你嘅腸道菌群可以94%準確度預測你住邊度!

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腸道微生物組可準確推斷你所居住的城市,準確率高達94%

你嘅腸道細菌可能比你嘅口音更能揭示你嘅身份。最新研究發現,科學家利用人類腸道微生物組嘅組成,可以高達94%準確率推斷出佢哋所居住嘅城市,呢個發現為「你係你食咗嘅嘢」呢句說話賦予全新意義。

隨住研究不斷深入,我哋對腸道微生物組嘅認識越嚟越多。從佢同大腦嘅關聯,到與癌症、多發性硬化症等疾病嘅關係,甚至腸道微生物組移植作為治療手段嘅潛力,都成為科學熱點。

今次由中國BGI基因組公司主導嘅研究,發現我哋嘅腸道細菌組成會因居住地區而異,而透過機器學習技術,可以憑腸道微生物組嘅特徵,準確推斷出個人所居住嘅城市。

BGI智能醫療研究院嘅李濤教授表示:「呢項研究挑戰咗過往認為腸道微生物差異只係喺大洲或者省份層面有意義嘅觀念。我哋發現即使係相鄰城市嘅人,佢哋嘅微生物組模式都存在顯著差異。」

研究團隊招募咗381名來自湖北省兩個城市嘅健康漢族成年人,分別係位於中國東中部嘅武漢同位於西北部嘅十堰,兩地相距約500公里。所有參與者都冇重大疾病,且過去三個月無服用抗生素。

研究透過「shotgun metagenomic sequencing」技術分析參與者嘅糞便樣本,捕捉細菌組成同代謝功能,識別出649種細菌同515條代謝路徑,並利用機器學習算法對比不同個體嘅數據,嘗試分類佢哋嘅居住城市。

結果顯示,武漢同十堰居民喺微生物多樣性同物種組成上有顯著差異。武漢人嘅腸道中,「Bacteroides stercoris」細菌含量較高,而十堰居民則以「Prevotella copri」為主導。前者係一種關鍵腸道菌,能分解複雜碳水化合物及產生短鏈脂肪酸(SCFAs),呢啲分子已被證實對健康有多種益處;後者亦參與膳食纖維分解及SCFAs生成。武漢居民嘅腸道微生物更活躍於與植物性飲食相關嘅代謝路徑,而十堰人嘅微生物則顯示出較多蛋白質或加工食品攝入嘅特徵,雖然研究未直接收集飲食數據。

研究團隊指出,兩個城市嘅主導飲食文化對腸道微生物組成有重要影響。武漢因地處濕地,居民飲食中多含淡水魚、蓮藕同葉菜類;十堰則受鄰近地區影響,飲食以小麥製品同辣椒為主。

研究人員建立咗一個機器學習模型,結合16種細菌物種同12條城市特有嘅代謝路徑,模型準確率高達94%,遠超只用物種或代謝路徑嘅模型,證明即使係相距唔遠嘅城市,居民嘅腸道微生物組都有獨特嘅「指紋」。

不過,研究亦有局限,例如只涉及同一省份內兩個城市,難以推廣至更廣泛嘅範圍;參與者男女比例不均,可能影響結果;未收集飲食或生活習慣數據,呢啲係影響腸道微生物嘅關鍵因素;亦未追蹤參與者嘅微生物組隨時間嘅穩定性。

儘管如此,呢項研究帶嚟多項實際應用前景。腸道微生物組可用於判斷個人地區來源,有助法醫學同失蹤人口調查。區域及性別特異嘅微生物差異亦提示益生菌或飲食干預應因地制宜,提升療效。最後,結合機器學習同微生物組分析,亦有望協助預測疾病風險或監測特定地區嘅人口健康狀況。

該研究發表於《Frontiers in Microbiology》期刊。

評論與啟示

呢項研究喺揭示腸道微生物組與地理位置嘅緊密聯繫方面,提供咗令人驚訝嘅新視角。過往我哋多數只係從宏觀層面理解飲食同環境對腸道生態嘅影響,但今次證明咗即使係相距唔遠嘅城市,居民嘅腸道菌群都可以呈現出明顯嘅地域特徵,呢點對個人化醫療同營養指導有重大意義。

對香港嚟講,呢個發現尤其值得關注。香港作為國際大都會,人口結構多元,飲食文化混合多樣,將來有冇可能通過分析腸道微生物組,來反映甚至判斷一個人嘅生活習慣、健康狀況甚至移居背景?呢啲都係值得探索嘅方向。

同時,研究指出益生菌同飲食干預需因地制宜,提醒我哋唔好盲目跟風所謂「通用」健康產品,而應該根據個人及地區特點量身定制,提升療效同預防疾病。

最後,機器學習嘅應用亦展現咗人工智能喺生物醫學領域嘅強大潛力,未來結合大數據,或可建立更精準嘅健康監測同預警系統,推動公共衛生管理升級。

總括而言,腸道微生物組已遠非單純嘅生物學研究,而係通往個人化醫療、營養科學同智慧健康管理嘅關鍵橋樑。香港嘅科研機構同醫療界應積極關注同投入相關研究,搶佔未來健康產業嘅先機。

以上文章由特價GPT API KEY所翻譯及撰寫。而圖片則由FLUX根據內容自動生成。

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