A Novel Role for FERM Domain-Containing Protein 3 (FRMD3) in CKD.

BACKGROUND: Currently there are limited methods to link disease severity and risk of disease progression in Chronic Kidney Disease (CKD). To better understand this potential relationship, we interrogated the renal transcriptomic profile of individuals with CKD with measures of CKD severity and identified FERM-domain containing protein 3 (FRMD3) as a candidate gene for follow-up study. METHODS: RNA-seq was used to profile the transcriptome of CKD biopsies from the North Dublin Renal BioBank the results of which were correlated with clinical parameters. The potential function of FRMD3 was explored by interrogating the FRMD3 interactome and assessing the impact of lentiviral mediated FRMD3 knock down on human renal proximal tubule epithelial cells by assessing cell viability, metabolic activity, and structural markers. RESULTS: We identified a subset of 93 genes which are significantly correlated with estimated glomerular filtration rate and percentage tubulointerstitial fibrosis at time of biopsy and with CKD progression 5 years post-biopsy. These results were validated against transcriptomic data from an external cohort of 432 nephrectomy samples. One of the top-ranking genes from this subset, FRMD3, has previously been associated with the risk of developing diabetic kidney disease. Interrogating the interactome of FRMD3 in tubule epithelial cells revealed interactions with cytoskeletal components of cell-cell junctions. Knockdown of FRMD3 expression in tubule epithelial cells resulted in increased pro-apoptotic activity within the cells as well as dysregulation of E-Cadherin. CONCLUSIONS: We have identified a panel of kidney-specific transcripts correlated with severity and progression of kidney disease, and from this have identified a possible role for FRMD3 in tubule cell structure and health.

Rare variant analyses in 51,256 type 2 diabetes cases and 370,487 controls reveal the pathogenicity spectrum of monogenic diabetes genes.

Type 2 diabetes (T2D) genome-wide association studies (GWASs) often overlook rare variants as a result of previous imputation panels' limitations and scarce whole-genome sequencing (WGS) data. We used TOPMed imputation and WGS to conduct the largest T2D GWAS meta-analysis involving 51,256 cases of T2D and 370,487 controls, targeting variants with a minor allele frequency as low as 5 × 10-5. We identified 12 new variants, including a rare African/African American-enriched enhancer variant near the LEP gene (rs147287548), associated with fourfold increased T2D risk. We also identified a rare missense variant in HNF4A (p.Arg114Trp), associated with eightfold increased T2D risk, previously reported in maturity-onset diabetes of the young with reduced penetrance, but observed here in a T2D GWAS. We further leveraged these data to analyze 1,634 ClinVar variants in 22 genes related to monogenic diabetes, identifying two additional rare variants in HNF1A and GCK associated with fivefold and eightfold increased T2D risk, respectively, the effects of which were modified by the individual's polygenic risk score. For 21% of the variants with conflicting interpretations or uncertain significance in ClinVar, we provided support of being benign based on their lack of association with T2D. Our work provides a framework for using rare variant GWASs to identify large-effect variants and assess variant pathogenicity in monogenic diabetes genes.

Identification of Immune Checkpoint Inhibitor-Induced Diabetes.

