Publications by authors named "Josine L Min"

42 Publications

Identical twins carry a persistent epigenetic signature of early genome programming.

Nat Commun 2021 09 28;12(1):5618. Epub 2021 Sep 28.

Institute of Molecular and Cellular Biology, A*STAR, Singapore, Singapore.

Monozygotic (MZ) twins and higher-order multiples arise when a zygote splits during pre-implantation stages of development. The mechanisms underpinning this event have remained a mystery. Because MZ twinning rarely runs in families, the leading hypothesis is that it occurs at random. Here, we show that MZ twinning is strongly associated with a stable DNA methylation signature in adult somatic tissues. This signature spans regions near telomeres and centromeres, Polycomb-repressed regions and heterochromatin, genes involved in cell-adhesion, WNT signaling, cell fate, and putative human metastable epialleles. Our study also demonstrates a never-anticipated corollary: because identical twins keep a lifelong molecular signature, we can retrospectively diagnose if a person was conceived as monozygotic twin.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-021-25583-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8479069PMC
September 2021

Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation.

Nat Genet 2021 09 6;53(9):1311-1321. Epub 2021 Sep 6.

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

Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype-phenotype map than previously anticipated.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41588-021-00923-xDOI Listing
September 2021

Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging.

Genome Biol 2021 06 29;22(1):194. Epub 2021 Jun 29.

Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA.

Background: Biological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field.

Results: Leveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels.

Conclusion: This study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s13059-021-02398-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8243879PMC
June 2021

Triangulating Molecular Evidence to Prioritize Candidate Causal Genes at Established Atopic Dermatitis Loci.

J Invest Dermatol 2021 Nov 24;141(11):2620-2629. Epub 2021 Apr 24.

MRC Integrative Epidemiology Unit, Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom. Electronic address:

GWASs for atopic dermatitis have identified 25 reproducible loci. We attempt to prioritize the candidate causal genes at these loci using extensive molecular resources compiled into a bioinformatics pipeline. We identified a list of 103 molecular resources for atopic dermatitis etiology, including expression, protein, and DNA methylation quantitative trait loci datasets in the skin or immune-relevant tissues, which were tested for overlap with GWAS signals. This was combined with functional annotation using regulatory variant prediction and features such as promoter‒enhancer interactions, expression studies, and variant fine mapping. For each gene at each locus, we condensed the evidence into a prioritization score. Across the investigated loci, we detected significant enrichment of genes with adaptive immune regulatory function and epidermal barrier formation among the top-prioritized genes. At eight loci, we were able to prioritize a single candidate gene (IL6R, ADO, PRR5L, IL7R, ETS1, INPP5D, MDM1, TRAF3). In addition, at 6 of the 25 loci, our analysis prioritizes less familiar candidates (SLC22A5, IL2RA, MDM1, DEXI, ADO, STMN3). Our analysis provides support for previously implicated genes at several atopic dermatitis GWAS loci as well as evidence for plausible additional candidates at others, which may represent potential targets for drug discovery.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jid.2021.03.027DOI Listing
November 2021

Assessing the role of genome-wide DNA methylation between smoking and risk of lung cancer using repeated measurements: the HUNT study.

Int J Epidemiol 2021 Mar 17. Epub 2021 Mar 17.

Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway.

Background: It is unclear if smoking-related DNA methylation represents a causal pathway between smoking and risk of lung cancer. We sought to identify novel smoking-related DNA methylation sites in blood, with repeated measurements, and to appraise the putative role of DNA methylation in the pathway between smoking and lung cancer development.

Methods: We derived a nested case-control study from the Trøndelag Health Study (HUNT), including 140 incident patients who developed lung cancer during 2009-13 and 140 controls. We profiled 850 K DNA methylation sites (Illumina Infinium EPIC array) in DNA extracted from blood that was collected in HUNT2 (1995-97) and HUNT3 (2006-08) for the same individuals. Epigenome-wide association studies (EWAS) were performed for a detailed smoking phenotype and for lung cancer. Two-step Mendelian randomization (MR) analyses were performed to assess the potential causal effect of smoking on DNA methylation as well as of DNA methylation (13 sites as putative mediators) on risk of lung cancer.

