Peter M Visscher

Publications of Peter M Visscher

• Genetic architecture of body size in mammals.

  Authors: Kathryn E Kemper, Peter M Visscher, Michael E Goddard

  Genome biology. 04/2012; 13(4):244.

  ABSTRACT: Much of the heritability for human stature is caused by mutations of small-to-medium effect. This is because detrimental pleiotropy restricts large-effect mutations to very low frequencies.

• Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits.

  Authors: Jian Yang, Teresa Ferreira, Andrew P Morris, Sarah E Medland, Pamela A F Madden, Andrew C Heath, Nicholas G Martin, Grant W Montgomery, Michael N Weedon, Ruth J Loos, Timothy M Frayling, Mark I McCarthy, Joel N Hirschhorn, Michael E Goddard, Peter M Visscher

  Nature genetics. 03/2012; 44(4):369-75.

  We present an approximate conditional and joint association analysis that can use summary-level statistics from a meta-analysis of genome-wide association studies (GWAS) and estimated linkageWe present an approximate conditional and joint association analysis that can use summary-level statistics from a meta-analysis of genome-wide association studies (GWAS) and estimated linkage disequilibrium (LD) from a reference sample with individual-level genotype data. Using this method, we analyzed meta-analysis summary data from the GIANT Consortium for height and body mass index (BMI), with the LD structure estimated from genotype data in two independent cohorts. We identified 36 loci with multiple associated variants for height (38 leading and 49 additional SNPs, 87 in total) via a genome-wide SNP selection procedure. The 49 new SNPs explain approximately 1.3% of variance, nearly doubling the heritability explained at the 36 loci. We did not find any locus showing multiple associated SNPs for BMI. The method we present is computationally fast and is also applicable to case-control data, which we demonstrate in an example from meta-analysis of type 2 diabetes by the DIAGRAM Consortium.

• Genetic contributions to stability and change in intelligence from childhood to old age.

  Authors: Ian J Deary, Jian Yang, Gail Davies, Sarah E Harris, Albert Tenesa, David Liewald, Michelle Luciano, Lorna M Lopez, Alan J Gow, Janie Corley, Paul Redmond, Helen C Fox, Suzanne J Rowe, Paul Haggarty, Geraldine McNeill, Michael E Goddard, David J Porteous, Lawrence J Whalley, John M Starr, Peter M Visscher

  Nature. 02/2012; 482(7384):212-5.

  Understanding the determinants of healthy mental ageing is a priority for society today. So far, we know that intelligence differences show high stability from childhood to old age and there areUnderstanding the determinants of healthy mental ageing is a priority for society today. So far, we know that intelligence differences show high stability from childhood to old age and there are estimates of the genetic contribution to intelligence at different ages. However, attempts to discover whether genetic causes contribute to differences in cognitive ageing have been relatively uninformative. Here we provide an estimate of the genetic and environmental contributions to stability and change in intelligence across most of the human lifetime. We used genome-wide single nucleotide polymorphism (SNP) data from 1,940 unrelated individuals whose intelligence was measured in childhood (age 11 years) and again in old age (age 65, 70 or 79 years). We use a statistical method that allows genetic (co)variance to be estimated from SNP data on unrelated individuals. We estimate that causal genetic variants in linkage disequilibrium with common SNPs account for 0.24 of the variation in cognitive ability change from childhood to old age. Using bivariate analysis, we estimate a genetic correlation between intelligence at age 11 years and in old age of 0.62. These estimates, derived from rarely available data on lifetime cognitive measures, warrant the search for genetic causes of cognitive stability and change.

• Five years of GWAS discovery.

  Authors: Peter M Visscher, Matthew A Brown, Mark I McCarthy, Jian Yang

  American journal of human genetics. 01/2012; 90(1):7-24.

  The past five years have seen many scientific and biological discoveries made through the experimental design of genome-wide association studies (GWASs). These studies were aimed at detectingThe past five years have seen many scientific and biological discoveries made through the experimental design of genome-wide association studies (GWASs). These studies were aimed at detecting variants at genomic loci that are associated with complex traits in the population and, in particular, at detecting associations between common single-nucleotide polymorphisms (SNPs) and common diseases such as heart disease, diabetes, auto-immune diseases, and psychiatric disorders. We start by giving a number of quotes from scientists and journalists about perceived problems with GWASs. We will then briefly give the history of GWASs and focus on the discoveries made through this experimental design, what those discoveries tell us and do not tell us about the genetics and biology of complex traits, and what immediate utility has come out of these studies. Rather than giving an exhaustive review of all reported findings for all diseases and other complex traits, we focus on the results for auto-immune diseases and metabolic diseases. We return to the perceived failure or disappointment about GWASs in the concluding section.

