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Graph pan-genome illuminates evolutionary trajectories and agronomic trait architecture in allotetraploid cotton 泛基因组图谱揭示了异源四倍体棉花的进化轨迹和农艺性状结构。
IF 29 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2026-01-02 DOI: 10.1038/s41588-025-02462-1
Zhaoen Yang, Zuoren Yang, Chenxu Gao, Mingjun Zhang, Guanjing Hu, Lan Yang, Yihao Zhang, Meng Ma, Renju Liu, Zhi Wang, Baibai Gao, Zhibin Zhang, Hang Zhao, Xuan Liu, Xiongfeng Ma, Jonathan F. Wendel, Xiaoyang Ge, Fuguang Li
Upland cotton (Gossypium hirsutum), one of the world’s major fiber crops, faces challenges from the genetic homogeneity of modern varieties. Here we present 107 gold-standard genome assemblies spanning the wild-to-domesticated continuum, revealing six large-scale structural variations, including a chromosomal reciprocal translocation and five inversions tracing the evolutionary history of cultivated cotton in the Americas. This history also involved continuous introgression from Gossypium barbadense, shaping the genetic diversity of G. hirsutum landraces and cultivars. Leveraging the graph pan-genome, we capture the sequence and structural diversity of nucleotide-binding site–leucine-rich repeat genes, uncovering pathogen-driven selection signatures and loci associated with disease resistance. A presence–absence variation genome-wide association study (GWAS) identified previously overlooked loci for key fiber traits, complementing single-nucleotide polymorphism–GWAS findings. Additionally, we construct a detailed map of large inversions, offering insights into hybridization dynamics and strategies to mitigate linkage drag. This study enhances our understanding of cotton evolution and domestication while delivering a valuable resource to enhance breeding. Genome assemblies of 100 cultivated and seven semi-wild Gossypium hirsutum accessions provide insights into the evolutionary history of upland cotton and the genetic basis of fiber trait variation.
陆地棉作为世界主要的纤维作物之一,面临着现代品种遗传同质性的挑战。在这里,我们展示了跨越野生到驯化连续体的107个金标准基因组组合,揭示了6个大规模的结构变异,包括染色体互反易位和追踪美洲栽培棉花进化史的5个倒置。这段历史还包括来自巴贝登棉的持续渗入,形成了陆地棉地方品种和栽培品种的遗传多样性。利用泛基因组图,我们捕获了核苷酸结合位点-富含亮氨酸的重复基因的序列和结构多样性,揭示了病原体驱动的选择特征和与抗病相关的位点。一项存在-缺失变异全基因组关联研究(GWAS)发现了以前被忽视的关键纤维性状位点,补充了单核苷酸多态性GWAS的发现。此外,我们还构建了大型反转的详细地图,为杂交动力学和减轻联动阻力的策略提供了见解。本研究提高了我们对棉花进化和驯化的认识,同时也为棉花育种提供了宝贵的资源。
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引用次数: 0
An accidental scientist’s journey from an uncertain beginning to advancing neurogenetics research in Africa 一个偶然的科学家的旅程,从一个不确定的开始推进神经遗传学研究在非洲。
IF 29 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2025-12-30 DOI: 10.1038/s41588-025-02453-2
Guida Landouré
Being an African scientist, I had to overcome several challenges to generate substantial data that shed light on the complexity of genomic medicine in African populations and abroad.
作为一名非洲科学家,我必须克服几个挑战,生成大量数据,揭示非洲人口和国外基因组医学的复杂性。
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引用次数: 0
Aneuploidy-driven vulnerabilities in breast cancer metastasis 非整倍体驱动的乳腺癌转移脆弱性。
IF 29 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2025-12-29 DOI: 10.1038/s41588-025-02444-3
Samuel F. Bakhoum
A study reveals how chromosomal instability and resultant TP53 loss enhance fatty acid metabolism to drive breast cancer brain metastasis. This metabolic dependency provides new insights into therapeutic vulnerabilities of aneuploid tumors.
