Publications by authors named "Daniel E Weeks"

136 Publications

An exploratory study of white blood cell proportions across preeclamptic and normotensive pregnancy by self-identified race in individuals with overweight or obesity.

Hypertens Pregnancy 2021 Oct 26:1-10. Epub 2021 Oct 26.

Department of Health Promotion and Development, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.

Objective: Examine white blood cell (WBC) proportions across preeclamptic (n = 28 cases) and normotensive (n = 28 controls) pregnancy in individuals with overweight/obesity.

Methods: WBC proportions were inferred from genome-wide DNA methylation data and compared by case/control status and self-identified race.

Results: In Trimester 1, ean B cell proportions were suggestively lower in cases in the overall sample and significantly lower in White participants but not in Black participants. More significant WBC proportion changes were observed across normotensive than preeclamptic pregnancy.

Conclusions: These findings in a small sample demonstrate need for additional studies investigating the relationship between self-identified race and WBCs in pregnancy.
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http://dx.doi.org/10.1080/10641955.2021.1987453DOI Listing
October 2021

A murine model of the human CREBRFR457Q obesity-risk variant does not influence energy or glucose homeostasis in response to nutritional stress.

PLoS One 2021 14;16(9):e0251895. Epub 2021 Sep 14.

Division of Endocrinology and Metabolism, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America.

Obesity and diabetes have strong heritable components, yet the genetic contributions to these diseases remain largely unexplained. In humans, a missense variant in Creb3 regulatory factor (CREBRF) [rs373863828 (p.Arg457Gln); CREBRFR457Q] is strongly associated with increased odds of obesity but decreased odds of diabetes. Although virtually nothing is known about CREBRF's mechanism of action, emerging evidence implicates it in the adaptive transcriptional response to nutritional stress downstream of TORC1. The objectives of this study were to generate a murine model with knockin of the orthologous variant in mice (CREBRFR458Q) and to test the hypothesis that this CREBRF variant promotes obesity and protects against diabetes by regulating energy and glucose homeostasis downstream of TORC1. To test this hypothesis, we performed extensive phenotypic analysis of CREBRFR458Q knockin mice at baseline and in response to acute (fasting/refeeding), chronic (low- and high-fat diet feeding), and extreme (prolonged fasting) nutritional stress as well as with pharmacological TORC1 inhibition, and aging to 52 weeks. The results demonstrate that the murine CREBRFR458Q model of the human CREBRFR457Q variant does not influence energy/glucose homeostasis in response to these interventions, with the exception of possible greater loss of fat relative to lean mass with age. Alternative preclinical models and/or studies in humans will be required to decipher the mechanisms linking this variant to human health and disease.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0251895PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8439463PMC
November 2021

CHIT: an allele-specific method for testing the association between molecular quantitative traits and phenotype-genotype interaction.

Bioinformatics 2021 Jul 29. Epub 2021 Jul 29.

Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, 15261, USA.

Motivation: Allele specific differences in molecular traits can be obtained from next generation sequencing data and could potentially improve testing power, but such information is usually overlooked in association studies. Furthermore, the variation of molecular quantitative traits (e.g., gene expression) could result from the interaction effect of genotypes and phenotypes, but it is challenging to identify such interaction signals in complex disease studies in humans due to small genetic effect sizes and/or small sample sizes.

Results: We develop a novel statistical method, the combined haplotype interaction test (CHIT), which tests for association between molecular quantitative traits and phenotype-genotype interactions by modeling the total read counts and allele-specific reads in a target region. CHIT can be used as a supplementary analysis to the regular linear interaction regression. In our simulations, CHIT obtains non-inflated type I error rates, and it has higher power than a standard interaction quantitative trait locus approach based on linear regression models. Finally, we illustrate CHIT by testing associations between gene expression obtained by RNA-seq and the interaction of SNPs and atopy status from a study of childhood asthma in Puerto Ricans, and results demonstrate that CHIT could be more powerful than a standard linear interaction expression quantitative trait loci (eQTL) approach.

Availability: The CHIT algorithm has been implemented in Python. The source code and documentation are available and can be downloaded from https://github.com/QiYanPitt/CHIT.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btab554DOI Listing
July 2021

Gene-Based Association Testing of Dichotomous Traits With Generalized Functional Linear Mixed Models Using Extended Pedigrees: Applications to Age-Related Macular Degeneration.

J Am Stat Assoc 2021 28;116(534):531-545. Epub 2020 Jul 28.

Computational and Statistical Genomics Branch, National Human Genome Research Institute, NIH, Baltimore, MD.

Genetics plays a role in age-related macular degeneration (AMD), a common cause of blindness in the elderly. There is a need for powerful methods for carrying out region-based association tests between a dichotomous trait like AMD and genetic variants on family data. Here, we apply our new generalized functional linear mixed models (GFLMM) developed to test for gene-based association in a set of AMD families. Using common and rare variants, we observe significant association with two known AMD genes: and . Using rare variants, we find suggestive signals in four genes: , , , and . Intriguingly, is down-regulated in AMD aqueous humor, and deficiency leads to retinal inflammation and increased vulnerability to oxidative stress. These findings were made possible by our GFLMM which model the effect of a major gene as a fixed mean, the polygenic contributions as a random variation, and the correlation of pedigree members by kinship coefficients. Simulations indicate that the GFLMM likelihood ratio tests (LRTs) accurately control the Type I error rates. The LRTs have similar or higher power than existing retrospective kernel and burden statistics. Our GFLMM-based statistics provide a new tool for conducting family-based genetic studies of complex diseases. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.
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http://dx.doi.org/10.1080/01621459.2020.1799809DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8315575PMC
July 2020

Acute DNA Methylation Trajectories in Cerebrospinal Fluid and Associations With Outcomes Following Severe Traumatic Brain Injury in Adults.

