Publications by authors named "Chloé Sarnowski"

33 Publications

Genetic analysis of dietary intake identifies new loci and functional links with metabolic traits.

Nat Hum Behav 2021 Aug 23. Epub 2021 Aug 23.

Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.

Dietary intake is a major contributor to the global obesity epidemic and represents a complex behavioural phenotype that is partially affected by innate biological differences. Here, we present a multivariate genome-wide association analysis of overall variation in dietary intake to account for the correlation between dietary carbohydrate, fat and protein in 282,271 participants of European ancestry from the UK Biobank (n = 191,157) and Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (n = 91,114), and identify 26 distinct genome-wide significant loci. Dietary intake signals map exclusively to specific brain regions and are enriched for genes expressed in specialized subtypes of GABAergic, dopaminergic and glutamatergic neurons. We identified two main clusters of genetic variants for overall variation in dietary intake that were differently associated with obesity and coronary artery disease. These results enhance the biological understanding of interindividual differences in dietary intake by highlighting neural mechanisms, supporting functional follow-up experiments and possibly providing new avenues for the prevention and treatment of prevalent complex metabolic diseases.
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http://dx.doi.org/10.1038/s41562-021-01182-wDOI Listing
August 2021

Genetic insights into biological mechanisms governing human ovarian ageing.

Nature 2021 08 4;596(7872):393-397. Epub 2021 Aug 4.

Genome Integrity and Instability Group, Institut de Biotecnologia i Biomedicina, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain.

Reproductive longevity is essential for fertility and influences healthy ageing in women, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.
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http://dx.doi.org/10.1038/s41586-021-03779-7DOI Listing
August 2021

Identification of novel and rare variants associated with handgrip strength using whole genome sequence data from the NHLBI Trans-Omics in Precision Medicine (TOPMed) Program.

PLoS One 2021 2;16(7):e0253611. Epub 2021 Jul 2.

Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States of America.

Handgrip strength is a widely used measure of muscle strength and a predictor of a range of morbidities including cardiovascular diseases and all-cause mortality. Previous genome-wide association studies of handgrip strength have focused on common variants primarily in persons of European descent. We aimed to identify rare and ancestry-specific genetic variants associated with handgrip strength by conducting whole-genome sequence association analyses using 13,552 participants from six studies representing diverse population groups from the Trans-Omics in Precision Medicine (TOPMed) Program. By leveraging multiple handgrip strength measures performed in study participants over time, we increased our effective sample size by 7-12%. Single-variant analyses identified ten handgrip strength loci among African-Americans: four rare variants, five low-frequency variants, and one common variant. One significant and four suggestive genes were identified associated with handgrip strength when aggregating rare and functional variants; all associations were ancestry-specific. We additionally leveraged the different ancestries available in the UK Biobank to further explore the ancestry-specific association signals from the single-variant association analyses. In conclusion, our study identified 11 new loci associated with handgrip strength with rare and/or ancestry-specific genetic variations, highlighting the added value of whole-genome sequencing in diverse samples. Several of the associations identified using single-variant or aggregate analyses lie in genes with a function relevant to the brain or muscle or were reported to be associated with muscle or age-related traits. Further studies in samples with sequence data and diverse ancestries are needed to confirm these findings.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0253611PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8253404PMC
July 2021

Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program.

Nature 2021 02 10;590(7845):290-299. Epub 2021 Feb 10.

The Broad Institute of MIT and Harvard, Cambridge, MA, USA.

The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes). In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.
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http://dx.doi.org/10.1038/s41586-021-03205-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7875770PMC
February 2021

Genome-wide meta-analysis of muscle weakness identifies 15 susceptibility loci in older men and women.

Nat Commun 2021 01 28;12(1):654. Epub 2021 Jan 28.

Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.

Low muscle strength is an important heritable indicator of poor health linked to morbidity and mortality in older people. In a genome-wide association study meta-analysis of 256,523 Europeans aged 60 years and over from 22 cohorts we identify 15 loci associated with muscle weakness (European Working Group on Sarcopenia in Older People definition: n = 48,596 cases, 18.9% of total), including 12 loci not implicated in previous analyses of continuous measures of grip strength. Loci include genes reportedly involved in autoimmune disease (HLA-DQA1 p = 4 × 10), arthritis (GDF5 p = 4 × 10), cell cycle control and cancer protection, regulation of transcription, and others involved in the development and maintenance of the musculoskeletal system. Using Mendelian randomization we report possible overlapping causal pathways, including diabetes susceptibility, haematological parameters, and the immune system. We conclude that muscle weakness in older adults has distinct mechanisms from continuous strength, including several pathways considered to be hallmarks of ageing.
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http://dx.doi.org/10.1038/s41467-021-20918-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7844411PMC
January 2021

Cerebral small vessel disease genomics and its implications across the lifespan.

Nat Commun 2020 12 8;11(1):6285. Epub 2020 Dec 8.

University of Alabama at Birmingham School of Medicine, Birmingham, AL, 35233, USA.

White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p = 2.5×10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials.
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http://dx.doi.org/10.1038/s41467-020-19111-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7722866PMC
December 2020

JEM: A joint test to estimate the effect of multiple genetic variants on DNA methylation.

Genet Epidemiol 2021 Apr 10;45(3):280-292. Epub 2020 Oct 10.

Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA.

