Publications by authors named "Tõnu Esko"

279 Publications

Resource profile and user guide of the Polygenic Index Repository.

Nat Hum Behav 2021 Jun 17. Epub 2021 Jun 17.

McCourt School of Public Policy, Georgetown University, Washington, DC, USA.

Polygenic indexes (PGIs) are DNA-based predictors. Their value for research in many scientific disciplines is growing rapidly. As a resource for researchers, we used a consistent methodology to construct PGIs for 47 phenotypes in 11 datasets. To maximize the PGIs' prediction accuracies, we constructed them using genome-wide association studies-some not previously published-from multiple data sources, including 23andMe and UK Biobank. We present a theoretical framework to help interpret analyses involving PGIs. A key insight is that a PGI can be understood as an unbiased but noisy measure of a latent variable we call the 'additive SNP factor'. Regressions in which the true regressor is this factor but the PGI is used as its proxy therefore suffer from errors-in-variables bias. We derive an estimator that corrects for the bias, illustrate the correction, and make a Python tool for implementing it publicly available.
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http://dx.doi.org/10.1038/s41562-021-01119-3DOI Listing
June 2021

Sex-Dependent Shared and Nonshared Genetic Architecture Across Mood and Psychotic Disorders.

Biol Psychiatry 2021 Mar 23. Epub 2021 Mar 23.

Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, Illinois; Department of Psychiatry and Behavioral Sciences, North Shore University Health System, Evanston, Illinois.

Background: Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk.

Methods: We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH.

Results: Across disorders, genome-wide significant single nucleotide polymorphism-by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10; rs73033497, p = 8.8 × 10; rs7914279, p = 6.4 × 10), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05).

Conclusions: In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels.
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http://dx.doi.org/10.1016/j.biopsych.2021.02.972DOI Listing
March 2021

Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology.

Nat Genet 2021 06 17;53(6):817-829. Epub 2021 May 17.

Department of Neuroscience, Istituto Di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.

Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.
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http://dx.doi.org/10.1038/s41588-021-00857-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8192451PMC
June 2021

Genome-wide analysis of 944 133 individuals provides insights into the etiology of haemorrhoidal disease.

Gut 2021 Apr 22. Epub 2021 Apr 22.

Department of Medicine I, Institute of Cancer Research, Medical University Vienna, Vienna, Austria.

Objective: Haemorrhoidal disease (HEM) affects a large and silently suffering fraction of the population but its aetiology, including suspected genetic predisposition, is poorly understood. We report the first genome-wide association study (GWAS) meta-analysis to identify genetic risk factors for HEM to date.

Design: We conducted a GWAS meta-analysis of 218 920 patients with HEM and 725 213 controls of European ancestry. Using GWAS summary statistics, we performed multiple genetic correlation analyses between HEM and other traits as well as calculated HEM polygenic risk scores (PRS) and evaluated their translational potential in independent datasets. Using functional annotation of GWAS results, we identified HEM candidate genes, which differential expression and coexpression in HEM tissues were evaluated employing RNA-seq analyses. The localisation of expressed proteins at selected loci was investigated by immunohistochemistry.

Results: We demonstrate modest heritability and genetic correlation of HEM with several other diseases from the GI, neuroaffective and cardiovascular domains. HEM PRS validated in 180 435 individuals from independent datasets allowed the identification of those at risk and correlated with younger age of onset and recurrent surgery. We identified 102 independent HEM risk loci harbouring genes whose expression is enriched in blood vessels and GI tissues, and in pathways associated with smooth muscles, epithelial and endothelial development and morphogenesis. Network transcriptomic analyses highlighted HEM gene coexpression modules that are relevant to the development and integrity of the musculoskeletal and epidermal systems, and the organisation of the extracellular matrix.

Conclusion: HEM has a genetic component that predisposes to smooth muscle, epithelial and connective tissue dysfunction.
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http://dx.doi.org/10.1136/gutjnl-2020-323868DOI Listing
April 2021

Multi-ancestry genome-wide gene-sleep interactions identify novel loci for blood pressure.

Mol Psychiatry 2021 Apr 15. Epub 2021 Apr 15.

Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.