一项研究揭示了染色体不稳定性和由此导致的TP53缺失如何增强脂肪酸代谢,从而驱动乳腺癌脑转移。这种代谢依赖性为非整倍体肿瘤的治疗脆弱性提供了新的见解。
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引用次数: 0
Unearthing soil biodiversity through collaborative genomic research and education 通过合作基因组研究和教育发掘土壤生物多样性。
IF 29 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2025-12-29 DOI: 10.1038/s41588-025-02442-5
The BioDIGS Consortium, Tristen Alberts, Claude F. Albritton, Rosa Alcazar, Zainab Aljabri, Maria Alvarez, Anish Aradhey, Mentewab Ayalew, Nareh Azizian, Yasmeen Balayah, Destiny D. Ball, Efren Barragan, Corey Beshoar, Lyle Best, Emily Biggane, Joseph Biggane, Jesse Blick, Myron Blosser, Alex Kenneth Brown, Michael C. Campbell, Zoe Canizares, Faith N. Chanhuhwa, Yu Chen, Daniel R. Chin, Kamal Chowdhury, Tyler Collins, Blair Compton, Jefferson Da Silva, Nia R. Davis, Natalie DeCaro, Frida Delgadillo, Youping Deng, Joceph Duncan, Arinzechukwu C. Egwu, Grace D. Ekalle, Noha Elnawam, Ray Enke, Naomi Ewhe, Marco A. Ferrel, Janna Fierst, Grace Freymiller, Karla Fuller, Lena Fulton-Wright, Valeriya Gaysinskaya, Torrence Gill, Ellie Gillespie, Perla Gonzalez Moreno, Sara Goodwin, Natajha Graham, Madeline E. Graham, Joseph L. Graves Jr., Emily Grob, Rachael Gutierrez, Aisha Hager, Shazia Tabassum Hakim, Aaliyah Harris, Ava M. Hoffman, Tobias Hoffmann, Alani M. Horton, Allison Hughes, Elizabeth M. Humphries, Josh-Samuel Ikechi-Konkwo, Aadil Ishtiaq, Ryan Jackson, Joshua Ronnie James, Kaitlan James, Sydney A. Jamison, Armando Jimenez, Rachel Johnson, Abigail Kauffman, Harkiran Kaur, Kritika Kc, Analyse Keeton, Olivia E. Kelly, Jennifer Kerr, Nataliya Kucher, Donna Lee Kuehu, Wendy A. Larson, Joslynn Lee, Andrew Lee, Jeffrey T. Leek, Danilo Lemaic, Lincoln E. Liburd II, Alan Fernando Lopez, Mohammadamin Mahmanzar, Karwitha Mamae, Raffi Manjikian, Michael Marone, Katerin Marquez, Amara Martinson, Senem Mavruk Eskipehlivan, Ashley Medrano, Melanie Melendrez-Vallard, Robert Meller, Loyda B. Méndez, Miguel P. Mendez Gonzalez, Nicolli Mesquita, Concepcion Martinez Miller, Isam Mohd-Ibrahim, Peter Mortensen, Stephen Mosher, Alketa Muja, Nadia Nasrin, Masaki Nasu, Matthew H. Nguyen, Ba Thong Nguyen, Michele Nishiguchi, Lance M. O’Connor, Disomi Okie, Tolulope Olowookorun, Alex Ostrovsky, Keyan Ozuna, Asmita Pandey, Shiv B. Patel, Gauri Paul, Shrikant Pawar, Andrea Pearson, Deborah Petrik, Jordan Platero, Carl Pontino, Arjun P. Pratap, Siddharth Pratap, Yujia Qin, Sudhir Kumar Rai, Nisttha Ray, Ethan Repesh, Kristen Rhinehardt, Brennan Roche, Ariana Rodriguez, Shriya Roy, Sourav Roy, Alexa Sawa, Michael C. Schatz, Shurjo K. Sen, Randon Serikawa, Tyler Smith, Loraye Smith, James Sniezek, Ryley D. Stewart, Edu B. Suarez-Martinez, Joelle Taganna, Frederick J. Tan, Nikolaos Tsotakos, Nwanneka Udolisa, Katherine Ulbricht, Tanner Veo, Jennifer Vessio, Lia Walker, Oscar Wang, Qingguo Wang, Robert Wappel, Kalynn Wesby, Malachi Whitford, Nicole Wild, Xianfa Xie, Hua Yang, Sayumi York, Lindsay Zirkle
The BioDIGS project is a nationwide initiative involving students, researchers and educators across more than 40 research and teaching institutions. Participants lead sample collection, computational analysis and results interpretation to understand the relationships between the soil microbiome, environment and health.
