The use of quantitative clinical pharmacology approaches to support moxidectin dosing recommendations in lactation.

Moxidectin is approved by the US Food and Drug Administration (US FDA) for the treatment of onchocerciasis (river-blindness) due to Onchocerca volvulus in patients aged 12 years and older. In onchocerciasis-endemic areas, mass drug administration (MDA) programs with ivermectin, with or without vector control, aim to control the disease, reduce morbidity, interrupt transmission, and more recently, achieve elimination. Moxidectin has the potential to be used in MDA programs. In countries where onchocerciasis is endemic, infants are often breastfed up to the age of 2 years, suggesting that some women are likely to be lactating during such periodic MDA programs. Quantitative analyses of non-clinical and clinical data using non-compartmental analysis and population based pharmacokinetic (popPK) modeling as well as physiologically based pharmacokinetic modeling (PBPK) were performed to determine the amount of moxidectin excreted in breast milk and subsequent exposures in the infant. The results of the analyses were similar. Concentrations of moxidectin in breast milk followed a similar pattern to those in plasma, with maximum concentrations occurring approximately 4 hours after dosing followed by a rapid decline in both breast milk and plasma. As early as two days after dosing, concentrations of moxidectin in breast milk were below the threshold for acceptable daily intake levels established by the European Medicines Agency (EMA) and FDA for secondary exposures from veterinary use, and below the WHO recommended relative infant dose (RID) safety threshold. The analyses were conducted to support prescribers and policy makers on dosing recommendations for moxidectin in lactation.

Guidance for estimating penetrance of monogenic disease-causing variants in population cohorts.

Penetrance is the probability that an individual with a pathogenic genetic variant develops a specific disease. Knowing the penetrance of variants for monogenic disorders is important for counseling of individuals. Until recently, estimates of penetrance have largely relied on affected individuals and their at-risk family members being clinically referred for genetic testing, a 'phenotype-first' approach. This approach substantially overestimates the penetrance of variants because of ascertainment bias. The recent availability of whole-genome sequencing data in individuals from very-large-scale population-based cohorts now allows 'genotype-first' estimates of penetrance for many conditions. Although this type of population-based study can underestimate penetrance owing to recruitment biases, it provides more accurate estimates of penetrance for secondary or incidental findings. Here, we provide guidance for the conduct of penetrance studies to ensure that robust genotypes and phenotypes are used to accurately estimate penetrance of variants and groups of similarly annotated variants from population-based studies.

Precision treatment of beta-cell monogenic diabetes: a systematic review.

BACKGROUND: Beta-cell monogenic forms of diabetes have strong support for precision medicine. We systematically analyzed evidence for precision treatments for GCK-related hyperglycemia, HNF1A-, HNF4A- and HNF1B-diabetes, and mitochondrial diabetes (MD) due to m.3243 A > G variant, 6q24-transient neonatal diabetes mellitus (TND) and SLC19A2-diabetes. METHODS: The search of PubMed, MEDLINE, and Embase for individual and group level data for glycemic outcomes using inclusion (English, original articles written after 1992) and exclusion (VUS, multiple diabetes types, absent/aggregated treatment effect measures) criteria. The risk of bias was assessed using NHLBI study-quality assessment tools. Data extracted from Covidence were summarized and presented as descriptive statistics in tables and text. RESULTS: There are 146 studies included, with only six being experimental studies. For GCK-related hyperglycemia, the six studies (35 individuals) assessing therapy discontinuation show no HbA1c deterioration. A randomized trial (18 individuals per group) shows that sulfonylureas (SU) were more effective in HNF1A-diabetes than in type 2 diabetes. Cohort and case studies support SU's effectiveness in lowering HbA1c. Two cross-over trials (each with 15-16 individuals) suggest glinides and GLP-1 receptor agonists might be used in place of SU. Evidence for HNF4A-diabetes is limited. Most reported patients with HNF1B-diabetes (N = 293) and MD (N = 233) are on insulin without treatment studies. Limited data support oral agents after relapse in 6q24-TND and for thiamine improving glycemic control and reducing/eliminating insulin requirement in SLC19A2-diabetes. CONCLUSION: There is limited evidence, and with moderate or serious risk of bias, to guide monogenic diabetes treatment. Further evidence is needed to examine the optimum treatment in monogenic subtypes.