• The brisbane systems genetics study: genetical genomics meets complex trait genetics.

  Authors: Joseph E Powell, Anjali K Henders, Allan F McRae, Anthony Caracella, Sara Smith, Margaret J Wright, John B Whitfield, Emmanouil T Dermitzakis, Nicholas G Martin, Peter M Visscher, Grant W Montgomery

  PloS one. 01/2012; 7(4):e35430.

  There is growing evidence that genetic risk factors for common disease are caused by hereditary changes of gene regulation acting in complex pathways. Clearly understanding the molecular geneticThere is growing evidence that genetic risk factors for common disease are caused by hereditary changes of gene regulation acting in complex pathways. Clearly understanding the molecular genetic relationships between genetic control of gene expression and its effect on complex diseases is essential. Here we describe the Brisbane Systems Genetics Study (BSGS), a family-based study that will be used to elucidate the genetic factors affecting gene expression and the role of gene regulation in mediating endophenotypes and complex diseases.BSGS comprises of a total of 962 individuals from 314 families, for which we have high-density genotype, gene expression and phenotypic data. Families consist of combinations of both monozygotic and dizygotic twin pairs, their siblings, and, for 72 families, both parents. A significant advantage of the inclusion of parents is improved power to disentangle environmental, additive genetic and non-additive genetic effects of gene expression and measured phenotypes. Furthermore, it allows for the estimation of parent-of-origin effects, something that has not previously been systematically investigated in human genetical genomics studies. Measured phenotypes available within the BSGS include blood phenotypes and biochemical traits measured from components of the tissue sample in which transcription levels are determined, providing an ideal test case for systems genetics approaches.We report results from an expression quantitative trait loci (eQTL) analysis using 862 individuals from BSGS to test for associations between expression levels of 17,926 probes and 528,509 SNP genotypes. At a study wide significance level approximately 15,000 associations were observed between expression levels and SNP genotypes. These associations corresponded to a total of 2,081 expression quantitative trait loci (eQTL) involving 1,503 probes. The majority of identified eQTL (87%) were located within cis-regions.

• Meta-analyses identify 13 loci associated with age at menopause and highlight DNA repair and immune pathways.

  Authors: Lisette Stolk, John R B Perry, Daniel I Chasman, Chunyan He, Massimo Mangino, Patrick Sulem, Maja Barbalic, Linda Broer, Enda M Byrne, Florian Ernst [......] Elizabeth A Streeten, Unnur Thorsteinsdottir, Manuela Uda, André G Uitterlinden, Cornelia M van Duijn, Henry Völzke, Anna Murray, Joanne M Murabito, Jenny A Visser, Kathryn L Lunetta

  Nature genetics. 01/2012; 44(3):260-8.

  To newly identify loci for age at natural menopause, we carried out a meta-analysis of 22 genome-wide association studies (GWAS) in 38,968 women of European descent, with replication in up to 14,435To newly identify loci for age at natural menopause, we carried out a meta-analysis of 22 genome-wide association studies (GWAS) in 38,968 women of European descent, with replication in up to 14,435 women. In addition to four known loci, we identified 13 loci newly associated with age at natural menopause (at P < 5 × 10(-8)). Candidate genes located at these newly associated loci include genes implicated in DNA repair (EXO1, HELQ, UIMC1, FAM175A, FANCI, TLK1, POLG and PRIM1) and immune function (IL11, NLRP11 and PRRC2A (also known as BAT2)). Gene-set enrichment pathway analyses using the full GWAS data set identified exoDNase, NF-κB signaling and mitochondrial dysfunction as biological processes related to timing of menopause.

  Download

• Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs.

  Authors: S Hong Lee, Teresa R DeCandia, Stephan Ripke, Jian Yang, Patrick F Sullivan, Michael E Goddard, Matthew C Keller, Peter M Visscher, Naomi R Wray

  Nature genetics. 01/2012; 44(3):247-50.