BioDIGS项目是一项全国性的倡议,涉及40多个研究和教学机构的学生、研究人员和教育工作者。参与者领导样本收集,计算分析和结果解释,以了解土壤微生物组,环境和健康之间的关系。
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引用次数: 0
p53 inactivation drives breast cancer metastasis to the brain through SCD1 upregulation and increased fatty acid metabolism p53失活通过SCD1上调和脂肪酸代谢增加驱动乳腺癌向脑部转移。
IF 29 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2025-12-29 DOI: 10.1038/s41588-025-02446-1
Kathrin Laue, Sabina Pozzi, Johanna Zerbib, Rebecca Bertolio, Yonatan Eliezer, Yael Cohen-Sharir, Tom Winkler, Manuel Caputo, Alessia A. Ricci, Lital Adler, Rami Khoury, Giuseppe Longobardi, Rachel Slutsky, Alicia I. Leikin-Frenkel, Shai Ovadia, Katharina Lange, Alessandra Rustighi, Silvano Piazza, Andrea Sacconi, Rayna Y. Magesh, Faith N. Keller, Jean Berthelet, Alexander Schäffer, Ron Saad, Sahar Israeli Dangoor, Karolina Szczepanowska, Iris Barshack, Yang Liao, Sergey Malitsky, Alexander Brandis, Thomas Broggini, Marcus Czabanka, Wei Shi, Delphine Merino, Emma V. Watson, Giovanni Blandino, Ayelet Erez, Ruth Ashery-Padan, Hind Medyouf, Luca Bertero, Giannino Del Sal, Ronit Satchi-Fainaro, Uri Ben-David
Brain metastasis (BM) carries a poor prognosis, yet the molecular basis of brain tropism remains unclear. Analysis of breast cancer BM (BCBM) revealed pervasive p53 inactivation through mutations and/or aneuploidy, with pathway disruption already present in primary tumors. Functionally, p53 inactivation markedly increased BCBM formation and growth in vivo, causally linking p53 perturbation to BM. Mechanistically, p53 inactivation upregulated SCD1 and fatty acid synthesis (FAS), essential for brain-metastasizing cells; SCD1 knockout abolished the p53-dependent growth advantage. Molecularly, p53 suppressed SCD1 directly through promoter binding and indirectly by downregulating its co-activator DEPDC1. Astrocytes further enhanced FAS by secreting factors that were metabolized in a p53-dependent manner, promoting tumor survival, proliferation and migration. Finally, p53-deficient tumors were sensitive to FAS inhibition ex vivo and in vivo. Thus, we identify p53 inactivation as a driver of BCBM, reveal p53-dependent and astrocyte-dependent FAS modulation and highlight FAS as a therapeutically targetable BCBM vulnerability. This study associates p53 loss and brain metastasis in breast cancer. Mechanistically, p53-null tumors recruit astrocytes that provide substrates for enhanced fatty acid synthesis via upregulated SCD1 expression, representing a targetable axis in the disease.