Results: The EWAS for smoking in HUNT2 identified associations at 76 DNA methylation sites (P < 5 × 10-8), including 16 novel sites. Smoking was associated with DNA hypomethylation in a dose-response relationship among 83% of the 76 sites, which was confirmed by analyses using repeated measurements from blood that was collected at 11 years apart for the same individuals. Two-step MR analyses showed evidence for a causal effect of smoking on DNA methylation but no evidence for a causal link between DNA methylation and the risk of lung cancer.

Conclusions: DNA methylation modifications in blood did not seem to represent a causal pathway linking smoking and the lung cancer risk.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/ije/dyab044DOI Listing
March 2021

Comparison of DNA methylation clocks in Black South African men.

Epigenomics 2021 Mar 8;13(6):437-449. Epub 2021 Mar 8.

Centre of Excellence for Nutrition, North-West University, Potchefstroom, 2520, South Africa.

DNA methylation clocks are widely used to estimate biological age, although limited data are available on non-European ethnicities. This manuscript characterizes the behavior of five DNA methylation clocks in 120 older Black South African men. The age estimation accuracy of the Horvath, Hannum and skin and blood clocks and the relative age-related mortality risk and predicted time to death portrayed by the PhenoAge and GrimAge biomarkers are investigated, respectively. The results confirm the tendency of DNA methylation clocks to underestimate the biological age of older individuals. GrimAge more accurately characterizes biological decline in this African cohort compared with PhenoAge owing to the unique inclusion of smoking-related damage in the GrimAge estimate. Each clock provides a different fraction of information regarding the aging body. It is essential to continue studying under-represented population groups to ensure methylation-derived indicators are robust and useful in all populations.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2217/epi-2020-0333DOI Listing
March 2021

Opportunities and Challenges in Functional Genomics Research in Osteoporosis: Report From a Workshop Held by the Causes Working Group of the Osteoporosis and Bone Research Academy of the Royal Osteoporosis Society on October 5th 2020.

Front Endocrinol (Lausanne) 2020 15;11:630875. Epub 2021 Feb 15.

Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom.

The discovery that sclerostin is the defective protein underlying the rare heritable bone mass disorder, sclerosteosis, ultimately led to development of anti-sclerostin antibodies as a new treatment for osteoporosis. In the era of large scale GWAS, many additional genetic signals associated with bone mass and related traits have since been reported. However, how best to interrogate these signals in order to identify the underlying gene responsible for these genetic associations, a prerequisite for identifying drug targets for further treatments, remains a challenge. The resources available for supporting functional genomics research continues to expand, exemplified by "multi-omics" database resources, with improved availability of datasets derived from bone tissues. These databases provide information about potential molecular mediators such as mRNA expression, protein expression, and DNA methylation levels, which can be interrogated to map genetic signals to specific genes based on identification of causal pathways between the genetic signal and the phenotype being studied. Functional evaluation of potential causative genes has been facilitated by characterization of the "osteocyte signature", by broad phenotyping of knockout mice with deletions of over 7,000 genes, in which more detailed skeletal phenotyping is currently being undertaken, and by development of zebrafish as a highly efficient additional model for functional studies of the skeleton. Looking to the future, this expanding repertoire of tools offers the hope of accurately defining the major genetic signals which contribute to osteoporosis. This may in turn lead to the identification of additional therapeutic targets, and ultimately new treatments for osteoporosis.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3389/fendo.2020.630875DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7917291PMC
May 2021

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

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

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

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

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-020-19366-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785747PMC
January 2021

Investigating DNA methylation as a potential mediator between pigmentation genes, pigmentary traits and skin cancer.

Pigment Cell Melanoma Res 2021 09 10;34(5):892-904. Epub 2020 Dec 10.

Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.

Pigmentation characteristics are well-known risk factors for skin cancer. Polymorphisms in pigmentation genes have been associated with these traits and with the risk of malignancy. However, the functional relationship between genetic variation and disease is still unclear. This study aims to assess whether pigmentation SNPs are associated with pigmentary traits and skin cancer via DNA methylation (DNAm). Using a meta-GWAS of whole-blood DNAm from 36 European cohorts (N = 27,750; the Genetics of DNA Methylation Consortium, GoDMC), we found that 19 out of 27 SNPs in 10 pigmentation genes were associated with 391 DNAm sites across 30 genomic regions. We examined the effect of 25 selected DNAm sites on pigmentation traits, sun exposure phenotypes and skin cancer and on gene expression in whole blood. We uncovered an association of DNAm site cg07402062 with red hair in the Avon Longitudinal Study of Parents and Children (ALSPAC). We also found that the expression of ASIP and CDK10 was associated with hair colour, melanoma and basal cell carcinoma. Our results indicate that DNAm and expression of pigmentation genes may play a role as potential mediators of the relationship between genetic variants, pigmentation phenotypes and skin cancer and thus deserve further scrutiny.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1111/pcmr.12948DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8518056PMC
September 2021

The Effect of Pre-Analytical Conditions on Blood Metabolomics in Epidemiological Studies.

Metabolites 2019 Apr 3;9(4). Epub 2019 Apr 3.

Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol BS8 2BN, UK.

Serum and plasma are commonly used in metabolomic-epidemiology studies. Their metabolome is susceptible to differences in pre-analytical conditions and the impact of this is unclear. Participant-matched EDTA-plasma and serum samples were collected from 37 non-fasting volunteers and profiled using a targeted nuclear magnetic resonance (NMR) metabolomics platform ( = 151 traits). Correlations and differences in mean of metabolite concentrations were compared between reference (pre-storage: 4 °C, 1.5 h; post-storage: no buffer addition delay or NMR analysis delay) and four pre-storage blood processing conditions, where samples were incubated at (i) 4 °C, 24 h; (ii) 4 °C, 48 h; (iii) 21 °C, 24 h; and (iv) 21 °C, 48 h, before centrifugation; and two post-storage sample processing conditions in which samples thawed overnight (i) then left for 24 h before addition of sodium buffer followed by immediate NMR analysis; and (ii) addition of sodium buffer, then left for 24 h before NMR profiling. We used multilevel linear regression models and Spearman's rank correlation coefficients to analyse the data. Most metabolic traits had high rank correlation and minimal differences in mean concentrations between samples subjected to reference and the different conditions tested, that may commonly occur in studies. However, glycolysis metabolites, histidine, acetate and diacylglycerol concentrations may be compromised and this could bias results in association/causal analyses.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/metabo9040064DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6523923PMC
April 2019

GARFIELD classifies disease-relevant genomic features through integration of functional annotations with association signals.

Nat Genet 2019 02 28;51(2):343-353. Epub 2019 Jan 28.

Human Genetics, Wellcome Sanger Institute, Hinxton, UK.

Loci discovered by genome-wide association studies predominantly map outside protein-coding genes. The interpretation of the functional consequences of non-coding variants can be greatly enhanced by catalogs of regulatory genomic regions in cell lines and primary tissues. However, robust and readily applicable methods are still lacking by which to systematically evaluate the contribution of these regions to genetic variation implicated in diseases or quantitative traits. Here we propose a novel approach that leverages genome-wide association studies' findings with regulatory or functional annotations to classify features relevant to a phenotype of interest. Within our framework, we account for major sources of confounding not offered by current methods. We further assess enrichment of genome-wide association studies for 19 traits within Encyclopedia of DNA Elements- and Roadmap-derived regulatory regions. We characterize unique enrichment patterns for traits and annotations driving novel biological insights. The method is implemented in standalone software and an R package, to facilitate its application by the research community.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41588-018-0322-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6908448PMC
February 2019

Low-frequency variation in TP53 has large effects on head circumference and intracranial volume.

