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KAKEN_17K19838seika.pdf
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Download
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:76.2 KB
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:Nov 15, 2022 |
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Total downloads since Nov 15, 2022 : 205
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慢性腎臓病の個別化予防実現へ向けたゲノム・メタボローム疫学研究
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| Kana |
マンセイ ジンゾウビョウ ノ コベツカ ヨボウ ジツゲン エ ムケタ ゲノム・メタボローム エキガク ケンキュウ
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Mansei jinzōbyō no kobetsuka yobō jitsugen e muketa genomu metaborōmu ekigaku kenkyū
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Metabolome- and genome-wide profiling for prevention of chronic kidney disease in a population-based study
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武林, 亨
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タケバヤシ, トオル
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Takebayashi, Tōru
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慶應義塾大学・医学部 (信濃町) ・教授
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Research team head
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科研費研究者番号 : 30265780
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原田, 成
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ハラダ, セイ
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Harada, Sei
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慶應義塾大学・医学部 (信濃町) ・講師
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Research team member
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科研費研究者番号 : 10738090
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2020
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科学研究費補助金研究成果報告書
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2019
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CE/MS法による尿中メタボローム測定の信頼性評価は、血漿のメタボローム測定と比較してもCVは良好で、本測定系の再現性は高いと考えられた。
ゲノム-メタボローム関連解析では、サンプルサイズが小さく、他方でゲノムとメタボロームの双方の変数が多いことから、多重比較調整のペナルティが非常に大きかったことから統計学的に有意な結果は得られなかったが遺伝子-代謝物の関連の強さのランキングからは、これまでの知見が再現されていることが示唆される知見、さらに本研究に特異的だと示唆される知見が得られており、本研究を継続する意義は大きいと考えられた。腎機能とGWASの関連においても同様であった。
Measurement reproductibility of urine metabolomics by CE/MS was high enough.
Although genome-metabolome association analysis did not show statistical significant results due to sample size reason, some key metabolites were found to be highly correlated with certain types of SNPs. Similar results were observed for GWAS analysis of kidney function. These results implies that increase in sample size, which is on-going up to 10000 samples, could lead to scientifically significant results with multi-omics approach of prevention of chronic kidney results.
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研究種目 : 挑戦的研究 (萌芽)
研究期間 : 2017～2019
課題番号 : 17K19838
研究分野 : 疫学、予防医学
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| Mar 5, 2021 | | インデックス を変更 |
| Nov 15, 2022 | | Creator Name,Creator Kana,Creator Romanization,Creator Affiliation,Creator Affiliation (Translated),Creator Role,Creator Link,Abstract 内容,Note 注記 を変更 |
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