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Introduction There are no established methods to identify children with atypical diabetes for further study. We aimed to develop strategies to systematically ascertain cases of atypical pediatric diabetes using electronic medical records (EMR).Research design and methods We tested two strategies in a large pediatric hospital in the USA. Strategy 1: we designed a questionnaire to rule out typical diabetes and applied it to the EMR of 100 youth with diabetes. Strategy 2: we built three electronic queries to generate reports of three atypical pediatric diabetes phenotypes: unknown type, type 2 diabetes (T2D) diagnosed

Abstract Background Monogenic diabetes presents opportunities for precision medicine but is underdiagnosed. This review systematically assessed the evidence for (1) clinical criteria and (2) methods for genetic testing for monogenic diabetes, summarized resources for (3) considering a gene or (4) variant as causal for monogenic diabetes, provided expert recommendations for (5) reporting of results; and reviewed (6) next steps after monogenic diabetes diagnosis and (7) challenges in precision medicine field. Methods Pubmed and Embase databases were searched (1990-2022) using inclusion/exclusion criteria for studies that sequenced one or more monogenic diabetes genes in at least 100 probands (Question 1), evaluated a non-obsolete genetic testing method to diagnose monogenic diabetes (Question 2). The risk of bias was assessed using the revised QUADAS-2 tool. Existing guidelines were summarized for questions 3-5, and review of studies for questions 6-7, supplemented by expert recommendations. Results were summarized in tables and informed recommendations for clinical practice. Results There are 100, 32, 36, and 14 studies included for questions 1, 2, 6, and 7 respectively. On this basis, four recommendations for who to test and five on how to test for monogenic diabetes are provided. Existing guidelines for variant curation and gene-disease validity curation are summarized. Reporting by gene names is recommended as an alternative to the term MODY. Key steps after making a genetic diagnosis and major gaps in our current knowledge are highlighted. Conclusions We provide a synthesis of current evidence and expert opinion on how to use precision diagnostics to identify individuals with monogenic diabetes.

Abstract Introduction: Diabetes mellitus in underrepresented racial and ethnic groups (URG) is rapidly increasing in incidence and has worse outcomes than diabetes in non-Hispanic White individuals. Rare and Atypical Diabetes Network (RADIANT) established recruitment targets based on the racial and ethnic distribution of the USA to enroll a diverse study population. We examined participation of URG across RADIANT study stages and described strategies to enhance recruitment and retention of URG. Materials and Methods: RADIANT is a multicenter NIH-funded study of people with uncharacterized forms of atypical diabetes. RADIANT participants consent online and progress through three sequential study stages, as eligible. Results: We enrolled 601 participants with mean age 44 ± 16.8 years, 64.4% female. At Stage 1, 80.6% were White, 7.2% African American (AA), 12.2% other/more than one race, and 8.4% Hispanic. Enrollment of URG was significantly below preset targets across most stages. Referral sources differed by race (p < 0.001) but not ethnicity (p = 0.15). Most AA participants were referred by RADIANT investigators (58.5% vs. 24.5% in Whites), whereas flyers, news, social media, and family or friends were more frequent referral sources for White individuals (26.4% vs. 12.2% in AA). Ongoing initiatives to increase enrollment of URG in RADIANT include engaging with clinics/hospitals serving URG, screening electronic medical records, and providing culturally competent study coordination and targeted advertisement. Conclusions: There is low participation of URG in RADIANT, potentially limiting the generalizability of its discoveries. Investigations into barriers and facilitators for recruitment and retention of URG in RADIANT, with implications for other studies, are ongoing.

Abstract Aims Numerous genes have been proposed as causal for maturity‐onset diabetes of the young (MODY). Scoring systems to annotate mutation pathogenicity have been widely used; however, statistical evidence for being a highly penetrant MODY gene has not been well‐established. Methods Participants were from the UK Biobank with whole‐exome sequencing data, including 14,622 with and 185,509 without diagnosis of diabetes. Pathogenic/likely pathogenic (P/LP) mutations in 14 reported and 3 possible MODY genes were annotated using American College of Medical Genetics criteria. Evidence for being a high‐penetrant MODY gene used two statistical criteria: frequency of aggregate P/LP mutations in each gene are (1) significantly more common in participants with a diagnosis of diabetes than without using the SKAT‐O (p

Penetrance of variants in monogenic disease and clinical utility of common polygenic variation has not been well explored on a large-scale. Here, the authors use exome sequencing data from 77,184 individuals to generate penetrance estimates and assess the utility of polygenic variation in risk prediction of monogenic variants.

