Screening by deep sequencing reveals mediators of microRNA tailing in C. elegans.

microRNAs are frequently modified by addition of untemplated nucleotides to the 3' end, but the role of this tailing is often unclear. Here we characterize the prevalence and functional consequences of microRNA tailing in vivo, using Caenorhabditis elegans. MicroRNA tailing in C. elegans consists mostly of mono-uridylation of mature microRNA species, with rarer mono-adenylation which is likely added to microRNA precursors. Through a targeted RNAi screen, we discover that the TUT4/TUT7 gene family member CID-1/CDE-1/PUP-1 is required for uridylation, whereas the GLD2 gene family member F31C3.2-here named GLD-2-related 2 (GLDR-2)-is required for adenylation. Thus, the TUT4/TUT7 and GLD2 gene families have broadly conserved roles in miRNA modification. We specifically examine the role of tailing in microRNA turnover. We determine half-lives of microRNAs after acute inactivation of microRNA biogenesis, revealing that half-lives are generally long (median = 20.7 h), as observed in other systems. Although we observe that the proportion of tailed species increases over time after biogenesis, disrupting tailing does not alter microRNA decay. Thus, tailing is not a global regulator of decay in C. elegans. Nonetheless, by identifying the responsible enzymes, this study lays the groundwork to explore whether tailing plays more specialized context- or miRNA-specific regulatory roles.

The zinc-finger protein CLAMP promotes gypsy chromatin insulator function in Drosophila.

Chromatin insulators are DNA-protein complexes that establish independent higher-order DNA domains to influence transcription. Insulators are functionally defined by two properties: they can block communication between an enhancer and a promoter, and also act as a barrier between heterochromatin and euchromatin. In Drosophila, the gypsy insulator complex contains three core components; Su(Hw), CP190 and Mod(mdg4)67.2. Here, we identify a novel role for Chromatin-linked adaptor for MSL proteins (CLAMP) in promoting gypsy chromatin insulator function. When clamp is knocked down, gypsy-dependent enhancer-blocking and barrier activities are strongly reduced. CLAMP associates physically with the core gypsy insulator complex, and ChIP-seq analysis reveals extensive overlap, particularly with promoter-bound CP190 on chromatin. Depletion of CLAMP disrupts CP190 binding at a minority of shared sites, whereas depletion of CP190 results in extensive loss of CLAMP chromatin association. Finally, reduction of CLAMP disrupts CP190 localization within the nucleus. Our results support a positive functional relationship between CLAMP and CP190 to promote gypsy chromatin insulator activity.

Feasibility and Reliability of Automatic Quantitative Analyses of Mitral Annular Plane Systolic Excursion by Handheld Ultrasound Devices: A Pilot Study.

OBJECTIVES: Handheld ultrasound devices (HUDs) have previously been limited to grayscale imaging without options for left ventricle (LV) quantification. We aimed to study the feasibility and reliability of automatic measurements of mitral annular plane systolic excursion (MAPSE) by HUDs. METHODS: An algorithm that automatically measured MAPSE from live grayscale recordings was implemented in a HUD. Twenty patients at a university hospital were examined by either a cardiologist or a sonographer. Standard echocardiography using a high-end scanner was performed. The apical 4-chamber view was recorded 4 times by both echocardiography and the HUD. MAPSE was measured by M-mode and color tissue Doppler (cTD) during echocardiography and automatically by the HUD. RESULTS: The automatic method underestimated mean MAPSE ± SD versus M-mode (9.6 ± 2.2 versus 10.9 ± 2.6 mm; difference, 1.2 ± 1.4 mm, P < .005). The difference between the automatic and cTD measurements was not significant (0.8 ± 1.8 mm; P = .073). The intraclass correlation coefficients (ICCs) between automatic and M-mode measurements was 0.85, and 0.81 for cTD measurements. There was good agreement between the methods, and the intra- and inter-rater ICCs were excellent for all methods (≥0.86). CONCLUSIONS: In this novel study evaluating automatic quantification of LV longitudinal function by HUD, we showed the high feasibility and reliability of the method. Compared to M-mode imaging, the automatic method underestimated MAPSE by 8% to 10%, but the difference with cTD imaging was nonsignificant. We conclude that this study's method for automatic quantitative assessment of LV function can be integrated in HUDs.

