Human metabolic individuality in biomedical and pharmaceutical research

Suhre, Karsten; Shin, So–Youn; Peters, Annette; Mohney, Robert P.; Meredith, David; Wägele, Brigitte; Altmaier, Elisabeth; Deloukas, Panos; Erdmann, Jeanette; Grundberg, Elin; Hammond, Christopher J; Angelis, Martin Hrabé de; Kastenmüller, Gabi; Köttgen, Anna; Kronenberg, Florian; Mangino, Massimo; Meisinger, Christa; Meitinger, Thomas; Mewes, Hans‐Werner; Milburn, Michael V.; Prehn, Cornelia; Raffler, Johannes; Ried, Janina S.; Römisch-Margl, Werner; Samani, Nilesh J.; Small, Kerrin S.; Wichmann, Heinz‐Erich; Zhai, Guangju; Illig, Thomas; Spector, Tim D.; Adamski, Jerzy; Soranzo, Nicole; Gieger, Christian

doi:10.1038/nature10354

Cited by 936 publications

(999 citation statements)

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“…Lead SNPs associated with IGF‐I and IGFBP‐3 concentrations were examined in a published metabolite‐SNP association database (Suhre et al ., 2011; Shin et al ., 2014). The IGF‐I‐associated SNP rs780093 at GCKR locus was associated with glucose/mannose ratio ( P = 9.4 × 10 −143 ), and the IGFBP‐3‐associated SNP rs4234798 at SORCS2 locus was associated with caprylate (8:0)/phenylalanine ratio ( P = 7.3 × 10 −7 ).…”

Section: Resultsmentioning

confidence: 99%

“…Top SNPs associated with levels of IGF‐I and IGFBP‐3 were examined in relationship to other phenotypes using published data on serum metabolites (Suhre et al ., 2011; Shin et al ., 2014), anthropometric traits (Heid et al ., 2010; Lango Allen et al ., 2010; Speliotes et al ., 2010), bone mineral density (Estrada et al ., 2012), diabetes (Voight et al ., 2010; Morris et al ., 2012) and glycemic traits (Dupuis et al ., 2010; Saxena et al ., 2010; Soranzo et al ., 2010), coronary artery disease (Coronary Artery Disease Genetics C, 2011; Schunkert et al ., 2011; Consortium CAD and Deloukas, 2013), and survival beyond 90 years (Broer et al ., 2015). Detailed information of the published datasets used including its references is given in Table S9 (Supporting information).…”

Section: Methodsmentioning

confidence: 99%

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Genomewide meta‐analysis identifies loci associated with IGF ‐I and IGFBP ‐3 levels with impact on age‐related traits

Teumer¹,

Qi²,

Nethander³

et al. 2016

Aging Cell

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SummaryThe growth hormone/insulin‐like growth factor (IGF) axis can be manipulated in animal models to promote longevity, and IGF‐related proteins including IGF‐I and IGF‐binding protein‐3 (IGFBP‐3) have also been implicated in risk of human diseases including cardiovascular diseases, diabetes, and cancer. Through genomewide association study of up to 30 884 adults of European ancestry from 21 studies, we confirmed and extended the list of previously identified loci associated with circulating IGF‐I and IGFBP‐3 concentrations (IGF1, IGFBP3,GCKR,TNS3, GHSR, FOXO3, ASXL2, NUBP2/IGFALS, SORCS2, and CELSR2). Significant sex interactions, which were characterized by different genotype–phenotype associations between men and women, were found only for associations of IGFBP‐3 concentrations with SNPs at the loci IGFBP3 and SORCS2. Analyses of SNPs, gene expression, and protein levels suggested that interplay between IGFBP3 and genes within the NUBP2 locus (IGFALS and HAGH) may affect circulating IGF‐I and IGFBP‐3 concentrations. The IGF‐I‐decreasing allele of SNP rs934073, which is an eQTL of ASXL2, was associated with lower adiposity and higher likelihood of survival beyond 90 years. The known longevity‐associated variant rs2153960 (FOXO3) was observed to be a genomewide significant SNP for IGF‐I concentrations. Bioinformatics analysis suggested enrichment of putative regulatory elements among these IGF‐I‐ and IGFBP‐3‐associated loci, particularly of rs646776 at CELSR2. In conclusion, this study identified several loci associated with circulating IGF‐I and IGFBP‐3 concentrations and provides clues to the potential role of the IGF axis in mediating effects of known (FOXO3) and novel (ASXL2) longevity‐associated loci.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Genomewide meta‐analysis identifies loci associated with IGF ‐I and IGFBP ‐3 levels with impact on age‐related traits