Importance: Immune checkpoint inhibitors (ICIs) have revolutionized cancer care; however, accompanying immune-related adverse events (irAEs) confer substantial morbidity and occasional mortality. Life-threatening irAEs may require permanent cessation of ICI, even in patients with positive tumor response. Therefore, it is imperative to comprehensively define the spectrum of irAEs to aid individualized decision-making around the initiation of ICI therapy. Objective: To define incidence, risk factors, and clinical spectrum of an irreversible and life-threatening irAE: ICI-induced diabetes. Design, Setting, and Participants: This cohort study, conducted at an academic integrated health care system examined 14 328 adult patients treated with ICIs, including 64 patients who developed ICI-induced diabetes, from July 2010 to January 2022. The data were analyzed from 2022 to 2023. Cases of ICI-induced diabetes were manually confirmed; detailed clinical phenotyping was performed at diagnosis and 1-year follow-up. For 862 patients, genotyping data were available, and polygenic risk for type 1 diabetes was determined. Main Outcomes and Measures: For ICI-induced diabetes cases and controls, demographic characteristics, comorbidities, tumor category, and ICI category were compared. Among ICI-induced diabetes cases, markers of glycemic physiology were examined at diagnosis and 1-year follow-up. For patients with available genotyping, a published type 1 diabetes polygenic score (T1D GRS2) was calculated. Results: Of 14 328 participants, 6571 (45.9%) were women, and the median (range) age was 66 (8-106) years. The prevalence of ICI-induced diabetes among ICI-treated patients was 0.45% (64 of 14 328), with an incidence of 124.8 per 100 000 person-years. Preexisting type 2 diabetes (odds ratio [OR], 5.91; 95% CI, 3.34-10.45) and treatment with combination ICI (OR, 2.57; 95% CI, 1.44-4.59) were significant clinical risk factors of ICI-induced diabetes. T1D GRS2 was associated with ICI-induced diabetes risk, with an OR of 4.4 (95% CI, 1.8-10.5) for patients in the top decile of T1D GRS2, demonstrating a genetic association between spontaneous autoimmunity and irAEs. Patients with ICI-induced diabetes were in 3 distinct phenotypic categories based on autoantibodies and residual pancreatic function, with varying severity of initial presentation. Conclusions and Relevance: The results of this analysis of 14 328 ICI-treated patients followed up from ICI initiation determined the incidence, risk factors and clinical spectrum of ICI-induced diabetes. Widespread implementation of this approach across organ-specific irAEs may enhance diagnosis and management of these conditions, and this becomes especially pertinent as ICI treatment rapidly expands to treat a wide spectrum of cancers and is used at earlier stages of treatment.

Hemoglobin A1c Genetics and Disparities in Risk of Diabetic Retinopathy in Individuals of Genetically Inferred African American/African British and European Ancestries.

OBJECTIVE: Individuals with diabetes who carry genetic variants that lower hemoglobin A1c (HbA1c) independently of glycemia may have higher real, but undetected, hyperglycemia compared with those without these variants despite achieving similar HbA1c targets, potentially placing them at greater risk for diabetes-related complications. We sought to determine whether these genetic variants, aggregated in a polygenic score, and the large-effect African ancestry-specific missense variant in G6PD (rs1050828) that lower HbA1c were associated with higher retinopathy risk. RESEARCH DESIGN AND METHODS: Using data from 29,828 type 2 diabetes cases of genetically inferred African American/African British and European ancestries, we calculated ancestry-specific nonglycemic HbA1c polygenic scores (ngA1cPS) composed of 122 variants associated with HbA1c at genome-wide significance, but not with glucose. We tested the association of the ngA1cPS and the G6PD variant with retinopathy, adjusting for measured HbA1c and retinopathy risk factors. RESULTS: Participants in the bottom quintile of the ngA1cPS showed between 20% and 50% higher retinopathy prevalence, compared with those above this quintile, despite similar levels of measured HbA1c. The adjusted meta-analytic odds ratio for the bottom quintile was 1.31 (95% CI 1.0, 1.73; P = 0.05) in African ancestry and 1.31 (95% CI 1.15, 1.50; P = 6.5 × 10-5) in European ancestry. Among individuals of African ancestry with HbA1c below 7%, retinopathy prevalence was higher in individuals below, compared with above, the 50th percentile of the ngA1cPS regardless of sex or G6PD carrier status. CONCLUSIONS: Genetic effects need to be considered to personalize HbA1c targets and improve outcomes of people with diabetes from diverse ancestries.

Variables de la condición física, predictores de los niveles de fragilidad en personas adultas mayores entre 60 y 64 años de Sabaneta, Antioquia / Physical condition variables, predictors of frailty levels in older adults between 60 And 64 Years Of Age from Sabaneta, Antioquia / Variáveis de condição física, preditores dos níveis de fragilidade em idosos entre 60 e 64 anos de Idade de Sabaneta, Antioquia

