Taylor Maurer

Abstract Animal studies show aging varies between individuals as well as between organs within an individual 1–4 , but whether this is true in humans and its effect on age-related diseases is unknown. We utilized levels of human blood plasma proteins originating from specific organs to measure organ-specific aging differences in living individuals. Using machine learning models, we analysed aging in 11 major organs and estimated organ age reproducibly in five independent cohorts encompassing 5,676 adults across the human lifespan. We discovered nearly 20% of the population show strongly accelerated age in one organ and 1.7% are multi-organ agers. Accelerated organ aging confers 20–50% higher mortality risk, and organ-specific diseases relate to faster aging of those organs. We find individuals with accelerated heart aging have a 250% increased heart failure risk and accelerated brain and vascular aging predict Alzheimer’s disease (AD) progression independently from and as strongly as plasma pTau-181 (ref. 5 ), the current best blood-based biomarker for AD. Our models link vascular calcification, extracellular matrix alterations and synaptic protein shedding to early cognitive decline. We introduce a simple and interpretable method to study organ aging using plasma proteomics data, predicting diseases and aging effects.

Abstract Around 60% of individuals with neurodevelopmental disorders (NDD) remain undiagnosed after comprehensive genetic testing, primarily of protein-coding genes 1 . Large genome-sequenced cohorts are improving our ability to discover new diagnoses in the non-coding genome. Here we identify the non-coding RNA RNU4-2 as a syndromic NDD gene. RNU4-2 encodes the U4 small nuclear RNA (snRNA), which is a critical component of the U4/U6.U5 tri-snRNP complex of the major spliceosome 2 . We identify an 18 base pair region of RNU4-2 mapping to two structural elements in the U4/U6 snRNA duplex (the T-loop and stem III) that is severely depleted of variation in the general population, but in which we identify heterozygous variants in 115 individuals with NDD. Most individuals (77.4%) have the same highly recurrent single base insertion (n.64_65insT). In 54 individuals in whom it could be determined, the de novo variants were all on the maternal allele. We demonstrate that RNU4-2 is highly expressed in the developing human brain, in contrast to RNU4-1 and other U4 homologues. Using RNA sequencing, we show how 5′ splice-site use is systematically disrupted in individuals with RNU4-2 variants, consistent with the known role of this region during spliceosome activation. Finally, we estimate that variants in this 18 base pair region explain 0.4% of individuals with NDD. This work underscores the importance of non-coding genes in rare disorders and will provide a diagnosis to thousands of individuals with NDD worldwide.

BACKGROUND: Grazing mammals rely on their ruminal microbial symbionts to convert plant structural biomass into metabolites they can assimilate. To explore how this complex metabolic system adapts to the host animal's diet, we inferred a microbiome-level metabolic network from shotgun metagenomic data. RESULTS: Using comparative genomics, we then linked this microbial network to that of the host animal using a set of interface metabolites likely to be transferred to the host. When the host sheep were fed a grain-based diet, the induced microbial metabolic network showed several critical differences from those seen on the evolved forage-based diet. Grain-based (e.g., concentrate) diets tend to be dominated by a smaller set of reactions that employ metabolites that are nearer in network space to the host's metabolism. In addition, these reactions are more central in the network and employ substrates with shorter carbon backbones. Despite this apparent lower complexity, the concentrate-associated metabolic networks are actually more dissimilar from each other than are those of forage-fed animals. Because both groups of animals were initially fed on a forage diet, we propose that the diet switch drove the appearance of a number of different microbial networks, including a degenerate network characterized by an inefficient use of dietary nutrients. We used network simulations to show that such disparate networks are not an unexpected result of a diet shift. CONCLUSION: We argue that network approaches, particularly those that link the microbial network with that of the host, illuminate aspects of the structure of the microbiome not seen from a strictly taxonomic perspective. In particular, different diets induce predictable and significant differences in the enzymes used by the microbiome. Nonetheless, there are clearly a number of microbiomes of differing structure that show similar functional properties. Changes such as a diet shift uncover more of this type of diversity.

