rs1136287 - SERPINF1

Magnitude 2.2 · 4 studies on file

Reported associations

• Metabolic GWAS of elite athletes reveals novel genetically-influenced metabolites associated with athletic performance - Unknown journal (n.d.) · Unknown authors · PubMed 31882771

  ABSTRACT: Genetic research of elite athletic performance has been hindered by the complex phenotype and the relatively small effect size of the identified genetic variants. The aims of this study were to identify genetic predisposition to elite athletic performance by investigating genetically-influenced metabolites that discriminate elite athletes from non-elite athletes and to identify those associated with endurance sports. By conducting a genome wide association study with high-resolution metabolomics profiling in 490 elite athletes, common variant metabolic quantitative trait loci (mQTLs) were identified and compared with previously identified mQTLs in non-elite athletes. Among the identified mQTLs, those associated with endurance metabolites were determined. Two novel genetic loci in

• Whole Genome Sequence Analysis of the Plasma Proteome in Black Adults Provides Novel Insights into Cardiovascular Disease - Unknown journal (n.d.) · Unknown authors · PubMed 34814699

  ABSTRACT: Background: Plasma proteins are critical mediators of cardiovascular processes and are the targets of many drugs. Previous efforts to characterize the genetic architecture of the plasma proteome have been limited by a focus on individuals of European descent and leveraged genotyping arrays and imputation. Here we describe whole genome sequence analysis of the plasma proteome in individuals with greater African ancestry, increasing our power to identify novel genetic determinants. Methods: Proteomic profiling of 1,301 proteins was performed in 1852 Black adults from the Jackson Heart Study using aptamer-based proteomics (SomaScan®). Whole genome sequencing association analysis was ascertained for all variants with minor allele count ≥ 5. Results were validated using an alternat

• A saturated map of common genetic variants associated with human height - Unknown journal (n.d.) · Unknown authors · PubMed 36224396

  ABSTRACT: Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation

• Co-regulatory networks of human serum proteins link genetics to disease - Unknown journal (n.d.) · Unknown authors · PubMed 30072576

  ABSTRACT: Proteins circulating in the blood are critical for age-related disease processes; however, the serum proteome has remained largely unexplored. To this end, 4137 proteins covering most predicted extracellular proteins were measured in the serum of 5457 Icelanders over 65 years of age. Pairwise correlation between proteins as they varied across individuals revealed 27 different network modules of serum proteins, many of which were associated with cardiovascular and metabolic disease states, as well as overall survival. The protein modules were controlled by cis- and trans-acting genetic variants, which in many cases were also associated with complex disease. This revealed co-regulated groups of circulating proteins that incorporated regulatory control between tissues and demonstrat

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