A U.K. study has uncovered distinctive genetic drivers of type 2 diabetes in South Asians that lead to faster development of complications, the need for earlier insulin replacement therapy and a weaker response to some widely prescribed drugs. That points to the need to refine care pathways. But in addition, the research provides a potent illustration of how the under-representation in genomics databases of people who are not of white European origin can skew results and be a source of discrimination.

Researchers at the University of Rochester have described a neuroimaging-based biomarker that could identify individuals with early psychosis, and improved their identification when it was added to a standard neurocognitive diagnostic test. In a group of roughly 160 participants in the Human Connectome Early Psychosis Project, individuals who were in the early stages of psychosis had stronger connections from the thalamus (a midbrain sensory processing area) to the cortex, but weaker connections between different cortical areas, than controls.

Fat cells from patients who had lost weight after bariatric surgery, as well as from animals who had gained and then lost weight, were transcriptionally distinct from cells that had not experienced such weight changes at the organism level. In the animal studies, those transcriptional changes were due to epigenetic changes. The findings, which were published online in Nature on Nov. 18, 2024, are a possible molecular-level explanation for the short-term nature of most weight loss.

An international consortium of thousands of scientists is creating the Human Cell Atlas, a three-dimensional map of all the cells in the body. The goal is to understand all the cells that make up human tissues, organs and systems, which will enable multiple medical applications. This collection of cell maps is openly available for navigation at single-cell resolution, identified through omics analyses that reveal the tridimensional distribution of each cell.

At the BioFuture 2024 conference held in New York in November, Seema Kumar, the CEO of Cure, described women’s health as something that has been directed at the “bikini area.” That “bikini” bias extended to both diseases and their causes – women’s health covered the breasts and reproductive system, and its causes were hormonal. Both concepts are far too narrow.

It’s difficult to fathom that the health of half the world’s population is underserved. But it’s a hard truth. There are many conditions that disproportionately impact women. Other conditions and diseases affect women in different ways than men. Decades of research excluding women from clinical trials and investment decisions in male-dominated board rooms have ignored these facts. Though an increasing number of women are now managing investments and driving the research, it’s all still woefully behind. In BioWorld’s new report, Healing the health divide, we’ve highlighted the disparities.

Six main cell types form glioblastomas (GBM), the most aggressive brain cancer due to its high rate of recurrence. Of these six, quiescent cancer stem cells are responsible for resistance to therapy and the reappearance of the tumor, according to a study that identified the six groups and highlighted the importance of these stem cells for the design of more effective therapies.

Cell and gene therapy companies are the beneficiaries of positive changes along the regulatory path that the U.S. FDA is paving for them, according to a panel of executives who spoke at the BioFuture 2024 conference in New York.

Some rare skin diseases not only reduce the quality of life of patients, but also can be devastating conditions, leading to amputations or death. At the 31st annual congress of the European Society of Gene and Cell Therapy (ESGCT), held last week in Rome, different laboratories showcased their approaches to editing mutations related to this group of diseases.

Currently, cancer therapy trial-and-error methodology is inefficient and unsustainable. Oncology is the worst therapeutic area for drug trial success; only 3.4% of drugs that enter phase I end up being FDA approved, and 57% fail due to poor drug efficacy in trials. Building tools that may aid in predicting an individual’s response to a specific therapy may help in reducing costs, guesswork, and importantly improve the outcome of patients and accelerate new drug development.