Space research to explore novel biochemical insights on Earth.

Travel to space has overcome unprecedent technological challenges and this has resulted in transfer of these technological results on Earth to better our lives. Health technology, medical devices, and research advancements in human biology are the first beneficiaries of this transfer. The real breakthrough came with the International Space Station, which endorsed multidisciplinary international scientific collaborations and boosted the research on pathophysiological adaptation of astronauts to life on space. These studies evidenced that life in space appeared to have exposed the astronauts to an accelerated aging-related pathophysiological dysregulation across multiple systems. In this review we emphasize the interaction between several biomarkers and their alteration in concentrations/expression/function by space stress factors. These altered interactions, suggest that different biochemical and hormonal factors, and cell signals, contribute to a complex network of pathophysiological mechanisms, orchestrating the homeostatic dysregulation of various organs/metabolic pathways. The main effects of space travel on altering cell organelles biology, ultrastructure, and cross-talk, have been observed in cell aging as well as in the disruption of metabolic pathways, which are also the causal factor of rare inherited metabolic disorders, one of the major pediatric health issue. The pathophysiologic breakthrough from space research could allow the development of precision health both on Earth and Space by promoting the validation of improved biomarker-based risk scores and the exploration of new pathophysiologic hypotheses and therapeutic targets. Nonstandard abbreviations: International Space Station (ISS), Artificial Intelligence (AI), European Space Agency (ESA), National Aeronautics and Space Agency (NASA), Low Earth Orbit (LEO), high sensitive troponin (hs-cTn), high sensitive troponin I (hs-cTn I), high sensitive troponin T, Brain Natriuretic Peptide (BNP), N terminal Brain Natriuretic Peptide (NT-BNP), cardiovascular disease (CVD), parathyroid hormone (PTH), urinary hydroxyproline (uHP), urinary C- and N-terminal telopeptides (uCTX and uNTX), pyridinoline (PYD), deoxypyridinoline (DPD), half-time (HF), serum Bone Alkaline Phosphatase (sBSAP), serum Alkaline Phosphatase (sAP), Carboxy-terminal Propeptide of Type 1 Procollagen (P1CP), serum Osteocalcin (sOC)), advanced glycation end products (AGEs), glycated hemoglobin A1c (HbA1c), Insulin-like growth factor 1 (IGF1), Growth Hormone (GH), amino acid (AA), ß-hydroxy-ß methyl butyrate (HMB), maple syrup urine disease (MSUD), non-communicable diseases (NCDs).

Household food insecurity and associations with hemoglobin A1c and acute diabetes-related complications in youth and young adults with type 1 diabetes: The SEARCH for Diabetes in Youth study.

AIMS: To examine, among youth and young adults (YYA) with type 1 diabetes (T1D), the association of household food insecurity (HFI) with: 1) HbA1c and 2) episodes of diabetic ketoacidosis (DKA) and severe hypoglycemia. METHODS: HFI was assessed using the U.S. Household Food Security Survey Module in SEARCH for Diabetes in Youth participants with T1D between 2016 and 2019. Linear and logistic regression models adjusted for age, diabetes duration, sex, race, ethnicity, clinic site, parent/participant education, household income, health insurance, and diabetes technology use. RESULTS: Of 1830 participants (mean age 20.8 ± 5.0 years, 70.0 % non-Hispanic White), HbA1c was collected for 1060 individuals (mean HbA1c 9.2 % ± 2.0 %). The prevalence of HFI was 16.4 %. In the past 12 months, 18.2 % and 9.9 % reported an episode of DKA or severe hypoglycemia, respectively. Compared to participants who were food secure, HFI was associated with a 0.33 % (95 % CI 0.003, 0.657) higher HbA1c level. Those with HFI had 1.58 (95 % CI 1.13, 2.21) times the adjusted odds of an episode of DKA and 1.53 (95 % CI 0.99, 2.37) times the adjusted odds of an episode of severe hypoglycemia as those without HFI. CONCLUSIONS: HFI is associated with higher HbA1c levels and increased odds of DKA in YYA with T1D.