Comparison of revised Functional Capacity Index scores with Abbreviated Injury Scale 2008 scores in predicting 12-month severe trauma outcomes.

INTRODUCTION: Anatomical injury as measured by the AIS often accounts for only a small proportion of variability in outcomes after injury. The predictive Functional Capacity Index (FCI) appended to the 2008 AIS claims to provide a widely available method of predicting 12-month function following injury. OBJECTIVES: To determine the extent to which AIS-based and FCI-based scoring is able to add to a simple predictive model of 12-month function following severe injury. METHODS: Adult trauma patients were drawn from the population-based Victorian State Trauma Registry. Major trauma and severely injured orthopaedic trauma patients were followed up via telephone interview including Glasgow Outcome Scale-Extended, the EQ-5D-3L and return to work status. A battery of AIS-based and FCI-based scores, and a simple count of AIS-coded injuries were added in turn to a base model using age and gender. RESULTS: A total of 20 813 patients survived to 12 months and had at least one functional outcome recorded, representing 85% follow-up. Predictions using the base model varied substantially across outcome measures. Irrespective of the method used to classify the severity of injury, adding injury severity to the model significantly, but only slightly improved model fit. Across the outcomes evaluated, no method of injury severity assessment consistently outperformed any other. CONCLUSIONS: Anatomical injury is a predictor of trauma outcome. However, injury severity as described by the FCI does not consistently improve discrimination, or even provide the best discrimination compared with AIS-based severity scores or a simple injury count.

Statistical correction of the Winner's Curse explains replication variability in quantitative trait genome-wide association studies.

Genome-wide association studies (GWAS) have identified hundreds of SNPs responsible for variation in human quantitative traits. However, genome-wide-significant associations often fail to replicate across independent cohorts, in apparent inconsistency with their apparent strong effects in discovery cohorts. This limited success of replication raises pervasive questions about the utility of the GWAS field. We identify all 332 studies of quantitative traits from the NHGRI-EBI GWAS Database with attempted replication. We find that the majority of studies provide insufficient data to evaluate replication rates. The remaining papers replicate significantly worse than expected (p < 10-14), even when adjusting for regression-to-the-mean of effect size between discovery- and replication-cohorts termed the Winner's Curse (p < 10-16). We show this is due in part to misreporting replication cohort-size as a maximum number, rather than per-locus one. In 39 studies accurately reporting per-locus cohort-size for attempted replication of 707 loci in samples with similar ancestry, replication rate matched expectation (predicted 458, observed 457, p = 0.94). In contrast, ancestry differences between replication and discovery (13 studies, 385 loci) cause the most highly-powered decile of loci to replicate worse than expected, due to difference in linkage disequilibrium.

Bias Characterization in Probabilistic Genotype Data and Improved Signal Detection with Multiple Imputation.

Missing data are an unavoidable component of modern statistical genetics. Different array or sequencing technologies cover different single nucleotide polymorphisms (SNPs), leading to a complicated mosaic pattern of missingness where both individual genotypes and entire SNPs are sporadically absent. Such missing data patterns cannot be ignored without introducing bias, yet cannot be inferred exclusively from nonmissing data. In genome-wide association studies, the accepted solution to missingness is to impute missing data using external reference haplotypes. The resulting probabilistic genotypes may be analyzed in the place of genotype calls. A general-purpose paradigm, called Multiple Imputation (MI), is known to model uncertainty in many contexts, yet it is not widely used in association studies. Here, we undertake a systematic evaluation of existing imputed data analysis methods and MI. We characterize biases related to uncertainty in association studies, and find that bias is introduced both at the imputation level, when imputation algorithms generate inconsistent genotype probabilities, and at the association level, when analysis methods inadequately model genotype uncertainty. We find that MI performs at least as well as existing methods or in some cases much better, and provides a straightforward paradigm for adapting existing genotype association methods to uncertain data.

High-depth whole genome sequencing of an Ashkenazi Jewish reference panel: enhancing sensitivity, accuracy, and imputation.

