From ‘Omics to Multi-omics Technologies: the Discovery of Novel Causal Mediators

Lander ES, Linton LM, Birren B, Nusbaum C, Zody MC, Baldwin J, et al. Initial sequencing and analysis of the human genome. Nature. 2001;409:860–921.

Article  Google Scholar 

Venter JC, Adams MD, Myers EW, Li PW, Mural RJ, Sutton GG, et al. The sequence of the human genome. Science. 2001;291:49.

Article  Google Scholar 

Uffelmann E, Huang QQ, Munung NS, de Vries J, Okada Y, Martin AR, et al. Genome-wide association studies. Nat Rev Methods Primer. 2021;1:59.

Article  Google Scholar 

Franceschini N, Giambartolomei C, de Vries PS, Finan C, Bis JC, Huntley RP, et al. GWAS and colocalization analyses implicate carotid intima-media thickness and carotid plaque loci in cardiovascular outcomes. Nat Commun. 2018;9:5141.

Article  Google Scholar 

Klarin D, Damrauer SM, Cho K, Sun YV, Teslovich TM, Honerlaw J, et al. Genetics of blood lipids among ~300,000 multi-ethnic participants of the Million Veteran Program. Nat Genet. 2018;50:1514–23.

Article  Google Scholar 

Teslovich TM, Musunuru K, Smith AV, Edmondson AC, Stylianou IM, Koseki M, et al. Biological, clinical and population relevance of 95 loci for blood lipids. Nature. 2010;466:707–13.

Article  Google Scholar 

Malik R, Chauhan G, Traylor M, Sargurupremraj M, Okada Y, Mishra A, et al. Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes. Nat Genet. 2018;50:524–37.

Article  Google Scholar 

the CARDIoGRAMplusC4D Consortium. A comprehensive 1000 Genomes–based genome-wide association meta-analysis of coronary artery disease. Nat Genet. 2015;47:1121–30.

Article  Google Scholar 

van der Harst P, Verweij N. Identification of 64 novel genetic loci provides an expanded view on the genetic architecture of coronary artery disease. Circ Res. 2018;122:433–43.

Article  Google Scholar 

Matsunaga H, Ito K, Akiyama M, Takahashi A, Koyama S, Nomura S, et al. Transethnic meta-analysis of genome-wide association studies identifies three new loci and characterizes population-specific differences for coronary artery disease. Circ Genomic Precis Med. 2020;13:e002670.

Article  Google Scholar 

Musunuru K, Strong A, Frank-Kamenetsky M, Lee NE, Ahfeldt T, Sachs KV, et al. From noncoding variant to phenotype via SORT1 at the 1p13 cholesterol locus. Nature. 2010;466:714–9.

Article  Google Scholar 

Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018;562:203–9.

Article  Google Scholar 

Sakaue S, Kanai M, Tanigawa Y, Karjalainen J, Kurki M, Koshiba S, et al. A cross-population atlas of genetic associations for 220 human phenotypes. Nat Genet. 2021;53:1415–24.

Article  Google Scholar 

Zhou W, Kanai M, Wu K-HH, Rasheed H, Tsuo K, Hirbo JB, et al. Global Biobank Meta-analysis Initiative: Powering genetic discovery across human disease. Cell Genomics. 2022;2:100192.

Article  Google Scholar 

Buniello A, MacArthur JAL, Cerezo M, Harris LW, Hayhurst J, Malangone C, et al. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019. Nucleic Acids Res. 2019;47:D1005–12.

Article  Google Scholar 

Zhang Y, Long H, Wang S, Xiao W, Xiong M, Liu J, et al. Genome-wide DNA methylation pattern in whole blood associated with primary intracerebral hemorrhage. Front Immunol. 2021;12:702244.

Article  Google Scholar 

Xue Y, Guo Y, Luo S, Zhou W, Xiang J, Zhu Y, et al. Aberrantly methylated-differentially expressed genes identify novel atherosclerosis risk subtypes. Front Genet. 2020;11:569572.

Article  Google Scholar 

Si J, Yang S, Sun D, Yu C, Guo Y, Lin Y, et al. Epigenome-wide analysis of DNA methylation and coronary heart disease: a nested case-control study. eLife. 2021;10:e68671.