Long and short sleep duration are associated with elevated blood pressure (BP), possibly through effects on molecular pathways that influence neuroendocrine and vascular systems. To gain new insights into the genetic basis of sleep-related BP variation, we performed genome-wide gene by short or long sleep duration interaction analyses on four BP traits (systolic BP, diastolic BP, mean arterial pressure, and pulse pressure) across five ancestry groups in two stages using 2 degree of freedom (df) joint test followed by 1df test of interaction effects. Primary multi-ancestry analysis in 62,969 individuals in stage 1 identified three novel gene by sleep interactions that were replicated in an additional 59,296 individuals in stage 2 (stage 1 + 2 P < 5 × 10), including rs7955964 (FIGNL2/ANKRD33) that increases BP among long sleepers, and rs73493041 (SNORA26/C9orf170) and rs10406644 (KCTD15/LSM14A) that increase BP among short sleepers (P < 5 × 10). Secondary ancestry-specific analysis identified another novel gene by long sleep interaction at rs111887471 (TRPC3/KIAA1109) in individuals of African ancestry (P = 2 × 10). Combined stage 1 and 2 analyses additionally identified significant gene by long sleep interactions at 10 loci including MKLN1 and RGL3/ELAVL3 previously associated with BP, and significant gene by short sleep interactions at 10 loci including C2orf43 previously associated with BP (P < 10). 2df test also identified novel loci for BP after modeling sleep that has known functions in sleep-wake regulation, nervous and cardiometabolic systems. This study indicates that sleep and primary mechanisms regulating BP may interact to elevate BP level, suggesting novel insights into sleep-related BP regulation.
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http://dx.doi.org/10.1038/s41380-021-01087-0DOI Listing
April 2021

Mendelian randomisation identifies alternative splicing of the FAS death receptor as a mediator of severe COVID-19.

medRxiv 2021 Apr 7. Epub 2021 Apr 7.

Severe COVID-19 is characterised by immunopathology and epithelial injury. Proteomic studies have identified circulating proteins that are biomarkers of severe COVID-19, but cannot distinguish correlation from causation. To address this, we performed Mendelian randomisation (MR) to identify proteins that mediate severe COVID-19. Using protein quantitative trait loci (pQTL) data from the SCALLOP consortium, involving meta-analysis of up to 26,494 individuals, and COVID-19 genome-wide association data from the Host Genetics Initiative, we performed MR for 157 COVID-19 severity protein biomarkers. We identified significant MR results for five proteins: FAS, TNFRSF10A, CCL2, EPHB4 and LGALS9. Further evaluation of these candidates using sensitivity analyses and colocalization testing provided strong evidence to implicate the apoptosis-associated cytokine receptor FAS as a causal mediator of severe COVID-19. This effect was specific to severe disease. Using RNA-seq data from 4,778 individuals, we demonstrate that the pQTL at the locus results from genetically influenced alternate splicing causing skipping of exon 6. We show that the risk allele for very severe COVID-19 increases the proportion of transcripts lacking exon 6, and thereby increases soluble FAS. Soluble FAS acts as a decoy receptor for FAS-ligand, inhibiting apoptosis induced through membrane-bound FAS. In summary, we demonstrate a novel genetic mechanism that contributes to risk of severe of COVID-19, highlighting a pathway that may be a promising therapeutic target.
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http://dx.doi.org/10.1101/2021.04.01.21254789DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8043484PMC
April 2021

Multivariate genome-wide analysis of immunoglobulin G N-glycosylation identifies new loci pleiotropic with immune function.

Hum Mol Genet 2021 Jun;30(13):1259-1270

Laboratory of Glycogenomics, Institute of Cytology and Genetics, Novosibirsk 630090, Russia.

The N-glycosylation of immunoglobulin G (IgG) affects its structure and function. It has been demonstrated that IgG N-glycosylation patterns are inherited as complex quantitative traits. Genome-wide association studies identified loci harboring genes encoding enzymes directly involved in protein glycosylation as well as loci likely to be involved in regulation of glycosylation biochemical pathways. Many of these loci could be linked to immune functions and risk of inflammatory and autoimmune diseases. The aim of the present study was to discover and replicate new loci associated with IgG N-glycosylation and to investigate possible pleiotropic effects of these loci onto immune function and the risk of inflammatory and autoimmune diseases. We conducted a multivariate genome-wide association analysis of 23 IgG N-glycosylation traits measured in 8090 individuals of European ancestry. The discovery stage was followed up by replication in 3147 people and in silico functional analysis. Our study increased the total number of replicated loci from 22 to 29. For the discovered loci, we suggest a number of genes potentially involved in the control of IgG N-glycosylation. Among the new loci, two (near RNF168 and TNFRSF13B) were previously implicated in rare immune deficiencies and were associated with levels of circulating immunoglobulins. For one new locus (near AP5B1/OVOL1), we demonstrated a potential pleiotropic effect on the risk of asthma. Our findings underline an important link between IgG N-glycosylation and immune function and provide new clues to understanding their interplay.
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http://dx.doi.org/10.1093/hmg/ddab072DOI Listing
June 2021

Genome-wide analyses of smoking behaviors in schizophrenia: Findings from the Psychiatric Genomics Consortium.

J Psychiatr Res 2021 05 18;137:215-224. Epub 2021 Feb 18.