While increasingly large reference panels for genome-wide imputation have been recently made available, the degree to which imputation accuracy can be enhanced by population-specific reference panels remains an open question. Here, we sequenced at full-depth (≥ 30×), across two platforms (Illumina X Ten and Complete Genomics, Inc.), a moderately large (n = 738) cohort of samples drawn from the Ashkenazi Jewish population. We developed a series of quality control steps to optimize sensitivity, specificity, and comprehensiveness of variant calls in the reference panel, and then tested the accuracy of imputation against target cohorts drawn from the same population. Quality control (QC) thresholds for the Illumina X Ten platform were identified that permitted highly accurate calling of single nucleotide variants across 94% of the genome. QC procedures also identified numerous regions that are poorly mapped using current reference or alternate assemblies. After stringent QC, the population-specific reference panel produced more accurate and comprehensive imputation results relative to publicly available, large cosmopolitan reference panels, especially in the range of rare variants that may be most critical to further progress in mapping of complex phenotypes. The population-specific reference panel also permitted enhanced filtering of clinically irrelevant variants from personal genomes.

FTO genotype is associated with phenotypic variability of body mass index.

There is evidence across several species for genetic control of phenotypic variation of complex traits, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using ∼170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype), is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of ∼0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI, possibly mediated by DNA methylation. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.

Impact of Trauma System Structure on Injury Outcomes: A Systematic Review and Meta-Analysis.

BACKGROUND: The effectiveness of trauma systems in decreasing injury mortality and morbidity has been well demonstrated. However, little is known about which components contribute to their effectiveness. We aimed to systematically review the evidence of the impact of trauma system components on clinically important injury outcomes. METHODS: We searched MEDLINE, EMBASE, Cochrane CENTRAL, and BIOSIS/Web of Knowledge, gray literature and trauma association Web sites to identify studies evaluating the association between at least one trauma system component and injury outcome. We calculated pooled effect estimates using inverse-variance random-effects models. We evaluated quality of evidence using GRADE criteria. RESULTS: We screened 15,974 records, retaining 41 studies for qualitative synthesis and 19 for meta-analysis. Two recommended trauma system components were associated with reduced odds of mortality: inclusive design (odds ratio [OR] = 0.72 [0.65-0.80]) and helicopter transport (OR = 0.70 [0.55-0.88]). Pre-Hospital Advanced Trauma Life Support was associated with a significant reduction in hospital days (mean difference [MD] = 5.7 [4.4-7.0]) but a nonsignificant reduction in mortality (OR = 0.78 [0.44-1.39]). Population density of surgeons was associated with a nonsignificant decrease in mortality (MD = 0.58 [-0.22 to 1.39]). Trauma system maturity was associated with a significant reduction in mortality (OR = 0.76 [0.68-0.85]). Quality of evidence was low or very low for mortality and healthcare utilization. CONCLUSIONS: This review offers low-quality evidence for the effectiveness of an inclusive design and trauma system maturity and very-low-quality evidence for helicopter transport in reducing injury mortality. Further research should evaluate other recommended components of trauma systems and non-fatal outcomes and explore the impact of system component interactions.

The landscape of recombination in African Americans.

Recombination, together with mutation, gives rise to genetic variation in populations. Here we leverage the recent mixture of people of African and European ancestry in the Americas to build a genetic map measuring the probability of crossing over at each position in the genome, based on about 2.1 million crossovers in 30,000 unrelated African Americans. At intervals of more than three megabases it is nearly identical to a map built in Europeans. At finer scales it differs significantly, and we identify about 2,500 recombination hotspots that are active in people of West African ancestry but nearly inactive in Europeans. The probability of a crossover at these hotspots is almost fully controlled by the alleles an individual carries at PRDM9 (P value < 10(-245)). We identify a 17-base-pair DNA sequence motif that is enriched in these hotspots, and is an excellent match to the predicted binding target of PRDM9 alleles common in West Africans and rare in Europeans. Sites of this motif are predicted to be risk loci for disease-causing genomic rearrangements in individuals carrying these alleles. More generally, this map provides a resource for research in human genetic variation and evolution.

Mapping adipose and muscle tissue expression quantitative trait loci in African Americans to identify genes for type 2 diabetes and obesity.