Teumer¹,

Qi²,

Nethander³

et al. 2016

Aging Cell

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show abstract

“…Additionally, metabolomics analyses in combination with genome-wide association studies are potentially providing new avenues for individualized drug therapy for a wide range of health problems (Suhre et al 2011). These scientific advances coupled with the increased availability of direct-to-consumer personal genome testing (DTC-PGT) (Samuel et al 2010) are allowing for easy accessibility to one's genetic information.…”

Section: Introductionmentioning

confidence: 99%

Perceptions of genetic research in three rural Appalachian Ohio communities

et al. 2012

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Appalachian Americans are an underserved population with increased risk for diseases having strong genetic and environmental precursors. The purpose of this study is to understand the thoughts and perceptions of genetic research of Appalachian Americans residing in eastern Ohio prior to conducting a genetic research study with this population. A genetic survey was developed and completed by 180 participants from Marietta, Cambridge and East Liverpool, Ohio. The majority of respondents were Caucasian women with a median age of 37.5 years. We found that participants had a high interest in participating in 80 %, allowing their children to participate in 78 %, and learning more about genetic research studies (90 %); moreover, they thought that genetic research studies are useful to society (93 %). When asked what information would be useful when deciding to participate in a genetic research study, the following were most important: how environmental pollutants affect their genes and their child's genes (84 %), types of biological specimens needed for genetic research studies (75 %) and who will have access to their samples (75 %). Of the 20 % who responded that they were "unsure" about participating in a genetic research study, the leading reason was "I don't have enough information about genetic research to make a decision" (56 %). We also asked respondents to choose their preferred method for receiving genetic information, and the principal response was to read a brochure (40 %). Findings from this study will improve community education materials and dissemination methods that are tailored for underserved populations engaged in genetic research.

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“…The variant correlated also to DL‐carnitine and propionyl‐L‐carnitine levels, which, in turn, were strongly associated with SUA. Carnitine was later experimentally validated to be a substrate of MCT9, whereas urate was demonstrated to be not transported by MCT9 53. Therefore, rs12356193 is suggested to have an indirect effect on urate excretion through aberrant carnitine levels 50.…”

Section: Metabolic Diseasesmentioning

confidence: 99%

Clinical and Functional Relevance of the Monocarboxylate Transporter Family in Disease Pathophysiology and Drug Therapy

Fisel

Schaeffeler

Schwab

2018

Clinical Translational Sci

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The solute carrier (SLC) SLC16 gene family comprises 14 members and encodes for monocarboxylate transporters (MCTs), which mediate the absorption and distribution of monocarboxylic compounds across plasma membranes. As the knowledge about their physiological function, activity, and regulation increases, their involvement and contribution to cancer and other diseases become increasingly evident. Moreover, promising opportunities for therapeutic interventions by directly targeting their endogenous functions or by exploiting their ability to deliver drugs to specific organ sites emerge.

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Human metabolic individuality in biomedical and pharmaceutical research

Cited by 936 publications

References 50 publications

Genomewide meta‐analysis identifies loci associated with IGF ‐I and IGFBP ‐3 levels with impact on age‐related traits

Genomewide meta‐analysis identifies loci associated with IGF ‐I and IGFBP ‐3 levels with impact on age‐related traits

Perceptions of genetic research in three rural Appalachian Ohio communities

Clinical and Functional Relevance of the Monocarboxylate Transporter Family in Disease Pathophysiology and Drug Therapy

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