  Schizophrenia is a complex disorder caused by both genetic and environmental factors. Using 9,087 affected individuals, 12,171 controls and 915,354 imputed SNPs from the Schizophrenia PsychiatricSchizophrenia is a complex disorder caused by both genetic and environmental factors. Using 9,087 affected individuals, 12,171 controls and 915,354 imputed SNPs from the Schizophrenia Psychiatric Genome-Wide Association Study (GWAS) Consortium (PGC-SCZ), we estimate that 23% (s.e. = 1%) of variation in liability to schizophrenia is captured by SNPs. We show that a substantial proportion of this variation must be the result of common causal variants, that the variance explained by each chromosome is linearly related to its length (r = 0.89, P = 2.6 × 10(-8)), that the genetic basis of schizophrenia is the same in males and females, and that a disproportionate proportion of variation is attributable to a set of 2,725 genes expressed in the central nervous system (CNS; P = 7.6 × 10(-8)). These results are consistent with a polygenic genetic architecture and imply more individual SNP associations will be detected for this disease as sample size increases.

• Genetic control of gene expression in whole blood and lymphoblastoid cell lines is largely independent.

  Authors: Joseph E Powell, Anjali K Henders, Allan F McRae, Margaret J Wright, Nicholas G Martin, Emmanouil T Dermitzakis, Grant W Montgomery, Peter M Visscher

  Genome research. 12/2011; 22(3):456-66.

  The degree to which the level of genetic variation for gene expression is shared across multiple tissues has important implications for research investigating the role of expression on the etiologyThe degree to which the level of genetic variation for gene expression is shared across multiple tissues has important implications for research investigating the role of expression on the etiology of complex human traits and diseases. In the last few years, several studies have been published reporting the extent of overlap in expression quantitative trait loci (eQTL) identified in multiple tissues or cell types. Although these studies provide important information on the regulatory control of genes across tissues, their limited power means that they can typically only explain a small proportion of genetic variation for gene expression. Here, using expression data from monozygotic twins (MZ), we investigate the genetic control of gene expression in lymphoblastoid cell lines (LCL) and whole blood (WB). We estimate the genetic correlation that represents the combined effects of all causal loci across the whole genome and is a measure of the level of common genetic control of gene expression between the two RNA sources. Our results show that, when averaged across the genome, mean levels of genetic correlation for gene expression in LCL and WB samples are close to zero. We support our results with evidence from gene expression in an independent sample of LCL, T-cells, and fibroblasts. In addition, we provide evidence that housekeeping genes, which maintain basic cellular functions, are more likely to have high genetic correlations between the RNA sources than non-housekeeping genes, implying a relationship between the transcript function and the degree to which a gene has tissue-specific genetic regulatory control.

• Association between ORMDL3, IL1RL1 and a deletion on chromosome 17q21 with asthma risk in Australia.

  Authors: Manuel A R Ferreira, Allan F McRae, Sarah E Medland, Dale R Nyholt, Scott D Gordon, Margaret J Wright, Anjali K Henders, Pamela A Madden, Peter M Visscher, Naomi R Wray, Andrew C Heath, Grant W Montgomery, David L Duffy, Nicholas G Martin

  European journal of human genetics : EJHG. 10/2011; 19(10):1109.

• Genome-wide association study identifies five new schizophrenia loci.

  Authors: Stephan Ripke, Alan R Sanders, Kenneth S Kendler, Douglas F Levinson, Pamela Sklar, Peter A Holmans, Dan-Yu Lin, Jubao Duan, Roel A Ophoff, Ole A Andreassen [......] Durk Wiersma, Dieter B Wildenauer, Hywel J Williams, Nigel M Williams, Brandon Wormley, Stan Zammit, Patrick F Sullivan, Michael C O'Donovan, Mark J Daly, Pablo V Gejman

  Nature genetics. 09/2011; 43(10):969-76.

  We examined the role of common genetic variation in schizophrenia in a genome-wide association study of substantial size: a stage 1 discovery sample of 21,856 individuals of European ancestry and aWe examined the role of common genetic variation in schizophrenia in a genome-wide association study of substantial size: a stage 1 discovery sample of 21,856 individuals of European ancestry and a stage 2 replication sample of 29,839 independent subjects. The combined stage 1 and 2 analysis yielded genome-wide significant associations with schizophrenia for seven loci, five of which are new (1p21.3, 2q32.3, 8p23.2, 8q21.3 and 10q24.32-q24.33) and two of which have been previously implicated (6p21.32-p22.1 and 18q21.2). The strongest new finding (P = 1.6 × 10(-11)) was with rs1625579 within an intron of a putative primary transcript for MIR137 (microRNA 137), a known regulator of neuronal development. Four other schizophrenia loci achieving genome-wide significance contain predicted targets of MIR137, suggesting MIR137-mediated dysregulation as a previously unknown etiologic mechanism in schizophrenia. In a joint analysis with a bipolar disorder sample (16,374 affected individuals and 14,044 controls), three loci reached genome-wide significance: CACNA1C (rs4765905, P = 7.0 × 10(-9)), ANK3 (rs10994359, P = 2.5 × 10(-8)) and the ITIH3-ITIH4 region (rs2239547, P = 7.8 × 10(-9)).