Some bacterial pathogens release NADase enzymes into the host cell that deplete the host’s NAD+ pool, thereby causing rapid cell death. Here, Strømland et al. identify NADases on the surface of fungal spores, and show that the enzymes display unique biochemical and structural properties.

The sirtuin protein family plays a role in the lifespan of various species and is involved in numerous key metabolic processes. To understand the evolutionary role of sirtuins in marmots, a long-living rodent species group with remarkable metabolic shutdown during hibernation, we conducted a phylogeny-based substitution rate analysis of coding genes based on genetic information of seven marmot species. We show that sirtuin 1 (SIRT1) has evolved under positive selection in the marmot lineage. We pinpoint three amino acid changes in four different marmot species that underlie the signal of positive selection and that may favor increased longevity in marmots. Based on a computational structural analysis we can show that all three substitutions affect the secondary structure of the same region in human SIRT1. We propose that the identified region is close to the catalytic domain and that the potential structural changes may impact the catalytic activity of the enzyme and therefore might be playing a functional role in marmot's extended lifespan and metabolic shutdown.

Songbirds have extensive germline–soma genome differences due to developmental elimination of a germline-specific chromosome (GRC). Here, the authors show that the GRC contains dozens of expressed developmental genes, some of which have been on the GRC since the ancestor of all songbirds.

Abstract Background Prediabetes describes a state of hyperglycemia outside of normal limits that does not meet the criteria for diabetes diagnosis, is generally symptomless, and affects an estimated 38% of adults in the United States. Prediabetes typically precedes the diagnosis of type 2 diabetes, which accounts for increased morbidity and mortality. Although the use of dietary and herbal supplements is popular worldwide, and a variety of single herbal medicines have been examined for glycemic management, the potential of increasingly common polyherbal formulations to return glycemic parameters to normal ranges among adults with prediabetes remains largely unexplored. The purpose of this study is to evaluate the efficacy of a commercially available, polyherbal dietary supplement on glycemic and lipid parameters in prediabetic individuals. Methods In this multi-site, double-blinded, randomized controlled clinical trial, 40 participants with prediabetes will be randomized to either a daily oral polyherbal dietary supplement (GlucoSupreme™ Herbal; Designs for Health®, Suffield, CT, USA; containing cinnamon bark (Cinnamomum cassia), banaba leaf (Lagerstroemia speciosa standardized to 1% corosolic acid), kudzu root (Pueraria lobata standardized to 40% isoflavones), fenugreek seed (Trigonella foenum-graceum standardized to 60% saponins), gymnema leaf (Gymnema sylvestre standardized to 25% gymnemic acid), American ginseng root (Panax quinquefolius standardized to 5% ginsenosides), and berberine HCl derived from bark (Berberis aristata)) or placebo for 12 weeks. Short-, medium-, and comparatively long-term markers of glycemic control (blood glucose and fasting insulin, fructosamine, and glycated hemoglobin/A1c, respectively), and other glycemic parameters (GlycoMark, β-cell function, and insulin sensitivity/resistance) will be obtained. Lipid profile (total cholesterol, LDL, HDL, and triglycerides), inflammation (hs-CRP), progression to type 2 diabetes mellitus, as well as safety indices (ALT, AST) will be obtained. An intention-to-treat analysis will be used to assess changes in study outcomes. Discussion Treatment options for adults with prediabetes are currently limited. This study aims to evaluate the safety and efficacy of a commercially available dietary supplement in the popular, but as yet insufficiently studied, category of polyherbal formulas for the management of glycemic parameters and other biomarkers associated with prediabetes. Trial registration ClinicalTrials.gov, ID: NCT03388762. Retrospectively registered on 4 January 2018.

Abstract Background A widely used approach in next-generation sequencing projects is the alignment of reads to a reference genome. Despite methodological and hardware improvements which have enhanced the efficiency and accuracy of alignments, a significant percentage of reads frequently remain unmapped. Usually, unmapped reads are discarded from the analysis process, but significant biological information and insights can be uncovered from these data. We explored the unmapped DNA (normal and bisulfite treated) and RNA sequence reads of the great tit (Parus major) reference genome individual. From the unmapped reads we generated de novo assemblies, after which the generated sequence contigs were aligned to the NCBI non-redundant nucleotide database using BLAST, identifying the closest known matching sequence. Results Many of the aligned contigs showed sequence similarity to different bird species and genes that were absent in the great tit reference assembly. Furthermore, there were also contigs that represented known P. major pathogenic species. Most interesting were several species of blood parasites such as Plasmodium and Trypanosoma. Conclusions Our analyses revealed that meaningful biological information can be found when further exploring unmapped reads. For instance, it is possible to discover sequences that are either absent or misassembled in the reference genome, and sequences that indicate infection or sample contamination. In this study we also propose strategies to aid the capture and interpretation of this information from unmapped reads.