Nat Commun 2019 01 21;10(1):357. Epub 2019 Jan 21.

School of Medicine and Public Health, Faculty of Medicine and Health, The University of Newcastle, Newcastle, NSW, 2308, Australia.

Cranial growth and development is a complex process which affects the closely related traits of head circumference (HC) and intracranial volume (ICV). The underlying genetic influences shaping these traits during the transition from childhood to adulthood are little understood, but might include both age-specific genetic factors and low-frequency genetic variation. Here, we model the developmental genetic architecture of HC, showing this is genetically stable and correlated with genetic determinants of ICV. Investigating up to 46,000 children and adults of European descent, we identify association with final HC and/or final ICV + HC at 9 novel common and low-frequency loci, illustrating that genetic variation from a wide allele frequency spectrum contributes to cranial growth. The largest effects are reported for low-frequency variants within TP53, with 0.5 cm wider heads in increaser-allele carriers versus non-carriers during mid-childhood, suggesting a previously unrecognized role of TP53 transcripts in human cranial development.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-018-07863-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6341110PMC
January 2019

Autosomal genetic variation is associated with DNA methylation in regions variably escaping X-chromosome inactivation.

Nat Commun 2018 09 14;9(1):3738. Epub 2018 Sep 14.

Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, 2333 ZC, The Netherlands.

X-chromosome inactivation (XCI), i.e., the inactivation of one of the female X chromosomes, restores equal expression of X-chromosomal genes between females and males. However, ~10% of genes show variable degrees of escape from XCI between females, although little is known about the causes of variable XCI. Using a discovery data-set of 1867 females and 1398 males and a replication sample of 3351 females, we show that genetic variation at three autosomal loci is associated with female-specific changes in X-chromosome methylation. Through cis-eQTL expression analysis, we map these loci to the genes SMCHD1/METTL4, TRIM6/HBG2, and ZSCAN9. Low-expression alleles of the loci are predominantly associated with mild hypomethylation of CpG islands near genes known to variably escape XCI, implicating the autosomal genes in variable XCI. Together, these results suggest a genetic basis for variable escape from XCI and highlight the potential of a population genomics approach to identify genes involved in XCI.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-018-05714-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6138682PMC
September 2018

Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits.

Am J Hum Genet 2017 Jun 25;100(6):865-884. Epub 2017 May 25.

Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UK; Department of Cardiology, Ealing Hospital NHS Trust, Middlesex UB1 3EU, UK.

Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader allelic architecture of 12 anthropometric traits associated with height, body mass, and fat distribution in up to 267,616 individuals. We report 106 genome-wide significant signals that have not been previously identified, including 9 low-frequency variants pointing to functional candidates. Of the 106 signals, 6 are in genomic regions that have not been implicated with related traits before, 28 are independent signals at previously reported regions, and 72 represent previously reported signals for a different anthropometric trait. 71% of signals reside within genes and fine mapping resolves 23 signals to one or two likely causal variants. We confirm genetic overlap between human monogenic and polygenic anthropometric traits and find signal enrichment in cis expression QTLs in relevant tissues. Our results highlight the potential of WGS strategies to enhance biologically relevant discoveries across the frequency spectrum.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ajhg.2017.04.014DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5473732PMC
June 2017

Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps.

Nat Genet 2016 11 26;48(11):1303-1312. Epub 2016 Sep 26.

Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands.