脑转移预后不佳,但脑向性的分子基础尚不清楚。对乳腺癌BM (BCBM)的分析显示,p53通过突变和/或非整倍体普遍失活,而在原发肿瘤中已经存在通路破坏。功能上,p53失活显著增加BCBM在体内的形成和生长,将p53的扰动与BM联系起来。机制上,p53失活上调SCD1和脂肪酸合成(FAS),这是脑转移细胞所必需的;SCD1敲除消除了p53依赖性生长优势。在分子上,p53通过启动子结合直接抑制SCD1,并通过下调其共激活子DEPDC1间接抑制SCD1。星形胶质细胞通过分泌以p53依赖方式代谢的因子进一步增强FAS,促进肿瘤存活、增殖和迁移。最后,p53缺陷肿瘤在体内和体外均对FAS抑制敏感。因此,我们确定p53失活是BCBM的驱动因素,揭示了p53依赖和星形胶质细胞依赖的FAS调节,并强调FAS是治疗上可靶向的BCBM脆弱性。
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引用次数: 0
Designing synthetic regulatory elements using the generative AI framework DNA-Diffusion 使用生成式人工智能框架dna -扩散设计合成调控元件
IF 29 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2025-12-23 DOI: 10.1038/s41588-025-02441-6
Lucas Ferreira DaSilva, Simon Senan, Judith F. Kribelbauer-Swietek, Zain Munir Patel, Lithin Karmel Louis, Aniketh Janardhan Reddy, Sameer Gabbita, Jonathan D. Rosen, Zach Nussbaum, César Miguel Valdez Córdova, Aaron Wenteler, Noah Weber, Tin M. Tunjic, Martino Mansoldo, Talha Ahmad Khan, Gue-Ho Hwang, Vincent Gardeux, David T. Humphreys, Cameron Smith, Matei Bejan, Peter Bromley, Will Connell, Bart Deplancke, Michael I. Love, Emily S. Wong, Wouter Meuleman, Luca Pinello
Systematically designing regulatory elements for precise gene expression control remains a central challenge in genomics and synthetic biology. Here we introduce DNA-Diffusion, a generative artificial intelligence framework that uses machine learning trained on DNA accessibility data from diverse cell lines to design compact regulatory elements with cell-type-specific activity. We show that DNA-Diffusion generates 200-base-pair synthetic elements that recapitulate endogenous transcription factor binding grammar while exhibiting enhanced cell-type specificity. We validated these elements using a 5,850-element STARR-seq library across three cell lines. Moreover, we demonstrated successful endogenous gene modulation using EXTRA-seq, reactivating AXIN2, a leukemia-protective gene, in its native genomic context. Our approach outperforms existing computational methods in balancing functional activity with cell-type specificity while maintaining sequence diversity. This work establishes DNA-Diffusion as a powerful tool for engineering compact, highly specific regulatory elements crucial for advancing gene therapies and understanding gene regulation. The authors present DNA-Diffusion, a generative AI framework that designs synthetic regulatory elements with tunable cell-type specificity. Experimental validation demonstrates their ability to reactivate AXIN2 expression, a leukemia-protective gene, in its native genomic context.
系统地设计精确的基因表达控制调控元件仍然是基因组学和合成生物学的核心挑战。在这里,我们介绍了DNA扩散,这是一个生成式人工智能框架,它使用来自不同细胞系的DNA可访问性数据训练的机器学习来设计具有细胞类型特异性活性的紧凑调节元件。我们发现DNA-Diffusion产生200个碱基对的合成元件,这些元件概括了内源性转录因子结合语法,同时表现出增强的细胞类型特异性。我们使用跨越三个细胞系的5,850个元素的STARR-seq库验证了这些元素。此外,我们证明了成功的内源性基因调节使用EXTRA-seq,重新激活AXIN2,白血病保护基因,在其原生基因组背景下。我们的方法在平衡功能活性与细胞类型特异性同时保持序列多样性方面优于现有的计算方法。这项工作建立了dna扩散作为一个强大的工具,用于工程紧凑,高度特异性的调控元件,对推进基因治疗和理解基因调控至关重要。
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引用次数: 0
Generative AI creates synthetic regulatory DNA sequences for precision gene control 生成式人工智能为精确的基因控制创造了合成的调控DNA序列。
IF 29 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2025-12-23 DOI: 10.1038/s41588-025-02443-4
We developed DNA-Diffusion, a generative artificial intelligence (AI) method that creates synthetic regulatory elements showing enhanced activity. Multiple synthetic elements demonstrated superior cell-type-specific expression in computational predictions and episomal assays, and when integrated at AXIN2, a leukemia-protective gene, outperformed naturally occurring protective variants, opening new possibilities for precision gene therapies.