Relative to European Americans, type 2 diabetes (T2D) is more prevalent in African Americans (AAs). Genetic variation may modulate transcript abundance in insulin-responsive tissues and contribute to risk; yet, published studies identifying expression quantitative trait loci (eQTLs) in African ancestry populations are restricted to blood cells. This study aims to develop a map of genetically regulated transcripts expressed in tissues important for glucose homeostasis in AAs, critical for identifying the genetic etiology of T2D and related traits. Quantitative measures of adipose and muscle gene expression, and genotypic data were integrated in 260 non-diabetic AAs to identify expression regulatory variants. Their roles in genetic susceptibility to T2D, and related metabolic phenotypes, were evaluated by mining GWAS datasets. eQTL analysis identified 1971 and 2078 cis-eGenes in adipose and muscle, respectively. Cis-eQTLs for 885 transcripts including top cis-eGenes CHURC1, USMG5, and ERAP2 were identified in both tissues. 62.1 % of top cis-eSNPs were within ±50 kb of transcription start sites and cis-eGenes were enriched for mitochondrial transcripts. Mining GWAS databases revealed association of cis-eSNPs for more than 50 genes with T2D (e.g. PIK3C2A, RBMS1, UFSP1), gluco-metabolic phenotypes (e.g. INPP5E, SNX17, ERAP2, FN3KRP), and obesity (e.g. POMC, CPEB4). Integration of GWAS meta-analysis data from AA cohorts revealed the most significant association for cis-eSNPs of ATP5SL and MCCC1 genes, with T2D and BMI, respectively. This study developed the first comprehensive map of adipose and muscle tissue eQTLs in AAs (publically accessible at https://mdsetaa.phs.wakehealth.edu ) and identified genetically regulated transcripts for delineating genetic causes of T2D, and related metabolic phenotypes.

Hundreds of variants clustered in genomic loci and biological pathways affect human height.

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Gene-centric approach identifies new and known loci for FVIII activity and VWF antigen levels in European Americans and African Americans.

Coagulation factor VIII and von Willebrand factor (VWF) are key proteins in procoagulant activation. Higher FVIII coagulant activity (FVIII :C) and VWF antigen (VWF :Ag) are risk factors for cardiovascular disease and venous thromboembolism. Beyond associations with ABO blood group, genetic determinants of FVIII and VWF are not well understood, especially in non European-American populations. We performed a genetic association study of FVIII :C and VWF:Ag that assessed 50,000 gene-centric single nucleotide polymorphisms (SNPs) in 18,556 European Americans (EAs) and 5,047 African Americans (AAs) from five population-based cohorts. Previously unreported associations for FVIII :C were identified in both AAs and EAs with KNG1 (most significantly associated SNP rs710446, Ile581Thr, Ile581Thr, P = 5.10 × 10(-7) in EAs and P = 3.88 × 10(-3) in AAs) and VWF rs7962217 (Gly2705Arg,P = 6.30 × 10(-9) in EAs and P = 2.98 × 10(-2) in AAs. Significant associations for FVIII :C were also observed with F8/TMLHE region SNP rs12557310 in EAs (P = 8.02 × 10(-10) ), with VWF rs1800380 in AAs (P = 5.62 × 10(-11) ), and with MAT1A rs2236568 in AAs (P51.69 × 10(-6) ). We replicated previously reported associations of FVIII :C and VWF :Ag with the ABO blood group, VWF rs1063856(Thr789Ala), rs216321 (Ala852Gln), and VWF rs2229446 (Arg2185Gln). Findings from this study expand our understanding of genetic influences for FVIII :C and VWF :Ag in both EAs and AAs.

The metabochip, a custom genotyping array for genetic studies of metabolic, cardiovascular, and anthropometric traits.