Clinical Prediction Models Combining Routine Clinical Measures Have High Accuracy in Identifying Youth-Onset Type 2 Diabetes Defined by Maintained Endogenous Insulin Secretion: The SEARCH for Diabetes in Youth Study.

OBJECTIVE: With high prevalence of obesity and overlapping features between diabetes subtypes, accurately classifying youth-onset diabetes can be challenging. We aimed to develop prediction models that, using characteristics available at diabetes diagnosis, can identify youth who will retain endogenous insulin secretion at levels consistent with type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS: We studied 2,966 youth with diabetes in the prospective SEARCH for Diabetes in Youth study (diagnosis age ≤19 years) to develop prediction models to identify participants with fasting C-peptide ≥250 pmol/L (≥0.75 ng/mL) after >3 years' (median 74 months) diabetes duration. Models included clinical measures at the baseline visit, at a mean diabetes duration of 11 months (age, BMI, sex, waist circumference, HDL cholesterol), with and without islet autoantibodies (GADA, IA-2A) and a Type 1 Diabetes Genetic Risk Score (T1DGRS). RESULTS: Models using routine clinical measures with or without autoantibodies and T1DGRS were highly accurate in identifying participants with C-peptide ≥0.75 ng/mL (17% of participants; 2.3% and 53% of those with and without positive autoantibodies) (area under the receiver operating characteristic curve [AUCROC] 0.95-0.98). In internal validation, optimism was very low, with excellent calibration (slope 0.995-0.999). Models retained high performance for predicting retained C-peptide in older youth with obesity (AUCROC 0.88-0.96) and in subgroups defined by self-reported race/ethnicity (AUCROC 0.88-0.97), autoantibody status (AUCROC 0.87-0.96), and clinically diagnosed diabetes types (AUCROC 0.81-0.92). CONCLUSIONS: Prediction models combining routine clinical measures at diabetes diagnosis, with or without islet autoantibodies or T1DGRS, can accurately identify youth with diabetes who maintain endogenous insulin secretion in the range associated with T2D.

Urinary sphingolipids in adolescents and young adults with youth-onset diabetes.

BACKGROUND: This study evaluated urinary sphingolipids as a marker of diabetic kidney disease (DKD) in adolescents and young adults with youth-onset type 1 and type 2 diabetes. METHODS: A comprehensive panel of urinary sphingolipids, including sphingomyelin (SM), glucosylceramide (GC), ceramide (Cer), and lactosylceramide (LC) species, was performed in patients with youth-onset diabetes from the SEARCH for Diabetes in Youth cohort. Sphingolipid levels, normalized to urine creatinine, were compared in 57 adolescents and young adults with type 1 diabetes, 59 with type 2 diabetes, and 44 healthy controls. The association of sphingolipids with albumin-to-creatinine (ACR) ratio and estimated glomerular filtration rate (eGFR) was evaluated. RESULTS: The median age (interquartile range [IQR]) of participants was 23.1 years (20.9, 24.9) and the median duration of diabetes was 9.3 (8.5, 10.2) years. Urinary sphingolipid concentrations in patients with and without DKD (ACR ≥ 30 mg/g) were significantly elevated compared to healthy controls. There were no significant differences in sphingolipid levels between participants with type 1 and type 2 diabetes. In multivariable analysis, many sphingolipid species were positively correlated with ACR. Most significant associations were evident for the following species: C18 SM, C24:1 SM, C24:1 GC, and C24:1 Cer (all p < 0.001). Sphingolipid levels were not associated with eGFR. However, several interaction terms (diabetes type*sphingolipid) were significant, indicating diabetes type may modify the association of sphingolipids with eGFR. CONCLUSION: Urinary sphingolipids are elevated in adolescents and young adults with youth-onset diabetes and correlate with ACR. Urinary sphingolipids may therefore represent an early biomarker of DKD.

Uric Acid Is Not Associated With Cardiovascular Health in Youth With Type 1 Diabetes: SEARCH for Diabetes in Youth Study.