我们开发了DNA-Diffusion,这是一种生成式人工智能(AI)方法,可以生成具有增强活性的合成调节元件。多种合成元件在计算预测和episomal分析中表现出优越的细胞类型特异性表达,并且当与AXIN2(一种白血病保护基因)整合时,表现优于自然发生的保护性变异,为精确基因治疗开辟了新的可能性。
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引用次数: 0
Mutation patterns drive mismatch repair-deficient glioma evolution 突变模式驱动错配修复缺陷胶质瘤进化。
IF 29 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2025-12-22 DOI: 10.1038/s41588-025-02424-7
Primary mismatch repair-deficient gliomas are hypermutant but molecularly heterogeneous cancers with poor prognosis. We show that non-random mutational signatures cause somatic mutations in key glioma drivers that define genetic subgroups of this disease. Each subgroup harbors distinct mechanisms of genomic instability that shape their biological behaviors and immunotherapy responses.
原发性错配修复缺陷胶质瘤是一种高突变但分子异质性的癌症,预后差。我们发现非随机突变特征导致胶质瘤驱动因素的体细胞突变,这些驱动因素定义了这种疾病的遗传亚群。每个亚群都有不同的基因组不稳定性机制,这些机制塑造了它们的生物学行为和免疫治疗反应。
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引用次数: 0
Patterns of hypermutation shape tumorigenesis and immunotherapy response in mismatch-repair-deficient glioma 错配修复缺陷胶质瘤的高突变形态、肿瘤发生模式和免疫治疗反应
IF 29 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2025-12-22 DOI: 10.1038/s41588-025-02420-x
Nicholas R. Fernandez, Yuan Chang, Nuno M. Nunes, Jose R. Dimayacyac, Adrian Levine, Amit Ringel, Logine Negm, Ayse Bahar Ercan, Julian M. Hess, Olfat Ahmad, Caitlin Lee, Lucie Stengs, Vanessa Bianchi, Melissa Edwards, Sheradan Doherty, Jiil Chung, Liana Nobre, Julie Bennett, Andrew J. Dodgshun, David T. W. Jones, Stefan M. Pfister, Anita Villani, David Malkin, Vijay Ramaswamy, Annie Huang, Eric Bouffet, Melyssa Aronson, Peter B. Dirks, Adam Shlien, Gad Getz, Yosef E. Maruvka, Birgit Ertl-Wagner, Cynthia Hawkins, Anirban Das, Uri Tabori
Primary mismatch-repair-deficient high-grade gliomas (priMMRD-HGG) are lethal tumors characterized by hypermutation, resistance to chemoradiation and variable response to immunotherapy. To investigate the mechanisms governing the emergence of driver mutations and their impact on gliomagenesis and patient outcomes, we analyzed genomic and clinical data from 162 priMMRD-HGG. Here we identified three subgroups defined by secondary driver mutations in replicative DNA polymerases or IDH1. These subgroups converge on glioma drivers through distinct combinations of genomic instability–generating mechanisms, displaying an inverse correlation between point mutations and copy number alterations. MMRD signatures drive the emergence of specific mutations in TP53 and IDH1, notably excluding common pediatric glioma drivers. Global hypomethylation stratifies priMMRD-HGG into a unique methylation cluster. DNA-polymerasemut priMMRD-HGG exhibit ultrahypermutation, an immune-hot microenvironment and immunotherapy responsiveness, whereas IDH1mut priMMRD-HGG are immune-cold and immunotherapy resistant. MMRD-driven gliomagenesis defines the role of nonrandom mutagenesis patterns in cancer development, providing frameworks for targeted and immune-therapeutics. The authors analyze 162 primary mismatch-repair-deficient gliomas and identify three subgroups underpinned by distinct somatic mutations in replicative DNA polymerases and IDH1.