Monogenic diabetes is a type of diabetes caused by changes in genes that affect how the body makes or responds to insulin. Precision medicine (where knowledge of the gene change directs the selection of treatment) is available for some forms of monogenic diabetes. This study evaluated the published literature for several forms of monogenic diabetes to assess the level of evidence supporting specific precision treatments. Among the 146 small studies that we reviewed, only six compared different treatments. However, we found evidence supporting oral medications for some types of monogenic diabetes, and evidence that treatment is not needed for one particular type. Based on our results, we provide treatment recommendations for certain forms of monogenic diabetes and identify future directions for research to help us optimize precision medicine in monogenic diabetes.

Comparison of Bayesian approaches for developing prediction models in rare disease: application to the identification of patients with Maturity-Onset Diabetes of the Young.

BACKGROUND: Clinical prediction models can help identify high-risk patients and facilitate timely interventions. However, developing such models for rare diseases presents challenges due to the scarcity of affected patients for developing and calibrating models. Methods that pool information from multiple sources can help with these challenges. METHODS: We compared three approaches for developing clinical prediction models for population screening based on an example of discriminating a rare form of diabetes (Maturity-Onset Diabetes of the Young - MODY) in insulin-treated patients from the more common Type 1 diabetes (T1D). Two datasets were used: a case-control dataset (278 T1D, 177 MODY) and a population-representative dataset (1418 patients, 96 MODY tested with biomarker testing, 7 MODY positive). To build a population-level prediction model, we compared three methods for recalibrating models developed in case-control data. These were prevalence adjustment ("offset"), shrinkage recalibration in the population-level dataset ("recalibration"), and a refitting of the model to the population-level dataset ("re-estimation"). We then developed a Bayesian hierarchical mixture model combining shrinkage recalibration with additional informative biomarker information only available in the population-representative dataset. We developed a method for dealing with missing biomarker and outcome information using prior information from the literature and other data sources to ensure the clinical validity of predictions for certain biomarker combinations. RESULTS: The offset, re-estimation, and recalibration methods showed good calibration in the population-representative dataset. The offset and recalibration methods displayed the lowest predictive uncertainty due to borrowing information from the fitted case-control model. We demonstrate the potential of a mixture model for incorporating informative biomarkers, which significantly enhanced the model's predictive accuracy, reduced uncertainty, and showed higher stability in all ranges of predictive outcome probabilities. CONCLUSION: We have compared several approaches that could be used to develop prediction models for rare diseases. Our findings highlight the recalibration mixture model as the optimal strategy if a population-level dataset is available. This approach offers the flexibility to incorporate additional predictors and informed prior probabilities, contributing to enhanced prediction accuracy for rare diseases. It also allows predictions without these additional tests, providing additional information on whether a patient should undergo further biomarker testing before genetic testing.

Development of a clinical calculator to aid the identification of MODY in pediatric patients at the time of diabetes diagnosis.

Maturity Onset Diabetes of the Young (MODY) is a young-onset, monogenic form of diabetes without needing insulin treatment. Diagnostic testing is expensive. To aid decisions on who to test, we aimed to develop a MODY probability calculator for paediatric cases at the time of diabetes diagnosis, when the existing "MODY calculator" cannot be used. Firth logistic regression models were developed on data from 3541 paediatric patients from the Swedish 'Better Diabetes Diagnosis' (BDD) population study (n = 46 (1.3%) MODY (HNF1A, HNF4A, GCK)). Model performance was compared to using islet autoantibody testing. HbA1c, parent with diabetes, and absence of polyuria were significant independent predictors of MODY. The model showed excellent discrimination (c-statistic = 0.963) and calibrated well (Brier score = 0.01). MODY probability > 1.3% (ie. above background prevalence) had similar performance to being negative for all 3 antibodies (positive predictive value (PPV) = 10% v 11% respectively i.e. ~ 1 in 10 positive test rate). Probability > 1.3% and negative for 3 islet autoantibodies narrowed down to 4% of the cohort, and detected 96% of MODY cases (PPV = 31%). This MODY calculator for paediatric patients at time of diabetes diagnosis will help target genetic testing to those most likely to benefit, to get the right diagnosis.

Rare variant associations with birth weight identify genes involved in adipose tissue regulation, placental function and insulin-like growth factor signalling.