Introduction Sex hormone binding globulin (SHBG) levels are reported to be inversely associated with diabetes risk. It is unknown whether diabetes prevention interventions increase SHBG and whether resultant changes in SHBG affect diabetes risk. The purpose of this analysis was to determine whether intensive lifestyle intervention (ILS) or metformin changed circulating SHBG and if resultant changes influenced diabetes risk in the Diabetes Prevention Program (DPP).Research design and methods This is a secondary analysis from the DPP (1996–2001), a randomized trial of ILS or metformin versus placebo on diabetes risk over a mean follow-up of 3.2 years. The DPP was conducted across 27 academic study centers in the USA. Men, premenopausal and postmenopausal women without hormone use in the DPP were evaluated. The DPP included overweight/obese persons with elevated fasting glucose and impaired glucose tolerance. Main outcomes measures were changes in SHBG levels at 1 year and risk of diabetes over 3 years.Results ILS resulted in significantly higher increases (postmenopausal women: p

Background The burden of diabetes and cardiovascular risk is not uniform across the USA, with much of this disparity tracking differences in socioeconomic status, cultural practices and lifestyle. To further evaluate disparities in these disorders, we assessed the prevalence of diabetes, hypertension, and hypercholesterolemia in an Old Order Amish community that is characterized by distinctive sociocultural practices that include a very cohesive social structure and limited use of modern technologies and medications. We compared prevalence of these conditions with that of the overall US population.Method We performed a community-wide survey in 5377 Amish individuals aged 18 years and older from the Lancaster County, Pennsylvania, Amish settlement that included a basic physical examination and fasting blood draw during the period 2010–2018. We then compared the prevalence of diabetes, hypertension, and high cholesterol, defined using standard criteria, between the Amish and the European Caucasian subsample of the 2013–2014 US National Health and Nutrition Examination Survey (NHANES).Results Prevalence rates for diabetes, hypertension and hypercholesterolemia were 3.3%, 12.7%, and 26.2% in the Amish compared with 13.2%, 37.8% and 35.7% in NHANES (p

Abstract Background To realize potential public health benefits from genetic and genomic innovations, understanding how best to implement the innovations into clinical care is important. The objective of this study was to synthesize data on challenges identified by six diverse projects that are part of a National Human Genome Research Institute (NHGRI)-funded network focused on implementing genomics into practice and strategies to overcome these challenges. Methods We used a multiple-case study approach with each project considered as a case and qualitative methods to elicit and describe themes related to implementation challenges and strategies. We describe challenges and strategies in an implementation framework and typology to enable consistent definitions and cross-case comparisons. Strategies were linked to challenges based on expert review and shared themes. Results Three challenges were identified by all six projects, and strategies to address these challenges varied across the projects. One common challenge was to increase the relative priority of integrating genomics within the health system electronic health record (EHR). Four projects used data warehousing techniques to accomplish the integration. The second common challenge was to strengthen clinicians’ knowledge and beliefs about genomic medicine. To overcome this challenge, all projects developed educational materials and conducted meetings and outreach focused on genomic education for clinicians. The third challenge was engaging patients in the genomic medicine projects. Strategies to overcome this challenge included use of mass media to spread the word, actively involving patients in implementation (e.g., a patient advisory board), and preparing patients to be active participants in their healthcare decisions. Conclusions This is the first collaborative evaluation focusing on the description of genomic medicine innovations implemented in multiple real-world clinical settings. Findings suggest that strategies to facilitate integration of genomic data within existing EHRs and educate stakeholders about the value of genomic services are considered important for effective implementation. Future work could build on these findings to evaluate which strategies are optimal under what conditions. This information will be useful for guiding translation of discoveries to clinical care, which, in turn, can provide data to inform continual improvement of genomic innovations and their applications.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-22476-7

The great tit (Parus major) is known for its complex social-cognitive behaviour. Here, the authors sequence genomes of the great tit and show genes related to learning and cognition in regions under positive selection, as well as neuronal non-CpG methylation patterns similar to those observed in mammals.