Multiple methods have been proposed to aggregate genetic variants in a gene or a region and jointly test their association with a trait of interest. However, these joint tests do not provide estimates of the individual effect of each variant. Moreover, few methods have evaluated the joint association of multiple variants with DNA methylation. We propose a method based on linear mixed models to estimate the joint and individual effect of multiple genetic variants on DNA methylation leveraging genomic annotations. Our approach is flexible, can incorporate covariates and annotation features, and takes into account relatedness and linkage disequilibrium (LD). Our method had correct Type-I error and overall high power for different simulated scenarios where we varied the number and specificity of functional annotations, number of causal and total genetic variants, frequency of genetic variants, LD, and genetic variant effect. Our method outperformed the family Sequence Kernel Association Test and had more stable estimations of effects than a classical single-variant linear mixed-effect model. Applied genome-wide to the Framingham Heart Study data, our method identified 921 DNA methylation sites influenced by at least one rare or low-frequency genetic variant located within 50 kilobases (kb) of the DNA methylation site.
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http://dx.doi.org/10.1002/gepi.22369DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8005415PMC
April 2021

Impact of Rare and Common Genetic Variants on Diabetes Diagnosis by Hemoglobin A1c in Multi-Ancestry Cohorts: The Trans-Omics for Precision Medicine Program.

Am J Hum Genet 2019 10 26;105(4):706-718. Epub 2019 Sep 26.

National Heart, Lung, and Blood Institute and Boston University's Framingham Heart Study, Framingham MA 01702, USA; Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20814, USA.

Hemoglobin A1c (HbA1c) is widely used to diagnose diabetes and assess glycemic control in individuals with diabetes. However, nonglycemic determinants, including genetic variation, may influence how accurately HbA1c reflects underlying glycemia. Analyzing the NHLBI Trans-Omics for Precision Medicine (TOPMed) sequence data in 10,338 individuals from five studies and four ancestries (6,158 Europeans, 3,123 African-Americans, 650 Hispanics, and 407 East Asians), we confirmed five regions associated with HbA1c (GCK in Europeans and African-Americans, HK1 in Europeans and Hispanics, FN3K and/or FN3KRP in Europeans, and G6PD in African-Americans and Hispanics) and we identified an African-ancestry-specific low-frequency variant (rs1039215 in HBG2 and HBE1, minor allele frequency (MAF) = 0.03). The most associated G6PD variant (rs1050828-T, p.Val98Met, MAF = 12% in African-Americans, MAF = 2% in Hispanics) lowered HbA1c (-0.88% in hemizygous males, -0.34% in heterozygous females) and explained 23% of HbA1c variance in African-Americans and 4% in Hispanics. Additionally, we identified a rare distinct G6PD coding variant (rs76723693, p.Leu353Pro, MAF = 0.5%; -0.98% in hemizygous males, -0.46% in heterozygous females) and detected significant association with HbA1c when aggregating rare missense variants in G6PD. We observed similar magnitude and direction of effects for rs1039215 (HBG2) and rs76723693 (G6PD) in the two largest TOPMed African American cohorts, and we replicated the rs76723693 association in the UK Biobank African-ancestry participants. These variants in G6PD and HBG2 were monomorphic in the European and Asian samples. African or Hispanic ancestry individuals carrying G6PD variants may be underdiagnosed for diabetes when screened with HbA1c. Thus, assessment of these variants should be considered for incorporation into precision medicine approaches for diabetes diagnosis.
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http://dx.doi.org/10.1016/j.ajhg.2019.08.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6817529PMC
October 2019

A meta-analysis of genome-wide association studies identifies multiple longevity genes.

Nat Commun 2019 08 14;10(1):3669. Epub 2019 Aug 14.

Department of Public Health, University of Southern Denmark, 5000, Odense C, Denmark.

Human longevity is heritable, but genome-wide association (GWA) studies have had limited success. Here, we perform two meta-analyses of GWA studies of a rigorous longevity phenotype definition including 11,262/3484 cases surviving at or beyond the age corresponding to the 90th/99th survival percentile, respectively, and 25,483 controls whose age at death or at last contact was at or below the age corresponding to the 60th survival percentile. Consistent with previous reports, rs429358 (apolipoprotein E (ApoE) ε4) is associated with lower odds of surviving to the 90th and 99th percentile age, while rs7412 (ApoE ε2) shows the opposite. Moreover, rs7676745, located near GPR78, associates with lower odds of surviving to the 90th percentile age. Gene-level association analysis reveals a role for tissue-specific expression of multiple genes in longevity. Finally, genetic correlation of the longevity GWA results with that of several disease-related phenotypes points to a shared genetic architecture between health and longevity.
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http://dx.doi.org/10.1038/s41467-019-11558-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6694136PMC
August 2019

Genome-wide interaction study of early-life smoking exposure on time-to-asthma onset in childhood.

Clin Exp Allergy 2019 10;49(10):1342-1351

Genetic Epidemiology and Functional Genomics of Multifactorial Diseases Team, Inserm, UMRS-1124, Université Paris Descartes, Paris, France.

Background: Asthma, a heterogeneous disease with variable age of onset, results from the interplay between genetic and environmental factors. Early-life tobacco smoke (ELTS) exposure is a major asthma risk factor. Only a few genetic loci have been reported to interact with ELTS exposure in asthma.

Objective: Our aim was to identify new loci interacting with ELTS exposure on time-to-asthma onset (TAO) in childhood.