CONTEXT: Uric acid's role in cardiovascular health in youth with type 1 diabetes is unknown. OBJECTIVE: Investigate whether higher uric acid is associated with increased blood pressure (BP) and arterial stiffness over time in adolescents and young adults with type 1 diabetes and if overweight/obesity modifies this relationship. METHODS: Longitudinal analysis of data from adolescents and young adults with type 1 diabetes from 2 visits (mean follow up 4.6 years) in the SEARCH for Diabetes in Youth multicenter prospective cohort study from 2007 to 2018. Our exposure was uric acid at the first visit and our outcome measures were the change in BP, pulse wave velocity (PWV), and augmentation index between visits. We used multivariable linear mixed-effects models and assessed for effect modification by overweight/obesity. RESULTS: Of 1744 participants, mean age was 17.6 years, 49.4% were female, 75.9% non-Hispanic White, and 45.4% had a follow-up visit. Mean uric acid was 3.7 mg/dL (SD 1.0). Uric acid was not associated with increased BP, PWV-trunk, or augmentation index over time. Uric acid was marginally associated with PWV-upper extremity (ß = .02 m/s/year, 95% CI 0.002 to 0.04). The magnitude of this association did not differ by overweight/obesity status. CONCLUSION: Among adolescents and young adults with type 1 diabetes, uric acid was not consistently associated with increased BP or arterial stiffness over time. These results support findings from clinical trials in older adults with diabetes showing that lowering uric acid levels does not improve cardiovascular outcomes.

Diabetes Stigma and Psychosocial Outcomes in Adolescents and Young Adults: The SEARCH for Diabetes in Youth Study.

OBJECTIVE: To examine the association between diabetes stigma, socioeconomic status, psychosocial variables, and substance use in adolescents and young adults (AYAs) with type 1 or type 2 diabetes. RESEARCH DESIGN AND METHODS: This is a cross-sectional analysis of AYAs from the SEARCH for Diabetes in Youth study who completed a survey on diabetes-related stigma, generating a total diabetes stigma score. Using multivariable modeling, stratified by diabetes type, we examined the relationship of diabetes stigma with variables of interest. RESULTS: Of the 1,608 AYAs who completed the diabetes-related stigma survey, 78% had type 1 diabetes, and the mean age was 21.7 years. Higher diabetes stigma scores were associated with food insecurity (P = 0.001), disordered eating (P < 0.0001), depressive symptoms (P < 0.0001), and decreased health-related (P < 0.0001) and diabetes-specific quality of life (P < 0.0001). CONCLUSIONS: Diabetes stigma is associated with food insecurity, disordered eating, and lower psychosocial well-being.

Prediction of atherosclerotic cardiovascular risk in early childhood.

Atherosclerotic lesions are present even in very young individuals and therefore, risk stratification for cardiovascular (CV) disease should be implemented in childhood to promote early prevention strategies. In this review we critically appraise clinical, biochemical and genetic biomarkers available for pediatric clinical practice, which might be integrated to build effective algorithms to identify children at risk of future CV events. The first critical issue is to characterize in children aged 2-5 years, those CV risk factors/clinical conditions associated with dramatically accelerated atherosclerosis. Presence of clinical conditions such as obesity, diabetes mellitus, Kawasaki disease, etc., or positive family history for premature CV disease should be evaluated. Subsequently, a complete lipid profile and Lipoprotein(a) determination are recommended for children with increased baseline CV risk. Individuals with altered lipid profile could then undergo genetic testing for monogenic dyslipidemias to identify children with high CV genetic risk, who will be directed to appropriate therapeutic options. In perspective, calculation of a polygenic risk score, based on the analysis of several common single-nucleotide polymorphisms, could be integrated for better risk assessment. We here emphasize the importance of a "holistic" strategy integrating biochemical, anamnestic and genetic data to stratify CV risk in early childhood.

Re-analysis and meta-analysis of summary statistics from gene-environment interaction studies.