Article  Google Scholar 

Lecce L, Xu Y, V’Gangula B, Chandel N, Pothula V, Caudrillier A, et al. Histone deacetylase 9 promotes endothelial-mesenchymal transition and an unfavorable atherosclerotic plaque phenotype. J Clin Invest. 2021;131:e131178.

Article  Google Scholar 

Grootaert MOJ, Finigan A, Figg NL, Uryga AK, Bennett MR. SIRT6 protects smooth muscle cells from senescence and reduces atherosclerosis. Circ Res. 2021;128:474–91.

Article  Google Scholar 

Mao Y, Huang P, Wang Y, Wang M, Li MD, Yang Z. Genome-wide methylation and expression analyses reveal the epigenetic landscape of immune-related diseases for tobacco smoking. Clin Epigenetics. 2021;13:215.

Article  Google Scholar 

Chi GC, Liu Y, Macdonald JW, Reynolds ML, Enquobahrie DA, Fitzpatrick LA, et al. Epigenome-wide analysis of long-term air pollution exposure and DNA methylation in monocytes: results from the multi-ethnic study of atherosclerosis. Epigenetics. 2022;17:297.

Article  Google Scholar 

Roadmap Epigenomics Consortium, Kundaje A, Meuleman W, Ernst J, Bilenky M, Yen A, et al. Integrative analysis of 111 reference human epigenomes. Nature. 2015;518:317.

Article  Google Scholar 

Wu Y, Zhan S, Xu Y, Gao X. RNA modifications in cardiovascular diseases, the potential therapeutic targets. Life Sci. 2021;278:119565.

Article  Google Scholar 

Flynn RA, Pedram K, Malaker SA, Batista PJ, Smith BAH, Johnson AG, et al. Small RNAs are modified with N-glycans and displayed on the surface of living cells. Cell. 2021;184:3109-3124.e22.

Article  Google Scholar 

Brackston RD, Lakatos E, Stumpf MPH. Transition state characteristics during cell differentiation. PLoS Comput Biol. 2018;14:e1006405.

Article  Google Scholar 

Quake SR. The cell as a bag of RNA. Trends Genet. 2021;37:1064–8.

Article  Google Scholar 

Raman K, O’Donnell MJ, Czlonkowska A, Duarte YC, Lopez-Jaramillo P, Peñaherrera E, et al. Peripheral blood MCEMP1 gene expression as a biomarker for stroke prognosis. Stroke. 2016;47:652–8.

Article  Google Scholar 

Vanhaverbeke M, Vausort M, Veltman D, Zhang L, Wu M, Laenen G, et al. Peripheral blood RNA levels of QSOX1 and PLBD1 are new independent predictors of left ventricular dysfunction after acute myocardial infarction. Circ Genomic Precis Med. 2019;12:e002656.

Article  Google Scholar 

Sulkava M, Raitoharju E, Levula M, Seppälä I, Lyytikäinen L-P, Mennander A, et al. Differentially expressed genes and canonical pathway expression in human atherosclerotic plaques – Tampere Vascular Study. Sci Rep. 2017;7:41483.

Article  Google Scholar 

Raman K, Aeschbacher S, Bossard M, Hochgruber T, Zimmermann AJ, Kaufmann BA, et al. Whole blood gene expression differentiates between atrial fibrillation and sinus rhythm after cardioversion Talkachova A, editor. Plos One. 2016;11:e0157550.

Article  Google Scholar 

de Goede OM, Nachun DC, Ferraro NM, Gloudemans MJ, Rao AS, Smail C, et al. Population-scale tissue transcriptomics maps long non-coding RNAs to complex disease. Cell. 2021;184:2633-2648.e19.

Article  Google Scholar 

Holdt LM, Stahringer A, Sass K, Pichler G, Kulak NA, Wilfert W, et al. Circular non-coding RNA ANRIL modulates ribosomal RNA maturation and atherosclerosis in humans. Nat Commun. 2016;7:12429.

Article  Google Scholar 

Cho H, Shen G-Q, Wang X, Wang F, Archacki S, Li Y, et al. Long noncoding RNA ANRIL regulates endothelial cell activities associated with coronary artery disease by up-regulating CLIP1, EZR, and LYVE1 genes. J Biol Chem. 2019;294:3881–98.