Neurorehabil Neural Repair 2021 Sep 25;35(9):790-800. Epub 2021 Jun 25.

Department of Human Genetics, 51303University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA, USA.

. Epigenetic biomarkers have the potential to explain outcome heterogeneity following traumatic brain injury (TBI) but are largely unexplored. . This exploratory pilot study characterized () DNA methylation trajectories following severe TBI. . DNA methylation trajectories in cerebrospinal fluid (CSF) over the first 5 days following severe TBI in 112 adults were examined in association with 3- and 12-month outcomes. . Group-based trajectory analysis revealed low and high DNA methylation groups at two cytosine-phosphate-guanine (CpG) targets that showed suggestive associations ( < .05) with outcomes. Membership in the high DNA methylation groups was associated with better outcomes after controlling for age, sex, and injury severity. Associations of age × trajectory group interactions with outcomes at a third CpG site revealed a pattern of the same or better outcomes with higher ages in the high DNA methylation group and worse outcomes with higher ages in the low DNA methylation group. . Although no observed associations met the empirical significance threshold after correcting for multiple comparisons, suggestive associations of the main effect models were consistent in their direction of effect and were observed across two CpG sites and two outcome time points. Results suggest that higher acute CSF DNA methylation may promote recovery following severe TBI in adults, and this effect may be more robust with higher age. While the results require replication in larger and racially diverse independent samples, DNA methylation may serve as an early postinjury biomarker helping to explain outcome heterogeneity following TBI.
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http://dx.doi.org/10.1177/15459683211028245DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8546867PMC
September 2021

Genome-Wide Association Studies-Based Machine Learning for Prediction of Age-Related Macular Degeneration Risk.

Transl Vis Sci Technol 2021 02;10(2):29

Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.

Purpose: Because age-related macular degeneration (AMD) is a progressive disorder and advanced AMD is currently hard to cure, an accurate and informative prediction of a person's AMD risk using genetic information is desirable for early diagnosis and potential individualized clinical management. The objective of this study was to develop and validate novel prediction models for AMD risk using large genome-wide association studies datasets with different machine learning approaches.

Methods: Genotype data from 32,215 Caucasian individuals with age of ≥50 years from the International AMD Genomics Consortium in dbGaP were used to establish and test prediction models for AMD risk. Four different machine learning approaches-neural network, lasso regression, support vector machine, and random forest-were implemented. A standard logistic regression model using a genetic risk score was also considered.

Results: All machine learning-based methods achieved satisfactory performance for predicting advanced AMD cases (vs. normal controls) (area under the curve = 0.81-0.82, Brier score = 0.17-0.18 in a separate test dataset) and any stage AMD (vs. normal controls) (area under the curve = 0.78-0.79, Brier score = 0.18-0.20 in a separate test dataset). The prediction performance was further validated in an independent dataset of 783 subjects from UK Biobank (area under the curve = 0.67).

Conclusions: By applying multiple state-of-art machine learning approaches on large AMD genome-wide association studies datasets, the predictive models we established can provide an accurate estimation of an individual's AMD risk profile based on genetic information along with age. The online prediction interface is available at: https://yanq.shinyapps.io/no_vs_amd_NN/.

Translational Relevance: The accurate and individualized risk prediction model interface will greatly improve early diagnosis and enhance tailored clinical management of AMD.
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http://dx.doi.org/10.1167/tvst.10.2.29DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7900884PMC
February 2021

An Exploratory Study of Epigenetic Age in Preeclamptic and Normotensive Pregnancy Reveals Differences by Self-Reported Race but Not Pregnancy Outcome.

Reprod Sci 2021 12 20;28(12):3519-3528. Epub 2021 Apr 20.

Department of Health Promotion and Development, School of Nursing, University of Pittsburgh, Pittsburgh, PA, USA.

Preeclampsia is a leading cause of maternal and neonatal morbidity and mortality. Chronological age and race are associated with preeclampsia, but the role of these factors is not entirely understood. We hypothesized that DNA methylation age, a measure of biological age, would be higher in individuals with preeclampsia than in individuals with normotensive pregnancy and that DNA methylation age would differ by race across pregnancy. This was a longitudinal, exploratory study of 56 pregnant individuals (n = 28 preeclampsia cases and n = 28 normotensive controls). Genome-wide DNA methylation data were generated from trimester-specific peripheral blood samples. DNA methylation age was estimated using the "Improved Precision" clock, and ∆age, the difference between DNA methylation age and chronological age, was computed. DNA methylation age was compared with chronological age using Pearson correlations. The relationships between ∆age and preeclampsia status, self-reported race, and covariates were tested using multiple linear regression and performed both with and without consideration of cell-type heterogeneity. We observed strong correlation between chronological age and DNA methylation age across pregnancy, with significantly stronger correlation observed in White participants than in Black participants. We observed no association between ∆age and preeclampsia status. However, ∆age was higher in participants with higher pre-pregnancy body mass index in trimester 1 and lower in Black participants than in White participants in trimesters 2 and 3. Observations were largely consistent when controlling for cell-type heterogeneity. Our findings in a small sample support the need for additional studies to investigate the relationship between race and biological age, which could provide further insight into racial disparities across pregnancy. However, this study does not support an association between ∆age and preeclampsia status.
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http://dx.doi.org/10.1007/s43032-021-00575-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8526649PMC
December 2021

A System for Phenotype Harmonization in the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) Program.