• Identification of IL6R and chromosome 11q13.5 as risk loci for asthma.

  Authors: Manuel A R Ferreira, Melanie C Matheson, David L Duffy, Guy B Marks, Jennie Hui, Peter Le Souëf, Patrick Danoy, Svetlana Baltic, Dale R Nyholt, Mark Jenkins [......] Haydn Walters, Nicholas G Martin, Alan James, Graham Jones, Michael J Abramson, Colin F Robertson, Shyamali C Dharmage, Matthew A Brown, Grant W Montgomery, Philip J Thompson

  Lancet. 09/2011; 378(9795):1006-14.

  We aimed to identify novel genetic variants affecting asthma risk, since these might provide novel insights into molecular mechanisms underlying the disease. We did a genome-wide association studyWe aimed to identify novel genetic variants affecting asthma risk, since these might provide novel insights into molecular mechanisms underlying the disease. We did a genome-wide association study (GWAS) in 2669 physician-diagnosed asthmatics and 4528 controls from Australia. Seven loci were prioritised for replication after combining our results with those from the GABRIEL consortium (n=26,475), and these were tested in an additional 25,358 independent samples from four in-silico cohorts. Quantitative multi-marker scores of genetic load were constructed on the basis of results from the GABRIEL study and tested for association with asthma in our Australian GWAS dataset. Two loci were confirmed to associate with asthma risk in the replication cohorts and reached genome-wide significance in the combined analysis of all available studies (n=57,800): rs4129267 (OR 1·09, combined p=2·4×10(-8)) in the interleukin-6 receptor (IL6R) gene and rs7130588 (OR 1·09, p=1·8×10(-8)) on chromosome 11q13.5 near the leucine-rich repeat containing 32 gene (LRRC32, also known as GARP). The 11q13.5 locus was significantly associated with atopic status among asthmatics (OR 1·33, p=7×10(-4)), suggesting that it is a risk factor for allergic but not non-allergic asthma. Multi-marker association results are consistent with a highly polygenic contribution to asthma risk, including loci with weak effects that might be shared with other immune-related diseases, such as NDFIP1, HLA-B, LPP, and BACH2. The IL6R association further supports the hypothesis that cytokine signalling dysregulation affects asthma risk, and raises the possibility that an IL6R antagonist (tocilizumab) may be effective to treat the disease, perhaps in a genotype-dependent manner. Results for the 11q13.5 locus suggest that it directly increases the risk of allergic sensitisation which, in turn, increases the risk of subsequent development of asthma. Larger or more functionally focused studies are needed to characterise the many loci with modest effects that remain to be identified for asthma. National Health and Medical Research Council of Australia. A full list of funding sources is provided in the webappendix.

• GWAS of butyrylcholinesterase activity identifies four novel loci, independent effects within BCHE and secondary associations with metabolic risk factors.

  Authors: Beben Benyamin, Rita P Middelberg, Penelope A Lind, Anne M Valle, Scott Gordon, Dale R Nyholt, Sarah E Medland, Anjali K Henders, Andrew C Heath, Pamela A F Madden, Peter M Visscher, Daniel T O'Connor, Grant W Montgomery, Nicholas G Martin, John B Whitfield

  Human molecular genetics. 08/2011; 20(22):4504-14.