Methods: We conducted genome-wide interaction analyses of ELTS exposure on time-to-asthma onset in childhood in five European-ancestry studies (totalling 8273 subjects) using Cox proportional-hazard model. The results of all five genome-wide analyses were meta-analysed.

Results: The 13q21 locus showed genome-wide significant interaction with ELTS exposure (P = 4.3 × 10 for rs7334050 within KLHL1 with consistent results across the five studies). Suggestive interactions (P < 5 × 10 ) were found at three other loci: 20p12 (rs13037508 within MACROD2; P = 4.9 × 10 ), 14q22 (rs7493885 near NIN; P = 2.9 × 10 ) and 2p22 (rs232542 near CYP1B1; P = 4.1 × 10 ). Functional annotations and the literature showed that the lead SNPs at these four loci influence DNA methylation in the blood and are located nearby CpG sites reported to be associated with exposure to tobacco smoke components, which strongly support our findings.

Conclusions And Clinical Relevance: We identified novel candidate genes interacting with ELTS exposure on time-to-asthma onset in childhood. These genes have plausible biological relevance related to tobacco smoke exposure. Further epigenetic and functional studies are needed to confirm these findings and to shed light on the underlying mechanisms.
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http://dx.doi.org/10.1111/cea.13476DOI Listing
October 2019

Quality of dietary fat and genetic risk of type 2 diabetes: individual participant data meta-analysis.

BMJ 2019 07 25;366:l4292. Epub 2019 Jul 25.

Objective: To investigate whether the genetic burden of type 2 diabetes modifies the association between the quality of dietary fat and the incidence of type 2 diabetes.

Design: Individual participant data meta-analysis.

Data Sources: Eligible prospective cohort studies were systematically sourced from studies published between January 1970 and February 2017 through electronic searches in major medical databases (Medline, Embase, and Scopus) and discussion with investigators.

Review Methods: Data from cohort studies or multicohort consortia with available genome-wide genetic data and information about the quality of dietary fat and the incidence of type 2 diabetes in participants of European descent was sought. Prospective cohorts that had accrued five or more years of follow-up were included. The type 2 diabetes genetic risk profile was characterized by a 68-variant polygenic risk score weighted by published effect sizes. Diet was recorded by using validated cohort-specific dietary assessment tools. Outcome measures were summary adjusted hazard ratios of incident type 2 diabetes for polygenic risk score, isocaloric replacement of carbohydrate (refined starch and sugars) with types of fat, and the interaction of types of fat with polygenic risk score.

Results: Of 102 305 participants from 15 prospective cohort studies, 20 015 type 2 diabetes cases were documented after a median follow-up of 12 years (interquartile range 9.4-14.2). The hazard ratio of type 2 diabetes per increment of 10 risk alleles in the polygenic risk score was 1.64 (95% confidence interval 1.54 to 1.75, I=7.1%, τ=0.003). The increase of polyunsaturated fat and total omega 6 polyunsaturated fat intake in place of carbohydrate was associated with a lower risk of type 2 diabetes, with hazard ratios of 0.90 (0.82 to 0.98, I=18.0%, τ=0.006; per 5% of energy) and 0.99 (0.97 to 1.00, I=58.8%, τ=0.001; per increment of 1 g/d), respectively. Increasing monounsaturated fat in place of carbohydrate was associated with a higher risk of type 2 diabetes (hazard ratio 1.10, 95% confidence interval 1.01 to 1.19, I=25.9%, τ=0.006; per 5% of energy). Evidence of small study effects was detected for the overall association of polyunsaturated fat with the risk of type 2 diabetes, but not for the omega 6 polyunsaturated fat and monounsaturated fat associations. Significant interactions between dietary fat and polygenic risk score on the risk of type 2 diabetes (P>0.05 for interaction) were not observed.

Conclusions: These data indicate that genetic burden and the quality of dietary fat are each associated with the incidence of type 2 diabetes. The findings do not support tailoring recommendations on the quality of dietary fat to individual type 2 diabetes genetic risk profiles for the primary prevention of type 2 diabetes, and suggest that dietary fat is associated with the risk of type 2 diabetes across the spectrum of type 2 diabetes genetic risk.
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http://dx.doi.org/10.1136/bmj.l4292DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6652797PMC
July 2019

Genetic meta-analysis of diagnosed Alzheimer's disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing.

Nat Genet 2019 03 28;51(3):414-430. Epub 2019 Feb 28.

Research Center and Memory Clinic of Fundació ACE, Institut Català de Neurociències Aplicades-Universitat Internacional de Catalunya, Barcelona, Spain.

Risk for late-onset Alzheimer's disease (LOAD), the most prevalent dementia, is partially driven by genetics. To identify LOAD risk loci, we performed a large genome-wide association meta-analysis of clinically diagnosed LOAD (94,437 individuals). We confirm 20 previous LOAD risk loci and identify five new genome-wide loci (IQCK, ACE, ADAM10, ADAMTS1, and WWOX), two of which (ADAM10, ACE) were identified in a recent genome-wide association (GWAS)-by-familial-proxy of Alzheimer's or dementia. Fine-mapping of the human leukocyte antigen (HLA) region confirms the neurological and immune-mediated disease haplotype HLA-DR15 as a risk factor for LOAD. Pathway analysis implicates immunity, lipid metabolism, tau binding proteins, and amyloid precursor protein (APP) metabolism, showing that genetic variants affecting APP and Aβ processing are associated not only with early-onset autosomal dominant Alzheimer's disease but also with LOAD. Analyses of risk genes and pathways show enrichment for rare variants (P = 1.32 × 10), indicating that additional rare variants remain to be identified. We also identify important genetic correlations between LOAD and traits such as family history of dementia and education.
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http://dx.doi.org/10.1038/s41588-019-0358-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6463297PMC
March 2019

Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps.

