{"id":10679,"date":"2024-03-12T18:07:19","date_gmt":"2024-03-12T18:07:19","guid":{"rendered":"https:\/\/dailyai.com\/?p=10679"},"modified":"2024-03-13T17:26:08","modified_gmt":"2024-03-13T17:26:08","slug":"researchers-use-ai-to-explore-how-genetics-influence-cardiac-structure","status":"publish","type":"post","link":"https:\/\/dailyai.com\/es\/2024\/03\/researchers-use-ai-to-explore-how-genetics-influence-cardiac-structure\/","title":{"rendered":"Investigadores exploran con IA c\u00f3mo influye la gen\u00e9tica en la estructura cardiaca"},"content":{"rendered":"

Un equipo internacional de investigaci\u00f3n utiliz\u00f3 la IA para explorar c\u00f3mo influye la gen\u00e9tica en la estructura del ventr\u00edculo izquierdo del coraz\u00f3n.<\/b><\/p>\n

En <\/span>estudiar<\/span><\/a>publicado en Nature, fue realizado por la Universidad de Manchester en colaboraci\u00f3n con la Universidad de Leeds, el Consejo Nacional de Investigaciones Cient\u00edficas y T\u00e9cnicas de Argentina e IBM Research de California.<\/span><\/p>\n

Los investigadores utilizaron el aprendizaje profundo no supervisado para analizar m\u00e1s de 50.000 im\u00e1genes de resonancia magn\u00e9tica en 3D del Biobanco del Reino Unido, creando una base para analizar \u00e1reas espec\u00edficas de la estructura del coraz\u00f3n en busca de asociaciones gen\u00e9ticas mediante estudios de asociaci\u00f3n de todo el genoma y de todo el transcriptoma (GWAS y TWAS).<\/span><\/p>\n

Su objetivo era determinar c\u00f3mo la estructura del coraz\u00f3n est\u00e1 vinculada a la gen\u00e9tica, abriendo as\u00ed v\u00edas para explorar c\u00f3mo la gen\u00e9tica influye en la formaci\u00f3n y estructura de los \u00f3rganos. <\/span><\/p>\n

Esto podr\u00eda impulsar la investigaci\u00f3n de formas de cardiopat\u00eda cong\u00e9nita con influencia gen\u00e9tica.\u00a0<\/span><\/p>\n

He aqu\u00ed un breve resumen de c\u00f3mo funcion\u00f3:<\/span><\/p>\n

    \n
  1. Recogida y preparaci\u00f3n de datos<\/b>: El equipo empez\u00f3 por aprovechar la base de datos del Biobanco del Reino Unido, seleccionando m\u00e1s de 50.000 im\u00e1genes tridimensionales de resonancia magn\u00e9tica del coraz\u00f3n. Estas im\u00e1genes proporcionaron los datos fundamentales para analizar la estructura y morfolog\u00eda del ventr\u00edculo izquierdo.<\/span><\/li>\n
  2. Entrenamiento de modelos no supervisados<\/b>: A continuaci\u00f3n, los investigadores utilizaron modelos de aprendizaje profundo sin supervisi\u00f3n para aprender estructuras a partir de estas im\u00e1genes, lo que significa que los modelos identificaron patrones y caracter\u00edsticas en los datos sin etiquetado previo.\u00a0<\/span><\/li>\n
  3. Extracci\u00f3n de caracter\u00edsticas geom\u00e9tricas<\/b>: Una vez establecidos los modelos no supervisados, el equipo se centr\u00f3 en extraer caracter\u00edsticas geom\u00e9tricas de las im\u00e1genes que representan el ventr\u00edculo izquierdo derivadas de los datos de la resonancia magn\u00e9tica cardiaca.\u00a0<\/span><\/li>\n
  4. Estudios de asociaci\u00f3n de genoma y transcriptoma (GWAS y TWAS)<\/b>: Armados con las caracter\u00edsticas extra\u00eddas, los investigadores realizaron GWAS y TWAS exhaustivos. Estos an\u00e1lisis les permitieron comprobar la asociaci\u00f3n entre la gen\u00e9tica y la estructura del ventr\u00edculo izquierdo.\u00a0<\/span><\/li>\n
  5. Resultados<\/b>: Se identificaron 49 nuevas localizaciones gen\u00e9ticas con fuertes asociaciones con la morfolog\u00eda del coraz\u00f3n, y otras 25 estaban moderadamente asociadas.\u00a0<\/span><\/li>\n<\/ol>\n