MOTIVATION: statistics from genome-wide association studies enable many valuable downstream analyses that are more efficient than individual-level data analysis while also reducing privacy concerns. As growing sample sizes enable better-powered analysis of gene-environment interactions, there is a need for gene-environment interaction-specific methods that manipulate and use summary statistics. RESULTS: We introduce two tools to facilitate such analysis, with a focus on statistical models containing multiple gene-exposure and/or gene-covariate interaction terms. REGEM (RE-analysis of GEM summary statistics) uses summary statistics from a single, multi-exposure genome-wide interaction study to derive analogous sets of summary statistics with arbitrary sets of exposures and interaction covariate adjustments. METAGEM (META-analysis of GEM summary statistics) extends current fixed-effects meta-analysis models to incorporate multiple exposures from multiple studies. We demonstrate the value and efficiency of these tools by exploring alternative methods of accounting for ancestry-related population stratification in genome-wide interaction study in the UK Biobank as well as by conducting a multi-exposure genome-wide interaction study meta-analysis in cohorts from the diabetes-focused ProDiGY consortium. These programs help to maximize the value of summary statistics from diverse and complex gene-environment interaction studies. AVAILABILITY AND IMPLEMENTATION: REGEM and METAGEM are open-source projects freely available at https://github.com/large-scale-gxe-methods/REGEM and https://github.com/large-scale-gxe-methods/METAGEM.

Health Care Transition to Adult Care in Type 1 Diabetes: Associations With Student and Employment Status-The SEARCH for Diabetes in Youth Study.

Successful transition from a pediatric to adult diabetes care provider is associated with reduced ambulatory diabetes care visits and increased acute complications. This study aimed to determine whether the degree of independence in diabetes care and the rate of acute complications after transition to adult diabetes care were associated with individuals' student or employment status. Nonstudents were found to be less likely than students to be independent with diabetes care, and employed nonstudents were at lower risk of diabetic ketoacidosis than unemployed nonstudents. Additional support may be needed for young adults who are not students or are unemployed to improve independence and reduce the risk for acute complications.

Clinical prediction models combining routine clinical measures identify participants with youth-onset diabetes who maintain insulin secretion in the range associated with type 2 diabetes: The SEARCH for Diabetes in Youth Study.

Objective: With the high prevalence of pediatric obesity and overlapping features between diabetes subtypes, accurately classifying youth-onset diabetes can be challenging. We aimed to develop prediction models that, using characteristics available at diabetes diagnosis, can identify youth who will retain endogenous insulin secretion at levels consistent with type 2 diabetes (T2D). Methods: We studied 2,966 youth with diabetes in the prospective SEARCH study (diagnosis age ≤19 years) to develop prediction models to identify participants with fasting c-peptide ≥250 pmol/L (≥0.75ng/ml) after >3 years (median 74 months) of diabetes duration. Models included clinical measures at baseline visit, at a mean diabetes duration of 11 months (age, BMI, sex, waist circumference, HDL-C), with and without islet autoantibodies (GADA, IA-2A) and a Type 1 Diabetes Genetic Risk Score (T1DGRS). Results: Models using routine clinical measures with or without autoantibodies and T1DGRS were highly accurate in identifying participants with c-peptide ≥0.75 ng/ml (17% of participants; 2.3% and 53% of those with and without positive autoantibodies) (area under receiver operator curve [AUCROC] 0.95-0.98). In internal validation, optimism was very low, with excellent calibration (slope=0.995-0.999). Models retained high performance for predicting retained c-peptide in older youth with obesity (AUCROC 0.88-0.96), and in subgroups defined by self-reported race/ethnicity (AUCROC 0.88-0.97), autoantibody status (AUCROC 0.87-0.96), and clinically diagnosed diabetes types (AUCROC 0.81-0.92). Conclusion: Prediction models combining routine clinical measures at diabetes diagnosis, with or without islet autoantibodies or T1DGRS, can accurately identify youth with diabetes who maintain endogenous insulin secretion in the range associated with type 2 diabetes.

Lipoprotein(a): a genetically determined risk factor for Cardiovascular disease.