It is well established that GC content varies across the genome in many species and that GC biased gene conversion, one form of meiotic recombination, is likely to contribute to this heterogeneity. Bird genomes provide an extraordinary system to study the impact of GC biased gene conversion owed to their specific genomic features. They are characterized by a high karyotype conservation with substantial heterogeneity in chromosome sizes, with up to a dozen large macrochromosomes and many smaller microchromosomes common across all bird species. This heterogeneity in chromosome morphology is also reflected by other genomic features, such as smaller chromosomes being gene denser, more compact and more GC rich relative to their macrochromosomal counterparts - illustrating that the intensity of GC biased gene conversion varies across the genome. Here we study whether it is possible to infer heterogeneity in GC biased gene conversion rates across the genome using a recently published method that accounts for GC biased gene conversion when estimating branch lengths in a phylogenetic context. To infer the strength of GC biased gene conversion we contrast branch length estimates across the genome both taking and not taking non-stationary GC composition into account. Using simulations we show that this approach works well when GC fixation bias is strong and note that the number of substitutions along a branch is consistently overestimated when GC biased gene conversion is not accounted for. We use this predictable feature to infer the strength of GC dynamics across the great tit genome by applying our new pipeline to data at 4-fold degenerate sites from three bird species—great tit, zebra finch and chicken—three species that are among the best annotated bird genomes to date. We show that using a simple one-dimensional binning we fail to capture a signal of fixation bias as observed in our simulations. However, using a multidimensional binning strategy, we find evidence for heterogeneity in the strength of fixation bias, including AT fixation bias. This highlights the difficulties when combining sequence data across different regions in the genome.

The cavities that develop in veteran trees represent a key microhabitat for forest biodiversity and especially for secondary cavity nesters that rely on this resource for shelter. Since the availability of deadwood, veteran and hollow trees is threatened by forest management, we explored the possibility of increasing the presence of these scarce resources. To increase the abundance of dead wood-microhabitats, 113 trees of the hybrid planes (Platanus x acerifolia) were converted into new living structures, the Habitat Trees (HT). To investigate the potential of this resource on the native avian fauna, six types of cavities were designed according to the size requirements of the target bird species. The temporal evolution of the cavities and their use by birds were then studied for eight years. The artificial cavities generally did not compromise growth and stability of the trees, and the majority remained alive. These hollows offered better thermal insulation compared to traditional nest-boxes and natural cavities. Their use increased during the first three years, reaching the 80%. In the following years, the use declined (probably because of the increase of rot and displacement of the lids).This highlights the need of management to maintain their suitability through time. Our results suggest a possible cost-effective alternative use of alien tree species, which should be included in management actions to compensate the shortage of hollow trees in managed forests.

Due to their relatively homogeneous lifestyle and living environment, the Amish offer a novel opportunity to study the health associations of tobacco smoke exposure, particularly secondhand smoke. We hypothesized that secondhand smoke exposure is associated with worse pulmonary and cardiometabolic health. We examined cross-sectional data on 3568 Amish study participants, including tobacco use and secondhand smoke exposure from family members included in the study. Thirty-four percent of Amish men reported ever smoking. Of this proportion, 64% used cigars, 46% cigarettes, and 21% pipes. Less than 1% of women reported ever smoking. Smoking was associated with lower spirometric lung function, higher body mass index, lower HDL cholesterol, higher heart rate, lower ankle-brachial index, and larger aortic diameter in men. A greater number of sources of secondhand smoke exposure (defined from the total of spouses, parents, and siblings who smoke) was associated with higher body mass index (p = 0.03) and with higher fasting glucose in men (p = 0.01), but not in women (p = 0.007 for sex*secondhand smoke interaction). Secondhand smoke exposure was also associated with reduced HDL cholesterol only in women (p = 0.002) and a lower heart rate only in men (p = 0.006). Smoking habits among the Old Order Amish are notable for the absence of female participation and a high proportion of cigar and pipe use. Smoking is associated with decreased spirometric indices of lung function and increased cardiovascular risk in this population and secondhand smoke exposure is associated with a greater burden of risk factors for cardiovascular disease. Sex differences in correlations could reflect differences in exposure patterns, mechanisms, or susceptibilities.

