Publications by authors named "P A Lenzini"
Article Synopsis
- * There is a need for larger datasets that capture a wide range of variables to improve insights into these disorders.
- * The review highlights effective methods for using existing databases, collecting new data, and emphasizes collaboration for future big data applications in neuroimaging and psychiatry.
This article describes primary data and resources available from the Boston Adolescent Neuroimaging of Depression and Anxiety (BANDA) study, a novel arm of the Human Connectome Project (HCP). Data were collected from 215 adolescents (14-17 years old), 152 of whom had current diagnoses of anxiety and/or depressive disorders at study intake. Data include cross-sectional structural (T1- and T2-weighted), functional (resting state and three tasks), and diffusion-weighted magnetic resonance images.
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- * The study analyzed changes in HbA1c in a group of non-diabetic Europeans to identify genetic variants influencing these changes, using advanced modeling techniques.
- * A significant gene variant (rs56340929) was found to explain a notable portion of the variation in HbA1c levels and was supported by additional data, suggesting a new genetic link to HbA1c in non-diabetic individuals.
Background: 1.The use of machine learning to classify diagnostic cases versus controls defined based on diagnostic ontologies such as the ICD-10 from neuroimaging features is now commonplace across a wide range of diagnostic fields. However, transdiagnostic comparisons of such classifications are lacking.
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- This study looked at how body size and shape traits, like height and BMI, can be linked to genetics and health problems related to the heart and metabolism.! -
- Scientists analyzed DNA from over 22,000 people to find genetic connections to these traits and discovered some specific genes that might affect height and BMI.! -
- They found important results related to height but faced difficulties in identifying the effects of rare genetic variants, which are harder to study but still important for understanding genetics.!