Investigating the genetic factors influencing human birth weight may lead to biological insights into fetal growth and long-term health. Genome-wide association studies of birth weight have highlighted associated variants in more than 200 regions of the genome, but the causal genes are mostly unknown. Rare genetic variants with robust evidence of association are more likely to point to causal genes, but to date, only a few rare variants are known to influence birth weight. We aimed to identify genes that harbour rare variants that impact birth weight when carried by either the fetus or the mother, by analysing whole exome sequence data in UK Biobank participants. We annotated rare (minor allele frequency <0.1%) protein-truncating or high impact missense variants on whole exome sequence data in up to 234,675 participants with data on their own birth weight (fetal variants), and up to 181,883 mothers who reported the birth weight of their first child (maternal variants). Variants within each gene were collapsed to perform gene burden tests and for each associated gene, we compared the observed fetal and maternal effects. We identified 8 genes with evidence of rare fetal variant effects on birth weight, of which 2 also showed maternal effects. One additional gene showed evidence of maternal effects only. We observed 10/11 directionally concordant associations in an independent sample of up to 45,622 individuals (sign test P=0.01). Of the genes identified, IGF1R and PAPPA2 (fetal and maternal-acting) have known roles in insulin-like growth factor bioavailability and signalling. PPARG, INHBE and ACVR1C (all fetal-acting) have known roles in adipose tissue regulation and rare variants in the latter two also showed associations with favourable adiposity patterns in adults. We highlight the dual role of PPARG in both adipocyte differentiation and placental angiogenesis. NOS3, NRK, and ADAMTS8 (fetal and maternal-acting) have been implicated in both placental function and hypertension. Analysis of rare coding variants has identified regulators of fetal adipose tissue and fetoplacental angiogenesis as determinants of birth weight, as well as further evidence for the role of insulin-like growth factors.

Galectin-4 Antimicrobial Activity Primarily Occurs Through its C-Terminal Domain.

Although immune tolerance evolved to reduce reactivity with self, it creates a gap in the adaptive immune response against microbes that decorate themselves in self-like antigens. This is particularly apparent with carbohydrate-based blood group antigens, wherein microbes can envelope themselves in blood group structures similar to human cells. In this study, we demonstrate that the innate immune lectin, galectin-4 (Gal-4), exhibits strain-specific binding and killing behavior towards microbes that display blood group-like antigens. Examination of binding preferences using a combination of microarrays populated with ABO(H) glycans and a variety of microbial strains, including those that express blood group-like antigens, demonstrated that Gal-4 binds mammalian and microbial antigens that have features of blood group and mammalian-like structures. Although Gal-4 was thought to exist as a monomer that achieves functional bivalency through its two linked carbohydrate recognition domains, our data demonstrate that Gal-4 forms dimers and that differences in the intrinsic ability of each domain to dimerize likely influences binding affinity. While each Gal-4 domain exhibited blood group-binding activity, the C-terminal domain (Gal-4C) exhibited dimeric properties, while the N-terminal domain (Gal-4N) failed to similarly display dimeric activity. Gal-4C not only exhibited the ability to dimerize but also possessed higher affinity toward ABO(H) blood group antigens and microbes expressing glycans with blood group-like features. Furthermore, when compared to Gal-4N, Gal-4C exhibited more potent antimicrobial activity. Even in the context of the full-length protein, where Gal-4N is functionally bivalent by virtue of Gal-4C dimerization, Gal-4C continued to display higher antimicrobial activity. These results demonstrate that Gal-4 exists as a dimer and exhibits its antimicrobial activity primarily through its C-terminal domain. In doing so, these data provide important insight into key features of Gal-4 responsible for its innate immune activity against molecular mimicry.

Hyperglycaemia is a causal risk factor for upper limb pathologies.