Am J Epidemiol 2021 10;190(10):1977-1992

Genotype-phenotype association studies often combine phenotype data from multiple studies to increase statistical power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data-set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data-sharing mechanisms. This system was developed for the National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine (TOPMed) program, which is generating genomic and other -omics data for more than 80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants (recruited in 1948-2012) from up to 17 studies per phenotype. Here we discuss challenges in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include 1) the software code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify, or extend these harmonizations to additional studies, and 2) the results of labeling thousands of phenotype variables with controlled vocabulary terms.
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http://dx.doi.org/10.1093/aje/kwab115DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8485147PMC
October 2021

AMD Genetics: Methods and Analyses for Association, Progression, and Prediction.

Adv Exp Med Biol 2021 ;1256:191-200

Division of Pulmonary Medicine, Department of Pediatrics, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, PA, USA.

Age-related macular degeneration (AMD) is a multifactorial neurodegenerative disease, which is a leading cause of vision loss among the elderly in the developed countries. As one of the most successful examples of genome-wide association study (GWAS), a large number of genetic studies have been conducted to explore the genetic basis for AMD and its progression, of which over 30 loci were identified and confirmed. In this chapter, we review the recent development and findings of GWAS for AMD risk and progression. Then, we present emerging methods and models for predicting AMD development or its progression using large-scale genetic data. Finally, we discuss a set of novel statistical and analytical methods that were recently developed to tackle the challenges such as analyzing bilateral correlated eye-level outcomes that are subject to censoring with high-dimensional genetic data. Future directions for analytical studies of AMD genetics are also proposed.
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http://dx.doi.org/10.1007/978-3-030-66014-7_7DOI Listing
April 2021

Chromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices.

Nat Commun 2021 04 12;12(1):2182. Epub 2021 Apr 12.

Division of Cardiology, George Washington University School of Medicine and Healthcare Sciences, Washington, DC, USA.

Autosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 × 10), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 × 10), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 × 10). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids.
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http://dx.doi.org/10.1038/s41467-021-22339-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8042019PMC
April 2021

Robust, flexible, and scalable tests for Hardy-Weinberg equilibrium across diverse ancestries.

Genetics 2021 05;218(1)

Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA.

Traditional Hardy-Weinberg equilibrium (HWE) tests (the χ2 test and the exact test) have long been used as a metric for evaluating genotype quality, as technical artifacts leading to incorrect genotype calls often can be identified as deviations from HWE. However, in data sets composed of individuals from diverse ancestries, HWE can be violated even without genotyping error, complicating the use of HWE testing to assess genotype data quality. In this manuscript, we present the Robust Unified Test for HWE (RUTH) to test for HWE while accounting for population structure and genotype uncertainty, and to evaluate the impact of population heterogeneity and genotype uncertainty on the standard HWE tests and alternative methods using simulated and real sequence data sets. Our results demonstrate that ignoring population structure or genotype uncertainty in HWE tests can inflate false-positive rates by many orders of magnitude. Our evaluations demonstrate different tradeoffs between false positives and statistical power across the methods, with RUTH consistently among the best across all evaluations. RUTH is implemented as a practical and scalable software tool to rapidly perform HWE tests across millions of markers and hundreds of thousands of individuals while supporting standard VCF/BCF formats. RUTH is publicly available at https://www.github.com/statgen/ruth.
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http://dx.doi.org/10.1093/genetics/iyab044DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8128395PMC
May 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

ECHS1 disease in two unrelated families of Samoan descent: Common variant - rare disorder.

Am J Med Genet A 2021 01 28;185(1):157-167. Epub 2020 Oct 28.

Division of Metabolic Disorders, CHOC Children's Hospital, Orange, California, USA.

Mutations in the short-chain enoyl-CoA hydratase (SCEH) gene, ECHS1, cause a rare autosomal recessive disorder of valine catabolism. Patients usually present with developmental delay, regression, dystonia, feeding difficulties, and abnormal MRI with bilateral basal ganglia involvement. We present clinical, biochemical, molecular, and functional data for four affected patients from two unrelated families of Samoan descent with identical novel compound heterozygous mutations. Family 1 has three affected boys while Family 2 has an affected daughter, all with clinical and MRI findings of Leigh syndrome and intermittent episodes of acidosis and ketosis. WES identified a single heterozygous variant in ECHS1 at position c.832G > A (p.Ala278Thr). However, western blot revealed significantly reduced ECHS1 protein for all affected family members. Decreased SCEH activity in fibroblasts and a mild increase in marker metabolites in urine further supported ECHS1 as the underlying gene defect. Additional investigations at the DNA (aCGH, WGS) and RNA (qPCR, RT-PCR, RNA-Seq, RNA-Array) level identified a silent, common variant at position c.489G > A (p.Pro163=) as the second mutation. This substitution, present at high frequency in the Samoan population, is associated with decreased levels of normally spliced mRNA. To our understanding, this is the first report of a novel, hypomorphic allele c.489G > A (p.Pro163=), associated with SCEH deficiency.
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http://dx.doi.org/10.1002/ajmg.a.61936DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7746601PMC
January 2021

Inherited causes of clonal haematopoiesis in 97,691 whole genomes.