  Serum butyrylcholinesterase (BCHE) activity is associated with obesity, blood pressure and biomarkers of cardiovascular and diabetes risk. We have conducted a genome-wide association scan to discoverSerum butyrylcholinesterase (BCHE) activity is associated with obesity, blood pressure and biomarkers of cardiovascular and diabetes risk. We have conducted a genome-wide association scan to discover genetic variants affecting BCHE activity, and to clarify whether the associations between BCHE activity and cardiometabolic risk factors are caused by variation in BCHE or whether BCHE variation is secondary to the metabolic abnormalities. We measured serum BCHE in adolescents and adults from three cohorts of Australian twin and family studies. The genotypes from ∼2.4 million single-nucleotide polymorphisms (SNPs) were available in 8791 participants with BCHE measurements. We detected significant associations with BCHE activity at three independent groups of SNPs at the BCHE locus (P = 5.8 × 10(-262), 7.8 × 10(-47), 2.9 × 10(-12)) and at four other loci: RNPEP (P = 9.4 × 10(-16)), RAPH1-ABI2 (P = 4.1 × 10(-18)), UGT1A1 (P = 4.0 × 10(-8)) and an intergenic region on chromosome 8 (P = 1.4 × 10(-8)). These loci affecting BCHE activity were not associated with metabolic risk factors. On the other hand, SNPs in genes previously associated with metabolic risk had effects on BCHE activity more often than can be explained by chance. In particular, SNPs within FTO and GCKR were associated with BCHE activity, but their effects were partly mediated by body mass index and triglycerides, respectively. We conclude that variation in BCHE activity is due to multiple variants across the spectrum from uncommon/large effect to common/small effect, and partly results from (rather than causes) metabolic abnormalities.

• Association of variants in MMEL1 and CTLA4 with rheumatoid arthritis in the Han Chinese population.

  Authors: Patrick Danoy, Meng Wei, Hadler Johanna, Lei Jiang, Dongyi He, Linyun Sun, Xiaofeng Zeng, Peter M Visscher, Matthew A Brown, Huji Xu

  Annals of the rheumatic diseases. 07/2011; 70(10):1793-7.

  The genome-wide association study era has made great progress in identifying susceptibility genes and genetic loci for rheumatoid arthritis (RA) in populations of White European ancestry. However,The genome-wide association study era has made great progress in identifying susceptibility genes and genetic loci for rheumatoid arthritis (RA) in populations of White European ancestry. However, few studies have tried to dissect disease aetiopathogenesis in other ethnic populations. To investigate these associations in the Han Chinese population. Haplotypes from the HapMap database Chinese population were used to select tag-single-nucleotide polymorphisms (SNPs) (r(2)=0.8) across 19 distinct RA genomic regions. A two phase case-control association study was performed, with 169 SNPs genotyped in phase I (n=571 cases, n=880 controls), and 64 SNPs achieving p<0.2 in the first phase being genotyped in phase II (n=464 cases, n=822 controls). Association statistics were calculated using permutation tests both unadjusted and adjusted for the number of markers studied. Robust association was detected for MMEL1 and CTLA4, and modest association was identified for another six loci: PADI4, STAT4, PRDM1, CDK6, TRAF1-C5 and KIF5A-PIP4K2C. All three markers genotyped in MMEL1 demonstrated association, with peak signal for rs3890745 (p=2.6 × 10(-5) unadjusted, p=0.003 adjusted, OR=0.79). For CTLA4, significance was detected for three of five variants showing association, with peak association for marker rs12992492 (p=4.3 × 10(-5) unadjusted, p=0.0021 adjusted, OR=0.77). Lack of association of common variants in PTPN22 with RA in Han Chinese was confirmed. This study identifies MMEL1 and CTLA4 as RA susceptibility genes, provides suggestive evidence of association for a further six loci in the Han Chinese population and confirms lack of PTPN22 association in Asian populations. It also confirms the value of multiethnic population studies to help dissect disease aetiopathogenesis.

• Response to browning and browning.

  Authors: Michael E Goddard, S Hong Lee, Jian Yang, Naomi R Wray, Peter M Visscher

  American journal of human genetics. 07/2011; 89(1):193-5.

• Quantification of inbreeding due to distant ancestors and its detection using dense single nucleotide polymorphism data.

  Authors: Matthew C Keller, Peter M Visscher, Michael E Goddard

  Genetics. 06/2011; 189(1):237-49.