Resumen Introducción: El estudio examina la prevalencia y los factores asociados con la fragilidad en personas adultas mayores, destacando la escasez de investigaciones en América Latina y la necesidad de un enfoque integral de atención de salud para abordar esta creciente preocupación epidemiológica. Propósito: El objetivo de este estudio descriptivo transversal correlacional con fase multivariada fue determinar las variables de la condición física que predicen la fragilidad en las personas adultas mayores de entre 60 y 64 años del municipio de Sabaneta, Antioquia durante el primer semestre del 2021 con 125 personas sanas. Metodología: Para las variables cualitativas, el sexo y la fragilidad se relacionan de forma estadísticamente significativa. En las variables cuantitativas, "fuerza muscular de las piernas", "fuerza muscular de los brazos derecha e izquierda", "agilidad de marcha" y "resistencia aeróbica en marcha" se asociaron de forma estadísticamente significativa con la fragilidad. Resultados: En el modelo de regresión lineal, se evidenció que la variable "agilidad de la marcha" fue la predictora de fragilidad en la persona adulta mayor. Prevalencia de fragilidad en el 85.6 % de los casos, de los cuales el 48 % presentan condiciones de prefragilidad. Variables como la fuerza de los brazos, fuerza de las piernas, agilidad de la marcha y resistencia aeróbica en la marcha fueron estadísticamente significativas. Conclusiones: La agilidad de la marcha es un factor predictivo de riesgo de fragilidad en la persona adulta mayor. Las personas con disminución en la agilidad de la marcha tienen un 26 % más de probabilidades de ser frágiles.

Abstract Introduction: The study examines the prevalence and factors associated with frailty in older adults, highlighting the scarcity of research in Latin America and the need for a comprehensive healthcare approach to address this growing epidemiological concern. Purpose: The aim of this cross-sectional correlational descriptive study with a multivariate phase was to determine the physical fitness variables that predict frailty in older adults aged 60-64 years. It was conducted in Sabaneta, Antioquia during the first semester of 2021 with 125 healthy individuals aged 60-64 years. Methodology: For the qualitative variables, sex and frailty were statistically significantly related. For the quantitative variables, "leg strength", "right and left arm strength", "walking agility", and "aerobic walking endurance" were significant in relation to frailty. Results: In the linear regression model, it was found that the variable "walking agility" was the predictor of frailty in older adults. Prevalence of frail conditions in 85.6% of the cases, of which 48% had pre-frail conditions. Variables such as arm strength, leg strength, walking agility, and aerobic walking endurance were statistically significant. Conclusions: Walking agility is a predictive risk factor for frailty in older adults. Individuals with decreased walking agility have a 26% higher probability of being frail.

Resumo Introdução: O estudo examina a prevalência e os fatores associados à fragilidade em idosos, destacando a escassez de pesquisas na América Latina e a necessidade de uma abordagem abrangente de cuidados de saúde para enfrentar essa preocupação epidemiológica crescente. Objetivo: O objetivo deste estudo descritivo correlacional transversal com uma fase multivariada foi determinar as variáveis de aptidão física que predizem a fragilidade em idosos de 60 a 64 anos. Foi realizado em Sabaneta, Antioquia, durante o primeiro semestre de 2021 com 125 indivíduos saudáveis com idades entre 60 e 64 anos. Metodologia: Para as variáveis qualitativas, sexo e fragilidade estavam relacionados estatisticamente de forma significativa. Para as variáveis quantitativas, "força das pernas", "força dos braços direito e esquerdo", "agilidade ao caminhar" e "endurance aeróbico ao caminhar" foram significativas em relação à fragilidade. Resultados: No modelo de regressão linear, constatou-se que a variável "agilidade ao caminhar" foi o preditor de fragilidade em idosos. Prevalência de condições frágeis em 85.6% dos casos, dos quais 48% tinham condições pré-frágeis. Variáveis como força dos braços, força das pernas, agilidade ao caminhar e endurance aeróbico ao caminhar foram estatisticamente significativas. Conclusões: A agilidade ao caminhar é um fator de risco preditivo para fragilidade em idosos. Indivíduos com agilidade ao caminhar diminuída têm uma probabilidade 26% maior de serem frágeis.

Increased Genetic Risk for ß-Cell Failure Is Associated With ß-Cell Function Decline in People With Prediabetes.

