Notable Genomics Research

Newborn screening (NBS) contributes to reduced newborn morbidity and mortality globally. While reducing morbidity and mortality is already a public health success, the need for expanded and more widely adopted NBS initiatives is emphasized by the United Nations’ goal to end preventable deaths of newborns and children under five years old by 2030. Incorporating genomic sequencing into NBS programs would enable earlier identification of a wide range of conditions, pushing us closer to this goal. Indeed, the value of including genomic sequencing in NBS programs is well recognized in the medical community, but an important component of ensuring successful implementation of such programs is understanding public values.

This work reveals heritable DNA methylation signatures in airway cells from children that reflected perturbations in processes defining cardinal endotypes of asthma and allergic diseases. The authors suggest that biases toward the development of these endotypes are present at birth and are poised to mediate epigenetic responses to early-life environments.

We present a stringent single-cell analytical framework using transcriptome-wide Mendelian randomization and colocalization. By resolving cell-type-specific expression effects missed by bulk methods, this approach improves causal gene prioritization in atherosclerotic cardiovascular disease and offers a scalable strategy for uncovering disease mechanisms and therapeutic targets across diverse traits.

Genome-wide association studies (GWAS) of 19 circulating fatty acid traits were performed in six ancestry groups from UK Biobank, with three primary models and sex-specific analyses. We identified between 37 and 124 loci for each trait. Integrative analysis with QTLs for six molecular phenotypes proposed underlying mechanisms for 35% of GWAS loci.

We identified digenic inheritance as a genetic mechanism underlying laterality defects. In an analysis of sequencing data from three cohorts, we found an enrichment of trans-heterozygous digenic variants, particularly in ciliary genes. These findings highlight the role of epistatic interactions in disease pathogenesis.

Health data are inherently multimodal; we developed a multimodal AI (M-REGLE) that jointly analyzes complementary physiological waveforms (like ECG and PPG) to enhance genetic discovery for cardiovascular traits. Compared to analyzing waveforms individually, our approach identifies significantly more genetic associations and improves out-of-sample prediction for cardiac conditions, including atrial fibrillation.

Recurrent de novo missense variants affecting CRNKL1, a component of the spliceosome, severely impact brain development, with a zebrafish model illustrating widespread cellular stress and apoptosis. This finding contributes to a growing disease cluster, where associated components act at the same spliceosomal stage and cause a severe neurological phenotype.

CADET is a transcriptome-wide association test for admixed cohorts that leverages local ancestry information to improve detection of trait-influencing genes. CADET outperformed existing methods using simulated data and, in UK Biobank data, the method uniquely identified 18 gene-trait hits supported by GWAS. Our findings highlight the importance of ancestry-aware analysis.

We describe a data model that organizes and retains detailed population descriptor data for future research use. The model supports a versatile, traceable, and reproducible harmonization system that affords researchers the flexibility to thoughtfully choose and scientifically justify their choice of population descriptors.

Using polygenic scores, we find that two types of natural selection, stabilizing selection and directional selection, can decrease the prediction accuracy of complex traits in ancient individuals. We show that the action of these types of natural selection must be considered before making predictions of complex traits in ancient individuals.

Mutations in FASTKD5, which codes for a protein essential for processing the primary mitochondrial transcript, were identified in subjects who presented with Leigh syndrome and cytochrome c oxidase deficiency. Leigh syndrome is a genetically heterogeneous, progressive neurodegenerative disorder, and these cases add to the growing list of causal genetic defects.

Sickle cell disease, though monogenic, exhibits complex clinical variability driven by genetic, epigenetic, and environmental factors. This commentary highlights advances in precision therapies and underscores the urgent need for equitable access, global collaboration, and personalized approaches to address the significant health disparities impacting individuals with sickle cell disease worldwide.

TM2D3 is present in many tissues, but its function and cell localization are not fully elucidated. Gabillard-Lefort and colleagues report TM2D3 variants that are associated with a syndromic neurodevelopmental disorder. They identified TM2D3 as an endoplasmic reticulum (ER) protein, mutations of which lead to exacerbated ER-stress response and secondary mitochondrial alterations.

Genomics will potentially transform newborn screening programs globally. To inform implementation, we surveyed 2,509 members of the Australian public to understand the importance they place on key aspects of genomic newborn screening and their preferences about how programs should be delivered in practice.

We present scalable algorithms and data structures for polygenic risk score inference from genome-wide data. Our method enables efficient variational inference on tens of millions of variants, reducing memory and runtime by orders of magnitude and achieving accuracy comparable to state-of-the-art tools.