Genome-wide association studies have identified hundreds of loci for type 2 diabetes, coronary artery disease and myocardial infarction, as well as for related traits such as body mass index, glucose and insulin levels, lipid levels, and blood pressure. These studies also have pointed to thousands of loci with promising but not yet compelling association evidence. To establish association at additional loci and to characterize the genome-wide significant loci by fine-mapping, we designed the "Metabochip," a custom genotyping array that assays nearly 200,000 SNP markers. Here, we describe the Metabochip and its component SNP sets, evaluate its performance in capturing variation across the allele-frequency spectrum, describe solutions to methodological challenges commonly encountered in its analysis, and evaluate its performance as a platform for genotype imputation. The metabochip achieves dramatic cost efficiencies compared to designing single-trait follow-up reagents, and provides the opportunity to compare results across a range of related traits. The metabochip and similar custom genotyping arrays offer a powerful and cost-effective approach to follow-up large-scale genotyping and sequencing studies and advance our understanding of the genetic basis of complex human diseases and traits.

New susceptibility loci associated with kidney disease in type 1 diabetes.

Diabetic kidney disease, or diabetic nephropathy (DN), is a major complication of diabetes and the leading cause of end-stage renal disease (ESRD) that requires dialysis treatment or kidney transplantation. In addition to the decrease in the quality of life, DN accounts for a large proportion of the excess mortality associated with type 1 diabetes (T1D). Whereas the degree of glycemia plays a pivotal role in DN, a subset of individuals with poorly controlled T1D do not develop DN. Furthermore, strong familial aggregation supports genetic susceptibility to DN. However, the genes and the molecular mechanisms behind the disease remain poorly understood, and current therapeutic strategies rarely result in reversal of DN. In the GEnetics of Nephropathy: an International Effort (GENIE) consortium, we have undertaken a meta-analysis of genome-wide association studies (GWAS) of T1D DN comprising ~2.4 million single nucleotide polymorphisms (SNPs) imputed in 6,691 individuals. After additional genotyping of 41 top ranked SNPs representing 24 independent signals in 5,873 individuals, combined meta-analysis revealed association of two SNPs with ESRD: rs7583877 in the AFF3 gene (P = 1.2 × 10(-8)) and an intergenic SNP on chromosome 15q26 between the genes RGMA and MCTP2, rs12437854 (P = 2.0 × 10(-9)). Functional data suggest that AFF3 influences renal tubule fibrosis via the transforming growth factor-beta (TGF-ß1) pathway. The strongest association with DN as a primary phenotype was seen for an intronic SNP in the ERBB4 gene (rs7588550, P = 2.1 × 10(-7)), a gene with type 2 diabetes DN differential expression and in the same intron as a variant with cis-eQTL expression of ERBB4. All these detected associations represent new signals in the pathogenesis of DN.

Establishing a standard for assessing the appropriateness of trauma team activation: a retrospective evaluation of two outcome measures.

BACKGROUND: Trauma team activation (TTA) is a well-recognised standard of care to provide rapid stabilisation of patients with time-critical, life-threatening injuries. TTA is associated with a substantial use of valuable hospital resources that may adversely impact upon the care of other patients if not carefully balanced. This study aimed to determine which of the two outcome measures would be a better standard for assessing the appropriateness of TTA at a paediatric centre: retrospective major trauma classification as defined within our state, and the use of emergency department high-level resources as recently published by Falcone et al (Falcone Interventions; FI). METHODS: Trauma registry data and patients' charts between February 2011 and June 2013 were reviewed. Over-triage and under-triage rates for TTA, using both major trauma and FIs as outcome measures, were compared. RESULTS: Totally, 280 patients received TTA, 243 met major trauma definition and 102 received one or more FIs. The rates of over-triage and under-triage were 39.7% (95% CI 35.0 to 44.6%) and 30.5% (95% CI 26.2 to 35.2%), when the major trauma definition was used as the outcome measure, and 67.5% (95% CI 62.2 to 72.5%) and 10.8% (95% CI 7.9 to 14.8%) when FI was used. Only 17.1% (95% CI 11.4% to 24.7%) of the under-triaged patients using the major trauma definition received one or more FIs. CONCLUSIONS: Assessment of TTA appropriateness varied significantly based on the outcome measure used. FIs better reflected the use of acute-care TTA-related resources compared with the major trauma definition, and it should be used as the gold standard to prospectively assess and refine TTA criteria.

Synthesizing genome-wide association studies and expression microarray reveals novel genes that act in the human growth plate to modulate height.

