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Digital phenotyping from wearables using AI characterizes psychiatric disorders and identifies genetic associations

Complex disorders require precise strategies for their characterization. AI-based digital phenotypes from biosensors can be used to predict psychiatric disorders and identify GWAS loci.

Genomic and phenotypic correlates of mosaic loss of chromosome Y in blood

Am J Hum Genet. 2025 Jan 6:S0002-9297(24)00456-7. doi: 10.1016/j.ajhg.2024.12.014. Online ahead of print.

ABSTRACT

Mosaic loss of Y (mLOY) is the most common somatic chromosomal alteration detected in human blood. The presence of mLOY is associated with altered blood cell counts and increased risk of Alzheimer disease, solid tumors, and other age-related diseases. We sought to gain a better understanding of genetic drivers and associated phenotypes of mLOY through analyses of whole-genome sequencing (WGS) of a large set of genetically diverse males from the Trans-Omics for Precision Medicine (TOPMed) program. We show that haplotype-based calling methods can be used with WGS data to successfully identify mLOY events. This approach enabled us to identify differences in mLOY frequencies across populations defined by genetic similarity, revealing a higher frequency of mLOY in the European (EUR) ancestry group compared to other ancestries. We identify multiple loci associated with mLOY susceptibility and show that subsets of human hematopoietic stem cells are enriched for the activity of mLOY susceptibility variants. Finally, we found that certain alleles on chromosome Y are more likely to be lost than others in detectable mLOY clones.

PMID:39809269 | DOI:10.1016/j.ajhg.2024.12.014

Liquid Biopsy for Spinal Tumors: On the Frontiers of Clinical Application

Global Spine J. 2025 Jan;15(1_suppl):16S-28S. doi: 10.1177/21925682231222012.

ABSTRACT

STUDY DESIGN: Narrative review.

OBJECTIVES: This article aims to provide a narrative review of the current state of research for liquid biopsy in spinal tumors and to discuss the potential application of liquid biopsy in the clinical management of patients with spinal tumors.

METHODS: A comprehensive review of the literature was performed using PubMed, Google Scholar, Medline, Embase and Cochrane databases, and the review was limited to articles of English language. All the relevant articles which were identified to be related to liquid biomarker study in spinal tumors, were studied in full text.

RESULTS: Liquid biopsy has revolutionized the field of precision medicine by guiding personalized clinical management of cancer patients based on the liquid biomarker status. In recent years, more research has been done to investigate its potential utilization in patients with tumors from the spine. Herein, we review the liquid biomarkers that have been proposed in different spine malignancies including chordoma, chondrosarcoma, Ewing sarcoma, osteosarcoma, astrocytoma and ependymoma. We also discuss the wide window of opportunity to utilize these liquid biomarkers in diagnosis, treatment response, monitoring, and detection of minimal residual disease in patients with spinal tumors.

CONCLUSIONS: Liquid biomarkers, especially blood-derived circulating tumor DNA, has a promising clinical utility as they are disease-specific, minimally invasive, and the procedure is repeatable. Prospective studies with larger populations are needed to fully establish its use in the setting of spinal tumors.

PMID:39801114 | PMC:PMC11726521 | DOI:10.1177/21925682231222012

A Real-World Assessment of Stage I Lung Cancer Through Electronic Nose Technology

J Thorac Oncol. 2024 Sep;19(9):1272-1283. doi: 10.1016/j.jtho.2024.05.006. Epub 2024 May 16.

ABSTRACT

INTRODUCTION: Electronic nose (E-nose) technology has reported excellent sensitivity and specificity in the setting of lung cancer screening. However, the performance of E-nose specifically for early-stage tumors remains unclear. Therefore, the aim of our study was to assess the diagnostic performance of E-nose technology in clinical stage I lung cancer.

METHODS: This phase IIc trial (NCT04734145) included patients diagnosed with a single greater than or equal to 50% solid stage I nodule. Exhalates were prospectively collected from January 2020 to August 2023. Blinded bioengineers analyzed the exhalates, using E-nose technology to determine the probability of malignancy. Patients were stratified into three risk groups (low-risk, [<0.2]; moderate-risk, [≥0.2-0.7]; high-risk, [≥0.7]). The primary outcome was the diagnostic performance of E-nose versus histopathology (accuracy and F1 score). The secondary outcome was the clinical performance of the E-nose versus clinicoradiological prediction models.

RESULTS: Based on the predefined cutoff (<0.20), E-nose agreed with histopathologic results in 86% of cases, achieving an F1 score of 92.5%, based on 86 true positives, two false negatives, and 12 false positives (n = 100). E-nose would refer fewer patients with malignant nodules to observation (low-risk: 2 versus 9 and 11, respectively; p = 0.028 and p = 0.011) than would the Swensen and Brock models and more patients with malignant nodules to treatment without biopsy (high-risk: 27 versus 19 and 6, respectively; p = 0.057 and p < 0.001).

CONCLUSIONS: In the setting of clinical stage I lung cancer, E-nose agrees well with histopathology. Accordingly, E-nose technology can be used in addition to imaging or as part of a "multiomics" platform.

PMID:38762120 | PMC:PMC11380592 | DOI:10.1016/j.jtho.2024.05.006

Bridge RNAs direct programmable recombination of target and donor DNA

Nature, Published online: 26 June 2024; doi:10.1038/s41586-024-07552-4

A bispecific non-coding RNA expressed by the IS110 family of mobile genetic elements forms the basis of a programmable genome-editing system that enables the insertion, excision or inversion of specific target DNA sequences.

Plasma proteomic associations with genetics and health in the UK Biobank

Nature, Published online: 04 October 2023; doi:10.1038/s41586-023-06592-6

The Pharma Proteomics Project generates the largest open-access plasma proteomics dataset to date, offering insights into trans protein quantitative trait loci across multiple biological domains, and highlighting genetic influences on ligand–receptor interactions and pathway perturbations across a diverse collection of cytokines and complement networks.
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