Department of Psychiatry and Behavioral Sciences, State University of New York Downstate Medical Center, Brooklyn, NY, USA; VA New York Harbor Healthcare System, Brooklyn, NY, USA. Electronic address:

While 17% of US adults use tobacco regularly, smoking rates among persons with schizophrenia are upwards of 60%. Research supports a shared etiological basis for smoking and schizophrenia, including findings from genome-wide association studies (GWAS). However, few studies have directly tested whether the same or distinct genetic variants also influence smoking behavior among schizophrenia cases. Using data from the Psychiatric Genomics Consortium (PGC) study of schizophrenia (35476 cases, 46839 controls), we estimated genetic correlations between these traits and tested whether polygenic risk scores (PRS) constructed from the results of smoking behaviors GWAS were associated with schizophrenia risk or smoking behaviors among schizophrenia cases. Results indicated significant genetic correlations of schizophrenia with smoking initiation (r = 0.159; P = 5.05 × 10), cigarettes-smoked-per-day (r = 0.094; P = 0.006), and age-of-onset of smoking (r = 0.10; P = 0.009). Comparing smoking behaviors among schizophrenia cases to the general population, we observe positive genetic correlations for smoking initiation (r = 0.624, P = 0.002) and cigarettes-smoked-per-day (r = 0.689, P = 0.120). Similarly, TAG-based PRS for smoking initiation and cigarettes-smoked-per-day were significantly associated with smoking initiation (P = 3.49 × 10) and cigarettes-smoked-per-day (P = 0.007) among schizophrenia cases. We performed the first GWAS of smoking behavior among schizophrenia cases and identified a novel association with cigarettes-smoked-per-day upstream of the TMEM106B gene on chromosome 7p21.3 (rs148253479, P = 3.18 × 10, n = 3520). Results provide evidence of a partially shared genetic basis for schizophrenia and smoking behaviors. Additionally, genetic risk factors for smoking behaviors were largely shared across schizophrenia and non-schizophrenia populations. Future research should address mechanisms underlying these associations to aid both schizophrenia and smoking treatment and prevention efforts.
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http://dx.doi.org/10.1016/j.jpsychires.2021.02.027DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8096167PMC
May 2021

Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability.

Nat Commun 2021 01 5;12(1):24. Epub 2021 Jan 5.

Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA.

Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.
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http://dx.doi.org/10.1038/s41467-020-19366-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785747PMC
January 2021

Genetic Predisposition to Coronary Artery Disease in Type 2 Diabetes Mellitus.

Circ Genom Precis Med 2020 12 13;13(6):e002769. Epub 2020 Aug 13.

The Usher Institute of Population Health Sciences & Informatics (A.D.M.), University of Edinburgh, Edinburgh, U.K.

Background: Coronary artery disease (CAD) is accelerated in subjects with type 2 diabetes mellitus (T2D).

Methods: To test whether this reflects differential genetic influences on CAD risk in subjects with T2D, we performed a systematic assessment of genetic overlap between CAD and T2D in 66 643 subjects (27 708 with CAD and 24 259 with T2D). Variants showing apparent association with CAD in stratified analyses or evidence of interaction were evaluated in a further 117 787 subjects (16 694 with CAD and 11 537 with T2D).

Results: None of the previously characterized CAD loci was found to have specific effects on CAD in T2D individuals, and a genome-wide interaction analysis found no new variants for CAD that could be considered T2D specific. When we considered the overall genetic correlations between CAD and its risk factors, we found no substantial differences in these relationships by T2D background.

Conclusions: This study found no evidence that the genetic architecture of CAD differs in those with T2D compared with those without T2D.
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http://dx.doi.org/10.1161/CIRCGEN.119.002769DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7748049PMC
December 2020

Association of circulating metabolites in plasma or serum and risk of stroke: Meta-analysis from seven prospective cohorts.

Neurology 2020 Dec 2. Epub 2020 Dec 2.

Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands;

Objective: To conduct a comprehensive analysis of circulating metabolites and incident stroke in large prospective population-based settings.

Methods: We investigated the association of metabolites with risk of stroke in seven prospective cohort studies including 1,791 incident stroke events among 38,797 participants in whom circulating metabolites were measured by Nuclear Magnetic Resonance (H-NMR) technology. The relationship between metabolites and stroke was assessed using Cox proportional hazards regression models. The analyses were performed considering all incident stroke events and ischemic and hemorrhagic events separately.

Results: The analyses revealed ten significant metabolite associations. Amino acid histidine (hazard ratio (HR) per standard deviation (SD) = 0.90, 95% confidence interval (CI): 0.85, 0.94; = 4.45×10), glycolysis-related metabolite pyruvate (HR per SD = 1.09, 95% CI: 1.04, 1.14; = 7.45×10), acute phase reaction marker glycoprotein acetyls (HR per SD = 1.09, 95% CI: 1.03, 1.15; = 1.27×10), cholesterol in high-density lipoprotein (HDL) 2 and several other lipoprotein particles were associated with risk of stroke. When focusing on incident ischemic stroke, a significant association was observed with phenylalanine (HR per SD = 1.12, 95% CI: 1.05, 1.19; 4.13×10) and total and free cholesterol in large HDL particles.

