Genetic studies of plasma analytes identify novel potential biomarkers for several complex traits
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ABSTRACT:
SUBMITTER: Deming Y
PROVIDER: S-EPMC4698720 | biostudies-literature | 2016 Jan
REPOSITORIES: biostudies-literature
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Project description:Evolve and resequence (E&R) studies are frequently used to dissect the genetic basis of quantitative traits. By subjecting a population to truncating selection for several generations and estimating the allele frequency differences between selected and nonselected populations using next-generation sequencing (NGS), the loci contributing to the selected trait may be identified. The role of different parameters, such as, the population size or the number of replicate populations has been examined in previous works. However, the influence of the selection regime, that is the strength of truncating selection during the experiment, remains little explored. Using whole genome, individual based forward simulations of E&R studies, we found that the power to identify the causative alleles may be maximized by gradually increasing the strength of truncating selection during the experiment. Notably, such an optimal selection regime comes at no or little additional cost in terms of sequencing effort and experimental time. Interestingly, we also found that a selection regime which optimizes the power to identify the causative loci is not necessarily identical to a regime that maximizes the phenotypic response. Finally, our simulations suggest that an E&R study with an optimized selection regime may have a higher power to identify the genetic basis of quantitative traits than a genome-wide association study, highlighting that E&R is a powerful approach for finding the loci underlying complex traits.
| S-EPMC6878953 | biostudies-literature
Project description:Delaying plasma separation after phlebotomy (processing delay) can cause perturbations of numerous small molecule analytes. This poses a major challenge to the clinical application of metabolomics analyses. In this study, we further define the analyte changes that occur during processing delays and generate a model for the post hoc detection of this preanalytical error.Using an untargeted metabolomics platform we analyzed EDTA-preserved plasma specimens harvested after processing delays lasting from minutes to days. Identified biomarkers were tested on (i) a test-set of samples exposed to either minimal (n=28) or long delays (n=40) and (ii) samples collected in a clinical setting for metabolomics analysis (n=141).A total of 149 of 803 plasma analytes changed significantly during processing delays lasting 0-20h. Biomarkers related to erythrocyte metabolism, e.g., 5-oxoproline, lactate, and an ornithine/arginine ratio, were the strongest predictors of plasma separation delays, providing 100% diagnostic accuracy in the test set. Together these biomarkers could accurately predict processing delays >2h in a pilot study and we found evidence of sample mishandling in 4 of 141 clinically derived specimens.Our study highlights the widespread effects of processing delays and proposes that erythrocyte metabolism creates a reproducible signal that can identify mishandled specimens in metabolomics studies.
| S-EPMC5321821 | biostudies-literature
Project description:BackgroundGenome-wide association studies can have limited power to identify QTL, partly due to the stringent correction for multiple testing and low linkage-disequilibrium between SNPs and QTL. Regional Heritability Mapping (RHM) has been advanced as an alternative approach to capture underlying genetic effects. In this study, RHM was used to identify loci underlying variation in the 16(th) QTLMAS workshop simulated traits.MethodsThe method was implemented by fitting a mixed model where a genomic region and the overall genetic background were added as random effects. Heritabilities for the genetic regional effects were estimated, and the presence of a QTL in the region was tested using a likelihood ratio test (LRT). Several region sizes were considered (100, 50 and 20 adjacent SNPs). Bonferroni correction was used to calculate the LRT thresholds for genome-wide (p < 0.05) and suggestive (i.e., one false positive per genome scan) significance.ResultsGenomic heritabilities (0.31, 0.32 and 0.48, respectively) and genetic correlations (0.80, -0.42 and 0.19, between trait-pairs 1&2, 1&3 and 2&3) were similar to the simulated ones. RHM identified 7 QTL (4 at genome-wide and 3 at suggestive level) for Trait1; 4 (2 genome-wide and 2 suggestive) for Trait2; and 7 (6 genome-wide and 1 suggestive) for Trait3. Only one of the identified suggestive QTL was a false-positive. The position of these QTL tended to coincide with the position where the largest QTL (or several of them) were simulated. Several signals were detected for the simulated QTL with smaller effect. A combined analysis including all significant regions showed that they explain more than half of the total genetic variance of the traits. However, this might be overestimated, due to Beavis effect. All QTL affecting traits 1&2 and 2&3 had positive correlations, following the trend of the overall correlation of both trait-pairs. All but one QTL affecting traits 1&3 were negatively correlated, in agreement with the simulated situation. Moreover, RHM identified extra loci that were not found by association and linkage analysis, highlighting the improved power of this approach.ConclusionsRHM identified the largest QTL among the simulated ones, with some signals for the ones with small effect. Moreover, RHM performed better than association and linkage analysis, in terms of both power and resolution.