BACKGROUND: Diabetes (regardless of type) and obesity are associated with a range of musculoskeletal disorders. The causal mechanisms driving these associations are unknown for many upper limb pathologies. We used genetic techniques to test the causal link between glycemia, obesity and musculoskeletal conditions. METHODS: In the UK Biobank's unrelated European cohort (N = 379 708) we performed mendelian randomisation (MR) analyses to test for a causal effect of long-term high glycaemia and adiposity on four musculoskeletal pathologies: frozen shoulder, Dupuytren's disease, carpal tunnel syndrome and trigger finger. We also performed single-gene MR using rare variants in the GCK gene. RESULTS: Using MR, we found evidence that long-term high glycaemia has a causal role in the aetiology of upper limb conditions. A 10-mmol/mol increase in genetically predicted haemoglobin A1C (HbA1c) was associated with frozen shoulder: odds ratio (OR) = 1.50 [95% confidence interval (CI), 1.20-1.88], Dupuytren's disease: OR = 1.17 (95% CI, 1.01-1.35), trigger finger: OR = 1.30 (95% CI, 1.09-1.55) and carpal tunnel syndrome: OR = 1.20 (95% CI, 1.09-1.33). Carriers of GCK mutations have increased odds of frozen shoulder: OR = 7.16 (95% CI, 2.93-17.51) and carpal tunnel syndrome: OR = 2.86 (95% CI, 1.50-5.44) but not Dupuytren's disease or trigger finger. We found evidence that an increase in genetically predicted body mass index (BMI) of 5 kg/m2 was associated with carpal tunnel syndrome: OR = 1.13 (95% CI, 1.10-1.16) and associated negatively with Dupuytren's disease: OR = 0.94 (95% CI, 0.90-0.98), but no evidence of association with frozen shoulder or trigger finger. Trigger finger (OR 1.96 (95% CI, 1.42-2.69) P = 3.6e-05) and carpal tunnel syndrome [OR 1.63 (95% CI, 1.36-1.95) P = 8.5e-08] are associated with genetically predicted unfavourable adiposity increase of one standard deviation of body fat. CONCLUSIONS: Our study consistently demonstrates a causal role of long-term high glycaemia in the aetiology of upper limb musculoskeletal conditions. Clinicians treating diabetes patients should be aware of these complications in clinic, specifically those managing the care of GCK mutation carriers. Upper limb musculoskeletal conditions should be considered diabetes complications.

Is Minimally Invasive Spinal Surgery Superior to Endoscopic Spine Surgery in Postoperative Radiologic Outcomes of Lumbar Spine Degenerative Disease? A Systematic Review.

BACKGROUND: Minimally invasive spinal surgery (ESS) are both well-established surgical techniques for lumbar spinal stenosis; however, there is limited literature comparing the efficacy of the two techniques with respect to radiologic decompression data. METHODS: In this review, PubMed, Google Scholar, and Scopus databases were systematically searched from inception until July 2022 for studies that reported the radiologic outcomes of endoscopic and minimally invasive approaches for decompressive spinal surgery, namely, the spinal canal area, neural foraminal area, and neural foraminal heights. RESULTS: Of the 378 articles initially retrieved using MeSH and keyword search, 9 studies reporting preoperative and postoperative spinal areas and foraminal areas and heights were finally included in our review. Of the total 581 patients, 391 (67.30%) underwent MISS and 190 (32.70%) underwent ESS. The weighted mean difference between the spinal canal diameter in pre- and postoperative conditions was 56.64 ± 7.11 and 79.52 ± 21.31 mm2 in the MISS and ESS groups, respectively. ESS was also associated with a higher mean difference in the foraminal area postoperatively (72 ± 1 vs. 35.81 ± 11.3 mm2 in the MISS and ESS groups, respectively), but it was comparable to MISS in terms of the foraminal height (0.32 ± 0.037 vs. 0.29 ± 0.03 cm in the MISS and endoscopic groups, respectively). CONCLUSIONS: Compared with MISS, ESS was associated with improved radiologic parameters, including spinal canal area and neural foraminal area in the lumbar spinal segments. Both techniques led to the same endpoint of neural decompression when starting with a more severe compression. However, the present data do not allow the correlation of the radiographic results with the related clinical outcomes.

Application of the model-informed drug development paradigm to datopotamab deruxtecan dose selection for late-stage development.

