| 1. |
- Sung, Yun Ju, et al.
(författare)
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A multi-ancestry genome-wide study incorporating gene-smoking interactions identifies multiple new loci for pulse pressure and mean arterial pressure
- 2019
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Ingår i: Human Molecular Genetics. - : Oxford University Press. - 0964-6906 .- 1460-2083. ; 28:15, s. 2615-2633
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Tidskriftsartikel (refereegranskat)abstract
- Elevated blood pressure (BP), a leading cause of global morbidity and mortality, is influenced by both genetic and lifestyle factors. Cigarette smoking is one such lifestyle factor. Across five ancestries, we performed a genome-wide gene–smoking interaction study of mean arterial pressure (MAP) and pulse pressure (PP) in 129 913 individuals in stage 1 and follow-up analysis in 480 178 additional individuals in stage 2. We report here 136 loci significantly associated with MAP and/or PP. Of these, 61 were previously published through main-effect analysis of BP traits, 37 were recently reported by us for systolic BP and/or diastolic BP through gene–smoking interaction analysis and 38 were newly identified (P < 5 × 10−8, false discovery rate < 0.05). We also identified nine new signals near known loci. Of the 136 loci, 8 showed significant interaction with smoking status. They include CSMD1 previously reported for insulin resistance and BP in the spontaneously hypertensive rats. Many of the 38 new loci show biologic plausibility for a role in BP regulation. SLC26A7 encodes a chloride/bicarbonate exchanger expressed in the renal outer medullary collecting duct. AVPR1A is widely expressed, including in vascular smooth muscle cells, kidney, myocardium and brain. FHAD1 is a long non-coding RNA overexpressed in heart failure. TMEM51 was associated with contractile function in cardiomyocytes. CASP9 plays a central role in cardiomyocyte apoptosis. Identified only in African ancestry were 30 novel loci. Our findings highlight the value of multi-ancestry investigations, particularly in studies of interaction with lifestyle factors, where genomic and lifestyle differences may contribute to novel findings.
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| 2. |
- Mosley, Jonathan D., et al.
(författare)
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Probing the Virtual Proteome to Identify Novel Disease Biomarkers
- 2018
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Ingår i: Circulation. - 1524-4539. ; 138:22, s. 2469-2481
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Proteomic approaches allow measurement of thousands of proteins in a single specimen, which can accelerate biomarker discovery. However, applying these technologies to massive biobanks is not currently feasible because of the practical barriers and costs of implementing such assays at scale. To overcome these challenges, we used a "virtual proteomic" approach, linking genetically predicted protein levels to clinical diagnoses in >40 000 individuals. METHODS: We used genome-wide association data from the Framingham Heart Study (n=759) to construct genetic predictors for 1129 plasma protein levels. We validated the genetic predictors for 268 proteins and used them to compute predicted protein levels in 41 288 genotyped individuals in the Electronic Medical Records and Genomics (eMERGE) cohort. We tested associations for each predicted protein with 1128 clinical phenotypes. Lead associations were validated with directly measured protein levels and either low-density lipoprotein cholesterol or subclinical atherosclerosis in the MDCS (Malmö Diet and Cancer Study; n=651). RESULTS: In the virtual proteomic analysis in eMERGE, 55 proteins were associated with 89 distinct diagnoses at a false discovery rate q<0.1. Among these, 13 associations involved lipid (n=7) or atherosclerosis (n=6) phenotypes. We tested each association for validation in MDCS using directly measured protein levels. At Bonferroni-adjusted significance thresholds, levels of apolipoprotein E isoforms were associated with hyperlipidemia, and circulating C-type lectin domain family 1 member B and platelet-derived growth factor receptor-β predicted subclinical atherosclerosis. Odds ratios for carotid atherosclerosis were 1.31 (95% CI, 1.08-1.58; P=0.006) per 1-SD increment in C-type lectin domain family 1 member B and 0.79 (0.66-0.94; P=0.008) per 1-SD increment in platelet-derived growth factor receptor-β. CONCLUSIONS: We demonstrate a biomarker discovery paradigm to identify candidate biomarkers of cardiovascular and other diseases.