Partitioned polygenic scores (pPS) have been developed to capture pathophysiologic processes underlying type 2 diabetes (T2D). We investigated the association of T2D pPS with diabetes-related traits and T2D incidence in the Diabetes Prevention Program. We generated five T2D pPS (ß-cell, proinsulin, liver/lipid, obesity, lipodystrophy) in 2,647 participants randomized to intensive lifestyle, metformin, or placebo arms. Associations were tested with general linear models and Cox regression with adjustment for age, sex, and principal components. Sensitivity analyses included adjustment for BMI. Higher ß-cell pPS was associated with lower insulinogenic index and corrected insulin response at 1-year follow-up with adjustment for baseline measures (effect per pPS SD -0.04, P = 9.6 × 10-7, and -8.45 µU/mg, P = 5.6 × 10-6, respectively) and with increased diabetes incidence with adjustment for BMI at nominal significance (hazard ratio 1.10 per SD, P = 0.035). The liver/lipid pPS was associated with reduced 1-year baseline-adjusted triglyceride levels (effect per SD -4.37, P = 0.001). There was no significant interaction between T2D pPS and randomized groups. The remaining pPS were associated with baseline measures only. We conclude that despite interventions for diabetes prevention, participants with a high genetic burden of the ß-cell cluster pPS had worsening in measures of ß-cell function.

Diabetes subgroups and sociodemographic inequalities in Mexico: a cross-sectional analysis of nationally representative surveys from 2016 to 2022.

Background: Differences in the prevalence of four diabetes subgroups have been reported in Mexico compared to other populations, but factors that may contribute to these differences are poorly understood. Here, we estimate the prevalence of diabetes subgroups in Mexico and evaluate their correlates with indicators of social disadvantage using data from national representative surveys. Methods: We analyzed serial, cross-sectional Mexican National Health and Nutrition Surveys spanning 2016, 2018, 2020, 2021, and 2022, including 23,354 adults (>20 years). Diabetes subgroups (obesity-related [MOD], severe insulin-deficient [SIDD], severe insulin-resistant [SIRD], and age-related [MARD]) were classified using self-normalizing neural networks based on a previously validated algorithm. We used the density-independent social lag index (DISLI) as a proxy of state-level social disadvantage. Findings: We identified 4204 adults (median age: 57, IQR: 47-66, women: 64%) living with diabetes, yielding a pooled prevalence of 16.04% [95% CI: 14.92-17.17]. When stratified by diabetes subgroup, prevalence was 6.62% (5.69-7.55) for SIDD, 5.25% (4.52-5.97) for MOD, 2.39% (1.95-2.83) for MARD, and 1.27% (1.00-1.54) for SIRD. SIDD and MOD clustered in Southern Mexico, whereas MARD and SIRD clustered in Northern Mexico and Mexico City. Each standard deviation increase in DISLI was associated with higher odds of SIDD (OR: 1.12, 95% CI: 1.06-1.12) and lower odds of MOD (OR: 0.93, 0.88-0.99). Speaking an indigenous language was associated with higher odds of SIDD (OR: 1.35, 1.16-1.57) and lower odds of MARD (OR 0.58, 0.45-0.74). Interpretation: Diabetes prevalence in Mexico is rising in the context of regional and sociodemographic inequalities across distinct diabetes subgroups. SIDD is a subgroup of concern that may be associated with inadequate diabetes management, mainly in marginalized states. Funding: This research was supported by Instituto Nacional de Geriatría in Mexico.

Placental IGFBP1 levels during early pregnancy and the risk of insulin resistance and gestational diabetes.

Reduced insulin sensitivity (insulin resistance) is a hallmark of normal physiology in late pregnancy and also underlies gestational diabetes mellitus (GDM). We conducted transcriptomic profiling of 434 human placentas and identified a positive association between insulin-like growth factor binding protein 1 gene (IGFBP1) expression in the placenta and insulin sensitivity at ~26 weeks gestation. Circulating IGFBP1 protein levels rose over the course of pregnancy and declined postpartum, which, together with high gene expression levels in our placenta samples, suggests a placental or decidual source. Higher circulating IGFBP1 levels were associated with greater insulin sensitivity (lesser insulin resistance) at ~26 weeks gestation in the same cohort and in two additional pregnancy cohorts. In addition, low circulating IGFBP1 levels in early pregnancy predicted subsequent GDM diagnosis in two cohorts of pregnant women. These results implicate IGFBP1 in the glycemic physiology of pregnancy and suggest a role for placental IGFBP1 deficiency in GDM pathogenesis.