Conclusions: We found association of amino acids, glycolysis-related metabolites, acute phase reaction markers, and several lipoprotein subfractions with the risk of stroke. These findings support the potential of metabolomics to provide new insights into the metabolic changes preceding stroke.
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http://dx.doi.org/10.1212/WNL.0000000000011236DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8055347PMC
December 2020

Genotype-first approach to the detection of hereditary breast and ovarian cancer risk, and effects of risk disclosure to biobank participants.

Eur J Hum Genet 2021 Mar 23;29(3):471-481. Epub 2020 Nov 23.

Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia.

Genotype-first approach allows to systematically identify carriers of pathogenic variants in BRCA1/2 genes conferring a high risk of familial breast and ovarian cancer. Participants of the Estonian biobank have expressed support for the disclosure of clinically significant findings. With an Estonian biobank cohort, we applied a genotype-first approach, contacted carriers, and offered return of results with genetic counseling. We evaluated participants' responses to and the clinical utility of the reporting of actionable genetic findings. Twenty-two of 40 contacted carriers of 17 pathogenic BRCA1/2 variants responded and chose to receive results. Eight of these 22 participants qualified for high-risk assessment based on National Comprehensive Cancer Network criteria. Twenty of 21 counseled participants appreciated being contacted. Relatives of 10 participants underwent cascade screening. Five of 16 eligible female BRCA1/2 variant carriers chose to undergo risk-reducing surgery, and 10 adhered to surveillance recommendations over the 30-month follow-up period. We recommend the return of results to population-based biobank participants; this approach could be viewed as a model for population-wide genetic testing. The genotype-first approach permits the identification of individuals at high risk who would not be identified by application of an approach based on personal and family histories only.
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http://dx.doi.org/10.1038/s41431-020-00760-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7940387PMC
March 2021

Discovery of rare variants associated with blood pressure regulation through meta-analysis of 1.3 million individuals.

Nat Genet 2020 12 23;52(12):1314-1332. Epub 2020 Nov 23.

Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark.

Genetic studies of blood pressure (BP) to date have mainly analyzed common variants (minor allele frequency > 0.05). In a meta-analysis of up to ~1.3 million participants, we discovered 106 new BP-associated genomic regions and 87 rare (minor allele frequency ≤ 0.01) variant BP associations (P < 5 × 10), of which 32 were in new BP-associated loci and 55 were independent BP-associated single-nucleotide variants within known BP-associated regions. Average effects of rare variants (44% coding) were ~8 times larger than common variant effects and indicate potential candidate causal genes at new and known loci (for example, GATA5 and PLCB3). BP-associated variants (including rare and common) were enriched in regions of active chromatin in fetal tissues, potentially linking fetal development with BP regulation in later life. Multivariable Mendelian randomization suggested possible inverse effects of elevated systolic and diastolic BP on large artery stroke. Our study demonstrates the utility of rare-variant analyses for identifying candidate genes and the results highlight potential therapeutic targets.
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http://dx.doi.org/10.1038/s41588-020-00713-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610439PMC
December 2020

MADloy: robust detection of mosaic loss of chromosome Y from genotype-array-intensity data.

BMC Bioinformatics 2020 Nov 23;21(1):533. Epub 2020 Nov 23.

Genetics Unit, Universitat Pompeu Fabra, Barcelona, Spain.

Background: Accurate protocols and methods to robustly detect the mosaic loss of chromosome Y (mLOY) are needed given its reported role in cancer, several age-related disorders and overall male mortality. Intensity SNP-array data have been used to infer mLOY status and to determine its prominent role in male disease. However, discrepancies of reported findings can be due to the uncertainty and variability of the methods used for mLOY detection and to the differences in the tissue-matrix used.

Results: We created a publicly available software tool called MADloy (Mosaic Alteration Detection for LOY) that incorporates existing methods and includes a new robust approach, allowing efficient calling in large studies and comparisons between methods. MADloy optimizes mLOY calling by correctly modeling the underlying reference population with no-mLOY status and incorporating B-deviation information. We observed improvements in the calling accuracy to previous methods, using experimentally validated samples, and an increment in the statistical power to detect associations with disease and mortality, using simulation studies and real dataset analyses. To understand discrepancies in mLOY detection across different tissues, we applied MADloy to detect the increment of mLOY cellularity in blood on 18 individuals after 3 years and to confirm that its detection in saliva was sub-optimal (41%). We additionally applied MADloy to detect the down-regulation genes in the chromosome Y in kidney and bladder tumors with mLOY, and to perform pathway analyses for the detection of mLOY in blood.

Conclusions: MADloy is a new software tool implemented in R for the easy and robust calling of mLOY status across different tissues aimed to facilitate its study in large epidemiological studies.
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http://dx.doi.org/10.1186/s12859-020-03768-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7682048PMC
November 2020

Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals.