It is likely that the strength of selection acting upon a mutation varies through time due to changes in the environment. However, most population genetic theory assumes that the strength of selection remains constant. Here we investigate the consequences of fluctuating selection pressures on the quantification of adaptive evolution using McDonald-Kreitman (MK) style approaches. In agreement with previous work, we show that fluctuating selection can generate evidence of adaptive evolution even when the expected strength of selection on a mutation is zero. However, we also find that the mutations, which contribute to both polymorphism and divergence tend, on average, to be positively selected during their lifetime, under fluctuating selection models. This is because mutations that fluctuate, by chance, to positive selected values, tend to reach higher frequencies in the population than those that fluctuate towards negative values. Hence the evidence of positive adaptive evolution detected under a fluctuating selection model by MK type approaches is genuine since fixed mutations tend to be advantageous on average during their lifetime. Never-the-less we show that methods tend to underestimate the rate of adaptive evolution when selection fluctuates.

Weight-loss interventions generally improve lipid profiles and reduce cardiovascular disease risk, but effects are variable and may depend on genetic factors. We performed a genetic association analysis of data from 2,993 participants in the Diabetes Prevention Program to test the hypotheses that a genetic risk score (GRS) based on deleterious alleles at 32 lipid-associated single-nucleotide polymorphisms modifies the effects of lifestyle and/or metformin interventions on lipid levels and nuclear magnetic resonance (NMR) lipoprotein subfraction size and number. Twenty-three loci previously associated with fasting LDL-C, HDL-C, or triglycerides replicated (P = 0.04-1 × 10(-17)). Except for total HDL particles (r = -0.03, P = 0.26), all components of the lipid profile correlated with the GRS (partial |r| = 0.07-0.17, P = 5 × 10(-5)-1 10(-19)). The GRS was associated with higher baseline-adjusted 1-year LDL cholesterol levels (β = +0.87, SEE ± 0.22 mg/dl/allele, P = 8 × 10(-5), P(interaction) = 0.02) in the lifestyle intervention group, but not in the placebo (β = +0.20, SEE ± 0.22 mg/dl/allele, P = 0.35) or metformin (β = -0.03, SEE ± 0.22 mg/dl/allele, P = 0.90; P(interaction) = 0.64) groups. Similarly, a higher GRS predicted a greater number of baseline-adjusted small LDL particles at 1 year in the lifestyle intervention arm (β = +0.30, SEE ± 0.012 ln nmol/L/allele, P = 0.01, P(interaction) = 0.01) but not in the placebo (β = -0.002, SEE ± 0.008 ln nmol/L/allele, P = 0.74) or metformin (β = +0.013, SEE ± 0.008 nmol/L/allele, P = 0.12; P(interaction) = 0.24) groups. Our findings suggest that a high genetic burden confers an adverse lipid profile and predicts attenuated response in LDL-C levels and small LDL particle number to dietary and physical activity interventions aimed at weight loss.

Lifespan increases observed in the United States and elsewhere throughout the developed world, have been attributed in part to improvements in medical care access and technology and to healthier lifestyles. To differentiate the relative contributions of these two factors, we have compared lifespan in the Old Order Amish (OOA), a population with historically low use of medical care, with that of Caucasian participants from the Framingham Heart Study (FHS), focusing on individuals who have reached at least age 30 years.Analyses were based on 2,108 OOA individuals from the Lancaster County, PA community born between 1890 and 1921 and 5,079 FHS participants born approximately the same time. Vital status was ascertained on 96.9% of the OOA cohort through 2011 and through systematic follow-up of the FHS cohort. The lifespan part of the study included an enlargement of the Anabaptist Genealogy Database to 539,822 individuals, which will be of use in other studies of the Amish. Mortality comparisons revealed that OOA men experienced better longevity (p

AIMS: The tendency to develop diabetic nephropathy is, in part, genetically determined, however this genetic risk is largely undefined. In this proof-of-concept study, we tested the hypothesis that combined analysis of multiple genetic variants can improve prediction. METHODS: Based on previous reports, we selected 27 SNPs in 15 genes from metabolic pathways involved in the pathogenesis of diabetic nephropathy and genotyped them in 1274 Ashkenazi or Sephardic Jewish patients with Type 1 or Type 2 diabetes of >10 years duration. A logistic regression model was built using a backward selection algorithm and SNPs nominally associated with nephropathy in our population. The model was validated by using random "training" (75%) and "test" (25%) subgroups of the original population and by applying the model to an independent dataset of 848 Ashkenazi patients. RESULTS: The logistic model based on 5 SNPs in 5 genes (HSPG2, NOS3, ADIPOR2, AGER, and CCL5) and 5 conventional variables (age, sex, ethnicity, diabetes type and duration), and allowing for all possible two-way interactions, predicted nephropathy in our initial population (C-statistic = 0.672) better than a model based on conventional variables only (C = 0.569). In the independent replication dataset, although the C-statistic of the genetic model decreased (0.576), it remained highly associated with diabetic nephropathy (χ(2) = 17.79, p