    El profesor Alejandro F. Frangi explic\u00f3 el estudio afirmando: \"Se trata de un logro que anta\u00f1o habr\u00eda parecido ciencia ficci\u00f3n, pero demostramos que es completamente posible utilizar la IA para comprender los fundamentos gen\u00e9ticos del ventr\u00edculo izquierdo, simplemente observando im\u00e1genes tridimensionales del coraz\u00f3n.\"\u00a0<\/span><\/p>\n

    Escribir en el <\/span>Blog de la Universidad de Manchester<\/span><\/a>Frangi habl\u00f3 de las limitaciones de los estudios anteriores y de los avances que han hecho posibles estos nuevos m\u00e9todos: \"Los estudios anteriores s\u00f3lo hab\u00edan investigado la asociaci\u00f3n de los fenotipos cl\u00ednicos tradicionales... Sin embargo, este estudio utiliz\u00f3 la IA no s\u00f3lo para delinear las c\u00e1maras cardiacas a partir de im\u00e1genes m\u00e9dicas tridimensionales al paso, sino tambi\u00e9n para desvelar nuevos loci gen\u00e9ticos asociados a diversos fenotipos cardiovasculares profundos.\"<\/span><\/p>\n

    Los hallazgos del estudio ofrecen una visi\u00f3n de los fundamentos gen\u00e9ticos de la salud cardiovascular y abren nuevas v\u00edas para el desarrollo de terapias dirigidas y medicina de precisi\u00f3n.\u00a0<\/span><\/p>\n

    Como describi\u00f3 el profesor Bryan Williams, de la Fundaci\u00f3n Brit\u00e1nica del Coraz\u00f3n, \"esta nueva investigaci\u00f3n muestra el enorme poder de los big data que vinculan los genes con la estructura del coraz\u00f3n. El aprendizaje autom\u00e1tico lo ha hecho posible transformando la forma en que procesamos, analizamos y obtenemos informaci\u00f3n de los macrodatos para abordar las cuestiones m\u00e1s importantes de la investigaci\u00f3n cardiovascular.\"\u00a0<\/span><\/p>\n

    Ya se han utilizado modelos de IA para producir mapas 3D detallados de \u00f3rganos, incluido el cerebro humano, como en el proyecto de la UE <\/span>Proyecto Cerebro Humano (HBP) a gran escala<\/span><\/a>.\u00a0<\/span><\/p>\n

    Esto supone un paso m\u00e1s en la vinculaci\u00f3n de la gen\u00e9tica a la estructura del \u00f3rgano, ofreciendo una comprensi\u00f3n m\u00e1s profunda de la morfolog\u00eda del coraz\u00f3n y sus impulsores gen\u00e9ticos.<\/span><\/p>","protected":false},"excerpt":{"rendered":"

    Un equipo internacional de investigaci\u00f3n ha utilizado la IA para estudiar c\u00f3mo influye la gen\u00e9tica en la estructura del ventr\u00edculo izquierdo del coraz\u00f3n. El estudio, publicado en Nature, fue realizado por la Universidad de Manchester en colaboraci\u00f3n con la Universidad de Leeds, el Consejo Nacional de Investigaciones Cient\u00edficas y T\u00e9cnicas de Argentina e IBM Research de California. Los investigadores utilizaron el aprendizaje profundo no supervisado para analizar m\u00e1s de 50.000 im\u00e1genes de resonancia magn\u00e9tica en 3D del Biobanco del Reino Unido, creando una base para analizar \u00e1reas espec\u00edficas de la estructura del coraz\u00f3n en busca de asociaciones gen\u00e9ticas mediante estudios de asociaci\u00f3n de todo el genoma y de todo el transcriptoma (GWAS y TWAS). Su objetivo era determinar c\u00f3mo se relaciona la estructura del coraz\u00f3n<\/p>","protected":false},"author":2,"featured_media":10680,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[203,204,178],"class_list":["post-10679","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-biotech","tag-healthcare","tag-medicine"],"yoast_head":"\nResearchers use AI to explore how genetics influence cardiac structure | DailyAI<\/title>\n<meta name=\"description\" content=\"An international research team used AI to explore how genetics influence the structure of the heart's left ventricle.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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