Polygenic scores for longitudinal prediction of incident type 2 diabetes in an ancestrally and medically diverse primary care physician network: a patient cohort study.

BACKGROUND: The clinical utility of genetic information for type 2 diabetes (T2D) prediction with polygenic scores (PGS) in ancestrally diverse, real-world US healthcare systems is unclear, especially for those at low clinical phenotypic risk for T2D. METHODS: We tested the association of PGS with T2D incidence in patients followed within a primary care practice network over 16 years in four hypothetical scenarios that varied by clinical data availability (N = 14,712): (1) age and sex; (2) age, sex, body mass index (BMI), systolic blood pressure, and family history of T2D; (3) all variables in (2) and random glucose; and (4) all variables in (3), HDL, total cholesterol, and triglycerides, combined in a clinical risk score (CRS). To determine whether genetic effects differed by baseline clinical risk, we tested for interaction with the CRS. RESULTS: PGS was associated with incident T2D in all models. Adjusting for age and sex only, the Hazard Ratio (HR) per PGS standard deviation (SD) was 1.76 (95% CI 1.68, 1.84) and the HR of top 5% of PGS vs interquartile range (IQR) was 2.80 (2.39, 3.28). Adjusting for the CRS, the HR per SD was 1.48 (1.40, 1.57) and HR of the top 5% of PGS vs IQR was 2.09 (1.72, 2.55). Genetic effects differed by baseline clinical risk ((PGS-CRS interaction p = 0.05; CRS below the median: HR 1.60 (1.43, 1.79); CRS above the median: HR 1.45 (1.35, 1.55)). CONCLUSIONS: Genetic information can help identify high-risk patients even among those perceived to be low risk in a clinical evaluation.

Multi-ancestry polygenic mechanisms of type 2 diabetes.

Type 2 diabetes (T2D) is a multifactorial disease with substantial genetic risk, for which the underlying biological mechanisms are not fully understood. In this study, we identified multi-ancestry T2D genetic clusters by analyzing genetic data from diverse populations in 37 published T2D genome-wide association studies representing more than 1.4 million individuals. We implemented soft clustering with 650 T2D-associated genetic variants and 110 T2D-related traits, capturing known and novel T2D clusters with distinct cardiometabolic trait associations across two independent biobanks representing diverse genetic ancestral populations (African, n = 21,906; Admixed American, n = 14,410; East Asian, n =2,422; European, n = 90,093; and South Asian, n = 1,262). The 12 genetic clusters were enriched for specific single-cell regulatory regions. Several of the polygenic scores derived from the clusters differed in distribution among ancestry groups, including a significantly higher proportion of lipodystrophy-related polygenic risk in East Asian ancestry. T2D risk was equivalent at a body mass index (BMI) of 30 kg m-2 in the European subpopulation and 24.2 (22.9-25.5) kg m-2 in the East Asian subpopulation; after adjusting for cluster-specific genetic risk, the equivalent BMI threshold increased to 28.5 (27.1-30.0) kg m-2 in the East Asian group. Thus, these multi-ancestry T2D genetic clusters encompass a broader range of biological mechanisms and provide preliminary insights to explain ancestry-associated differences in T2D risk profiles.

Genetic architecture and biology of youth-onset type 2 diabetes.

The prevalence of youth-onset type 2 diabetes (T2D) and childhood obesity has been rising steadily1, producing a growing public health concern1 that disproportionately affects minority groups2. The genetic basis of youth-onset T2D and its relationship to other forms of diabetes are unclear3. Here we report a detailed genetic characterization of youth-onset T2D by analysing exome sequences and common variant associations for 3,005 individuals with youth-onset T2D and 9,777 adult control participants matched for ancestry, including both males and females. We identify monogenic diabetes variants in 2.4% of individuals and three exome-wide significant (P < 2.6 × 10-6) gene-level associations (HNF1A, MC4R, ATXN2L). Furthermore, we report rare variant association enrichments within 25 gene sets related to obesity, monogenic diabetes and ß-cell function. Many youth-onset T2D associations are shared with adult-onset T2D, but genetic risk factors of all frequencies-and rare variants in particular-are enriched within youth-onset T2D cases (5.0-fold increase in the rare variant and 3.4-fold increase in common variant genetic liability relative to adult-onset cases). The clinical presentation of participants with youth-onset T2D is influenced in part by the frequency of genetic risk factors within each individual. These findings portray youth-onset T2D as a heterogeneous disease situated on a spectrum between monogenic diabetes and adult-onset T2D.