BackgroundObesity is associated with low-grade chronic inflammation, and serum markers of inflammation are independent risk factors for cardiovascular disease (CVD). However, the molecular and cellular mechanisms that link obesity to chronic inflammation and CVD are poorly understood.Methods and findingsAcute-phase serum amyloid A (A-SAA) mRNA levels, and A-SAA adipose secretion and serum levels were measured in obese and nonobese individuals, obese participants who underwent weight-loss, and persons treated with the insulin sensitizer rosiglitazone. Inflammation-eliciting activity of A-SAA was investigated in human adipose stromal vascular cells, coronary vascular endothelial cells and a murine monocyte cell line. We demonstrate that A-SAA was highly and selectively expressed in human adipocytes. Moreover, A-SAA mRNA levels and A-SAA secretion from adipose tissue were significantly correlated with body mass index (r = 0.47; p = 0.028 and r = 0.80; p = 0.0002, respectively). Serum A-SAA levels decreased significantly after weight loss in obese participants (p = 0.006), as well as in those treated with rosiglitazone (p = 0.033). The magnitude of the improvement in insulin sensitivity after weight loss was significantly correlated with decreases in serum A-SAA (r = -0.74; p = 0.034). SAA treatment of vascular endothelial cells and monocytes markedly increased the production of inflammatory cytokines, e.g., interleukin (IL)-6, IL-8, tumor necrosis factor alpha, and monocyte chemoattractant protein-1. In addition, SAA increased basal lipolysis in adipose tissue culture by 47%.ConclusionsA-SAA is a proinflammatory and lipolytic adipokine in humans. The increased expression of A-SAA by adipocytes in obesity suggests that it may play a critical role in local and systemic inflammation and free fatty acid production and could be a direct link between obesity and its comorbidities, such as insulin resistance and atherosclerosis. Accordingly, improvements in systemic inflammation and insulin resistance with weight loss and rosiglitazone therapy may in part be mediated by decreases in adipocyte A-SAA production.

A major challenge in evaluating the contribution of rare variants to complex disease is identifying enough copies of the rare alleles to permit informative statistical analysis. To investigate the contribution of rare variants to the risk of type 2 diabetes (T2D) and related traits, we performed deep whole-genome analysis of 1,034 members of 20 large Mexican-American families with high prevalence of T2D. If rare variants of large effect accounted for much of the diabetes risk in these families, our experiment was powered to detect association. Using gene expression data on 21,677 transcripts for 643 pedigree members, we identified evidence for large-effect rare-variant cis-expression quantitative trait loci that could not be detected in population studies, validating our approach. However, we did not identify any rare variants of large effect associated with T2D, or the related traits of fasting glucose and insulin, suggesting that large-effect rare variants account for only a modest fraction of the genetic risk of these traits in this sample of families. Reliable identification of large-effect rare variants will require larger samples of extended pedigrees or different study designs that further enrich for such variants.

Identifying genes that result in monogenic diabetes can provide insights that can build a scientific foundation for precision medicine. At present, nearly 20% of neonatal diabetes cases have unknown causes. In this issue of the JCI, De Franco and Lytrivi et al. sequenced the genome of two probands with a rare neonatal diabetes subtype that also associated with microcephaly and epilepsy. The authors revealed mutations in the YIPF5 gene. YIPF5 resides in the Golgi apparatus and is thought to play a critical role in vesicular trafficking. Notably, disrupting YIPF5 in [beta] cell-based models induced ER stress signaling and resulted in the accumulation of intracellular proinsulin. We believe that utilizing registries and biobanks to reveal other monogenic atypical forms of diabetes is an important approach to gaining insight and suggest that an insulin sensitizer may alleviate ER stress associated with YIPF5 disruption by decreasing the demand for insulin secretion., Monogenic diabetes genes Precision medicine for diabetes is often said to be on the horizon. However, as noted in the recent joint American Diabetes Association (ADA)/European Association for the Study [...]