Lipoprotein(a) is a complex lipoprotein with unique characteristics distinguishing it from all the other apolipoprotein B-containing lipoprotein particles. Its lipid composition and the presence of a single molecule of apolipoprotein B per particle, render lipoprotein(a) similar to low-density lipoproteins. However, the presence of a unique, carbohydrate-rich protein termed apolipoprotein(a), linked by a covalent bond to apolipoprotein B imparts unique characteristics to lipoprotein(a) distinguishing it from all the other lipoproteins. Apolipoprotein(a) is highly polymorphic in size ranging in molecular weight from <300 KDa to >800 kDa. Both the size polymorphism and the concentration of lipoprotein(a) in plasma are genetically determined and unlike other lipoproteins, plasma concentration is minimally impacted by lifestyle modifications or lipid-lowering drugs. Many studies involving hundreds of thousands of individuals have provided strong evidence that elevated lipoprotein(a) is genetically determined and a causal risk factor for atherosclerotic cardiovascular disease. The concentration attained in adulthood is already present in children at around 5 years of age and therefore, those with elevated lipoprotein(a) are prematurely exposed to a high risk of cardiovascular disease. Despite the large number of guidelines and consensus statements on the management of lipoprotein(a) in atherosclerotic cardiovascular disease published in the last decade, lipoprotein(a) is still seldom measured in clinical settings. In this review, we provide an overview of the most important features that characterize lipoprotein(a), its role in cardiovascular disease, and the importance of adding the measurement of lipoprotein(a) for screening adults and youths to identify those at increased risk of atherosclerotic cardiovascular disease due to their elevated plasma concentration of lipoprotein(a).

Heterogeneity of Lipoprotein(a) Levels Among Hispanic or Latino Individuals Residing in the US.

Importance: Lipoprotein(a) (Lp[a]) is a genetically determined risk-enhancing factor for atherosclerotic cardiovascular disease (ASCVD). The Lp(a) distribution among the diverse Hispanic or Latino community residing in the US has not been previously described, to the authors' knowledge. Objective: To determine the distribution of Lp(a) levels across a large cohort of diverse Hispanic or Latino adults living in the US and by key demographic groups. Design, Setting, and Participants: The Hispanic Community Health Study/Study of Latinos (HCHS/SOL) is a prospective, population-based, cohort study of diverse Hispanic or Latino adults living in the US. At screening, participants aged 18 to 74 years were recruited between 2008 and 2011 from 4 US metropolitan areas (Bronx, New York; Chicago, Illinois; Miami, Florida; San Diego, California). HCHS/SOL included 16 415 noninstitutionalized adults recruited through probability sampling of randomly selected households. The study population represents Hispanic or Latino participants from diverse self-identified geographic and cultural backgrounds: Central American, Cuban, Dominican, Mexican, Puerto Rican, and South American. This study evaluated a subset of HCHS/SOL participants who underwent Lp(a) measurement. Sampling weights and surveys methods were used to account for HCHS/SOL sampling design. Data for this study were analyzed from April 2021 to April 2023. Exposure: Lp(a) molar concentration was measured by a particle-enhanced turbidimetric assay with minimized sensitivity to apolipoprotein(a) size variation. Main Outcome and Measure: Lp(a) quintiles were compared using analysis of variance among key demographic groups, including self-identified Hispanic or Latino background. Median percentage genetic ancestry (Amerindian, European, West African) were compared across Lp(a) quintiles. Results: Lp(a) molar concentration was measured in 16 117 participants (mean [SD] age, 41 [14.8] years; 9680 female [52%]; 1704 Central American [7.7%], 2313 Cuban [21.1%], 1436 Dominican [10.3%], 6395 Mexican [39.1%], 2652 Puerto Rican [16.6%], 1051 South American [5.1%]). Median (IQR) Lp(a) level was 19.7 (7.4-59.7) nmol/L. Across Hispanic or Latino background groups, there was significant heterogeneity in median Lp(a) levels ranging from 12 to 41 nmol/L in those reporting a Mexican vs Dominican background. Median (IQR) West African genetic ancestry was lowest in the first quintile of Lp(a) level and highest in the fifth quintile (5.5% [3.4%-12.9%] and 12.1% [5.0%-32.5%]; respectively; P < .001), whereas the converse was seen for Amerindian ancestry (32.8% [9.9%-53.2%] and 10.7% [4.9%-30.7%], respectively; P < .001). Conclusions and Relevance: Results of this cohort study suggest that differences in Lp(a) level distribution across the diverse US Hispanic or Latino population may carry important implications for the use of Lp(a) level in ASCVD risk assessment for this group. Cardiovascular outcomes data are needed to better understand the clinical impact of differences in Lp(a) levels by Hispanic or Latino background.

