JP6441892B2 - 出生前スクリーニング - Google Patents
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Classifications
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- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
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- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
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- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/483—Physical analysis of biological material
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- G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
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- G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
- G01N33/689—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids related to pregnancy or the gonads
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
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Description
本発明は、ダウン症候群などの胎児異数性の特徴であることがわかり、他の胎児の異常および妊娠性絨毛疾患を含む妊娠性疾患のスクリーニングの用途を有する、質量スペクトルのフィンガープリントのパターンの変化を用いて母体の尿試料をスクリーニングする方法に関する。
ダウン症候群として一般に知られている21トリソミーは、21番染色体の余分なコピーによって特徴づけられ、学齢期の子供における重大な学習障害の最も頻度の高い単一の原因をもたらす、最も一般的な重度の先天的異常の1つである。ダウン症候群を患っている人は、重度の精神遅滞、平均寿命の低下、および重度の感染症にかかりやすくする異常な免疫反応がある。ダウン症候群患者の40%には先天性心疾患があり、白血病を発症するリスクが高い。ダウン症候群を有する40歳以上のすべての人は、アルツハイマー病に特有の神経病理学的変化を発症しやすい。
hCGのグリコシル化は非常に変化しやすく、hCGのハイパーグリコシル化は妊娠性疾患およびダウン症候群などの胎児異数性において起こる。現在では、妊娠第2期まで、好ましくは妊娠7〜13週の妊婦から得られる、抽出されていない、未処理の尿試料をMADLI−ToF MS分析することによって、グリコシル化変異体でパターンの変化を示しうる独特な質量スペクトルが得られることがわかっている。パターンのこれらの変化は、妊娠性疾患および胎児異数性におけるトロホブラスト細胞でのグリコシル化プロセスに特徴的なハイパーグリコシル化hCGの代謝産物を示し、したがってこれらの状態を示す。
a)妊婦から母体の尿試料を採取し;
b)前記試料を直接質量スペクトル分析し;
c)前記分析から得られたパターンを正常な妊婦からの母体の尿試料から得られた質量スペクトルパターンと比較して、妊婦からの前記試料からの前記パターンが妊娠性疾患または胎児異数性を示すかどうかを決定する;
ことを含む、妊娠第2期までの妊娠性疾患または胎児異数性の検出方法を記載する。
母親の年齢および民族性に関係なく、32の非選択の単胎妊娠の尿試料のアーカイブコレクションを用いた。
その後、カンマ区切りのデータを、MATLABソフトウエアで読めるようにするためにM.fileフォーマットに変換した。
合併症のない単胎妊娠と比較したダウン症候群の6,000〜14,000m/zの間のフィンガープリントのパターンのスペクトル強度の相対的なレベルを評価するための計算モデルは、妊娠12〜13週の妊婦の尿からの、6,000〜14,000ダルトンの質量電荷比(m/z)に対する、すべてのビンの規格化曲線下面積の対数の中央値、95パーセンタイル値および5パーセンタイル値をプロットすることによって作製した。