To replace the conventional maximum tolerated dose (MTD) approach, a paradigm for dose optimization and dose selection that relies on model-informed drug development (MIDD) approaches has been proposed in oncology. Here, we report our application of an MIDD approach during phase I to inform dose selection for the late-stage development of datopotamab deruxtecan (Dato-DXd). Dato-DXd is a TROP2-directed antibody-drug conjugate being developed for advanced/metastatic non-small cell lung cancer (NSCLC) and other tumors. Data on pharmacokinetics (PKs), efficacy, and safety in NSCLC were collected in the TROPION-PanTumor01 phase I dose-expansion and -escalation study over a wide dose range of 0.27-10 mg/kg administered every 3 weeks. Population PK and exposure-response analyses were performed iteratively at three data cutoffs to inform dose selection. The 6 mg/kg dose was identified as the optimal dose by the second data cutoff analysis and confirmed by the subsequent third data cutoff analysis. The 6 mg/kg dose was more tolerable (i.e., lower rates of interstitial lung disease, stomatitis, and mucosal inflammation) than the MTD (8 mg/kg) and was more efficacious than 4 mg/kg (simulated mean objective response rate: 23.8% vs. 18.6%; mean hazard ratio of progression-free survival: 0.74) - a candidate dose studied just below 6 mg/kg. Therefore, the 6 mg/kg dose was judged to afford the optimal benefit-risk balance. This case study demonstrated the utility of an MIDD approach for dose optimization and dose selection.

Penetrance and expressivity of mitochondrial variants in a large clinically unselected population.

Whole genome sequencing (WGS) from large clinically unselected cohorts provides a unique opportunity to assess the penetrance and expressivity of rare and/or known pathogenic mitochondrial variants in population. Using WGS from 179 862 clinically unselected individuals from the UK Biobank, we performed extensive single and rare variant aggregation association analyses of 15 881 mtDNA variants and 73 known pathogenic variants with 15 mitochondrial disease-relevant phenotypes. We identified 12 homoplasmic and one heteroplasmic variant (m.3243A>G) with genome-wide significant associations in our clinically unselected cohort. Heteroplasmic m.3243A>G (MAF = 0.0002, a known pathogenic variant) was associated with diabetes, deafness and heart failure and 12 homoplasmic variants increased aspartate aminotransferase levels including three low-frequency variants (MAF ~0.002 and beta~0.3 SD). Most pathogenic mitochondrial disease variants (n = 66/74) were rare in the population (<1:9000). Aggregated or single variant analysis of pathogenic variants showed low penetrance in unselected settings for the relevant phenotypes, except m.3243A>G. Multi-system disease risk and penetrance of diabetes, deafness and heart failure greatly increased with m.3243A>G level ≥ 10%. The odds ratio of these traits increased from 5.61, 12.3 and 10.1 to 25.1, 55.0 and 39.5, respectively. Diabetes risk with m.3243A>G was further influenced by type 2 diabetes genetic risk. Our study of mitochondrial variation in a large-unselected population identified novel associations and demonstrated that pathogenic mitochondrial variants have lower penetrance in clinically unselected settings. m.3243A>G was an exception at higher heteroplasmy showing a significant impact on health making it a good candidate for incidental reporting.

Outcomes of Patients with a Mechanical Heart Valve and Poor Anticoagulation Control on Warfarin.

BACKGROUND: Patients with a mechanical heart valve (MHV) require oral anticoagulation. Poor anticoagulation control is thought to be associated with adverse outcomes, but data are limited. OBJECTIVE: To assess the risks of clinical outcomes in patients with a MHV and poor anticoagulation control on warfarin. METHODS: We conducted a retrospective study of consecutive patients undergoing MHV implantation at a tertiary care center (2010-2019). Primary outcome was a composite of ischemic stroke, systemic embolism, or prosthetic valve thrombosis. Major bleeding and death were key secondary outcomes. We constructed multivariable regression models to assess the association between time in therapeutic range (TTR) on warfarin beyond 90 days after surgery with outcomes. RESULTS: We included 671 patients with a MHV (80.6% in aortic, 14.6% in mitral position; mean age 61 years, 30.3% female). Median follow-up was 4.9 years, mean TTR was 62.5% (14.5% TTR <40%, 24.6% TTR 40-60%, and 61.0% TTR >60%). Overall rates of the primary outcome, major bleeding, and death were 0.73, 1.41, and 1.44 per 100 patient-years. Corresponding rates for patients with TTR <40% were 1.31, 2.77, and 3.22 per 100 patient-years. In adjusted analyses, every 10% decrement in TTR was associated with a 31% increase in hazard for the primary outcome (hazard ratio [HR]: 1.31, 95% confidence interval [CI]: 1.13-1.52), 34% increase in major bleeding (HR: 1.34, 95% CI: 1.17-1.52), and 32% increase in death (HR: 1.32, 95% CI: 1.11-1.57). CONCLUSION: In contemporary patients with a MHV, poor anticoagulation control on warfarin was associated with increased risks of thrombotic events, bleeding, and death.