原发性错配修复缺陷高级别胶质瘤(priMMRD-HGG)是一种致死性肿瘤,其特点是高突变、对放化疗有耐药性和对免疫治疗的不同反应。为了研究驱动突变出现的机制及其对胶质瘤形成和患者预后的影响,我们分析了162例priMMRD-HGG的基因组和临床数据。在这里,我们确定了由复制DNA聚合酶或IDH1的次要驱动突变定义的三个亚组。这些亚群通过基因组不稳定性产生机制的不同组合聚集在胶质瘤驱动因子上,显示出点突变和拷贝数改变之间的负相关。MMRD特征驱动TP53和IDH1特异性突变的出现,特别是排除了常见的小儿胶质瘤驱动因素。全局低甲基化将priMMRD-HGG分层成一个独特的甲基化簇。dna聚合体priMMRD-HGG表现出超突变、免疫热微环境和免疫治疗反应性,而IDH1mut priMMRD-HGG则表现出免疫冷和免疫治疗耐药。mmrd驱动的胶质瘤发生定义了非随机突变模式在癌症发展中的作用,为靶向和免疫治疗提供了框架。
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引用次数: 0
Multitrait analyses identify genetic variants associated with aortic valve function and aortic stenosis risk 多性状分析确定了与主动脉瓣功能和主动脉狭窄风险相关的遗传变异。
IF 29 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2025-12-19 DOI: 10.1038/s41588-025-02397-7
Shinwan Kany, Joel T. Rämö, Cody Hou, Sean J. Jurgens, Shaan Khurshid, Victor Nauffal, Jonathan W. Cunningham, Emily S. Lau, Satoshi Koyama, FinnGen, Jennifer E. Ho, Jeffrey E. Olgin, Sammy Elmariah, Aarno Palotie, Mark E. Lindsay, Patrick T. Ellinor, James P. Pirruccello
The genetic influences on normal aortic valve function and their impact on aortic stenosis risk are of substantial interest. We used deep learning to measure peak velocity, mean gradient and aortic valve area from magnetic resonance imaging and conducted genome-wide association studies (GWAS) in 59,571 participants in the UK Biobank. Incorporating the aortic valve measurement GWAS with aortic stenosis GWAS using multitrait analysis of GWAS (MTAG), we identified 166 distinct loci (134 with aortic valve traits, 134 with aortic stenosis and 166 unique loci across all GWAS), including PCSK9 and LDLR. The MTAG aortic stenosis PGS was associated with aortic stenosis in All of Us (hazard ratio (HR) = 3.32 for top 5% versus all others, P = 8.8 × 10−22) and Mass General Brigham Biobank (HR = 2.76, P = 7.8 × 10−15). Using Mendelian randomization, we found evidence supporting a potential causal role for Lp(a) and LDL on aortic valve function. These findings have implications for the early pathogenesis of aortic stenosis and suggest modifiable pathways as targets for preventive therapy. Genome-wide association studies (GWAS) of deep learning-derived measurements of aortic valve function, along with multitrait analyses incorporating disease-based GWAS, identify 166 genetic loci associated with aortic valve function or aortic stenosis.
基因对正常主动脉瓣功能的影响及其对主动脉瓣狭窄风险的影响是非常有趣的。我们使用深度学习来测量磁共振成像的峰值速度、平均梯度和主动脉瓣面积,并在英国生物银行的59,571名参与者中进行了全基因组关联研究(GWAS)。利用多性状分析(MTAG),我们确定了166个不同的基因座(134个与主动脉瓣性状相关,134个与主动脉瓣狭窄相关,166个在所有GWAS中都有独特的基因座),包括PCSK9和LDLR。MTAG主动脉狭窄PGS与我们所有人的主动脉狭窄相关(前5%的风险比(HR) = 3.32, P = 8.8 × 10-22)和Mass General Brigham Biobank (HR = 2.76, P = 7.8 × 10-15)。通过孟德尔随机化,我们发现了支持Lp(a)和LDL对主动脉瓣功能潜在因果作用的证据。这些发现提示了主动脉瓣狭窄的早期发病机制,并建议将可改变的途径作为预防治疗的目标。
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引用次数: 0
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Nature genetics
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