  Inbreeding depression, which refers to reduced fitness among offspring of related parents, has traditionally been studied using pedigrees. In practice, pedigree information is difficult to obtain,Inbreeding depression, which refers to reduced fitness among offspring of related parents, has traditionally been studied using pedigrees. In practice, pedigree information is difficult to obtain, potentially unreliable, and rarely assessed for inbreeding arising from common ancestors who lived more than a few generations ago. Recently, there has been excitement about using SNP data to estimate inbreeding (F) arising from distant common ancestors in apparently "outbred" populations. Statistical power to detect inbreeding depression using SNP data depends on the actual variation in inbreeding in a population, the accuracy of detecting that with marker data, the effect size, and the sample size. No one has yet investigated what variation in F is expected in SNP data as a function of population size, and it is unclear which estimate of F is optimal for detecting inbreeding depression. In the present study, we use theory, simulated genetic data, and real genetic data to find the optimal estimate of F, to quantify the likely variation in F in populations of various sizes, and to estimate the power to detect inbreeding depression. We find that F estimated from runs of homozygosity (Froh), which reflects shared ancestry of genetic haplotypes, retains variation in even large populations (e.g., SD=0.5% when Ne=10,000) and is likely to be the most powerful method of detecting inbreeding effects from among several alternative estimates of F. However, large samples (e.g., 12,000-65,000) will be required to detect inbreeding depression for likely effect sizes, and so studies using Froh to date have probably been underpowered.

• Genome partitioning of genetic variation for complex traits using common SNPs.

  Authors: Jian Yang, Teri A Manolio, Louis R Pasquale, Eric Boerwinkle, Neil Caporaso, Julie M Cunningham, Mariza de Andrade, Bjarke Feenstra, Eleanor Feingold, M Geoffrey Hayes [......] Peng Lin, Hua Ling, William Lowe, Rasika A Mathias, Mads Melbye, Elizabeth Pugh, Marilyn C Cornelis, Bruce S Weir, Michael E Goddard, Peter M Visscher

  Nature genetics. 06/2011; 43(6):519-25.

  We estimate and partition genetic variation for height, body mass index (BMI), von Willebrand factor and QT interval (QTi) using 586,898 SNPs genotyped on 11,586 unrelated individuals. We estimateWe estimate and partition genetic variation for height, body mass index (BMI), von Willebrand factor and QT interval (QTi) using 586,898 SNPs genotyped on 11,586 unrelated individuals. We estimate that ∼45%, ∼17%, ∼25% and ∼21% of the variance in height, BMI, von Willebrand factor and QTi, respectively, can be explained by all autosomal SNPs and a further ∼0.5-1% can be explained by X chromosome SNPs. We show that the variance explained by each chromosome is proportional to its length, and that SNPs in or near genes explain more variation than SNPs between genes. We propose a new approach to estimate variation due to cryptic relatedness and population stratification. Our results provide further evidence that a substantial proportion of heritability is captured by common SNPs, that height, BMI and QTi are highly polygenic traits, and that the additive variation explained by a part of the genome is approximately proportional to the total length of DNA contained within genes therein.

• Human population dispersal "Out of Africa" estimated from linkage disequilibrium and allele frequencies of SNPs.

  Authors: Brian P McEvoy, Joseph E Powell, Michael E Goddard, Peter M Visscher

  Genome research. 06/2011; 21(6):821-9.

  Genetic and fossil evidence supports a single, recent (<200,000 yr) origin of modern Homo sapiens in Africa, followed by later population divergence and dispersal across the globe (the "Out ofGenetic and fossil evidence supports a single, recent (<200,000 yr) origin of modern Homo sapiens in Africa, followed by later population divergence and dispersal across the globe (the "Out of Africa" model). However, there is less agreement on the exact nature of this migration event and dispersal of populations relative to one another. We use the empirically observed genetic correlation structure (or linkage disequilibrium) between 242,000 genome-wide single nucleotide polymorphisms (SNPs) in 17 global populations to reconstruct two key parameters of human evolution: effective population size (N(e)) and population divergence times (T). A linkage disequilibrium (LD)-based approach allows changes in human population size to be traced over time and reveals a substantial reduction in N(e) accompanying the "Out of Africa" exodus as well as the dramatic re-expansion of non-Africans as they spread across the globe. Secondly, two parallel estimates of population divergence times provide clear evidence of population dispersal patterns "Out of Africa" and subsequent dispersal of proto-European and proto-East Asian populations. Estimates of divergence times between European-African and East Asian-African populations are inconsistent with its simplest manifestation: a single dispersal from the continent followed by a split into Western and Eastern Eurasian branches. Rather, population divergence times are consistent with substantial ancient gene flow to the proto-European population after its divergence with proto-East Asians, suggesting distinct, early dispersals of modern H. sapiens from Africa. We use simulated genetic polymorphism data to demonstrate the validity of our conclusions against alternative population demographic scenarios.