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| 3. |
- Ngo, Debby, et al.
(författare)
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Proteomic profiling reveals novel biomarkers and pathways in yype 2 diabetes risk
- 2021
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Ingår i: JCI Insight. - : American Society for Clinical Investigation. - 2379-3708. ; 6:5
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Tidskriftsartikel (refereegranskat)abstract
- Recent advances in proteomic technologies have made high throughput profiling of low abundance proteins in large epidemiological cohorts increasingly feasible. We investigated whether aptamer-based proteomic profiling could identify biomarkers associated with future development of type 2 diabetes (T2DM) beyond known risk factors. We identified dozens of markers with highly significant associations with future T2DM across two large longitudinal cohorts (n=2,839) followed for up to 16 years. We leveraged proteomic, metabolomic, genetic and clinical data from humans to nominate one specific candidate to test for potential causal relationships in model systems. Our studies identified functional effects of aminoacylase 1 (ACY1), a top protein association with future T2DM risk, on amino acid metabolism and insulin homeostasis in vitro and in vivo. Further, a loss-of-function variant associated with circulating levels of the biomarker WAP, Kazal, immunoglobulin, Kunitz and NTR domain-containing protein 2 (WFIKKN2) was in turn associated with fasting glucose, hemoglobin A1c and HOMA-IR measurements in humans. In addition to identifying novel disease markers and potential pathways in T2DM, we provide publicly available data to be leveraged for new insights about gene function and disease pathogenesis in the context of human metabolism. .
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| 4. |
- Satizabal, Claudia L., et al.
(författare)
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Genetic architecture of subcortical brain structures in 38,851 individuals
- 2019
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Ingår i: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 51:11, s. 1624-
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Tidskriftsartikel (refereegranskat)abstract
- Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.
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| 5. |
- Escott-Price, Valentina, et al.
(författare)
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Gene-Wide Analysis Detects Two New Susceptibility Genes for Alzheimer's Disease
- 2014
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 9:6, s. e94661-
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Tidskriftsartikel (refereegranskat)abstract
- Background: Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls. Principal Findings: In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p = 1.4x10(-6)) and 14 (IGHV1-67 p = 7.9x10(-8)) which indexed novel susceptibility loci. Significance: The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease.
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| 6. |
- Lango Allen, Hana, et al.
(författare)
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Hundreds of variants clustered in genomic loci and biological pathways affect human height.
- 2010
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 467:7317, s. 832-8
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 7. |
- Chen, Dorothy M, et al.
(författare)
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Transcriptome-Wide Association Analysis Identifies Candidate Susceptibility Genes for Prostate-Specific Antigen Levels in Men Without Prostate Cancer
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Ingår i: Human Genetics and Genomics Advances. - 2666-2477.
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Tidskriftsartikel (refereegranskat)abstract
- Deciphering the genetic basis of prostate-specific antigen (PSA) levels may improve their utility for prostate cancer (PCa) screening. Using genome-wide summary statistics from 95,768 PCa-free men, we conducted a transcriptome-wide association study (TWAS) to examine impacts of genetically predicted gene expression on PSA. Analyses identified 41 statistically significant (p < 0.05/12,192 = 4.10×10 -6) associations in whole blood and 39 statistically significant (p < 0.05/13,844 = 3.61×10 -6) associations in prostate tissue, with 18 genes associated in both tissues. Cross-tissue analyses identified 155 statistically significantly (p < 0.05/22,249 = 2.25×10 -6) genes. Out of 173 unique PSA-associated genes across analyses, we replicated 151 (87.3%) in TWAS of 209,318 PCa-free individuals from the Million Veteran Program. Based on conditional analyses, we found 20 genes (11 single-tissue, nine cross-tissue) that were associated with PSA levels in the discovery TWAS that were not attributable to a lead variant from a genome-wide association study (GWAS). Ten of these 20 genes replicated, and two of the replicated genes had colocalization probability > 0.5: CCNA2 and HIST1H2BN. Six of the 20 identified genes are not known to impact PCa risk. Fine mapping based on whole blood and prostate tissue revealed five protein-coding genes with evidence of causal relationships with PSA levels. Of these five genes, four exhibited evidence of colocalization and one was conditionally independent of previous GWAS findings. These results yield hypotheses that should be further explored to improve understanding of genetic factors underlying PSA levels.