Nat Genet 2018 11 8;50(11):1505-1513. Epub 2018 Oct 8.

Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.

We expanded GWAS discovery for type 2 diabetes (T2D) by combining data from 898,130 European-descent individuals (9% cases), after imputation to high-density reference panels. With these data, we (i) extend the inventory of T2D-risk variants (243 loci, 135 newly implicated in T2D predisposition, comprising 403 distinct association signals); (ii) enrich discovery of lower-frequency risk alleles (80 index variants with minor allele frequency <5%, 14 with estimated allelic odds ratio >2); (iii) substantially improve fine-mapping of causal variants (at 51 signals, one variant accounted for >80% posterior probability of association (PPA)); (iv) extend fine-mapping through integration of tissue-specific epigenomic information (islet regulatory annotations extend the number of variants with PPA >80% to 73); (v) highlight validated therapeutic targets (18 genes with associations attributable to coding variants); and (vi) demonstrate enhanced potential for clinical translation (genome-wide chip heritability explains 18% of T2D risk; individuals in the extremes of a T2D polygenic risk score differ more than ninefold in prevalence).
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http://dx.doi.org/10.1038/s41588-018-0241-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6287706PMC
November 2018

Interactive effect between ATPase-related genes and early-life tobacco smoke exposure on bronchial hyper-responsiveness detected in asthma-ascertained families.

Thorax 2019 03 3;74(3):254-260. Epub 2018 Oct 3.

Aging and Chronic Diseases-Epidemiological and Public Health Approaches (VIMA), Inserm, U1168, Villejuif, France.

Background: A positional cloning study of bronchial hyper-responsiveness (BHR) at the 17p11 locus in the French Epidemiological study on the Genetics and Environment of Asthma (EGEA) families showed significant interaction between early-life environmental tobacco smoke (ETS) exposure and genetic variants located in . This gene encodes the heavy chain subunit of axonemal dynein, which is involved with ATP in the motile cilia function.Our goal was to identify genetic variants at other genes interacting with ETS in BHR by investigating all genes belonging to the '' and '' pathways which include are targets of cigarette smoke and play a crucial role in the airway inflammation.

Methods: Family-based interaction tests between ETS-exposed and unexposed BHR siblings were conducted in 388 EGEA families. Twenty single-nucleotide polymorphisms (SNP) showing interaction signals (p5.10) were tested in the 253 Saguenay-Lac-Saint-Jean (SLSJ) families.

Results: One of these SNPs was significantly replicated for interaction with ETS in SLSJ families (p=0.003). Another SNP reached the significance threshold after correction for multiple testing in the combined analysis of the two samples (p=10). Results were confirmed using both a robust log-linear test and a gene-based interaction test.

Conclusion: The SNPs showing interaction with ETS belong to the and genes, which play a role in the maintenance of asymmetry and homeostasis of lung membrane lipids.
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http://dx.doi.org/10.1136/thoraxjnl-2018-211797DOI Listing
March 2019

Application of novel and existing methods to identify genes with evidence of epigenetic association: results from GAW20.

BMC Genet 2018 09 17;19(Suppl 1):72. Epub 2018 Sep 17.

Department of Mathematics and Statistics, Dordt College, Sioux Center, IA, 51250, USA.

Background: The rise in popularity and accessibility of DNA methylation data to evaluate epigenetic associations with disease has led to numerous methodological questions. As part of GAW20, our working group of 8 research groups focused on gene searching methods.

Results: Although the methods were varied, we identified 3 main themes within our group. First, many groups tackled the question of how best to use pedigree information in downstream analyses, finding that (a) the use of kinship matrices is common practice, (b) ascertainment corrections may be necessary, and (c) pedigree information may be useful for identifying parent-of-origin effects. Second, many groups also considered multimarker versus single-marker tests. Multimarker tests had modestly improved power versus single-marker methods on simulated data, and on real data identified additional associations that were not identified with single-marker methods, including identification of a gene with a strong biological interpretation. Finally, some of the groups explored methods to combine single-nucleotide polymorphism (SNP) and DNA methylation into a single association analysis.

Conclusions: A causal inference method showed promise at discovering new mechanisms of SNP activity; gene-based methods of summarizing SNP and DNA methylation data also showed promise. Even though numerous questions still remain in the analysis of DNA methylation data, our discussions at GAW20 suggest some emerging best practices.
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http://dx.doi.org/10.1186/s12863-018-0647-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6157126PMC
September 2018

Comparison of novel and existing methods for detecting differentially methylated regions.

BMC Genet 2018 09 17;19(Suppl 1):84. Epub 2018 Sep 17.

Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, 3rd Floor, Boston, MA, 02118, USA.

Background: Single-probe analyses in epigenome-wide association studies (EWAS) have identified associations between DNA methylation and many phenotypes, but do not take into account information from neighboring probes. Methods to detect differentially methylated regions (DMRs) (clusters of neighboring probes associated with a phenotype) may provide more power to detect associations between DNA methylation and diseases or phenotypes of interest.