Nat Metab 2020 10 16;2(10):1135-1148. Epub 2020 Oct 16.

SCALLOP consortium.

Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. Here, we map and replicate protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, resulting in 451 pQTLs for 85 proteins. For each protein, we further perform pathway mapping to obtain trans-pQTL gene and regulatory designations. We substantiate these regulatory findings with orthogonal evidence for trans-pQTLs using mouse knockdown experiments (ABCA1 and TRIB1) and clinical trial results (chemokine receptors CCR2 and CCR5), with consistent regulation. Finally, we evaluate known drug targets, and suggest new target candidates or repositioning opportunities using Mendelian randomization. This identifies 11 proteins with causal evidence of involvement in human disease that have not previously been targeted, including EGF, IL-16, PAPPA, SPON1, F3, ADM, CASP-8, CHI3L1, CXCL16, GDF15 and MMP-12. Taken together, these findings demonstrate the utility of large-scale mapping of the genetics of the proteome and provide a resource for future precision studies of circulating proteins in human health.
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http://dx.doi.org/10.1038/s42255-020-00287-2DOI Listing
October 2020

Development and validation of two SCORE-based cardiovascular risk prediction models for Eastern Europe: a multicohort study.

Eur Heart J 2020 09;41(35):3325-3333

Department of Epidemiology & Public Health, University College London, 1-19 Torrington Place, London WC1E 7HB, UK.

Aims: Cardiovascular disease (CVD) risk prediction models are used in Western European countries, but less so in Eastern European countries where rates of CVD can be two to four times higher. We recalibrated the SCORE prediction model for three Eastern European countries and evaluated the impact of adding seven behavioural and psychosocial risk factors to the model.

Methods And Results: We developed and validated models using data from the prospective HAPIEE cohort study with 14 598 participants from Russia, Poland, and the Czech Republic (derivation cohort, median follow-up 7.2 years, 338 fatal CVD cases) and Estonian Biobank data with 4632 participants (validation cohort, median follow-up 8.3 years, 91 fatal CVD cases). The first model (recalibrated SCORE) used the same risk factors as in the SCORE model. The second model (HAPIEE SCORE) added education, employment, marital status, depression, body mass index, physical inactivity, and antihypertensive use. Discrimination of the original SCORE model (C-statistic 0.78 in the derivation and 0.83 in the validation cohorts) was improved in recalibrated SCORE (0.82 and 0.85) and HAPIEE SCORE (0.84 and 0.87) models. After dichotomizing risk at the clinically meaningful threshold of 5%, and when comparing the final HAPIEE SCORE model against the original SCORE model, the net reclassification improvement was 0.07 [95% confidence interval (CI) 0.02-0.11] in the derivation cohort and 0.14 (95% CI 0.04-0.25) in the validation cohort.

Conclusion: Our recalibrated SCORE may be more appropriate than the conventional SCORE for some Eastern European populations. The addition of seven quick, non-invasive, and cheap predictors further improved prediction accuracy.
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http://dx.doi.org/10.1093/eurheartj/ehaa571DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7544536PMC
September 2020

Genome-wide association study identifies 48 common genetic variants associated with handedness.

Nat Hum Behav 2021 01 28;5(1):59-70. Epub 2020 Sep 28.

Institute of Biological Psychiatry, Mental Health Services of Copenhagen, Copenhagen, Denmark.

Handedness has been extensively studied because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and the International Handedness Consortium, we conducted a genome-wide association meta-analysis of handedness (N = 1,766,671). We found 41 loci associated (P < 5 × 10) with left-handedness and 7 associated with ambidexterity. Tissue-enrichment analysis implicated the CNS in the aetiology of handedness. Pathways including regulation of microtubules and brain morphology were also highlighted. We found suggestive positive genetic correlations between left-handedness and neuropsychiatric traits, including schizophrenia and bipolar disorder. Furthermore, the genetic correlation between left-handedness and ambidexterity is low (r = 0.26), which implies that these traits are largely influenced by different genetic mechanisms. Our findings suggest that handedness is highly polygenic and that the genetic variants that predispose to left-handedness may underlie part of the association with some psychiatric disorders.
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http://dx.doi.org/10.1038/s41562-020-00956-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7116623PMC
January 2021

The Polygenic and Monogenic Basis of Blood Traits and Diseases.

Cell 2020 09;182(5):1214-1231.e11

Laboratory of Epidemiology and Population Science, National Institute on Aging/NIH, Baltimore, MD, 21224, USA.