• LPAR1 and ITGA4 regulate peripheral blood monocyte counts.

  Authors: Narelle Maugeri, Joseph E Powell, Peter A C 't Hoen, Eco J C de Geus, Gonneke Willemsen, Mathijs Kattenberg, Anjali K Henders, Leanne Wallace, Brenda Penninx, Jouke-Jan Hottenga, Sarah E Medland, Viatcheslav Saviouk, Nicholas G Martin, Peter M Visscher, Gert-Jan B van Ommen, Ian H Frazer, Dorret I Boomsma, Grant W Montgomery, Manuel A R Ferreira

  Human mutation. 05/2011; 32(8):873-6.

  We recently mapped a quantitative trait locus for monocyte counts to chromosome 9q31 (rs7023923). Here we extend this work by showing with two independent approaches that rs7023923 regulates theWe recently mapped a quantitative trait locus for monocyte counts to chromosome 9q31 (rs7023923). Here we extend this work by showing with two independent approaches that rs7023923 regulates the expression levels of the nearby LPAR1 gene (P<0.0001), specifically implicating this gene in monocyte development. Furthermore, we tested 10 additional loci identified in the original analysis for replication in 1,122 individuals and confirm that rs6740847 near the alpha-4-integrin gene (ITGA4) associates with variation in monocyte counts (combined P=2.7×10(-10)). This variant is in complete linkage disequilibrium (r(2) =1) with a previously reported eQTL for ITGA4 (rs2124440), indicating that this is the likely causal gene in the region. Our results indicate that rs7023923 and rs6740847 respectively upregulate LPAR1 and downregulate ITGA4 expression and this increases the number of monocytes circulating in the peripheral blood. Further studies that investigate the downstream mechanism involved and the impact on immune function are warranted.

• Genetic predictors of fibrin D-dimer levels in healthy adults.

  Authors: Nicholas L Smith, Jennifer E Huffman, David P Strachan, Jie Huang, Abbas Dehghan, Stella Trompet, Lorna M Lopez, So-Youn Shin, Jens Baumert, Veronique Vitart [......] Bruce M Psaty, James F Wilson, Gordon D O Lowe, Christopher J O'Donnell, Jacqueline C M Witteman, J Wouter Jukema, Ian J Deary, Nicole Soranzo, Wolfgang Koenig, Caroline Hayward

  Circulation. 05/2011; 123(17):1864-72.

  Fibrin fragment D-dimer, one of several peptides produced when crosslinked fibrin is degraded by plasmin, is the most widely used clinical marker of activated blood coagulation. To identity geneticFibrin fragment D-dimer, one of several peptides produced when crosslinked fibrin is degraded by plasmin, is the most widely used clinical marker of activated blood coagulation. To identity genetic loci influencing D-dimer levels, we performed the first large-scale, genome-wide association search. A genome-wide investigation of the genomic correlates of plasma D-dimer levels was conducted among 21 052 European-ancestry adults. Plasma levels of D-dimer were measured independently in each of 13 cohorts. Each study analyzed the association between ≈2.6 million genotyped and imputed variants across the 22 autosomal chromosomes and natural-log–transformed D-dimer levels using linear regression in additive genetic models adjusted for age and sex. Among all variants, 74 exceeded the genome-wide significance threshold and marked 3 regions. At 1p22, rs12029080 (P=6.4×10(-52)) was 46.0 kb upstream from F3, coagulation factor III (tissue factor). At 1q24, rs6687813 (P=2.4×10(-14)) was 79.7 kb downstream of F5, coagulation factor V. At 4q32, rs13109457 (P=2.9×10(-18)) was located between 2 fibrinogen genes: 10.4 kb downstream from FGG and 3.0 kb upstream from FGA. Variants were associated with a 0.099-, 0.096-, and 0.061-unit difference, respectively, in natural-log–transformed D-dimer and together accounted for 1.8% of the total variance. When adjusted for nonsynonymous substitutions in F5 and FGA loci known to be associated with D-dimer levels, there was no evidence of an additional association at either locus. Three genes were associated with fibrin D-dimer levels. Of these 3, the F3 association was the strongest, and has not been previously reported.

• Cattle gain stature.

  Authors: Peter M Visscher, Michael E Goddard

  Nature genetics. 05/2011; 43(5):397-8.