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| 8. |
- Chen, Dorothy M, et al.
(författare)
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Transcriptome-Wide Association Analysis Identifies Novel Candidate Susceptibility Genes for Prostate-Specific Antigen Levels in Men Without Prostate Cancer
- 2023
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Deciphering the genetic basis of prostate-specific antigen (PSA) levels may improve their utility to screen for prostate cancer (PCa). We thus conducted a transcriptome-wide association study (TWAS) of PSA levels using genome-wide summary statistics from 95,768 PCa-free men, the MetaXcan framework, and gene prediction models trained in Genotype-Tissue Expression (GTEx) project data. Tissue-specific analyses identified 41 statistically significant (p < 0.05/12,192 = 4.10e-6) associations in whole blood and 39 statistically significant (p < 0.05/13,844 = 3.61e-6) associations in prostate tissue, with 18 genes associated in both tissues. Cross-tissue analyses that combined associations across 45 tissues identified 155 genes that were statistically significantly (p < 0.05/22,249 = 2.25e-6) associated with PSA levels. Based on conditional analyses that assessed whether TWAS associations were attributable to a lead GWAS variant, we found 20 novel genes (11 single-tissue, 9 cross-tissue) that were associated with PSA levels in the TWAS. Of these novel genes, five showed evidence of colocalization (colocalization probability > 0.5): EXOSC9, CCNA2, HIST1H2BN, RP11-182L21.6 , and RP11-327J17.2 . Six of the 20 novel genes are not known to impact PCa risk. These findings yield new hypotheses for genetic factors underlying PSA levels that should be further explored toward improving our understanding of PSA biology.
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| 9. |
- Hoffmann, Thomas J, et al.
(författare)
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Genome-wide association study of prostate-specific antigen levels in 392,522 men identifies new loci and improves cross-ancestry prediction
- 2023
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- We conducted a multi-ancestry genome-wide association study of prostate-specific antigen (PSA) levels in 296,754 men (211,342 European ancestry; 58,236 African ancestry; 23,546 Hispanic/Latino; 3,630 Asian ancestry; 96.5% of participants were from the Million Veteran Program). We identified 318 independent genome-wide significant (p≤5e-8) variants, 184 of which were novel. Most demonstrated evidence of replication in an independent cohort (n=95,768). Meta-analyzing discovery and replication (n=392,522) identified 447 variants, of which a further 111 were novel. Out-of-sample variance in PSA explained by our new polygenic risk score reached 16.9% (95% CI=16.1%-17.8%) in European ancestry, 9.5% (95% CI=7.0%-12.2%) in African ancestry, 18.6% (95% CI=15.8%-21.4%) in Hispanic/Latino, and 15.3% (95% CI=12.7%-18.1%) in Asian ancestry, and lower for higher age. Our study highlights how including proportionally more participants from underrepresented populations improves genetic prediction of PSA levels, with potential to personalize prostate cancer screening.
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| 10. |
- Jones, Lesley, et al.
(författare)
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Convergent genetic and expression data implicate immunity in Alzheimer's disease
- 2015
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Ingår i: Alzheimer's & Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 11:6, s. 658-671
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Tidskriftsartikel (refereegranskat)abstract
- Background: Late-onset Alzheimer's disease (AD) is heritable with 20 genes showing genome-wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease, we extended these genetic data in a pathway analysis. Methods: The ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain. Results: ALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response (P = 3.27 X 10(-12) after multiple testing correction for pathways), regulation of endocytosis (P = 1.31 X 10(-11)), cholesterol transport (P = 2.96 X 10(-9)), and proteasome-ubiquitin activity (P = 1.34 X 10(-6)). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected P = .002-.05). Conclusions: The immime response, regulation of endocytosis, cholesterol transport, and protein ubiquitination represent prime targets for AD therapeutics.
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