The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes.

AIMS/HYPOTHESIS: The Latino population has been systematically underrepresented in large-scale genetic analyses, and previous studies have relied on the imputation of ungenotyped variants based on the 1000 Genomes (1000G) imputation panel, which results in suboptimal capture of low-frequency or Latino-enriched variants. The National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) released the largest multi-ancestry genotype reference panel representing a unique opportunity to analyse rare genetic variations in the Latino population. We hypothesise that a more comprehensive analysis of low/rare variation using the TOPMed panel would improve our knowledge of the genetics of type 2 diabetes in the Latino population. METHODS: We evaluated the TOPMed imputation performance using genotyping array and whole-exome sequence data in six Latino cohorts. To evaluate the ability of TOPMed imputation to increase the number of identified loci, we performed a Latino type 2 diabetes genome-wide association study (GWAS) meta-analysis in 8150 individuals with type 2 diabetes and 10,735 control individuals and replicated the results in six additional cohorts including whole-genome sequence data from the All of Us cohort. RESULTS: Compared with imputation with 1000G, the TOPMed panel improved the identification of rare and low-frequency variants. We identified 26 genome-wide significant signals including a novel variant (minor allele frequency 1.7%; OR 1.37, p=3.4 × 10-9). A Latino-tailored polygenic score constructed from our data and GWAS data from East Asian and European populations improved the prediction accuracy in a Latino target dataset, explaining up to 7.6% of the type 2 diabetes risk variance. CONCLUSIONS/INTERPRETATION: Our results demonstrate the utility of TOPMed imputation for identifying low-frequency variants in understudied populations, leading to the discovery of novel disease associations and the improvement of polygenic scores. DATA AVAILABILITY: Full summary statistics are available through the Common Metabolic Diseases Knowledge Portal ( https://t2d.hugeamp.org/downloads.html ) and through the GWAS catalog ( https://www.ebi.ac.uk/gwas/ , accession ID: GCST90255648). Polygenic score (PS) weights for each ancestry are available via the PGS catalog ( https://www.pgscatalog.org , publication ID: PGP000445, scores IDs: PGS003443, PGS003444 and PGS003445).

Candidate biomarkers as predictors of future kidney disease and cardiovascular dysfunction in adolescents with type 2 diabetes.

AIMS: Evaluate changes in circulating biomarkers as predictors of kidney disease, and cardiac/vascular dysfunction in participants from the Treatment Options for type 2 Diabetes in Adolescents and Youth (TODAY) study. METHODS: Candidate biomarkers were assessed annually in 507 participants over a mean follow-up of 6.9 ± 2.4 years. Moderate albuminuria was defined as urine albumin-to-creatinine ratio ≥ 30 mg/g and hyperfiltration as eGFR ≥ 135 mL/min/1.73 m2 at two consecutive visits. Echocardiography (n = 256) and pulse wave velocity (n = 193) were evaluated twice, 5 years apart. Adjusted Cox proportional hazard models and logistic regression models were used to examine associations between biomarkers and outcomes. RESULTS: At baseline, 35.7% were male, with a mean age 13.9 years, diabetes duration 7.8 months, and HbA1c 6.0%. Higher concentrations of E-selectin and proinsulin were associated with incident moderate albuminuria and hyperfiltration. Higher concentrations of FGF-23 were associated with lower risk of hyperfiltration and negatively correlated with eGFR. No candidate biomarkers predicted a decline in cardiac or vascular function. CONCLUSIONS: Circulating biomarkers of endothelial dysfunction and markers of ß-cell dysfunction and insulin sensitivity could be used in a more personalized risk assessment of kidney disease in youth-onset type 2 diabetes. However, biomarkers studied have limited value in predicting cardiac dysfunction or vascular stiffness.

Prevalence, Progression, and Modifiable Risk Factors for Diabetic Retinopathy in Youth and Young Adults With Youth-Onset Type 1 and Type 2 Diabetes: The SEARCH for Diabetes in Youth Study.