Results: We proposed a novel approach, GlobalP, and perform comparisons with 3 methods-DMRcate, Bumphunter, and comb-p-to identify DMRs associated with log triglycerides (TGs) in real GAW20 data before and after fenofibrate treatment. We applied these methods to the summary statistics from an EWAS performed on the methylation data. Comb-p, DMRcate, and GlobalP detected very similar DMRs near the gene CPT1A on chromosome 11 in both the pre- and posttreatment data. In addition, GlobalP detected 2 DMRs before fenofibrate treatment in the genes ETV6 and ABCG1. Bumphunter identified several DMRs on chromosomes 1 and 20, which did not overlap with DMRs detected by other methods.

Conclusions: Our novel method detected the same DMR identified by two existing methods and detected two additional DMRs not identified by any of the existing methods we compared.
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http://dx.doi.org/10.1186/s12863-018-0637-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6156895PMC
September 2018

Investigation of parent-of-origin effects induced by fenofibrate treatment on triglycerides levels.

BMC Genet 2018 09 17;19(Suppl 1):83. Epub 2018 Sep 17.

Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA, 02118, USA.

Background: Genome-wide association studies performed on triglycerides (TGs) have not accounted for epigenetic mechanisms that may partially explain trait heritability.

Results: Parent-of-origin (POO) effect association analyses using an agnostic approach or a candidate approach were performed for pretreatment TG levels, posttreatment TG levels, and pre- and posttreatment TG-level differences in the real GAW20 family data set. We detected 22 genetic variants with suggestive POO effects with at least 1 phenotype (P ≤ 10). We evaluated the association of these 22 significant genetic variants showing POO effects with close DNA methylation probes associated with TGs. A total of 18 DNA methylation probes located in the vicinity of the 22 SNPs were associated with at least 1 phenotype and 6 SNP-probe pairs were associated with DNA methylation probes at the nominal level of P < 0.05, among which 1 pair presented evidence of POO effect. Our analyses identified a paternal effect of SNP rs301621 on the difference between pre- and posttreatment TG levels (P = 1.2 × 10). This same SNP showed evidence for a maternal effect on methylation levels of a nearby probe (cg10206250; P = 0.01). Using a causal inference test we established that the observed POO effect of rs301621 was not mediated by DNA methylation at cg10206250.

Conclusions: We performed POO effect association analyses of SNPs with TGs, as well as association analyses of SNPs with DNA methylation probes. These analyses, which were followed by a causal inference test, established that the paternal effect at the SNP rs301621 is induced by treatment and is not mediated by methylation level at cg10206250.
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http://dx.doi.org/10.1186/s12863-018-0640-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6156838PMC
September 2018

Do changes in DNA methylation mediate or interact with SNP variation? A pharmacoepigenetic analysis.

BMC Genet 2018 09 17;19(Suppl 1):70. Epub 2018 Sep 17.

Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Ave. 3rd floor, Boston, MA, 02118, USA.

Background: In studies with multi-omics data available, there is an opportunity to investigate interdependent mechanisms of biological causality. The GAW20 data set includes both DNA genotype and methylation measures before and after fenofibrate treatment. Using change in triglyceride (TG) levels pre- to posttreatment as outcome, we present a mediation analysis that incorporates methylation. This approach allows us to simultaneously consider a mediation hypothesis that genotype affects change in TG level by means of its effect on methylation, and an interaction hypothesis that the effect of change in methylation on change in TG levels differs by genotype. We select 322 single-nucleotide polymorphism-cytosine-phosphate-guanine (SNP-CpG) site pairs for mediation analysis on the basis of proximity and marginal genome-wide association study (GWAS) and epigenome-wide association study (EWAS) significance, and present results from the real-data sample of 407 individuals with complete genotype, methylation, TG levels, and covariate data.

Results: We identified 3 SNP-CpG site pairs with significant interaction effects at a Bonferroni-corrected significance threshold of 1.55E-4. None of the analyzed sites showed significant evidence of mediation. Power analysis by simulation showed that a sample size of at least 19,500 is needed to detect nominally significant indirect effects with true effect sizes equal to the point estimates at the locus with strongest evidence of mediation.

Conclusions: These results suggest that there is stronger evidence for interaction between genotype and methylation on change in triglycerides than for methylation mediating the effect of genotype.
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http://dx.doi.org/10.1186/s12863-018-0635-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6156904PMC
September 2018

Whole exome sequencing study identifies novel rare and common Alzheimer's-Associated variants involved in immune response and transcriptional regulation.

Mol Psychiatry 2020 08 14;25(8):1859-1875. Epub 2018 Aug 14.

McDonnell Genome Institute, Washington University, St. Louis, MO, USA.