Article  Google Scholar 

Lo Sardo V, Chubukov P, Ferguson W, Kumar A, Teng EL, Duran M, et al. Unveiling the role of the most impactful cardiovascular risk locus through haplotype editing. Cell. 2018;175:1796-1810.e20.

Article  Google Scholar 

Meckelmann SW, Hawksworth JI, White D, Andrews R, Rodrigues P, O’Connor A, et al. Metabolic dysregulation of the lysophospholipid/autotaxin axis in the chromosome 9p21 gene SNP rs10757274. Circ Genomic Precis Med. 2020;13:e002806.

Article  Google Scholar 

Kojima Y, Ye J, Nanda V, Wang Y, Flores AM, Jarr K-U, et al. Knockout of the murine ortholog to the human 9p21 coronary artery disease locus leads to smooth muscle cell proliferation, vascular calcification, and advanced atherosclerosis. Circulation. 2020;141:1274–6.

Article  Google Scholar 

Feinberg MW, Moore KJ. MicroRNA Regulation of Atherosclerosis. Circ Res. 2016;118:703–20.

Article  Google Scholar 

Altesha M, Ni T, Khan A, Liu K, Zheng X. Circular RNA in cardiovascular disease. J Cell Physiol. 2019;234:5588–600.

Article  Google Scholar 

Li M, Yang Y, Wang Z, Zong T, Fu X, Aung LHH, et al. Piwi-interacting RNAs (piRNAs) as potential biomarkers and therapeutic targets for cardiovascular diseases. Angiogenesis. 2021;24:19–34.

Article  Google Scholar 

Wagschal A, Najafi-Shoushtari SH, Wang L, Goedeke L, Sinha S, deLemos AS, et al. Genome-wide identification of microRNAs regulating cholesterol and triglyceride homeostasis. Nat Med. 2015;21:1290–7.

Article  Google Scholar 

Aguet F, Anand S, Ardlie KG, Gabriel S, Getz GA, Graubert A, et al. The GTEx consortium atlas of genetic regulatory effects across human tissues. Science. 2020;369:1318–30.

Article  Google Scholar 

Barrett T, Wilhite SE, Ledoux P, Evangelista C, Kim IF, Tomashevsky M, et al. NCBI GEO: archive for functional genomics data sets—update. Nucleic Acids Res. 2012;41:D991–5.

Article  Google Scholar 

Krassowski M, Pellegrina D, Mee MW, Fradet-Turcotte A, Bhat M, Reimand J. ActiveDriverDB: interpreting genetic variation in human and cancer genomes using post-translational modification sites and signaling networks (2021 Update). Front Cell Dev Biol. 2021;9:626821.

Article  Google Scholar 

Krassowski M, Paczkowska M, Cullion K, Huang T, Dzneladze I, Ouellette BFF, et al. ActiveDriverDB: human disease mutations and genome variation in post-translational modification sites of proteins. Nucleic Acids Res. 2018;46:D901–10.

Article  Google Scholar 

Suhre K, McCarthy MI, Schwenk JM. Genetics meets proteomics: perspectives for large population-based studies. Nat Rev Genet. 2021;22:19–37.

Article  Google Scholar 

Rastogi T, Girerd N, Lamiral Z, Bresso E, Bozec E, Boivin J-M, et al. Impact of smoking on cardiovascular risk and premature ageing: findings from the STANISLAS cohort. Atherosclerosis. 2022;346:1–9.

Article  Google Scholar 

Cornelis MC, Gustafsson S, Ärnlöv J, Elmståhl S, Söderberg S, Sundström J, et al. Targeted proteomic analysis of habitual coffee consumption. J Intern Med. 2018;283:200–11.

Article  Google Scholar 

Dencker M, Gårdinger Y, Björgell O, Hlebowicz J. Effect of food intake on 92 biomarkers for cardiovascular disease Schmidt HH, editor. Plos One. 2017;12:e0178656.

Article  Google Scholar 

Hoogeveen RM, Pereira JPB, Nurmohamed NS, Zampoleri V, Bom MJ, Baragetti A, et al. Improved cardiovascular risk prediction using targeted plasma proteomics in primary prevention. Eur Heart J. 2020;41:3998–4007.

Article 

留言 (0)

沒有登入
gif