Precision Medicine and Ancestry

XXYLT1 and Mendelian Retinal Dystrophy

Key Points Question Can a genome-wide association study (GWAS) approach be used to identify genes associated with inherited retinal disease (IRD)? Findings Using a recessive model, this GWAS identified 13 loci (9 known and 4 previously unknown putative loci) with genome-wide significance. One of the identified genes, XXYLT1, was confirmed as a rare mendelian IRD gene in independent Finnish and UK clinical cohorts; an XXYLT1 c.505-1G>C founder variant showed a loss-of-function effect. Meaning These findings support the need to include XXYLT1 in clinical IRD gene panels.

2025 update of the National French consensus on gene lists for the diagnosis of muscle diseases using high-throughput sequencing

Diagnosing rare muscle diseases can be challenging due to their genetic heterogeneity. The French National Network for Rare Neuromuscular Diseases (FILNEMUS) has previously established a pioneering nationwide strategy based on gene lists organized in 13 phenotype-specific gene panels. We now revise these lists and add recently described genes. Using data collected from all FILNEMUS diagnostic laboratories, we also establish a “Major Muscle Genes” panel that includes genes responsible for the most frequent genetic muscle diseases. The updated diagnostic strategy of the FILNEMUS network will help reduce the turn-around time for genetic results and facilitate rapid access to the French national genome sequencing platforms.

Precision Medicine and Pharmacogenomics: From One-Size-Fits-All to Data-Driven Individualized Therapy

Precision medicine is moving away from a "one size fits all" model and moving towards the treatment of the individual patient. The paradigm shift is tied to a study of how genetic variation affects drug response, called Pharmacogenomics (PGx). This paper highlights three undeniably interrelated trends: Firstly, the need for ancestry diverse datasets for equitable implementation of PGx; secondly, a pharmacist-led economically viable model of PGx delivery; thirdly, Decoding drug-response phenotypes using a synthetic process of integrating AI with multi-omics data. Existing data suggests that the combination of AI tools for analytics, integrated multi-omics tools that incorporate metabolomics, and community implementation is all driving PGx from an area of research curiosity to a clinical standard, despite the issues of algorithmic bias, reimbursement, and translation that will require resolution. A blueprint is provided for both researchers, clinicians, and policymakers.

Precision medicine in resource-limited settings: the central role of pathology

Precision medicine (also known as individualized or personalized medicine) is a novel approach that integrates genetic, environmental, and lifestyle data to drive medical care decisions. It aims to give more precise approaches to illness prevention, diagnosis, and treatment.(1) In oncology, precision medicine is based on the premise that malignancies are not all the same, and people may respond differently to therapies depending on their genetic, environmental, and lifestyle variables.(2) In high-income countries, precision medicine is frequently associated with genomics and molecular profiling. The most common cancers (lung, breast, colorectal, prostate, stomach) all require histopathological diagnosis and immunohistochemistry (IHC) (e.g. ER/PR/HER2 in breast cancer) as part of the WHO Essential Diagnostics framework. Therefore, precision medicine does not have to include expensive whole-genome sequencing. Accurate pathology, basic immunohistochemistry, morphology, and low-cost molecular diagnostics can all provide precision treatment.

Artificial Intelligence in Clinical Genetics: Current Applications and Challenges

Combining genome-wide polygenic scores with registry data for colorectal cancer risk-based screening.

BACKGROUND Polygenic risk scores (PRS) show potential for risk-based colorectal cancer (CRC) screening, but their utility must be assessed across diverse ancestries and tumour characteristics and compared with the current standard, the faecal immunochemical test (FIT). DESIGN The cohort included 112,204 individuals from the Copenhagen Hospital Biobank (8995 with adenoma and 9246 with CRC), all with linked genetic and health registry data. A subset (N = 20,658) also had FIT results. CRC PRSs were evaluated for their association with lifetime adenoma and CRC risk and their predictive value individually and combined with FIT. RESULTS PRS stratified population-calibrated lifetime adenoma and CRC risk independently of ancestry and sex. Individuals with a high PRS reached the incidence of low-PRS individuals up to 10 years earlier, between ages 45-60. PRS stratified risk across tumour location and histologies but showed no association among individuals with deficient mismatch repair tumours (N = 623). Combining PRS with FIT did not meaningfully improve prediction of adenoma or CRC at first screening, negative colonoscopy outcomes among FIT-positive participants, or outcomes within 2 years after a negative FIT. CONCLUSION PRS stratifies lifetime adenoma and CRC risk and may inform risk-based screening initiation and intensity but adds limited predictive value when combined with FIT.