Higher Maternal Body Mass Index Is Associated With Lower Placental Expression of EPYC: A Genome-Wide Transcriptomic Study.

CONTEXT: Elevated body mass index (BMI) in pregnancy is associated with adverse maternal and fetal outcomes. The placental transcriptome may elucidate molecular mechanisms underlying these associations. OBJECTIVE: We examined the association of first-trimester maternal BMI with the placental transcriptome in the Gen3G prospective cohort. METHODS: We enrolled participants at 5 to 16 weeks of gestation and measured height and weight. We collected placenta samples at delivery. We performed whole-genome RNA sequencing using Illumina HiSeq 4000 and aligned RNA sequences based on the GTEx v8 pipeline. We conducted differential gene expression analysis of over 15 000 genes from 450 placental samples and reported the change in normalized gene expression per 1-unit increase in log2 BMI (kg/m2) as a continuous variable using Limma Voom. We adjusted models for maternal age, fetal sex, gestational age at delivery, gravidity, and surrogate variables accounting for technical variability. We compared participants with BMI of 18.5 to 24.9 mg/kg2 (N = 257) vs those with obesity (BMI ≥30 kg/m2, N = 82) in secondary analyses. RESULTS: Participants' mean ± SD age was 28.2 ± 4.4 years and BMI was 25.4 ± 5.5 kg/m2 in early pregnancy. Higher maternal BMI was associated with lower placental expression of EPYC (slope = -1.94, false discovery rate [FDR]-adjusted P = 7.3 × 10-6 for continuous BMI; log2 fold change = -1.35, FDR-adjusted P = 3.4 × 10-3 for BMI ≥30 vs BMI 18.5-24.9 kg/m2) and with higher placental expression of IGFBP6, CHRDL1, and CXCL13 after adjustment for covariates and accounting for multiple testing (FDR < 0.05). CONCLUSION: Our genome-wide transcriptomic study revealed novel genes potentially implicated in placental biologic response to higher maternal BMI in early pregnancy.

Placental RNA sequencing implicates IGFBP1 in insulin sensitivity during pregnancy and in gestational diabetes.

Reduced insulin sensitivity (or greater insulin resistance) is a hallmark of normal physiology in late pregnancy and also underlies gestational diabetes mellitus (GDM) pathophysiology. We conducted transcriptomic profiling of 434 human placentas and identified a strong positive association between insulin-like growth factor binding protein 1 gene (IGFBP1) expression in the placenta and insulin sensitivity at ~ 26 weeks' gestation. Circulating IGFBP1 protein levels rose over the course of pregnancy and declined postpartum, which together with high placental gene expression levels, suggests a placental source. Higher circulating IGFBP1 levels were strongly associated with greater insulin sensitivity (lesser insulin resistance) at ~ 26 weeks' gestation in the same cohort and two additional pregnancy cohorts. In addition, low circulating IGFBP1 levels in early pregnancy predicted subsequent GDM diagnosis in two cohorts. These results implicate IGFBP1 in the glycemic physiology of pregnancy and suggest a role for placental IGFBP1 deficiency in GDM pathogenesis.

A Type 1 Diabetes Polygenic Score Is Not Associated With Prevalent Type 2 Diabetes in Large Population Studies.

Context: Both type 1 diabetes (T1D) and type 2 diabetes (T2D) have significant genetic contributions to risk and understanding their overlap can offer clinical insight. Objective: We examined whether a T1D polygenic score (PS) was associated with a diagnosis of T2D in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium. Methods: We constructed a T1D PS using 79 known single nucleotide polymorphisms associated with T1D risk. We analyzed 13 792 T2D cases and 14 169 controls from CHARGE cohorts to determine the association between the T1D PS and T2D prevalence. We validated findings in an independent sample of 2256 T2D cases and 27 052 controls from the Mass General Brigham Biobank (MGB Biobank). As secondary analyses in 5228 T2D cases from CHARGE, we used multivariable regression models to assess the association of the T1D PS with clinical outcomes associated with T1D. Results: The T1D PS was not associated with T2D both in CHARGE (P = .15) and in the MGB Biobank (P = .87). The partitioned human leukocyte antigens only PS was associated with T2D in CHARGE (OR 1.02 per 1 SD increase in PS, 95% CI 1.01-1.03, P = .006) but not in the MGB Biobank. The T1D PS was weakly associated with insulin use (OR 1.007, 95% CI 1.001-1.012, P = .03) in CHARGE T2D cases but not with other outcomes. Conclusion: In large biobank samples, a common variant PS for T1D was not consistently associated with prevalent T2D. However, possible heterogeneity in T2D cannot be ruled out and future studies are needed do subphenotyping.