OBJECTIVE: To determine the prevalence, progression, and modifiable risk factors associated with the development of diabetic retinopathy (DR) in a population-based cohort of youth-onset diabetes. RESEARCH DESIGN AND METHODS: We conducted a multicenter, population-based prospective cohort study (2002-2019) of youth and young adults with youth-onset type 1 diabetes (n = 2,519) and type 2 diabetes (n = 447). Modifiable factors included baseline and change from baseline to follow-up in BMI z score, waist/height ratio, systolic and diastolic blood pressure z score, and A1C. DR included evidence of mild or moderate nonproliferative DR or proliferative retinopathy. Prevalence estimates were standardized to estimate the burden of DR, and inverse probability weighting for censoring was applied for estimating risk factors for DR at two points of follow-up. RESULTS: DR in youth-onset type 1 and type 2 diabetes is highly prevalent, with 52% of those with type 1 diabetes and 56% of those with type 2 diabetes demonstrating retinal changes at follow-up (mean [SD] 12.5 [2.2] years from diagnosis). Higher baseline A1C, increase in A1C across follow-up, and increase in diastolic and systolic blood pressure were associated with the observation of DR at follow-up for both diabetes types. Increase in A1C across follow-up was associated with retinopathy progression. BMI z score and waist/height ratio were inconsistently associated, with both positive and inverse associations noted. CONCLUSIONS: Extrapolated to all youth-onset diabetes in the U.S., we estimate 110,051 cases of DR developing within ∼12 years postdiagnosis. Tight glucose and blood pressure management may offer the opportunity to mitigate development and progression of DR in youth-onset diabetes.

Trends in incidence of youth-onset type 1 and type 2 diabetes in the USA, 2002-18: results from the population-based SEARCH for Diabetes in Youth study.

BACKGROUND: The incidence of diabetes is increasing in children and young people. We aimed to describe the incidence of type 1 and type 2 diabetes in children and young people aged younger than 20 years over a 17-year period. METHODS: The SEARCH for Diabetes in Youth study identified children and young people aged 0-19 years with a physician diagnosis of type 1 or type 2 diabetes at five centres in the USA between 2002 and 2018. Eligible participants included non-military and non-institutionalised individuals who resided in one of the study areas at the time of diagnosis. The number of children and young people at risk of diabetes was obtained from the census or health plan member counts. Generalised autoregressive moving average models were used to examine trends, and data are presented as incidence of type 1 diabetes per 100 000 children and young people younger than 20 years and incidence of type 2 diabetes per 100 000 children and young people aged between 10 years and younger than 20 years across categories of age, sex, race or ethnicity, geographical region, and month or season of diagnosis. FINDINGS: We identified 18 169 children and young people aged 0-19 years with type 1 diabetes in 85 million person-years and 5293 children and young people aged 10-19 years with type 2 diabetes in 44 million person-years. In 2017-18, the annual incidence of type 1 diabetes was 22·2 per 100 000 and that of type 2 diabetes was 17·9 per 100 000. The model for trend captured both a linear effect and a moving-average effect, with a significant increasing (annual) linear effect for both type 1 diabetes (2·02% [95% CI 1·54-2·49]) and type 2 diabetes (5·31% [4·46-6·17]). Children and young people from racial and ethnic minority groups such as non-Hispanic Black and Hispanic children and young people had greater increases in incidence for both types of diabetes. Peak age at diagnosis was 10 years (95% CI 8-11) for type 1 diabetes and 16 years (16-17) for type 2 diabetes. Season was significant for type 1 diabetes (p=0·0062) and type 2 diabetes (p=0·0006), with a January peak in diagnoses of type 1 diabetes and an August peak in diagnoses of type 2 diabetes. INTERPRETATION: The increasing incidence of type 1 and type 2 diabetes in children and young people in the USA will result in an expanding population of young adults at risk of developing early complications of diabetes whose health-care needs will exceed those of their peers. Findings regarding age and season of diagnosis will inform focused prevention efforts. FUNDING: US Centers for Disease Control and Prevention and US National Institutes of Health.

Exploring Racial and Ethnic Differences in Arterial Stiffness Among Youth and Young Adults With Type 1 Diabetes.

