Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.

OBJECTIVE Genetic risk scores (GRS) have been developed that differentiate individuals with type 1 diabetes from those with other forms of diabetes and are starting to be used for population screening; however, most studies were conducted in European-ancestry populations. This study identifies novel genetic variants associated with type 1 diabetes risk in African-ancestry participants and develops an African-specific GRS. RESEARCH DESIGN AND METHODS We generated single nucleotide polymorphism (SNP) data with the ImmunoChip on 1,021 African-ancestry participants with type 1 diabetes and 2,928 control participants. HLA class I and class II alleles were imputed using SNP2HLA. Logistic regression models were used to identify genome-wide significant (P < 5.0 × 10⁻⁸) SNPs associated with type 1 diabetes in the African-ancestry samples and validate SNPs associated with risk in known European-ancestry loci (P < 2.79 × 10⁻⁵). RESULTS African-specific (HLA-DQA1*03:01-HLA-DQB1*02:01) and known European-ancestry HLA haplotypes (HLA-DRB1*03:01-HLA-DQA1*05:01-HLA-DQB1*02:01, HLA-DRB1*04:01-HLA-DQA1*03:01-HLA-DQB1*03:02) were significantly associated with type 1 diabetes risk. Among European-ancestry defined non-HLA risk loci, six risk loci were significantly associated with type 1 diabetes in subjects of African ancestry. An African-specific GRS provided strong prediction of type 1 diabetes risk (area under the curve 0.871), performing significantly better than a European-based GRS and two polygenic risk scores in independent discovery and validation cohorts. CONCLUSIONS Genetic risk of type 1 diabetes includes ancestry-specific, disease-associated variants. The GRS developed here provides improved prediction of type 1 diabetes in African-ancestry subjects and a means to identify groups of individuals who would benefit from immune monitoring for early detection of islet autoimmunity.

The retrotrapezoid nucleus (RTN) consists, by definition, of Phox2b-expressing, glutamatergic, non-catecholaminergic, noncholinergic neurons located in the parafacial region of the medulla oblongata. An unknown proportion of RTN neurons are central respiratory chemoreceptors and there is mounting evidence for biochemical diversity among these cells. Here, we used multiplexedin situhybridization and single-cell RNA-Seq in male and female mice to provide a more comprehensive view of the phenotypic diversity of RTN neurons. We now demonstrate that the RTN of mice can be identified with a single and specific marker,Neuromedin BmRNA (Nmb). Most (∼75%) RTN neurons express low-to-moderate levels ofNmband display chemoreceptor properties. Namely they are activated by hypercapnia, but not by hypoxia, and express proton sensors, TASK-2 and Gpr4. TheseNmb-low RTN neurons also express varying levels of transcripts forGal,Penk, andAdcyap1, and receptors for substance P, orexin, serotonin, and ATP. A subset of RTN neurons (∼20–25%), typically larger than average, express very high levels ofNmbmRNA. TheseNmb-high RTN neurons do not expressFosafter hypercapnia and have low-to-undetectable levels ofKcnk5orGpr4transcripts; they also expressAdcyap1, but are essentially devoid ofPenkandGaltranscripts. In male rats,Nmbis also a marker of the RTN but, unlike in mice, this gene is expressed by other types of nearby neurons located within the ventromedial medulla. In sum,Nmbis a selective marker of the RTN in rodents;Nmb-low neurons, the vast majority, are central respiratory chemoreceptors, whereasNmb-high neurons likely have other functions.SIGNIFICANCE STATEMENTCentral respiratory chemoreceptors regulate arterial PCO₂by adjusting lung ventilation. Such cells have recently been identified within the retrotrapezoid nucleus (RTN), a brainstem nucleus defined by genetic lineage and a cumbersome combination of markers. Using single-cell RNA-Seq and multiplexedin situhybridization, we show here that a single marker,Neuromedin BmRNA (Nmb), identifies RTN neurons in rodents. We also suggest that >75% of theseNmbneurons are chemoreceptors because they are strongly activated by hypercapnia and express high levels of proton sensors (Kcnk5andGpr4). The other RTN neurons express very high levels ofNmb, but low levels ofKcnk5/Gpr4/pre-pro-galanin/pre-pro-enkephalin, and do not respond to hypercapnia. Their function is unknown.