| S-EPMC4195407 | biostudies-literature
Project description:Aims: Differential expression profiles of microRNAs (miRNAs) are associated with autoimmune diseases. This study sought to elucidate the plasma exosomal miRNA expression profiles of patients with rheumatoid arthritis (RA) and their potential clinical significance. Methods: In the screening phase, small RNA sequencing was performed to characterize dysregulated exosome-derived miRNAs in the plasma samples from six RA patients and six healthy controls. In the independent validation phase, the candidate plasma exosomal miRNAs were verified in 40 RA patients and 32 healthy controls using quantitative real-time PCR. The association of miRNA levels with clinical characteristics in RA patients was tested. The value of these miRNAs in diagnosing RA was assessed with the receiver operating characteristic curve. Results: Totally 177 and 129 miRNAs were upregulated and downregulated, respectively in RA patients versus healthy controls in the screening phase. There were 10 candidate plasma exosomal miRNAs selected for the next identification. Compared with the healthy controls, eight plasma exosomal miRNAs (let-7a-5p, let-7b-5p, let-7d-5p, let-7f-5p, let-7g-5p, let-7i-5p, miR-128-3p, and miR-25-3p) were significantly elevated in RA patients, but miR-144-3p and miR-15a-5p expression exhibited no significant changes. The let-7a-5p and miR-25-3p levels were associated with rheumatoid factor-positive phenotype in RA patients. For the eight miRNAs, the area under the receiver operating characteristic curve (AUC) ranged from 0.641 to 0.843, and their combination had a high diagnostic accuracy for RA (AUC = 0.916). Conclusions: Our study illustrates that novel exosomal miRNAs in the plasma may represent potential noninvasive biomarkers for RA.
2023-09-24 | GSE218599 | GEO
Project description:Aiming to identify novel genetic loci for pigmentation and skin cancer, we conducted a series of genome-wide association studies on hair color, eye color, number of sunburns, tanning ability and number of non-melanoma skin cancers (NMSCs) among 10 183 European Americans in the discovery stage and 4504 European Americans in the replication stage (for eye color, 3871 males in the discovery stage and 2496 males in the replication stage). We targeted novel chromosome regions besides the known ones for replication. As a result, we identified a new region downstream of the EDNRB gene on 13q22 associated with hair color and the strongest association was the single-nucleotide polymorphism (SNP) rs975739 (P = 2.4 × 10(-14); P = 5.4 × 10(-9) in the discovery set and P = 1.2 × 10(-6) in the replication set). Using blue, intermediate (including green) and brown eye colors as co-dominant outcomes, we identified the SNP rs3002288 in VASH2 on 1q32.3 associated with brown eye (P = 7.0 × 10(-8); P = 5.3 × 10(-5) in the discovery set and P = 0.02 in the replication set). Additionally, we identified a significant interaction between the SNPs rs7173419 and rs12913832 in the OCA2 gene region on brown eye color (P-value for interaction = 3.8 × 10(-3)). As for the number of NMSCs, we identified two independent SNPs on chr6 and one SNP on chromosome 14: rs12203592 in IRF4 (P = 7.2 × 10(-14); P = 1.8 × 10(-8) in the discovery set and P = 6.7 × 10(-7) in the replication set), rs12202284 between IRF4 and EXOC2 (P = 5.0 × 10(-8); P = 6.6 × 10(-7) in the discovery set and P = 3.0 × 10(-3) in the replication set) and rs8015138 upstream of GNG2 (P = 6.6 × 10(-8); P = 5.3 × 10(-7) in the discovery set and P = 0.01 in the replication set).
| S-EPMC3690971 | biostudies-literature
Project description:The availability of affordable high throughput technology for parallel genotyping has opened the field of genetics to genome-wide association studies (GWAS), and in the last few years hundreds of articles reporting results of GWAS for a variety of heritable traits have been published. What do these results tell us? Although GWAS have discovered a few hundred reproducible associations, this number is underwhelming in relation to the huge amount of data produced, and challenges the conjecture that common variants may be the genetic causes of common diseases. We argue that the massive amount of genetic data that result from these studies remains largely unexplored and unexploited because of the challenge of mining and modeling enormous data sets, the difficulty of using nontraditional computational techniques and the focus of accepted statistical analyses on controlling the false positive rate rather than limiting the false negative rate. In this article, we will review the common approach to analysis of GWAS data and then discuss options to learn more from these data. We will use examples from our ongoing studies of sickle cell anemia and also GWAS in multigenic traits.