The Alzheimer's Disease Sequencing Project (ADSP) undertook whole exome sequencing in 5,740 late-onset Alzheimer disease (AD) cases and 5,096 cognitively normal controls primarily of European ancestry (EA), among whom 218 cases and 177 controls were Caribbean Hispanic (CH). An age-, sex- and APOE based risk score and family history were used to select cases most likely to harbor novel AD risk variants and controls least likely to develop AD by age 85 years. We tested ~1.5 million single nucleotide variants (SNVs) and 50,000 insertion-deletion polymorphisms (indels) for association to AD, using multiple models considering individual variants as well as gene-based tests aggregating rare, predicted functional, and loss of function variants. Sixteen single variants and 19 genes that met criteria for significant or suggestive associations after multiple-testing correction were evaluated for replication in four independent samples; three with whole exome sequencing (2,778 cases, 7,262 controls) and one with genome-wide genotyping imputed to the Haplotype Reference Consortium panel (9,343 cases, 11,527 controls). The top findings in the discovery sample were also followed-up in the ADSP whole-genome sequenced family-based dataset (197 members of 42 EA families and 501 members of 157 CH families). We identified novel and predicted functional genetic variants in genes previously associated with AD. We also detected associations in three novel genes: IGHG3 (p = 9.8 × 10), an immunoglobulin gene whose antibodies interact with β-amyloid, a long non-coding RNA AC099552.4 (p = 1.2 × 10), and a zinc-finger protein ZNF655 (gene-based p = 5.0 × 10). The latter two suggest an important role for transcriptional regulation in AD pathogenesis.
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http://dx.doi.org/10.1038/s41380-018-0112-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6375806PMC
August 2020

Genome-wide meta-analysis of macronutrient intake of 91,114 European ancestry participants from the cohorts for heart and aging research in genomic epidemiology consortium.

Mol Psychiatry 2019 12 9;24(12):1920-1932. Epub 2018 Jul 9.

Department of Clinical Chemistry, Fimlab Laboratories, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland.

Macronutrient intake, the proportion of calories consumed from carbohydrate, fat, and protein, is an important risk factor for metabolic diseases with significant familial aggregation. Previous studies have identified two genetic loci for macronutrient intake, but incomplete coverage of genetic variation and modest sample sizes have hindered the discovery of additional loci. Here, we expanded the genetic landscape of macronutrient intake, identifying 12 suggestively significant loci (P < 1 × 10) associated with intake of any macronutrient in 91,114 European ancestry participants. Four loci replicated and reached genome-wide significance in a combined meta-analysis including 123,659 European descent participants, unraveling two novel loci; a common variant in RARB locus for carbohydrate intake and a rare variant in DRAM1 locus for protein intake, and corroborating earlier FGF21 and FTO findings. In additional analysis of 144,770 participants from the UK Biobank, all identified associations from the two-stage analysis were confirmed except for DRAM1. Identified loci might have implications in brain and adipose tissue biology and have clinical impact in obesity-related phenotypes. Our findings provide new insight into biological functions related to macronutrient intake.
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http://dx.doi.org/10.1038/s41380-018-0079-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6326896PMC
December 2019

Impact of Genetic Determinants of HbA1c on Type 2 Diabetes Risk and Diagnosis.

Curr Diab Rep 2018 06 21;18(8):52. Epub 2018 Jun 21.

Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA, USA.

Purpose Of Review: Glycated hemoglobin (A1c) is used to diagnose type 2 diabetes and monitor glycemic control. Specific genetic variants interfere with A1c and effects/frequencies of some variants vary by ancestry. In this review, we summarize findings from large trans-ethnic meta-analyses of genome-wide association studies (GWAS) of A1c and describe some variants influencing erythrocyte biology and interfering with A1c.

Recent Findings: Recent GWAS meta-analyses have revealed 60 loci associated with A1c in multi-ethnic populations. The main A1c genetic driver in African Americans is rs1050828 (G6PD). Some identified loci are located in/near genes known as monogenic causes of erythrocytic disorders (ANK1, SPTA1) or iron disorders (TMPRSS6, HFE). Uncommon genetic variants (not revealed by GWAS) that are known to cause hemoglobinopathies may also influence A1C levels, partly by interfering with laboratory assays. Specific genetic variants that have a large impact on A1c levels may influence clinical practice, especially in individuals of African descent. Efforts to reveal novel A1c loci should focus on increasing representation of GWAS in non-European ancestries, and on using better genome-wide coverage of uncommon variants that are specific to each population.
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http://dx.doi.org/10.1007/s11892-018-1022-4DOI Listing
June 2018

Whole genome sequence analyses of brain imaging measures in the Framingham Study.

Neurology 2018 01 27;90(3):e188-e196. Epub 2017 Dec 27.

From the Department of Epidemiology (C.S., L.A.C., A.S.B., A.L.D., J.D.), Boston University School of Public Health; Boston University and the NHLBI's Framingham Heart Study (C.L.S., A.N.P., L.A.C., R.S.V., A.S.B., A.L.D., J.D., S.S.); Departments of Neurology (C.L.S., A.S.B., A.L.D., S.S.) and Cardiology, Preventive Medicine & Epidemiology (R.S.V.), Boston University School of Medicine, Boston, MA; Department of Neurology and Center for Neuroscience (C.D.), University of California at Davis; Department of Physiology and Biophysics (J.G.W.), University of Mississippi Medical Center, Jackson; Cardiovascular Health Research Unit (J.C.B.), Department of Medicine, University of Washington, Seattle; and Institute of Molecular Medicine (M.F.), University of Texas Health Science Center, Houston.

Objective: We sought to identify rare variants influencing brain imaging phenotypes in the Framingham Heart Study by performing whole genome sequence association analyses within the Trans-Omics for Precision Medicine Program.

Methods: We performed association analyses of cerebral and hippocampal volumes and white matter hyperintensity (WMH) in up to 2,180 individuals by testing the association of rank-normalized residuals from mixed-effect linear regression models adjusted for sex, age, and total intracranial volume with individual variants while accounting for familial relatedness. We conducted gene-based tests for rare variants using (1) a sliding-window approach, (2) a selection of functional exonic variants, or (3) all variants.