Blood cells play essential roles in human health, underpinning physiological processes such as immunity, oxygen transport, and clotting, which when perturbed cause a significant global health burden. Here we integrate data from UK Biobank and a large-scale international collaborative effort, including data for 563,085 European ancestry participants, and discover 5,106 new genetic variants independently associated with 29 blood cell phenotypes covering a range of variation impacting hematopoiesis. We holistically characterize the genetic architecture of hematopoiesis, assess the relevance of the omnigenic model to blood cell phenotypes, delineate relevant hematopoietic cell states influenced by regulatory genetic variants and gene networks, identify novel splice-altering variants mediating the associations, and assess the polygenic prediction potential for blood traits and clinical disorders at the interface of complex and Mendelian genetics. These results show the power of large-scale blood cell trait GWAS to interrogate clinically meaningful variants across a wide allelic spectrum of human variation.
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http://dx.doi.org/10.1016/j.cell.2020.08.008DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7482360PMC
September 2020

Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations.

Cell 2020 09;182(5):1198-1213.e14

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA 02130, USA; Department of Medicine, Division on Aging, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA.

Most loci identified by GWASs have been found in populations of European ancestry (EUR). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EUR individuals, we identified 5,552 trait-variant associations at p < 5 × 10, including 71 novel associations not found in EUR populations. We also identified 28 additional novel variants in ancestry-specific, non-EUR meta-analyses, including an IL7 missense variant in South Asians associated with lymphocyte count in vivo and IL-7 secretion levels in vitro. Fine-mapping prioritized variants annotated as functional and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EUR-only results. We explored the clinical significance and predictive value of trans-ethnic variants in multiple populations and compared genetic architecture and the effect of natural selection on these blood phenotypes between populations. Altogether, our results for hematological traits highlight the value of a more global representation of populations in genetic studies.
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http://dx.doi.org/10.1016/j.cell.2020.06.045DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7480402PMC
September 2020

Genome-wide Study Identifies Association between HLA-B55:01 and Self-Reported Penicillin Allergy.

Am J Hum Genet 2020 10 3;107(4):612-621. Epub 2020 Sep 3.

Department of Epidemiology Research, Statens Serum Institut, Copenhagen 2300, Denmark; Department of Clinical Sciences, Lund University Diabetes Centre, 214 28 Malmö, Sweden; Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland.

Hypersensitivity reactions to drugs are often unpredictable and can be life threatening, underscoring a need for understanding their underlying mechanisms and risk factors. The extent to which germline genetic variation influences the risk of commonly reported drug allergies such as penicillin allergy remains largely unknown. We extracted data from the electronic health records of more than 600,000 participants from the UK, Estonian, and Vanderbilt University Medical Center's BioVU biobanks to study the role of genetic variation in the occurrence of self-reported penicillin hypersensitivity reactions. We used imputed SNP to HLA typing data from these cohorts to further fine map the human leukocyte antigen (HLA) association and replicated our results in 23andMe's research cohort involving a total of 1.12 million individuals. Genome-wide meta-analysis of penicillin allergy revealed two loci, including one located in the HLA region on chromosome 6. This signal was further fine-mapped to the HLA-B55:01 allele (OR 1.41 95% CI 1.33-1.49, p value 2.04 × 10) and confirmed by independent replication in 23andMe's research cohort (OR 1.30 95% CI 1.25-1.34, p value 1.00 × 10). The lead SNP was also associated with lower lymphocyte counts and in silico follow-up suggests a potential effect on T-lymphocytes at HLA-B55:01. We also observed a significant hit in PTPN22 and the GWAS results correlated with the genetics of rheumatoid arthritis and psoriasis. We present robust evidence for the role of an allele of the major histocompatibility complex (MHC) I gene HLA-B in the occurrence of penicillin allergy.
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http://dx.doi.org/10.1016/j.ajhg.2020.08.008DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7536643PMC
October 2020

Genetic and In Vitro Inhibition of and Calcific Aortic Valve Stenosis.

JACC Basic Transl Sci 2020 Jul 1;5(7):649-661. Epub 2020 Jul 1.

Centre de Recherche de l'Institut Universitaire de Cardiologie et de Pneumologie de Québec, Québec, Canada.

The authors investigated whether PCSK9 inhibition could represent a therapeutic strategy in calcific aortic valve stenosis (CAVS). A meta-analysis of 10 studies was performed to determine the impact of the R46L variant on CAVS, and the authors found that CAVS was less prevalent in carriers of this variant (odds ratio: 0.80 [95% confidence interval: 0.70 to 0.91]; p = 0.0011) compared with noncarriers. PCSK9 expression was higher in the aortic valves of patients CAVS compared with control patients. In human valve interstitials cells submitted to a pro-osteogenic medium, PCSK9 levels increased and a PCSK9 neutralizing antibody significantly reduced calcium accumulation.
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http://dx.doi.org/10.1016/j.jacbts.2020.05.004DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7393433PMC
July 2020

Differences in local population history at the finest level: the case of the Estonian population.

Eur J Hum Genet 2020 11 25;28(11):1580-1591. Epub 2020 Jul 25.

Estonian Biocentre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia.