Nature 2020 10 14;586(7831):763-768. Epub 2020 Oct 14.

Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA.

Age is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown. The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer and coronary heart disease-this phenomenon is termed clonal haematopoiesis of indeterminate potential (CHIP). Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIP driver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues.
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http://dx.doi.org/10.1038/s41586-020-2819-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7944936PMC
October 2020

Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale.

Nat Genet 2020 09 24;52(9):969-983. Epub 2020 Aug 24.

Department of Data Sciences, Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Large-scale whole-genome sequencing studies have enabled the analysis of rare variants (RVs) associated with complex phenotypes. Commonly used RV association tests have limited scope to leverage variant functions. We propose STAAR (variant-set test for association using annotation information), a scalable and powerful RV association test method that effectively incorporates both variant categories and multiple complementary annotations using a dynamic weighting scheme. For the latter, we introduce 'annotation principal components', multidimensional summaries of in silico variant annotations. STAAR accounts for population structure and relatedness and is scalable for analyzing very large cohort and biobank whole-genome sequencing studies of continuous and dichotomous traits. We applied STAAR to identify RVs associated with four lipid traits in 12,316 discovery and 17,822 replication samples from the Trans-Omics for Precision Medicine Program. We discovered and replicated new RV associations, including disruptive missense RVs of NPC1L1 and an intergenic region near APOC1P1 associated with low-density lipoprotein cholesterol.
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http://dx.doi.org/10.1038/s41588-020-0676-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7483769PMC
September 2020

Genome-wide association studies in Samoans give insight into the genetic architecture of fasting serum lipid levels.

J Hum Genet 2021 Feb 5;66(2):111-121. Epub 2020 Aug 5.

Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.

The current understanding of the genetic architecture of lipids has largely come from genome-wide association studies (GWAS). To date, few GWAS have examined the genetic architecture of lipids in Polynesians, and none have in Samoans, whose unique population history, including many population bottlenecks, may provide insight into the biological foundations of variation in lipid levels. Here we performed a GWAS of four fasting serum lipid levels: total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and triglycerides (TG) in a sample of 2849 Samoans, with validation genotyping for associations in a replication cohort comprising 1798 Samoans and American Samoans. We identified multiple genome-wide significant associations (P < 5 × 10) previously seen in other populations-APOA1 with TG, CETP with HDL, and APOE with TC and LDL-and several suggestive associations (P < 1 × 10), including an association of variants downstream of MGAT1 and RAB21 with HDL. However, we observed different association signals for variants near APOE than what has been previously reported in non-Polynesian populations. The association with several known lipid loci combined with the newly identified associations with variants near MGAT1 and RAB21 suggest that while some of the genetic architecture of lipids is shared between Samoans and other populations, part of the genetic architecture may be Polynesian-specific.
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http://dx.doi.org/10.1038/s10038-020-0816-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785639PMC
February 2021

Exploring the Paradoxical Relationship of a Creb 3 Regulatory Factor Missense Variant With Body Mass Index and Diabetes Among Samoans: Protocol for the Soifua Manuia (Good Health) Observational Cohort Study.

JMIR Res Protoc 2020 Jul 23;9(7):e17329. Epub 2020 Jul 23.

Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, United States.

Background: The prevalence of obesity and diabetes in Samoa, like many other Pacific Island nations, has reached epidemic proportions. Although the etiology of these conditions can be largely attributed to the rapidly changing economic and nutritional environment, a recently identified genetic variant, rs373863828 (CREB 3 regulatory factor, CREBRF: c.1370G>A p.[R457Q]) is associated with increased odds of obesity, but paradoxically, decreased odds of diabetes.

Objective: The overarching goal of the Soifua Manuia (Good Health) study was to precisely characterize the association of the CREBRF variant with metabolic (body composition and glucose homeostasis) and behavioral traits (dietary intake, physical activity, sleep, and weight control behaviors) that influence energy homeostasis in 500 adults.

Methods: A cohort of adult Samoans who participated in a genome-wide association study of adiposity in Samoa in 2010 was followed up, based on the presence or absence of the CREBRF variant, between August 2017 and March 2019. Over a period of 7-10 days, each participant completed the main study protocol, which consisted of anthropometric measurements (weight, height, circumferences, and skinfolds), body composition assessment (bioelectrical impedance and dual-energy x-ray absorptiometry), point-of-care glycated hemoglobin measurement, a fasting blood draw and oral glucose tolerance test, urine collection, blood pressure measurement, hand grip strength measurement, objective physical activity and sleep apnea monitoring, and questionnaire measures (eg, health interview, cigarette and alcohol use, food frequency questionnaire, socioeconomic position, stress, social support, food and water insecurity, sleep, body image, and dietary preferences). In January 2019, a subsample of the study participants (n=118) completed a buttock fat biopsy procedure to collect subcutaneous adipose tissue samples.

Results: Enrollment of 519 participants was completed in March 2019. Data analyses are ongoing, with results expected in 2020 and 2021.

Conclusions: While the genetic variant rs373863828, in CREBRF, has the largest known effect size of any identified common obesity gene, very little is currently understood about the mechanisms by which it confers increased odds of obesity but paradoxically lowered odds of type 2 diabetes. The results of this study will provide insights into how the gene functions on a whole-body level, which could provide novel targets to prevent or treat obesity, diabetes, and associated metabolic disorders. This study represents the human arm of a comprehensive and integrated approach involving humans as well as preclinical models that will provide novel insights into metabolic disease.