実施例1の方法を、妊娠第2期、すなわち、妊娠15、16および17週に得た尿試料を用いて繰り返した。
妊娠性絨毛疾患(例えば、奇胎妊娠および妊娠悪阻)を有する女性からの尿試料を、正常妊娠の女性から得られた試料と比較した。三分枝(tri−antennary)糖型によるhCGβcfハイパーグリコシル化が、奇胎妊娠および妊娠悪阻を有する女性の尿において、正常妊娠からの試料と比較して最も高いことがわかった。このような分子は代謝処理をされるが、これは、hCGが妊娠性疾患および異常妊娠でより多くN−結合ハイパーグリコシル化されていることを示した、以前発表したデータを支持する。hCGのグリコシル化のこれらの違いは、質量スペクトル分析によって検出可能な質量変化をもたらす。これらの変化は、本発明の方法において、妊娠性絨毛疾患などの妊娠性疾患を検出するために用いられうる。
Claims (13)
- 妊娠第2期までの妊娠性絨毛疾患または胎児異数性の検出のための、妊婦からの母体尿試料の質量スペクトル分析の方法であって、
希釈されていないか、または希釈した、検出しようとするタンパク質を濃縮していない妊婦からの母体尿試料を直接質量スペクトル分析することを含み、
行われる質量スペクトル分析は、マトリックス支援レーザー脱離/イオン化飛行時間型質量分析法(MALDI−ToF MS)であり、前記検出は、前記質量スペクトル分析から得られたパターンを妊娠性絨毛疾患または胎児異数性のない妊婦からの尿試料から得られた質量スペクトルパターンと比較し、その比較の結果を、前記母体尿試料からの前記質量スペクトル分析から得られたパターンが妊娠性絨毛疾患または胎児異数性を示すかどうかの指標とすることを含む、方法。 - 前記尿試料を直接質量スペクトル分析することを含み、
前記検出は、前記質量スペクトル分析から得られたパターンを異数性を有さない胎児を持つ妊婦からの尿試料から得られた質量スペクトルパターンと比較し、その比較の結果を、前記母体尿試料からの前記質量スペクトル分析から得られたパターンが胎児異数性を示すかどうかの指標とすることを含む、妊娠第2期までの胎児異数性の検出のための、請求項1に記載の方法。 - 前記母体尿試料は、妊娠7〜16週の妊婦からのものである、請求項1または2に記載の方法。
- 前記尿試料は、直接質量スペクトル分析の前に希釈される、請求項1〜3のいずれか1項に記載の方法。
- 前記質量スペクトルのパターンは、妊娠性絨毛疾患または胎児異数性のない妊婦からの尿試料の質量スペクトルと妊娠性絨毛疾患または異数性を有する胎児を持つ妊婦からの尿試料の質量スペクトルパターンとを区別することができる自動化された定量的な方法によって決定される、請求項1〜4のいずれか1項に記載の方法。
- 前記質量スペクトルのパターンは、異数性を有さない胎児を持つ妊婦からの尿試料の質量スペクトルと異数性を有する胎児を持つ妊婦からの尿試料の質量スペクトルパターンとを区別することができる自動化された定量的な方法によって決定される、請求項1〜5のいずれか1項に記載の方法。
- 前記胎児異数性は、ダウン症候群である、請求項6に記載の方法。
- 各試料は、同等の妊娠期間の妊娠性絨毛疾患または胎児異数性のない妊婦の尿試料の収集の統計的分析から決定される約500〜100,000m/zの予測質量の参照スペクトルモデルに対して比較される、請求項1〜7のいずれか1項に記載の方法。
- 各試料は、同等の妊娠期間の異数性を有さない胎児を持つ妊婦からの尿試料の収集の統計的分析から決定される約6,000〜14,000m/zの予測質量の参照スペクトルモデルに対して比較される、請求項1〜8のいずれか1項に記載の方法。
- 前記参照スペクトルモデルは、500〜100,000m/zの間の質量スペクトルの相対的比率の規格化された統計学的に決定された指標をもたらすデータ処理方法によって作製される、請求項8または9に記載の方法。
- 疾患モデルは、妊娠8〜16週の妊娠性絨毛疾患または胎児異数性を有する妊婦から得られた母体の尿からの500〜100,000m/zの間の質量スペクトルの相対的比率の規格化された統計学的に決定された指標をもたらすデータ処理方法によって作製される、請求項8〜10のいずれか1項に記載の方法。
- 疾患モデルは、妊娠8〜16週の胎児異数性を有する妊婦から得られた母体の尿からの6,000〜14,000m/zの間の質量スペクトルの相対的比率の規格化された統計学的に決定された指標をもたらすデータ処理方法によって作製される、請求項8〜11のいずれか1項に記載の方法。
- 前記参照スペクトルモデルおよび前記疾患モデルは、2つのモデルの間の相違点を特定するためにプロッティングによって比較される、請求項11または12に記載の方法。
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