Several recent studies detected fine-scale genetic structure in human populations. Hence, groups conventionally treated as single populations harbour significant variation in terms of allele frequencies and patterns of haplotype sharing. It has been shown that these findings should be considered when performing studies of genetic associations and natural selection, especially when dealing with polygenic phenotypes. However, there is little understanding of the practical effects of such genetic structure on demography reconstructions and selection scans when focusing on recent population history. Here we tested the impact of population structure on such inferences using high-coverage (~30×) genome sequences of 2305 Estonians. We show that different regions of Estonia differ in both effective population size dynamics and signatures of natural selection. By analyzing identity-by-descent segments we also reveal that some Estonian regions exhibit evidence of a bottleneck 10-15 generations ago reflecting sequential episodes of wars, plague and famine, although this signal is virtually undetected when treating Estonia as a single population. Besides that, we provide a framework for relating effective population size estimated from genetic data to actual census size and validate it on the Estonian population. This approach may be widely used both to cross-check estimates based on historical sources as well as to get insight into times and/or regions with no other information available. Our results suggest that the history of human populations within the last few millennia can be highly region specific and cannot be properly studied without taking local genetic structure into account.
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http://dx.doi.org/10.1038/s41431-020-0699-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7575549PMC
November 2020

Polymorphic Inversions Underlie the Shared Genetic Susceptibility of Obesity-Related Diseases.

Am J Hum Genet 2020 06 28;106(6):846-858. Epub 2020 May 28.

IMIM (Hospital del Mar Research Institute), Barcelona 08003, Spain; Department of Experimental and Health Sciences (CEXS), Universitat Pompeu Fabra, Barcelona 08003, Spain; Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Barcelona 08003, Spain; Women's and Children's Hospital, South Australian Health and Medical Research Institute & University of Adelaide, Adelaide, SA 5005, Australia.

The burden of several common diseases including obesity, diabetes, hypertension, asthma, and depression is increasing in most world populations. However, the mechanisms underlying the numerous epidemiological and genetic correlations among these disorders remain largely unknown. We investigated whether common polymorphic inversions underlie the shared genetic influence of these disorders. We performed an inversion association analysis including 21 inversions and 25 obesity-related traits on a total of 408,898 Europeans and validated the results in 67,299 independent individuals. Seven inversions were associated with multiple diseases while inversions at 8p23.1, 16p11.2, and 11q13.2 were strongly associated with the co-occurrence of obesity with other common diseases. Transcriptome analysis across numerous tissues revealed strong candidate genes for obesity-related traits. Analyses in human pancreatic islets indicated the potential mechanism of inversions in the susceptibility of diabetes by disrupting the cis-regulatory effect of SNPs from their target genes. Our data underscore the role of inversions as major genetic contributors to the joint susceptibility to common complex diseases.
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http://dx.doi.org/10.1016/j.ajhg.2020.04.017DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7273535PMC
June 2020

Integrating untargeted metabolomics, genetically informed causal inference, and pathway enrichment to define the obesity metabolome.

Int J Obes (Lond) 2020 07 28;44(7):1596-1606. Epub 2020 May 28.

Department of Genetics, Harvard Medical School, Boston, MA, USA.

Background: Obesity and its associated diseases are major health problems characterized by extensive metabolic disturbances. Understanding the causal connections between these phenotypes and variation in metabolite levels can uncover relevant biology and inform novel intervention strategies. Recent studies have combined metabolite profiling with genetic instrumental variable (IV) analysis (Mendelian randomization) to infer the direction of causality between metabolites and obesity, but often omitted a large portion of untargeted profiling data consisting of unknown, unidentified metabolite signals.

Methods: We expanded upon previous research by identifying body mass index (BMI)-associated metabolites in multiple untargeted metabolomics datasets, and then performing bidirectional IV analysis to classify metabolites based on their inferred causal relationships with BMI. Meta-analysis and pathway analysis of both known and unknown metabolites across datasets were enabled by our recently developed bioinformatics suite, PAIRUP-MS.

Results: We identified ten known metabolites that are more likely to be causes (e.g., alpha-hydroxybutyrate) or effects (e.g., valine) of BMI, or may have more complex bidirectional cause-effect relationships with BMI (e.g., glycine). Importantly, we also identified about five times more unknown than known metabolites in each of these three categories. Pathway analysis incorporating both known and unknown metabolites prioritized 40 enriched (p < 0.05) metabolite sets for the cause versus effect groups, providing further support that these two metabolite groups are linked to obesity via distinct biological mechanisms.

Conclusions: These findings demonstrate the potential utility of our approach to uncover causal connections with obesity from untargeted metabolomics datasets. Combining genetically informed causal inference with the ability to map unknown metabolites across datasets provides a path to jointly analyze many untargeted datasets with obesity or other phenotypes. This approach, applied to larger datasets with genotype and untargeted metabolite data, should generate sufficient power for robust discovery and replication of causal biological connections between metabolites and various human diseases.
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http://dx.doi.org/10.1038/s41366-020-0603-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7332400PMC
July 2020

The effect of LRRK2 loss-of-function variants in humans.