International Registered Report Identifier (irrid): RR1-10.2196/17329.
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http://dx.doi.org/10.2196/17329DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7413272PMC
July 2020

Methylation Data Processing Protocol and Comparison of Blood and Cerebral Spinal Fluid Following Aneurysmal Subarachnoid Hemorrhage.

Front Genet 2020 26;11:671. Epub 2020 Jun 26.

Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, United States.

One challenge in conducting DNA methylation-based epigenome-wide association study (EWAS) is the appropriate cleaning and quality-checking of data to minimize biases and experimental artifacts, while simultaneously retaining potential biological signals. These issues are compounded in studies that include multiple tissue types, and/or tissues for which reference data are unavailable to assist in adjusting for cell-type mixture, for example cerebral spinal fluid (CSF). For our study that evaluated blood and CSF taken from aneurysmal subarachnoid hemorrhage (aSAH) patients, we developed a protocol to clean and quality-check genome-wide methylation levels and compared the methylomic profiles of the two tissues to determine whether blood is a suitable surrogate for CSF. CSF samples were collected from 279 aSAH patients longitudinally during the first 14 days of hospitalization, and a subset of 88 of these patients also provided blood samples within the first 2 days. Quality control (QC) procedures included identification and exclusion of poor performing samples and low-quality probes, functional normalization, and correction for cell-type heterogeneity via surrogate variable analysis (SVA). Significant differences in rates of poor sample performance was observed between blood (1.1% failing QC) and CSF (9.12% failing QC; = 0.003). Functional normalization increased the concordance of methylation values among technical replicates in both CSF and blood. SVA improved the asymptotic behavior of the test of association in a simulated EWAS under the null hypothesis. To determine the suitability of blood as a surrogate for CSF, we calculated the correlations of adjusted methylation values at each CpG between blood and CSF globally and by genomic regions. Overall, mean within-CpG correlation was low ( < 0.26), suggesting that blood is not a suitable surrogate for global methylation in CSF. However, differences in the magnitude of the correlation were observed by genomic region (CpG island, shore, shelf, open sea; < 0.001 for all) and orientation with respect to nearby genes (3' UTR, transcription start site, exon, body, 5' UTR; < 0.01 for all). In conclusion, the correlation analysis and QC pipelines indicated that DNA extracted from blood was not, overall, a suitable surrogate for DNA from CSF in aSAH methylomic studies.
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http://dx.doi.org/10.3389/fgene.2020.00671DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7332758PMC
June 2020

Evolutionary history of modern Samoans.

Proc Natl Acad Sci U S A 2020 04 14;117(17):9458-9465. Epub 2020 Apr 14.

Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201;

Archaeological studies estimate the initial settlement of Samoa at 2,750 to 2,880 y ago and identify only limited settlement and human modification to the landscape until about 1,000 to 1,500 y ago. At this point, a complex history of migration is thought to have begun with the arrival of people sharing ancestry with Near Oceanic groups (i.e., Austronesian-speaking and Papuan-speaking groups), and was then followed by the arrival of non-Oceanic groups during European colonialism. However, the specifics of this peopling are not entirely clear from the archaeological and anthropological records, and is therefore a focus of continued debate. To shed additional light on the Samoan population history that this peopling reflects, we employ a population genetic approach to analyze 1,197 Samoan high-coverage whole genomes. We identify population splits between the major Samoan islands and detect asymmetrical gene flow to the capital city. We also find an extreme bottleneck until about 1,000 y ago, which is followed by distinct expansions across the islands and subsequent bottlenecks consistent with European colonization. These results provide for an increased understanding of Samoan population history and the dynamics that inform it, and also demonstrate how rapid demographic processes can shape modern genomes.
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http://dx.doi.org/10.1073/pnas.1913157117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7196816PMC
April 2020

Deep-learning-based Prediction of Late Age-Related Macular Degeneration Progression.

Nat Mach Intell 2020 Feb 14;2(2):141-150. Epub 2020 Feb 14.

Division of Pulmonary Medicine, Department of Pediatrics, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, PA.

Both genetic and environmental factors influence the etiology of age-related macular degeneration (AMD), a leading cause of blindness. AMD severity is primarily measured by fundus images and recently developed machine learning methods can successfully predict AMD progression using image data. However, none of these methods have utilized both genetic and image data for predicting AMD progression. Here we jointly used genotypes and fundus images to predict an eye as having progressed to late AMD with a modified deep convolutional neural network (CNN). In total, we used 31,262 fundus images and 52 AMD-associated genetic variants from 1,351 subjects from the Age-Related Eye Disease Study (AREDS) with disease severity phenotypes and fundus images available at baseline and follow-up visits over a period of 12 years. Our results showed that fundus images coupled with genotypes could predict late AMD progression with an averaged area under the curve (AUC) value of 0.85 (95%CI: 0.83-0.86). The results using fundus images alone showed an averaged AUC of 0.81 (95%CI: 0.80-0.83). We implemented our model in a cloud-based application for individual risk assessment.
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http://dx.doi.org/10.1038/s42256-020-0154-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7153739PMC
February 2020

Genetic Variability in the Iron Homeostasis Pathway and Patient Outcomes After Aneurysmal Subarachnoid Hemorrhage.