Precision medicine of obesity as an integral part of type 2 diabetes management - past, present, and future.

Obesity is a complex and heterogeneous condition that leads to various metabolic complications, including type 2 diabetes. Unfortunately, for some, treatment options to date for obesity are insufficient, with many people not reaching sustained weight loss or having improvements in metabolic health. In this Review, we discuss advances in the genetics of obesity from the past decade-with emphasis on developments from the past 5 years-with a focus on metabolic consequences, and their potential implications for precision management of the disease. We also provide an overview of the potential role of genetics in guiding weight loss strategies. Finally, we propose a vision for the future of precision obesity management that includes developing an obesity-centred multidisease management algorithm that targets both obesity and its comorbidities. However, further collaborative efforts and research are necessary to fully realise its potential and improve metabolic health outcomes.

Precision medicine for cardiometabolic disease: a framework for clinical translation.

Cardiometabolic disease is a major threat to global health. Precision medicine has great potential to help to reduce the burden of this common and complex disease cluster, and to enhance contemporary evidence-based medicine. Its key pillars are diagnostics; prediction (of the primary disease); prevention (of the primary disease); prognosis (prediction of complications of the primary disease); treatment (of the primary disease or its complications); and monitoring (of risk exposure, treatment response, and disease progression or remission). To contextualise precision medicine in both research and clinical settings, and to encourage the successful translation of discovery science into clinical practice, in this Series paper we outline a model (the EPPOS model) that builds on contemporary evidence-based approaches; includes precision medicine that improves disease-related predictions by stratifying a cohort into subgroups of similar characteristics, or using participants' characteristics to model treatment outcomes directly; includes personalised medicine with the use of a person's data to objectively gauge the efficacy, safety, and tolerability of therapeutics; and subjectively tailors medical decisions to the individual's preferences, circumstances, and capabilities. Precision medicine requires a well functioning system comprised of multiple stakeholders, including health-care recipients, health-care providers, scientists, health economists, funders, innovators of medicines and technologies, regulators, and policy makers. Powerful computing infrastructures supporting appropriate analysis of large-scale, well curated, and accessible health databases that contain high-quality, multidimensional, time-series data will be required; so too will prospective cohort studies in diverse populations designed to generate novel hypotheses, and clinical trials designed to test them. Here, we carefully consider these topics and describe a framework for the integration of precision medicine in cardiometabolic disease.

Multi-ancestry Polygenic Mechanisms of Type 2 Diabetes Elucidate Disease Processes and Clinical Heterogeneity.

We identified genetic subtypes of type 2 diabetes (T2D) by analyzing genetic data from diverse groups, including non-European populations. We implemented soft clustering with 650 T2D-associated genetic variants, capturing known and novel T2D subtypes with distinct cardiometabolic trait associations. The twelve genetic clusters were distinctively enriched for single-cell regulatory regions. Polygenic scores derived from the clusters differed in distribution between ancestry groups, including a significantly higher proportion of lipodystrophy-related polygenic risk in East Asian ancestry. T2D risk was equivalent at a BMI of 30 kg/m2 in the European subpopulation and 24.2 (22.9-25.5) kg/m2 in the East Asian subpopulation; after adjusting for cluster-specific genetic risk, the equivalent BMI threshold increased to 28.5 (27.1-30.0) kg/m2 in the East Asian group, explaining about 75% of the difference in BMI thresholds. Thus, these multi-ancestry T2D genetic subtypes encompass a broader range of biological mechanisms and help explain ancestry-associated differences in T2D risk profiles.