Nat Med 2020 06 27;26(6):869-877. Epub 2020 May 27.

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

Human genetic variants predicted to cause loss-of-function of protein-coding genes (pLoF variants) provide natural in vivo models of human gene inactivation and can be valuable indicators of gene function and the potential toxicity of therapeutic inhibitors targeting these genes. Gain-of-kinase-function variants in LRRK2 are known to significantly increase the risk of Parkinson's disease, suggesting that inhibition of LRRK2 kinase activity is a promising therapeutic strategy. While preclinical studies in model organisms have raised some on-target toxicity concerns, the biological consequences of LRRK2 inhibition have not been well characterized in humans. Here, we systematically analyze pLoF variants in LRRK2 observed across 141,456 individuals sequenced in the Genome Aggregation Database (gnomAD), 49,960 exome-sequenced individuals from the UK Biobank and over 4 million participants in the 23andMe genotyped dataset. After stringent variant curation, we identify 1,455 individuals with high-confidence pLoF variants in LRRK2. Experimental validation of three variants, combined with previous work, confirmed reduced protein levels in 82.5% of our cohort. We show that heterozygous pLoF variants in LRRK2 reduce LRRK2 protein levels but that these are not strongly associated with any specific phenotype or disease state. Our results demonstrate the value of large-scale genomic databases and phenotyping of human loss-of-function carriers for target validation in drug discovery.
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http://dx.doi.org/10.1038/s41591-020-0893-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7303015PMC
June 2020

Genomic analysis of diet composition finds novel loci and associations with health and lifestyle.

Mol Psychiatry 2020 May 11. Epub 2020 May 11.

Department of Endocrinology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands.

We conducted genome-wide association studies (GWAS) of relative intake from the macronutrients fat, protein, carbohydrates, and sugar in over 235,000 individuals of European ancestries. We identified 21 unique, approximately independent lead SNPs. Fourteen lead SNPs are uniquely associated with one macronutrient at genome-wide significance (P < 5 × 10), while five of the 21 lead SNPs reach suggestive significance (P < 1 × 10) for at least one other macronutrient. While the phenotypes are genetically correlated, each phenotype carries a partially unique genetic architecture. Relative protein intake exhibits the strongest relationships with poor health, including positive genetic associations with obesity, type 2 diabetes, and heart disease (r ≈ 0.15-0.5). In contrast, relative carbohydrate and sugar intake have negative genetic correlations with waist circumference, waist-hip ratio, and neighborhood deprivation (|r| ≈ 0.1-0.3) and positive genetic correlations with physical activity (r ≈ 0.1 and 0.2). Relative fat intake has no consistent pattern of genetic correlations with poor health but has a negative genetic correlation with educational attainment (r ≈-0.1). Although our analyses do not allow us to draw causal conclusions, we find no evidence of negative health consequences associated with relative carbohydrate, sugar, or fat intake. However, our results are consistent with the hypothesis that relative protein intake plays a role in the etiology of metabolic dysfunction.
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http://dx.doi.org/10.1038/s41380-020-0697-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7767645PMC
May 2020

Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci.

Mol Psychiatry 2020 May 5. Epub 2020 May 5.

Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, 21224, USA.

Educational attainment is widely used as a surrogate for socioeconomic status (SES). Low SES is a risk factor for hypertension and high blood pressure (BP). To identify novel BP loci, we performed multi-ancestry meta-analyses accounting for gene-educational attainment interactions using two variables, "Some College" (yes/no) and "Graduated College" (yes/no). Interactions were evaluated using both a 1 degree of freedom (DF) interaction term and a 2DF joint test of genetic and interaction effects. Analyses were performed for systolic BP, diastolic BP, mean arterial pressure, and pulse pressure. We pursued genome-wide interrogation in Stage 1 studies (N = 117 438) and follow-up on promising variants in Stage 2 studies (N = 293 787) in five ancestry groups. Through combined meta-analyses of Stages 1 and 2, we identified 84 known and 18 novel BP loci at genome-wide significance level (P < 5 × 10). Two novel loci were identified based on the 1DF test of interaction with educational attainment, while the remaining 16 loci were identified through the 2DF joint test of genetic and interaction effects. Ten novel loci were identified in individuals of African ancestry. Several novel loci show strong biological plausibility since they involve physiologic systems implicated in BP regulation. They include genes involved in the central nervous system-adrenal signaling axis (ZDHHC17, CADPS, PIK3C2G), vascular structure and function (GNB3, CDON), and renal function (HAS2 and HAS2-AS1, SLIT3). Collectively, these findings suggest a role of educational attainment or SES in further dissection of the genetic architecture of BP.
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http://dx.doi.org/10.1038/s41380-020-0719-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7641978PMC
May 2020
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