Neurocrit Care 2020 12;33(3):749-758

Department of Health Promotion and Development, School of Nursing, University of Pittsburgh, 440 Victoria Building, 3500 Victoria Street, Pittsburgh, PA, 15261, USA.

Background/objective: Iron can be detrimental to most tissues both in excess and in deficiency. The brain in particular is highly susceptible to the consequences of excessive iron, especially during blood brain barrier disruption after injury. Preliminary evidence suggests that iron homeostasis is important during recovery after neurologic injury; therefore, the exploration of genetic variability in genes involved in iron homeostasis is an important area of patient outcomes research. The purpose of this study was to examine the relationship between tagging single nucleotide polymorphisms (SNPs) in candidate genes related to iron homeostasis and acute and long-term patient outcomes after aneurysmal subarachnoid hemorrhage (aSAH).

Methods: This study was a longitudinal, observational, candidate gene association study of participants with aSAH that used a two-tier design including tier 1 (discovery, n = 197) and tier 2 (replication, n = 277). Participants were followed during the acute outcome phase for development of cerebral vasospasm and delayed cerebral ischemia (DCI) and during the long-term outcome phase for death and gross functional outcome using the Glasgow Outcome Scale (GOS; poor = 1-3). Genetic association analyses were performed using a logistic regression model adjusted for age, sex, and Fisher grade. Approximate Bayes factors (ABF) and Bayesian false discovery probabilities (BFDP) were used to prioritize and interpret results.

Results: In tier 1, 235 tagging SNPs in 28 candidate genes were available for analysis and 26 associations (20 unique SNPs in 12 genes) were nominated for replication in tier 2. In tier 2, we observed an increase in evidence of association for three associations in the ceruloplasmin (CP) and cubilin (CUBN) genes. We observed an association of rs17838831 (CP) with GOS at 3 months (tier 2 results, odds ratio [OR] = 2.10, 95% confidence interval [CI] = 1.14-3.86, p = 0.018, ABF = 0.52, and BFDP = 70.8%) and GOS at 12 months (tier 2 results, OR = 1.86, 95% CI 0.98-3.52, p = 0.058, ABF = 0.72, and BFDP = 77.3%) as well as rs10904850 (CUBN) with DCI (tier 2 results, OR = 0.70, 95% CI 0.48-1.02, p = 0.064, ABF = 0.59, and BFDP = 71.8%).

Conclusions: Among the genes examined, our findings support a role for CP and CUBN in patient outcomes after aSAH. In an effort to translate these findings into clinical utility and improve outcomes after aSAH, additional research is needed to examine the functional roles of these genes after aSAH.
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http://dx.doi.org/10.1007/s12028-020-00961-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7541432PMC
December 2020

A missense variant in CREBRF is associated with taller stature in Samoans.

Am J Hum Biol 2020 11 19;32(6):e23414. Epub 2020 Mar 19.

Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.

Objectives: Studies have demonstrated that rs373863828, a missense variant in CREBRF, is associated with a number of anthropometric traits including body mass index (BMI), obesity, percent body fat, hip circumference, and abdominal circumference. Given the biological relationship between height and adiposity, we hypothesized that the effect of this variant on BMI might be due in part to an association of this variant with height.

Methods: We tested the hypothesis that minor allele of rs373863828 is associated with height in a Samoan population in two adult cohorts and in a separate cohort of children (age 5-18 years old) using linear mixed modeling.

Results: We found evidence of a strong relationship between rs373863828 and greater mean height in Samoan adults (0.77 cm greater average height for each copy of the minor allele) with the same direction of effect in Samoan children.

Conclusions: These results suggest that the missense variant rs373863828 in CREBRF, first identified through an association with larger BMI, may be related to an underlying biological mechanism affecting overall body size including stature.
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http://dx.doi.org/10.1002/ajhb.23414DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7501196PMC
November 2020

Transcriptome-wide and differential expression network analyses of childhood asthma in nasal epithelium.

J Allergy Clin Immunol 2020 09 20;146(3):671-675. Epub 2020 Feb 20.

Division of Pulmonary Medicine, Department of Pediatrics, UPMC Children's Hospital of Pittsburgh, Pittsburgh, Pa; University of Pittsburgh School of Medicine, Pittsburgh, Pa. Electronic address:

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http://dx.doi.org/10.1016/j.jaci.2020.02.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7438239PMC
September 2020

Genetic Variability and Trajectories of DNA Methylation May Support a Role for HAMP in Patient Outcomes After Aneurysmal Subarachnoid Hemorrhage.

Neurocrit Care 2020 04;32(2):550-563

Department of Health Promotion and Development, School of Nursing, University of Pittsburgh, 440 Victoria Building, 3500 Victoria Street, Pittsburgh, PA, 15261, USA.

Background/objective: Preclinical evidence suggests that iron homeostasis is an important biological mechanism following aneurysmal subarachnoid hemorrhage (aSAH); however, this concept is underexplored in humans. This study examined the relationship between patient outcomes following aSAH and genetic variants and DNA methylation in the hepcidin gene (HAMP), a key regulator of iron homeostasis.