| S-EPMC2895326 | biostudies-literature
Project description:Complex traits and diseases can be influenced by both genetics and environment. However, given the large number of environmental stimuli and power challenges for gene-by-environment testing, it remains a critical challenge to identify and prioritize specific disease-relevant environmental exposures. We propose a novel framework for leveraging signals from transcriptional responses to environmental perturbations to identify disease-relevant perturbations that can modulate genetic risk for complex traits and inform the functions of genetic variants associated with complex traits. We perturbed human skeletal muscle, fat, and liver relevant cell lines with 21 perturbations affecting insulin resistance, glucose homeostasis, and metabolic regulation in humans and identified thousands of environmentally responsive genes. By combining these data with GWAS from 31 distinct polygenic traits, we show that the heritability of multiple traits is enriched in regions surrounding genes responsive to specific perturbations and, further, that environmentally responsive genes are enriched for associations with specific diseases and phenotypes from the GWAS catalog. Overall, we demonstrate the advantages of large-scale characterization of transcriptional changes in diversely stimulated and pathologically relevant cells to identify disease-relevant perturbations.
2021-07-09 | GSE179347 | GEO
Project description:BackgroundBiological 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.ResultsLeveraging 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.ConclusionThis study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.
| S-EPMC8243879 | biostudies-literature
Project description:Non-human primates provide genetic model systems biologically intermediate between humans and other mammalian model organisms. Populations of Caribbean vervet monkeys (Chlorocebus aethiops sabaeus) are genetically homogeneous and large enough to permit well-powered genetic mapping studies of quantitative traits relevant to human health, including expression quantitative trait loci (eQTL). Previous transcriptome-wide investigation in an extended vervet pedigree identified 29 heritable transcripts for which levels of expression in peripheral blood correlate strongly with expression levels in the brain. Quantitative trait linkage analysis using 261 microsatellite markers identified significant (n = 8) and suggestive (n = 4) linkages for 12 of these transcripts, including both cis- and trans-eQTL. Seven transcripts, located on different chromosomes, showed maximum linkage to markers in a single region of vervet chromosome 9; this observation suggests the possibility of a master trans-regulator locus in this region. For one cis-eQTL (at B3GALTL, beta-1,3-glucosyltransferase), we conducted follow-up single nucleotide polymorphism genotyping and fine-scale association analysis in a sample of unrelated Caribbean vervets, localizing this eQTL to a region of <200 kb. These results suggest the value of pedigree and population samples of the Caribbean vervet for linkage and association mapping studies of quantitative traits. The imminent whole genome sequencing of many of these vervet samples will enhance the power of such investigations by providing a comprehensive catalog of genetic variation.
| S-EPMC3392106 | biostudies-literature
Project description:The successes of genome-wide association (GWA) studies have mainly come from studies performed in populations of European descent. Since complex traits are characterized by marked genetic heterogeneity, the findings so far may provide an incomplete picture of the genetic architecture of complex traits. However, the recent GWA studies performed on East Asian populations now allow us to globally assess the heterogeneity of association signals between populations of European ancestry and East Asians, and the possible obstacles for multi-ethnic GWA studies. We focused on four different traits that represent a broad range of complex phenotypes, which have been studied in both Europeans and East Asians: type 2 diabetes, systemic lupus erythematosus, ulcerative colitis and height. For each trait, we observed that most of the risk loci identified in East Asians were shared with Europeans. However, we also observed that a significant part of the association signals at these shared loci seems to be independent between populations. This suggests that disease aetiology is common between populations, but that risk variants are often population specific. These variants could be truly population specific and result from natural selection, genetic drift and recent mutations, or they could be spurious, caused by the limitations of the method of analysis employed in the GWA studies. We therefore propose a three-stage framework for multi-ethnic GWA analyses, starting with the commonly used single-nucleotide polymorphism-based analysis, and followed by a gene-based approach and a pathway-based analysis, which will take into account the heterogeneity of association between populations at different levels.
| S-EPMC3179384 | biostudies-literature