BACKGROUND AND AIMS: Both clonal haematopoiesis of indeterminate potential (CHIP) and atrial fibrillation (AF) are age-related conditions. This study investigated the potential role of CHIP in the development and progression of AF. METHODS: Deep-targeted sequencing of 24 CHIP mutations (a mean depth of coverage = 1000×) was performed in 1004 patients with AF and 3341 non-AF healthy subjects. Variant allele fraction ≥ 2.0% indicated the presence of CHIP mutations. The association between CHIP and AF was evaluated by the comparison of (i) the prevalence of CHIP mutations between AF and non-AF subjects and (ii) clinical characteristics discriminated by CHIP mutations within AF patients. Furthermore, the risk of clinical outcomes-the composite of heart failure, ischaemic stroke, or death-according to the presence of CHIP mutations in AF was investigated from the UK Biobank cohort. RESULTS: The mean age was 67.6 ± 6.9 vs. 58.5 ± 6.5 years in AF (paroxysmal, 39.0%; persistent, 61.0%) and non-AF cohorts, respectively. CHIP mutations with a variant allele fraction of ≥2.0% were found in 237 (23.6%) AF patients (DNMT3A, 13.5%; TET2, 6.6%; and ASXL1, 1.5%) and were more prevalent than non-AF subjects [356 (10.7%); P < .001] across the age. After multivariable adjustment (age, sex, smoking, body mass index, diabetes, and hypertension), CHIP mutations were 1.4-fold higher in AF [adjusted odds ratio (OR) 1.38; 95% confidence interval 1.10-1.74, P < .01]. The ORs of CHIP mutations were the highest in the long-standing persistent AF (adjusted OR 1.50; 95% confidence interval 1.14-1.99, P = .004) followed by persistent (adjusted OR 1.44) and paroxysmal (adjusted OR 1.33) AF. In gene-specific analyses, TET2 somatic mutation presented the highest association with AF (adjusted OR 1.65; 95% confidence interval 1.05-2.60, P = .030). AF patients with CHIP mutations were older and had a higher prevalence of diabetes, a longer AF duration, a higher E/E', and a more severely enlarged left atrium than those without CHIP mutations (all P < .05). In UK Biobank analysis of 21 286 AF subjects (1297 with CHIP and 19 989 without CHIP), the CHIP mutation in AF is associated with a 1.32-fold higher risk of a composite clinical event (heart failure, ischaemic stroke, or death). CONCLUSIONS: CHIP mutations, primarily DNMT3A or TET2, are more prevalent in patients with AF than non-AF subjects whilst their presence is associated with a more progressive nature of AF and unfavourable clinical outcomes.

A prescription is a health-care program implemented by a physician or other qualified practitioner in the form of instructions that govern the plan of care for an individual patient. Although the algorithmic nature of prescriptions is axiomatic, this insight has not been applied systematically to medication safety. We used software design principles and debugging methods to create a "Patient-oriented Prescription for Analgesia" (POPA), assessed the rate and extent of adoption of POPA by physicians, and conducted a statistical process control clinical trial and a subsidiary cohort analysis to evaluate whether POPA would reduce the rate of severe and fatal opioid-associated adverse drug events (ADEs). We conducted the study in a population of 153,260 hospitalized adults, 50,576 (33%) of whom received parenteral opioids. Hospitalwide, the use of POPA increased to 62% of opioid prescriptions (diffusion half-life = 98 days), while opioid-associated severe/fatal ADEs fell from an initial peak of seven per month to zero per month during the final 6 months (P < 0.0016) of the study. In the nested orthopedics subcohort, the use of POPA increased the practice of recording pain scores (94% vs. 72%, P < 0.00001) and the use of adjuvant analgesics (95% vs. 40%, P < 0.00001) and resulted in fewer opioid-associated severe ADEs than routine patient-controlled analgesia (PCA) (0% vs. 2.7%, number needed to treat (NNT) = 35, P < 0.015). The widespread diffusion of POPA was associated with a substantial hospitalwide decline in opioid-associated severe/fatal ADEs.