Methods: In this exploratory, longitudinal observational study, participants with verified aSAH were monitored for acute outcomes including cerebral vasospasm (CV) and delayed cerebral ischemia (DCI) and evaluated post-discharge at 3 and 12 months for long-term outcomes of death and functional status using the Modified Rankin Scale (mRS; poor = 3-6) and Glasgow Outcome Scale (GOS; poor = 1-3). Participants were genotyped for two genetic variants, and DNA methylation data were collected from serial cerebrospinal fluid over 14 days post-aSAH at eight methylation sites within HAMP. Participants were grouped based on their site-specific DNA methylation trajectory, with and without correcting for cell-type heterogeneity (CTH), and the associations between genetic variants and inferred DNA methylation trajectory groups and patient outcomes were tested. To correct for multiple testing, an empirical significance threshold was computed using permutation testing.

Results: Genotype data for rs10421768 and rs7251432 were available for 241 and 371 participants, respectively, and serial DNA methylation data were available for 260 participants. Acute outcome prevalence included CV in 45% and DCI in 37.1% of the overall sample. Long-term outcome prevalence at 3 and 12 months included poor GOS in 23% and 21%, poor mRS in 31.6% and 27.3%, and mortality in 15.1% and 18.2%, respectively, in the overall sample. Being homozygous for the rs7251432 variant allele was significantly associated with death at 3 months (p = 0.003) and was the only association identified that passed adjustment for multiple testing mentioned above. Suggestive associations (defined as trending toward significance, p value < 0.05, but not meeting empirical significance thresholds) were identified between the homozygous variant allele for rs7251432 and poor GOS and mRS at 3 months (both p = 0.04) and death at 12 months (p = 0.02). For methylation trajectory groups, no associations remained significant after correction for multiple testing. However, for methylation trajectory groups not adjusted for CTH, suggestive associations were identified between cg18149657 and poor GOS and mRS at 3 months (p = 0.003 and p = 0.04, respectively) and death at 3 months (p = 0.04), and between cg26283059 and DCI (p = 0.01). For methylation trajectory groups adjusted for CTH, suggestive associations were identified between cg02131995 and good mRS at 12 months (p = 0.02), and between cg26283059 and DCI (p = 0.01).

Conclusions: This exploratory pilot study offers preliminary evidence that HAMP may play a role in patient outcomes after aSAH. Replication of this study and mechanistic investigation of the role of HAMP in patient outcomes after aSAH are needed.
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http://dx.doi.org/10.1007/s12028-019-00787-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6981002PMC
April 2020

The Mega2R package: R tools for accessing and processing genetic data in common formats.

F1000Res 2018 29;7:1352. Epub 2018 Aug 29.

Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA.

The standalone C++ Mega2 program has been facilitating data-reformatting for linkage and association analysis programs since 2000. Support for more analysis programs has been added over time. Currently, Mega2 converts data from several different genetic data formats (including PLINK, VCF, BCF, and IMPUTE2) into the specific data requirements for over 40 commonly-used linkage and association analysis programs (including Mendel, Merlin, Morgan, SHAPEIT, ROADTRIPS, MaCH/minimac3). Recently, Mega2 has been enhanced to use a SQLite database as an intermediate data representation. Additionally, Mega2 now stores bialleleic genotype data in a highly compressed form, like that of the GenABEL R package and the PLINK binary format. Our new Mega2R package now makes it easy to load Mega2 SQLite databases directly into R as data frames. In addition, Mega2R is memory efficient, keeping its genotype data in a compressed format, portions of which are only expanded when needed. Mega2R has functions that ease the process of applying gene-based tests by looping over genes, efficiently pulling out genotypes for variants within the desired boundaries. We have also created several more functions that illustrate how to use the data frames: these permit one to run the pedgene package to carry out gene-based association tests on family data, to run the SKAT package to carry out gene-based association tests, to output the Mega2R data as a VCF file and related files (for phenotype and family data), and to convert the data frames into GenABEL format. The Mega2R package enhances GenABEL since it supports additional input data formats (such as PLINK, VCF, and IMPUTE2) not currently supported by GenABEL. The Mega2 program and the Mega2R R package are both open source and are freely available, along with extensive documentation, from https://watson.hgen.pitt.edu/register for Mega2 and https://CRAN.R-project.org/package=Mega2R for Mega2R.
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http://dx.doi.org/10.12688/f1000research.15949.2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6137409PMC
November 2019

Spinning convincing stories for both true and false association signals.

Genet Epidemiol 2019 06 18;43(4):356-364. Epub 2019 Jan 18.

Department of Human Genetics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania.

When interpreting genome-wide association peaks, it is common to annotate each peak by searching for genes with plausible relationships to the trait. However, "all that glitters is not gold"-one might interpret apparent patterns in the data as plausible even when the peak is a false positive. Accordingly, we sought to see how human annotators interpreted association results containing a mixture of peaks from both the original trait and a genetically uncorrelated "synthetic" trait. Two of us prepared a mix of original and synthetic peaks of three significance categories from five different scans along with relevant literature search results and then we all annotated these regions. Three annotators also scored the strength of evidence connecting each peak to the scanned trait and the likelihood of further studying that region. While annotators found original peaks to have stronger evidence (p  = 0.017) and higher likelihood of further study ( p  = 0.006) than synthetic peaks, annotators often made convincing connections between the synthetic peaks and the original trait, finding these connections 55% of the time. These results show that it is not difficult for annotators to make convincing connections between synthetic association signals and genes found in those regions.
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http://dx.doi.org/10.1002/gepi.22189DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6590226PMC
June 2019

DNA methylation in nasal epithelium, atopy, and atopic asthma in children: a genome-wide study.

Lancet Respir Med 2019 04 21;7(4):336-346. Epub 2018 Dec 21.