Tumor treating fields for the treatment of glioblastoma: Current understanding and future perspectives.

Background: This review focuses on the recently published evidence on tumor treating fields (TTFields) administered alone or in combination with locoregional and systemic options for treating glioblastoma (GBM) in the past ten years. The aim is to critically summarize the novelty and results obtained with this innovative tool, which is becoming part of the armamentarium of neurosurgeons and neuro-oncologists. Methods: A comprehensive search and analysis were conducted on pivotal studies published in the past ten years. Furthermore, all completed clinical trials, whose results were published on clinicaltrials.gov, were examined and included in the present review, encompassing both recurrent (r) and newly diagnosed (n) GBM. Finally, an additional examination of the ongoing clinical trials was also conducted. Results: Recent trials have shown promising results both in patients with nGBM and rGBM/progressive (rGBM), leading to Food and Drug Administration approval in selected patients and the Congress of Neurological Surgeons to include TTFields into current guidelines on the management of GBM (P100034/S001-029). Recently, different randomized trials have demonstrated promising results of TTFields in combination with standard treatment of n- and rGBM, especially when considering progression-free and overall survival, maintaining a low rate of mild to moderate adverse events. Conclusion: Optimal outcomes were obtained in nGBM and progressive disease. A possible future refinement of TTFields could significantly impact the treatment of rGBM and the actual standard of care for GBM, given the better safety profile and survival effects.

Genotype-stratified treatment for monogenic insulin resistance: a systematic review.

BACKGROUND: Monogenic insulin resistance (IR) includes lipodystrophy and disorders of insulin signalling. We sought to assess the effects of interventions in monogenic IR, stratified by genetic aetiology. METHODS: Systematic review using PubMed, MEDLINE and Embase (1 January 1987 to 23 June 2021). Studies reporting individual-level effects of pharmacologic and/or surgical interventions in monogenic IR were eligible. Individual data were extracted and duplicates were removed. Outcomes were analysed for each gene and intervention, and in aggregate for partial, generalised and all lipodystrophy. RESULTS: 10 non-randomised experimental studies, 8 case series, and 23 case reports meet inclusion criteria, all rated as having moderate or serious risk of bias. Metreleptin use is associated with the lowering of triglycerides and haemoglobin A1c (HbA1c) in all lipodystrophy (n = 111), partial (n = 71) and generalised lipodystrophy (n = 41), and in LMNA, PPARG, AGPAT2 or BSCL2 subgroups (n = 72,13,21 and 21 respectively). Body Mass Index (BMI) is lowered in partial and generalised lipodystrophy, and in LMNA or BSCL2, but not PPARG or AGPAT2 subgroups. Thiazolidinediones are associated with improved HbA1c and triglycerides in all lipodystrophy (n = 13), improved HbA1c in PPARG (n = 5), and improved triglycerides in LMNA (n = 7). In INSR-related IR, rhIGF-1, alone or with IGFBP3, is associated with improved HbA1c (n = 17). The small size or absence of other genotype-treatment combinations preclude firm conclusions. CONCLUSIONS: The evidence guiding genotype-specific treatment of monogenic IR is of low to very low quality. Metreleptin and Thiazolidinediones appear to improve metabolic markers in lipodystrophy, and rhIGF-1 appears to lower HbA1c in INSR-related IR. For other interventions, there is insufficient evidence to assess efficacy and risks in aggregated lipodystrophy or genetic subgroups.

The hormone insulin stimulates nutrient uptake from the bloodstream into tissues. In insulin resistance (IR), this action is blunted. Some rare gene alterations cause severe IR, diabetes that is difficult to control, and early complications. Many treatments have been suggested, but reliable evidence of their risks and benefits is sparse. We analysed all available reports describing treatment outcomes in severe IR. We found that the evidence is of low to very low quality overall. Injections of leptin, a hormone from fat tissue, or thiazolidinedione tablets that increase fat tissue both appear to improve diabetes control in people with reduced ability to make fat tissue. Injections of another treatment, insulin-like growth factor, appear to improve diabetes control in people with direct blockage of insulin action. There is a pressing need to improve evidence for treatment in these rare and severe conditions.

Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine.

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.

Insights into the genetics of menopausal vasomotor symptoms: genome-wide analyses of routinely-collected primary care health records.

BACKGROUND: Vasomotor symptoms (VMS) can often significantly impact women's quality of life at menopause. In vivo studies have shown that increased neurokinin B (NKB) / neurokinin 3 receptor (NK3R) signalling contributes to VMS, with previous genetic studies implicating the TACR3 gene locus that encodes NK3R. Large-scale genomic analyses offer the possibility of biological insights but few such studies have collected data on VMS, while proxy phenotypes such as hormone replacement therapy (HRT) use are likely to be affected by changes in clinical practice. We investigated the genetic basis of VMS by analysing routinely-collected health records. METHODS: We performed a GWAS of VMS derived from linked primary-care records and cross-sectional self-reported HRT use in up to 153,152 women from UK Biobank, a population-based cohort. In a subset of this cohort (n = 39,356), we analysed exome-sequencing data to test the association with VMS of rare deleterious genetic variants. Finally, we used Mendelian randomisation analysis to investigate the reasons for HRT use over time. RESULTS: Our GWAS of health-records derived VMS identified a genetic signal near TACR3 associated with a lower risk of VMS (OR=0.76 (95% CI 0.72,0.80) per A allele, P=3.7x10-27), which was consistent with previous studies, validating this approach. Conditional analyses demonstrated independence of genetic signals for puberty timing and VMS at the TACR3 locus, including a rare variant predicted to reduce functional NK3R levels that was associated with later menarche (P = 5 × 10-9) but showed no association with VMS (P = 0.6). Younger menopause age was causally-associated with greater HRT use before 2002 but not after. CONCLUSIONS: We provide support for TACR3 in the genetic basis of VMS but unexpectedly find that rare genomic variants predicted to lower NK3R levels did not modify VMS, despite the proven efficacy of NK3R antagonists. Using genomics we demonstrate changes in genetic associations with HRT use over time, arising from a change in clinical practice since the early 2000s, which is likely to reflect a switch from preventing post-menopausal complications in women with earlier menopause to primarily treating VMS. Our study demonstrates that integrating routinely-collected primary care health records and genomic data offers great potential for exploring the genetic basis of symptoms.

DSENet: Directional Signal Extraction Network for Hearing Improvement on Edge Devices.

In this paper, we propose a directional signal extraction network (DSENet). DSENet is a low-latency, real-time neural network that, given a reverberant mixture of signals captured by a microphone array, aims at extracting the reverberant signal whose source is located within a directional region of interest. If there are multiple sources situated within the directional region of interest, DSENet will aim at extracting a combination of their reverberant signals. As such, the formulation of DSENet circumvents the well-known crosstalk problem in beamforming while providing an alternative and perhaps more practical approach to other spatially constrained signal extraction methods proposed in the literature. DSENet is based on a computationally efficient and low-distortion linear model formulated in the time domain. As a result, an important application of our work is hearing improvement on edge devices. Simulation results show that DSENet outperforms oracle beamformers, as well as state-of-the-art in low-latency causal speech separation, while incurring a system latency of only 4 ms. Additionally, DSENet has been successfully deployed as a real-time application on a smartphone.

Incretin hormone responses to carbohydrate and protein/fat are preserved in adults with sulfonylurea-treated KCNJ11 neonatal diabetes.

The incretin hormones glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP), are thought to be the main drivers of insulin secretion in individuals with sulfonylurea (SU)-treated KCNJ11 permanent neonatal diabetes. The aim of this study was to assess for the first time the incretin hormone response to carbohydrate and protein/fat in adults with sulfonylurea-treated KCNJ11 permanent neonatal diabetes compared with that of controls without diabetes. Participants were given a breakfast high in carbohydrate and an isocaloric breakfast high in protein/fat on two different mornings. Incremental area under the curve and total area under the curve (0-240 minutes) for total GLP-1 and GIP were compared between groups, using non-parametric statistical methods. Post-meal GLP-1 and GIP secretion were similar in cases and controls, suggesting this process is adenosine triphosphate-sensitive potassium channel-independent. Future research will investigate whether treatments targeting the incretin pathway are effective in individuals with KCNJ11 permanent neonatal diabetes who do not have good glycemic control on sulfonylurea alone.