Previous meta-analysis of genome-wide association (GWA) studies has identified 180 loci that influence adult height. However, each GWA locus typically comprises a set of contiguous genes, only one of which presumably modulates height. We reasoned that many of the causative genes within these loci influence height because they are expressed in and function in the growth plate, a cartilaginous structure that causes bone elongation and thus determines stature. Therefore, we used expression microarray studies of mouse and rat growth plate, human disease databases and a mouse knockout phenotype database to identify genes within the GWAS loci that are likely required for normal growth plate function. Each of these approaches identified significantly more genes within the GWA height loci than at random genomic locations (P < 0.0001 each), supporting the validity of the approach. The combined analysis strongly implicates 78 genes in growth plate function, including multiple genes that participate in PTHrP-IHH, BMP and CNP signaling, and many genes that have not previously been implicated in the growth plate. Thus, this analysis reveals a large number of novel genes that regulate human growth plate chondrogenesis and thereby contribute to the normal variations in human adult height. The analytic approach developed for this study may be applied to GWA studies for other common polygenic traits and diseases, thus providing a new general strategy to identify causative genes within GWA loci and to translate genetic associations into mechanistic biological insights.

Large multiethnic Candidate Gene Study for C-reactive protein levels: identification of a novel association at CD36 in African Americans.

C-reactive protein (CRP) is a heritable biomarker of systemic inflammation and a predictor of cardiovascular disease (CVD). Large-scale genetic association studies for CRP have largely focused on individuals of European descent. We sought to uncover novel genetic variants for CRP in a multiethnic sample using the ITMAT Broad-CARe (IBC) array, a custom 50,000 SNP gene-centric array having dense coverage of over 2,000 candidate CVD genes. We performed analyses on 7,570 African Americans (AA) from the Candidate gene Association Resource (CARe) study and race-combined meta-analyses that included 29,939 additional individuals of European descent from CARe, the Women's Health Initiative (WHI) and KORA studies. We observed array-wide significance (p < 2.2 × 10(-6)) for four loci in AA, three of which have been reported previously in individuals of European descent (IL6R, p = 2.0 × 10(-6); CRP, p = 4.2 × 10(-71); APOE, p = 1.6 × 10(-6)). The fourth significant locus, CD36 (p = 1.6 × 10(-6)), was observed at a functional variant (rs3211938) that is extremely rare in individuals of European descent. We replicated the CD36 finding (p = 1.8 × 10(-5)) in an independent sample of 8,041 AA women from WHI; a meta-analysis combining the CARe and WHI AA results at rs3211938 reached genome-wide significance (p = 1.5 × 10(-10)). In the race-combined meta-analyses, 13 loci reached significance, including ten (CRP, TOMM40/APOE/APOC1, HNF1A, LEPR, GCKR, IL6R, IL1RN, NLRP3, HNF4A and BAZ1B/BCL7B) previously associated with CRP, and one (ARNTL) previously reported to be nominally associated with CRP. Two novel loci were also detected (RPS6KB1, p = 2.0 × 10(-6); CD36, p = 1.4 × 10(-6)). These results highlight both shared and unique genetic risk factors for CRP in AA compared to populations of European descent.

Genome-wide comparison of African-ancestry populations from CARe and other cohorts reveals signals of natural selection.

The study of recent natural selection in human populations has important applications to human history and medicine. Positive natural selection drives the increase in beneficial alleles and plays a role in explaining diversity across human populations. By discovering traits subject to positive selection, we can better understand the population level response to environmental pressures including infectious disease. Our study examines unusual population differentiation between three large data sets to detect natural selection. The populations examined, African Americans, Nigerians, and Gambians, are genetically close to one another (F(ST) < 0.01 for all pairs), allowing us to detect selection even with moderate changes in allele frequency. We also develop a tree-based method to pinpoint the population in which selection occurred, incorporating information across populations. Our genome-wide significant results corroborate loci previously reported to be under selection in Africans including HBB and CD36. At the HLA locus on chromosome 6, results suggest the existence of multiple, independent targets of population-specific selective pressure. In addition, we report a genome-wide significant (p = 1.36 × 10(-11)) signal of selection in the prostate stem cell antigen (PSCA) gene. The most significantly differentiated marker in our analysis, rs2920283, is highly differentiated in both Africa and East Asia and has prior genome-wide significant associations to bladder and gastric cancers.