Division of Pulmonary Medicine, Children's Hospital of Pittsburgh of UPMC, Pittsburgh, PA, USA; Department of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA. Electronic address:

Background: Epigenetic mechanisms could alter the airway epithelial barrier and ultimately lead to atopic diseases such as asthma. We aimed to identify DNA methylation profiles that are associated with-and could accurately classify-atopy and atopic asthma in school-aged children.

Methods: We did a genome-wide study of DNA methylation in nasal epithelium and atopy or atopic asthma in 483 Puerto Rican children aged 9-20 years, recruited using multistage probability sampling. Atopy was defined as at least one positive IgE (≥0·35 IU/mL) to common aeroallergens, and asthma was defined as a physician's diagnosis plus wheeze in the previous year. Significant (false discovery rate p<0·01) methylation signals were correlated with gene expression, and top CpGs were validated by pyrosequencing. We then replicated our top methylation findings in a cohort of 72 predominantly African American children, and in 432 children from a European birth cohort. Next, we tested classification models based on nasal methylation for atopy or atopic asthma in all cohorts.

Findings: DNA methylation profiles were markedly different between children with (n=312) and without (n=171) atopy in the Puerto Rico discovery cohort, recruited from Feb 12, 2014, until May 8, 2017. After adjustment for covariates and multiple testing, we found 8664 differentially methylated CpGs by atopy, with false discovery rate-adjusted p values ranging from 9·58 × 10 to 2·18 × 10 for the top 30 CpGs. These CpGs were in or near genes relevant to epithelial barrier function, including CDHR3 and CDH26, and in other genes related to airway epithelial integrity and immune regulation, such as FBXL7, NTRK1, and SLC9A3. Moreover, 28 of the top 30 CpGs replicated in the same direction in both independent cohorts. Classification models of atopy based on nasal methylation performed well in the Puerto Rico cohort (area under the curve [AUC] 0·93-0·94 and accuracy 85-88%) and in both replication cohorts (AUC 0·74-0·92, accuracy 68-82%). The models also performed well for atopic asthma in the Puerto Rico cohort (AUC 0·95-1·00, accuracy 88%) and the replication cohorts (AUC 0·82-0·88, accuracy 86%).

Interpretation: We identified specific methylation profiles in airway epithelium that are associated with atopy and atopic asthma in children, and a nasal methylation panel that could classify children by atopy or atopic asthma. Our findings support the feasibility of using the nasal methylome for future clinical applications, such as predicting the development of asthma among wheezing infants.

Funding: US National Institutes of Health.
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http://dx.doi.org/10.1016/S2213-2600(18)30466-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6441380PMC
April 2019

Linear mixed models for association analysis of quantitative traits with next-generation sequencing data.

Genet Epidemiol 2019 03 9;43(2):189-206. Epub 2018 Dec 9.

Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health (NIH), Bethesda, Maryland.

We develop linear mixed models (LMMs) and functional linear mixed models (FLMMs) for gene-based tests of association between a quantitative trait and genetic variants on pedigrees. The effects of a major gene are modeled as a fixed effect, the contributions of polygenes are modeled as a random effect, and the correlations of pedigree members are modeled via inbreeding/kinship coefficients. F -statistics and χ likelihood ratio test (LRT) statistics based on the LMMs and FLMMs are constructed to test for association. We show empirically that the F -distributed statistics provide a good control of the type I error rate. The F -test statistics of the LMMs have similar or higher power than the FLMMs, kernel-based famSKAT (family-based sequence kernel association test), and burden test famBT (family-based burden test). The F -statistics of the FLMMs perform well when analyzing a combination of rare and common variants. For small samples, the LRT statistics of the FLMMs control the type I error rate well at the nominal levels α = 0.01 and 0.05 . For moderate/large samples, the LRT statistics of the FLMMs control the type I error rates well. The LRT statistics of the LMMs can lead to inflated type I error rates. The proposed models are useful in whole genome and whole exome association studies of complex traits.
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http://dx.doi.org/10.1002/gepi.22177DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6375753PMC
March 2019

Y chromosome mosaicism is associated with age-related macular degeneration.

Eur J Hum Genet 2019 01 29;27(1):36-41. Epub 2018 Aug 29.

Institute of Human Genetics, University of Regensburg, Regensburg, Germany.

Age-related macular degeneration (AMD) is the leading cause of blindness in industrialised countries, and thereby a major individual but also a socio-economic burden. Y chromosome loss in nucleated blood cells has been implicated in age-related diseases such as Alzheimer disease and was shown to be caused by increasing age, smoking and genetic factors. Mosaic loss of Y chromosome (mLOY) in peripheral blood was estimated from normalised dosages of genotyping chip data covering the male-specific region of the Y chromosome. After quality control, we assessed the association of mLOY on AMD risk in 5772 male cases and 6732 male controls. In controls the prevalence of mLOY increased significantly with age, which is consistent with previous reports. Importantly, mLOY was associated with late-stage AMD with genome-wide significance (OR: 1.332 [95% CI: 1.206; 1.472], P = 1.60e-08), independent of age, the AMD genetic risk score and the first two principle components of ancestry. Additionally conditioning on smoking behaviour had no influence on the observed association strength. mLOY was strongest associated in individuals aged between 65 and 75 years. Taken together, mLOY is significantly associated with risk for AMD, independent of known and potential confounding factors.
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http://dx.doi.org/10.1038/s41431-018-0238-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6303255PMC
January 2019
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