Large-scale whole-genome sequence data sets offer novel opportunities to identify genetic variation underlying human traits. Here we apply genotype imputation based on whole-genome sequence data from the UK10K and 1000 Genomes Project into 35,981 study participants of European ancestry, followed by association analysis with 20 quantitative cardiometabolic and hematological traits. We describe 17 new associations, including 6 rare (minor allele frequency (MAF) < 1%) or low-frequency (1% < MAF < 5%) variants with platelet count (PLT), red blood cell indices (MCH and MCV) and HDL cholesterol. Applying fine-mapping analysis to 233 known and new loci associated with the 20 traits, we resolve the associations of 59 loci to credible sets of 20 or fewer variants and describe trait enrichments within regions of predicted regulatory function. These findings improve understanding of the allelic architecture of risk factors for cardiometabolic and hematological diseases and provide additional functional insights with the identification of potentially novel biological targets.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/ng.3668DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5279872PMC
November 2016

A reference panel of 64,976 haplotypes for genotype imputation.

Nat Genet 2016 10 22;48(10):1279-83. Epub 2016 Aug 22.

IRGB, CNR, Sardinia, Italy.

We describe a reference panel of 64,976 human haplotypes at 39,235,157 SNPs constructed using whole-genome sequence data from 20 studies of predominantly European ancestry. Using this resource leads to accurate genotype imputation at minor allele frequencies as low as 0.1% and a large increase in the number of SNPs tested in association studies, and it can help to discover and refine causal loci. We describe remote server resources that allow researchers to carry out imputation and phasing consistently and efficiently.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/ng.3643DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5388176PMC
October 2016

Systematic identification of genetic influences on methylation across the human life course.

Genome Biol 2016 Mar 31;17:61. Epub 2016 Mar 31.

MRC Integrative Epidemiology Unit (IEU) & School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.

Background: The influence of genetic variation on complex diseases is potentially mediated through a range of highly dynamic epigenetic processes exhibiting temporal variation during development and later life. Here we present a catalogue of the genetic influences on DNA methylation (methylation quantitative trait loci (mQTL)) at five different life stages in human blood: children at birth, childhood, adolescence and their mothers during pregnancy and middle age.

Results: We show that genetic effects on methylation are highly stable across the life course and that developmental change in the genetic contribution to variation in methylation occurs primarily through increases in environmental or stochastic effects. Though we map a large proportion of the cis-acting genetic variation, a much larger component of genetic effects influencing methylation are acting in trans. However, only 7 % of discovered mQTL are trans-effects, suggesting that the trans component is highly polygenic. Finally, we estimate the contribution of mQTL to variation in complex traits and infer that methylation may have a causal role consistent with an infinitesimal model in which many methylation sites each have a small influence, amounting to a large overall contribution.

Conclusions: DNA methylation contains a significant heritable component that remains consistent across the lifespan. Our results suggest that the genetic component of methylation may have a causal role in complex traits. The database of mQTL presented here provide a rich resource for those interested in investigating the role of methylation in disease.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s13059-016-0926-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4818469PMC
March 2016

Involvement of astrocyte and oligodendrocyte gene sets in migraine.

Cephalalgia 2016 Jun 7;36(7):640-7. Epub 2015 Dec 7.

Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Neuroscience Campus Amsterdam, VU University, The Netherlands Department of Clinical Genetics, VU University Medical Centre, The Netherlands.

Background: Migraine is a common episodic brain disorder characterized by recurrent attacks of severe unilateral headache and additional neurological symptoms. Two main migraine types can be distinguished based on the presence of aura symptoms that can accompany the headache: migraine with aura and migraine without aura. Multiple genetic and environmental factors confer disease susceptibility. Recent genome-wide association studies (GWAS) indicate that migraine susceptibility genes are involved in various pathways, including neurotransmission, which have already been implicated in genetic studies of monogenic familial hemiplegic migraine, a subtype of migraine with aura.

Methods: To further explore the genetic background of migraine, we performed a gene set analysis of migraine GWAS data of 4954 clinic-based patients with migraine, as well as 13,390 controls. Curated sets of synaptic genes and sets of genes predominantly expressed in three glial cell types (astrocytes, microglia and oligodendrocytes) were investigated.

