Precision Medicine

Obesity is a chronic multifactorial disease with a strong genetic component. Although glucagon-like peptide-1 (GLP-1) receptor agonists such as semaglutide and dual glucose-dependent insulinotropic polypeptide (GIP)/GLP-1 receptor agonists, such as tirzepatide, are highly effective treatments for obesity, substantial inter-individual variability in weight loss response remains. Genetic factors may contribute to these differences in treatment outcomes. The aim of this prospective cohort study is to investigate whether a Genetic Risk Score (GRS) and selected obesity-related single nucleotide polymorphisms (SNPs) can predict weight loss response to semaglutide or tirzepatide in adults with obesity. Participants initiating treatment with either medication will undergo clinical, biochemical, and genetic assessment at baseline and will be followed for six months. The study will evaluate the association between genetic markers and treatment response and develop predictive models integrating genetic and clinical variables. The findings may contribute to the development of personalized treatment strategies for obesity.

The goal of this study is to learn whether eating a small serving of almonds before meals can improve blood sugar control in adults who have early signs of problems with blood sugar regulation. The main questions it aims to answer are: 1. Does eating almonds before a meal reduce the rise in blood sugar after eating? 2. Do some people consistently benefit more than others from eating almonds before meals?

The goal of this trial is to learn if a machine learning (ML) model can help optimize drug therapy in the pediatric population. The main question\[s\] it aims to answer are whether a machine learning model predicting receipt of a targeted medication within the next three months: * Increases the offering of pharmacogenetic testing prior to receipt of a targeted medication * Increases the number of patients with pharmacogenetic results prior to receipt of a targeted medication * Increases the number of patients who have alteration in medication choice or dose based on pharmacogenetic results This trial only focuses on the prediction and provision of participants with a high-risk of receiving a medication with a pharmacogenetic indication in the next three months.

NAFLD is most frequently linked to excess adiposity, insulin resistance and cardiometabolic risk factors, it has become the leading cause of liver disease worldwide, and is associated with increased mortality due to multiple causes. HFC has a strong genetic component and the investigators recently showed that it plays a causal role in determining progressive liver disease and insulin resistance. The genetic risk score predicting liver fat content (HFC-GRS) improves the stratification of liver related events, and the investigators have preliminary data on new common and rare variants that contribute to NAFLD susceptibility, and on a new non-invasive circulating biomarker associated with hepatic fat and lipotoxicity (Interleukin-32). However, no data are yet available on the causal role of hepatic fat on the procoagulant state associated with NAFLD, which could participate to liver damage and is a causal factor in atherothrombotic complications. The aim of the study is to examine the potential application of a precision medicine approach to the improvement of stratification of the risk of liver-related and cardiovascular thrombotic complications of hepatic fat accumulation (HFC) and non-alcoholic fatty liver disease (NAFLD), with a special focus on the role of procoagulant imbalance in mediating the at-risk phenotypes.

This study is testing software designed to help healthcare providers choose the best HIV treatment combinations for their patients. HIV medicines, known as antiretroviral therapy (ART), can be complex to manage because the right regimen depends on many factors-such as drug resistance, other health conditions, and medication schedules. Many people with HIV are cared for by general clinicians who may not have access to HIV specialists, which can make treatment decisions more challenging. In this study, healthcare providers will use patient cases to compare standard HIV treatment resources with a new clinical decision support tool that gives evidence-based ART recommendations at the point of care. The investigators hypothesize that using the tool will help providers select treatment plans that better match clinical guidelines, make decisions faster, reduce mental effort, and increase overall satisfaction with the prescribing process.

The efficacy and safety of Pazopanib combined with Palbociclib in the third line and above treatment of refractory solid tumors co amplified in the 11q13 region (FGF3/4/19/CCND1).

Bagaev et al. have identified four tumor microenvironment (TME) subtypes that are conserved across diverse cancers and correlated with immunotherapy response in melanoma, bladder, and gastric cancers. They provided a visual tool revealing the TME subtypes integrated with targetable genomic alterations, which provided a planetary view of each tumor that can aid in oncology clinical decision making. We aim to use this tool to prospectively analyse the biopsy specimens of osteosarcomas to identify their TME subtypes so as to deliver appropriate treatment strategy if these osteosarcomas experience disease progression afterwards. We will compare the past sequencing date stored in PKUPH bank so as to compare the event-free survival(EFS) of these patients to check the Superiority of this method later.

The main purpose of this study is to explore the feasibility of selecting treatment plans based on genomic variations guided by MTB in patients with advanced refractory solid tumors.