcriptome sequencing is a promising new tool to identify these mutations; however, it will be a challenge to obtain disease-relevant tissue for RNA. Here, we describe an individual with a sporadic atypical spinal muscular atrophy, in whom clinical DNA sequencing reported one pathogenic ASAH1 mutation (c.458A>G;p.Tyr153Cys). Transcriptome sequencing on patient leukocytes identified a highly significant and atypical ASAH1 isoform not explained by c.458A>G(p<10 ). Subsequent Sanger-sequencing identified the splice mutation responsible for the isoform (c.504A>C;p.Lys168Asn) and provided a molecular diagnosis of autosomal-recessive spinal muscular atrophy with progressive myoclonic epilepsy. Our findings demonstrate the utility of RNA sequencing from blood to identify splice-impacting disease mutations for nonhematological conditions, providing a diagnosis for these otherwise unsolved patients.
Keywords: Acid Ceramidase; Child, Preschool; Humans; Male; Muscular Atrophy, Spinal; Mutation; Myoclonic Epilepsies, Progressive; Pathology, Molecular; RNA Splicing; Sequence Analysis, DNA; Transcriptome