Discussion: Our results show that gene sets containing astrocyte- and oligodendrocyte-related genes are associated with migraine, which is especially true for gene sets involved in protein modification and signal transduction. Observed differences between migraine with aura and migraine without aura indicate that both migraine types, at least in part, seem to have a different genetic background.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1177/0333102415618614DOI Listing
June 2016

Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel.

Nat Commun 2015 Sep 14;6:8111. Epub 2015 Sep 14.

The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK.

Imputing genotypes from reference panels created by whole-genome sequencing (WGS) provides a cost-effective strategy for augmenting the single-nucleotide polymorphism (SNP) content of genome-wide arrays. The UK10K Cohorts project has generated a data set of 3,781 whole genomes sequenced at low depth (average 7x), aiming to exhaustively characterize genetic variation down to 0.1% minor allele frequency in the British population. Here we demonstrate the value of this resource for improving imputation accuracy at rare and low-frequency variants in both a UK and an Italian population. We show that large increases in imputation accuracy can be achieved by re-phasing WGS reference panels after initial genotype calling. We also present a method for combining WGS panels to improve variant coverage and downstream imputation accuracy, which we illustrate by integrating 7,562 WGS haplotypes from the UK10K project with 2,184 haplotypes from the 1000 Genomes Project. Finally, we introduce a novel approximation that maintains speed without sacrificing imputation accuracy for rare variants.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/ncomms9111DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4579394PMC
September 2015

The UK10K project identifies rare variants in health and disease.

Nature 2015 Oct 14;526(7571):82-90. Epub 2015 Sep 14.

The contribution of rare and low-frequency variants to human traits is largely unexplored. Here we describe insights from sequencing whole genomes (low read depth, 7×) or exomes (high read depth, 80×) of nearly 10,000 individuals from population-based and disease collections. In extensively phenotyped cohorts we characterize over 24 million novel sequence variants, generate a highly accurate imputation reference panel and identify novel alleles associated with levels of triglycerides (APOB), adiponectin (ADIPOQ) and low-density lipoprotein cholesterol (LDLR and RGAG1) from single-marker and rare variant aggregation tests. We describe population structure and functional annotation of rare and low-frequency variants, use the data to estimate the benefits of sequencing for association studies, and summarize lessons from disease-specific collections. Finally, we make available an extensive resource, including individual-level genetic and phenotypic data and web-based tools to facilitate the exploration of association results.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/nature14962DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4773891PMC
October 2015

An interactive genome browser of association results from the UK10K cohorts project.

Bioinformatics 2015 Dec 26;31(24):4029-31. Epub 2015 Aug 26.

Wellcome Trust Sanger Institute, Genome Campus, Hinxton CB10 1HH, UK, Department of Haematology, University of Cambridge, Cambridge CB2 1TN, UK.

Unlabelled: High-throughput sequencing technologies survey genetic variation at genome scale and are increasingly used to study the contribution of rare and low-frequency genetic variants to human traits. As part of the Cohorts arm of the UK10K project, genetic variants called from low-read depth (average 7×) whole genome sequencing of 3621 cohort individuals were analysed for statistical associations with 64 different phenotypic traits of biomedical importance. Here, we describe a novel genome browser based on the Biodalliance platform developed to provide interactive access to the association results of the project.

Availability And Implementation: The browser is available at http://www.uk10k.org/dalliance.html. Source code for the Biodalliance platform is available under a BSD license from http://github.com/dasmoth/dalliance, and for the LD-display plugin and backend from http://github.com/dasmoth/ldserv.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/bioinformatics/btv491DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4673976PMC
December 2015

Genetic studies of body mass index yield new insights for obesity biology.

Nature 2015 Feb;518(7538):197-206

Department of Genetics, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands.

Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/nature14177DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4382211PMC
February 2015

New genetic loci link adipose and insulin biology to body fat distribution.

Nature 2015 Feb;518(7538):187-196

Department of Genetics, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/nature14132DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4338562PMC
February 2015

A rare variant in APOC3 is associated with plasma triglyceride and VLDL levels in Europeans.