Results: We detected new loci in 1p21 for cerebral volume (minor allele frequency [MAF] 0.005, = 10) and in 16q23 for hippocampal volume (MAF 0.05, = 2.7 × 10). Previously identified associations in 12q24 for hippocampal volume (rs7294919, = 4.4 × 10) and in 17q25 for WMH (rs7214628, = 2.0 × 10) were confirmed. Gene-based tests detected associations ( ≤ 2.3 × 10) in new loci for cerebral (5q13, 8p12, 9q31, 13q12-q13, 15q24, 17q12, 19q13) and hippocampal volumes (2p12) and WMH (3q13, 4p15) including Alzheimer disease- () and Parkinson disease-associated genes (). Pathway analyses evidenced enrichment of associated genes in immunity, inflammation, and Alzheimer disease and Parkinson disease pathways.

Conclusions: Whole genome sequence-wide search reveals intriguing new loci associated with brain measures. Replication of novel loci is needed to confirm these findings.
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http://dx.doi.org/10.1212/WNL.0000000000004820DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5772158PMC
January 2018

Genetic variants associated with earlier age at menopause increase the risk of cardiovascular events in women.

Menopause 2018 04;25(4):451-457

Framingham Heart Study, Framingham, Massachusetts. Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA.

Objective: To better understand the relationship between cardiovascular disease risk and age-at-natural menopause using genetic data.

Methods: Early menopause is associated with cardiovascular disease risk. We constructed a genetic risk score comprising 56 age-at-natural menopause decreasing alleles in men and women from the Framingham Heart Study, the Atherosclerosis Risk in Communities Study, and the Rotterdam Study. If the genetic predisposition to earlier age-at-natural menopause is associated with increased cardiovascular disease risk, it is reasonable to ask whether the risk is shared by men carrying the alleles, despite not experiencing menopause. We estimated the hazard ratio for the score for time to first cardiovascular event. To investigate the possible genetic pleiotropy between age-at-natural menopause and cardiovascular disease, we performed cross-trait linkage disequilibrium score regressions between age-at-natural menopause and cardiovascular disease and risk factors using genome-wide association studies.

Results: Twenty-two thousand five hundred and sixty-eight cardiovascular disease-free participants at baseline were analyzed (9,808 men, 12,760 women). Each additional unit of the genetic propensity to earlier age-at-natural menopause increased the hazard of both cardiovascular disease and cardiac death in women (cardiovascular disease: hazard ratio 1.10 [1.04-1.16], P = 9.7 × 10; cardiac death: 1.12 [1.02-1.24], P = 0.03), whereas no effect was observed for either outcome in men (hazard ratio 0.99 [0.95-1.04], P = 0.71; 1.05 [0.94-1.16], P = 0.34). We found significant negative genetic correlations in women, but not men, between age-at-natural menopause and cardiovascular disease and risk factors.

Conclusion: Genetic variants associated with earlier age-at-natural menopause are associated with increased cardiovascular disease risk in women, but not men, suggesting sex-specific genetic effects on cardiovascular disease risk.
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http://dx.doi.org/10.1097/GME.0000000000001017DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5866156PMC
April 2018

A novel role for ciliary function in atopy: ADGRV1 and DNAH5 interactions.

J Allergy Clin Immunol 2018 05 18;141(5):1659-1667.e11. Epub 2017 Sep 18.

Genetic Variation and Human Diseases Unit, INSERM, Université Paris Diderot, Université Sorbonne Paris Cité, Paris, France.

Background: Atopy, an endotype underlying allergic diseases, has a substantial genetic component.

Objective: Our goal was to identify novel genes associated with atopy in asthma-ascertained families.

Methods: We implemented a 3-step analysis strategy in 3 data sets: the Epidemiological Study on the Genetics and Environment of Asthma (EGEA) data set (1660 subjects), the Saguenay-Lac-Saint-Jean study data set (1138 subjects), and the Medical Research Council (MRC) data set (446 subjects). This strategy included a single nucleotide polymorphism (SNP) genome-wide association study (GWAS), the selection of related gene pairs based on statistical filtering of GWAS results, and text-mining filtering using Gene Relationships Across Implicated Loci and SNP-SNP interaction analysis of selected gene pairs.

Results: We identified the 5q14 locus, harboring the adhesion G protein-coupled receptor V1 (ADGRV1) gene, which showed genome-wide significant association with atopy (rs4916831, meta-analysis P value = 6.8 × 10). Statistical filtering of GWAS results followed by text-mining filtering revealed relationships between ADGRV1 and 3 genes showing suggestive association with atopy (P ≤ 10). SNP-SNP interaction analysis between ADGRV1 and these 3 genes showed significant interaction between ADGRV1 rs17554723 and 2 correlated SNPs (rs2134256 and rs1354187) within the dynein axonemal heavy chain 5 (DNAH5) gene (P = 3.6 × 10 and 6.1 × 10, which met the multiple-testing corrected threshold of 7.3 × 10). Further conditional analysis indicated that rs2134256 alone accounted for the interaction signal with rs17554723.

Conclusion: Because both DNAH5 and ADGRV1 contribute to ciliary function, this study suggests that ciliary dysfunction might represent a novel mechanism underlying atopy. Combining GWAS and epistasis analysis driven by statistical and knowledge-based evidence represents a promising approach for identifying new genes involved in complex traits.
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http://dx.doi.org/10.1016/j.jaci.2017.06.050DOI Listing
May 2018

SigMod: an exact and efficient method to identify a strongly interconnected disease-associated module in a gene network.