Nat Commun 2014 Sep 16;5:4871. Epub 2014 Sep 16.

1] Department of Twin Research and Genetic Epidemiology, Kings College London, London SE1 7EH, UK [2] Departments of Medicine, Human Genetics, Epidemiology and Biostatistics, Jewish General Hospital, 3755 Cote-Ste-Catherine Road, Montreal, Quebec, Canada H3T 1E2.

The analysis of rich catalogues of genetic variation from population-based sequencing provides an opportunity to screen for functional effects. Here we report a rare variant in APOC3 (rs138326449-A, minor allele frequency ~0.25% (UK)) associated with plasma triglyceride (TG) levels (-1.43 s.d. (s.e.=0.27 per minor allele (P-value=8.0 × 10(-8))) discovered in 3,202 individuals with low read-depth, whole-genome sequence. We replicate this in 12,831 participants from five additional samples of Northern and Southern European origin (-1.0 s.d. (s.e.=0.173), P-value=7.32 × 10(-9)). This is consistent with an effect between 0.5 and 1.5 mmol l(-1) dependent on population. We show that a single predicted splice donor variant is responsible for association signals and is independent of known common variants. Analyses suggest an independent relationship between rs138326449 and high-density lipoprotein (HDL) levels. This represents one of the first examples of a rare, large effect variant identified from whole-genome sequencing at a population scale.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/ncomms5871DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4167609PMC
September 2014

Distinct developmental profile of lower-body adipose tissue defines resistance against obesity-associated metabolic complications.

Diabetes 2014 Nov 19;63(11):3785-97. Epub 2014 Jun 19.

Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, U.K. National Institute for Health Research, Oxford Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, U.K.

Upper- and lower-body fat depots exhibit opposing associations with obesity-related metabolic disease. We defined the relationship between DEXA-quantified fat depots and diabetes/cardiovascular risk factors in a healthy population-based cohort (n = 3,399). Gynoid fat mass correlated negatively with insulin resistance after total fat mass adjustment, whereas the opposite was seen for abdominal fat. Paired transcriptomic analysis of gluteal subcutaneous adipose tissue (GSAT) and abdominal subcutaneous adipose tissue (ASAT) was performed across the BMI spectrum (n = 49; 21.4-45.5 kg/m(2)). In both depots, energy-generating metabolic genes were negatively associated and inflammatory genes were positively associated with obesity. However, associations were significantly weaker in GSAT. At the systemic level, arteriovenous release of the proinflammatory cytokine interleukin-6 (n = 34) was lower from GSAT than ASAT. Isolated preadipocytes retained a depot-specific transcriptional "memory" of embryonic developmental genes and exhibited differential promoter DNA methylation of selected genes (HOTAIR, TBX5) between GSAT and ASAT. Short hairpin RNA-mediated silencing identified TBX5 as a regulator of preadipocyte proliferation and adipogenic differentiation in ASAT. In conclusion, intrinsic differences in the expression of developmental genes in regional adipocytes provide a mechanistic basis for diversity in adipose tissue (AT) function. The less inflammatory nature of lower-body AT offers insight into the opposing metabolic disease risk associations between upper- and lower-body obesity.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2337/db14-0385DOI Listing
November 2014

Sex-stratified genome-wide association studies including 270,000 individuals show sexual dimorphism in genetic loci for anthropometric traits.

PLoS Genet 2013 Jun 6;9(6):e1003500. Epub 2013 Jun 6.

Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom.

Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%), including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were genome-wide significant in women (P<5×10(-8)), but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1371/journal.pgen.1003500DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3674993PMC
June 2013

Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture.

Nat Genet 2013 May 7;45(5):501-12. Epub 2013 Apr 7.

US Department of Health and Human Services, Division of Cancer Epidemiology and Genetics, National Cancer Institute, US National Institutes of Health, Bethesda, Maryland, USA.

Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/ng.2606DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3973018PMC
May 2013
-->