Bioinformatics 2017 May;33(10):1536-1544

INSERM, Genetic Variation and Human Diseases Unit, UMR-946, Paris, France.

Motivation: Apart from single marker-based tests classically used in genome-wide association studies (GWAS), network-assisted analysis has become a promising approach to identify a set of genes associated with disease. To date, most network-assisted methods aim at finding genes connected in a background network, whatever the density or strength of their connections. This can hamper the findings as sparse connections are non-robust against noise from either the GWAS results or the network resource.

Results: We present SigMod, a novel and efficient method integrating GWAS results and gene network to identify a strongly interconnected gene module enriched in high association signals. Our method is formulated as a binary quadratic optimization problem, which can be solved exactly through graph min-cut algorithms. Compared to existing methods, SigMod has several desirable properties: (i) edge weights quantifying confidence of connections between genes are taken into account, (ii) the selection path can be computed rapidly, (iii) the identified gene module is strongly interconnected, hence includes genes of high functional relevance, and (iv) the method is robust against noise from either the GWAS results or the network resource. We applied SigMod to both simulated and real data. It was found to outperform state-of-the-art network-assisted methods in identifying disease-associated genes. When SigMod was applied to childhood-onset asthma GWAS results, it successfully identified a gene module enriched in consistently high association signals and made of functionally related genes that are biologically relevant for asthma.

Availability And Implementation: An R package SigMod is available at: https://github.com/YuanlongLiu/SigMod.

Contact: [email protected]

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btx004DOI Listing
May 2017

Genes Involved in Interleukin-1 Receptor Type II Activities Are Associated With Asthmatic Phenotypes.

Allergy Asthma Immunol Res 2016 Sep;8(5):466-70

Département des sciences fondamentales, Université du Québec à Chicoutimi, Chicoutimi, Canada.

Purpose: Interleukin-1 (IL-1) plays a key role in inflammation and immunity and its decoy receptor, IL-1R2, has been implicated in transcriptomic and genetic studies of asthma.

Methods: Two large asthma family collections, the French-Canadian Saguenay-Lac-St-Jean (SLSJ) study and the French Epidemiological Study on the Genetics and Environment of Asthma (EGEA), were used to investigate the association of SNPs in 10 genes that modulate IL-1R2 activities with asthma, allergic asthma, and atopy. Gene-gene interactions were also tested.

Results: One SNP in BACE2 was associated with allergic asthma in the SLSJ study and replicated in the EGEA study before statistical correction for multiple testing. Additionally, two SNPs in the MMP2 gene were replicated in both studies prior to statistical correction and reached significance in the combined analysis. Moreover, three gene-gene interactions also survived statistical correction in the combined analyses (BACE1-IL1RAP in asthma and allergic asthma and IL1R1-IL1RAP in atopy).

Conclusions: Our results highlight the relevance of genes involved in the IL-1R2 activity in the context of asthma and asthma-related traits.
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http://dx.doi.org/10.4168/aair.2016.8.5.466DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4921702PMC
September 2016

Identification of a new locus at 16q12 associated with time to asthma onset.

J Allergy Clin Immunol 2016 10 6;138(4):1071-1080. Epub 2016 Apr 6.

Inserm, UMR-946, Paris, France; Université Paris Diderot, Sorbonne Paris Cité, Institut Universitaire d'Hématologie, Paris, France. Electronic address:

Background: Asthma is a heterogeneous disease in which age of onset plays an important role.

Objective: We sought to identify the genetic variants associated with time to asthma onset (TAO).

Methods: We conducted a large-scale meta-analysis of 9 genome-wide association studies of TAO (total of 5462 asthmatic patients with a broad range of age of asthma onset and 8424 control subjects of European ancestry) performed by using survival analysis techniques.

Results: We detected 5 regions associated with TAO at the genome-wide significant level (P < 5 × 10). We evidenced a new locus in the 16q12 region (near cylindromatosis turban tumor syndrome gene [CYLD]) and confirmed 4 asthma risk regions: 2q12 (IL-1 receptor-like 1 [IL1RL1]), 6p21 (HLA-DQA1), 9p24 (IL33), and 17q12-q21 (zona pellucida binding protein 2 [ZPBP2]-gasdermin A [GSDMA]). Conditional analyses identified 2 distinct signals at 9p24 (both upstream of IL33) and 17q12-q21 (near ZPBP2 and within GSDMA). Together, these 7 distinct loci explained 6.0% of the variance in TAO. In addition, we showed that genetic variants at 9p24 and 17q12-q21 were strongly associated with an earlier onset of childhood asthma (P ≤ .002), whereas the 16q12 single nucleotide polymorphism was associated with later asthma onset (P = .04). A high burden of disease risk alleles at these loci was associated with earlier age of asthma onset (4 vs 9-12 years, P = 10).

Conclusion: The new susceptibility region for TAO at 16q12 harbors variants that correlate with the expression of CYLD and nucleotide-binding oligomerization domain 2 (NOD2), 2 strong candidates for asthma. This study demonstrates that incorporating the variability of age of asthma onset in asthma modeling is a helpful approach in the search for disease susceptibility genes.
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http://dx.doi.org/10.1016/j.jaci.2016.03.018DOI Listing
October 2016
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