Background We examined arterial stiffness in individuals with type 1 diabetes, and explored whether differences between Hispanic, non-Hispanic Black (NHB), and non-Hispanic White (NHW) individuals were attributable to modifiable clinical and social factors. Methods and Results Participants (n=1162; 22% Hispanic, 18% NHB, and 60% NHW) completed 2 to 3 research visits from ≈10 months to ≈11 years post type 1 diabetes diagnosis (mean ages of ≈9 to ≈20 years, respectively) providing data on socioeconomic factors, type 1 diabetes characteristics, cardiovascular risk factors, health behaviors, quality of clinical care, and perception of clinical care. Arterial stiffness (carotid-femoral pulse wave velocity [PWV], m/s) was measured at ≈20 years of age. We analyzed differences in PWV by race and ethnicity, then explored the individual and combined impact of the clinical and social factors on these differences. PWV did not differ between Hispanic (adjusted mean 6.18 [SE 0.12]) and NHW (6.04 [0.11]) participants after adjustment for cardiovascular risks (P=0.06) and socioeconomic factors (P=0.12), or between Hispanic and NHB participants (6.36 [0.12]) after adjustment for all factors (P=0.08). PWV was higher in NHB versus NHW participants in all models (all P<0.001). Adjustment for modifiable factors reduced the difference in PWV by 15% for Hispanic versus NHW participants; by 25% for Hispanic versus NHB; and by 21% for NHB versus NHW. Conclusions Cardiovascular and socioeconomic factors explain one-quarter of the racial and ethnic differences in PWV of young people with type 1 diabetes, but NHB individuals still experienced greater PWV. Exploration of pervasive inequities potentially driving these persistent differences is needed.

Food Insecurity and Adequacy of Dietary Intake in Youth and Young Adults With Youth-Onset Type 1 and Type 2 Diabetes.

BACKGROUND: Household food insecurity is associated with poor dietary intake in the general population, but little is known about this association in persons with diabetes. OBJECTIVE: We examined the degree of adherence to the dietary reference intakes and 2020-2025 Dietary Guidelines for Americans overall and according to food security status and diabetes type among youth and young adults (YYA) with youth-onset diabetes. DESIGN, PARTICIPANTS, AND SETTING: The SEARCH for Diabetes in Youth study includes 1,197 YYA with type 1 diabetes (mean age = 21 ± 5 years) and 319 YYA with type 2 diabetes (25 ± 4 years). Participants (or parents if younger than age 18 years) completed the US Department of Agriculture Household Food Security Survey Module, wherein ≥3 affirmations indicate food insecurity. MAIN OUTCOME MEASURES: Diet was assessed via food frequency questionnaire and compared with age- and sex-specific dietary reference intakes for 10 nutrients and dietary components (calcium; fiber; magnesium; potassium; sodium; vitamins C, D, and E; added sugar; and saturated fat). STATISTICAL ANALYSES PERFORMED: Median regression models controlled for sex- and type-specific means for age, diabetes duration, and daily energy intake. RESULTS: Prevalence of guideline adherence was overarchingly poor, with <40% of participants meeting recommendations for eight of 10 nutrients and dietary components; however, higher adherence (>47%) was observed for vitamin C and added sugars. YYA with type 1 diabetes who were food insecure were more likely to meet recommendations for calcium, magnesium, and vitamin E (P < 0.05), and less likely for sodium (P < 0.05) than those with food security. In adjusted models, YYA with type 1 diabetes who were food secure had closer median adherence to sodium (P = 0.002) and fiber (P = 0.042) guidelines than those food insecure. No associations were observed in YYA with type 2 diabetes. CONCLUSIONS: Food insecurity is associated with lesser adherence to fiber and sodium guidelines in YYA with type 1 diabetes, which may lead to diabetes complications and other chronic diseases.

Diabetes Stigma and Clinical Outcomes in Adolescents and Young Adults: The SEARCH for Diabetes in Youth Study.

OBJECTIVE: To examine the association between diabetes stigma and HbA1c, treatment plan and acute and chronic complications in adolescents and young adults (AYAs) with type 1 or type 2 diabetes. RESEARCH DESIGN AND METHODS: The SEARCH for Diabetes in Youth study is a multicenter cohort study that collected questionnaire, laboratory, and physical examination data about AYAs with diabetes diagnosed in childhood. A five-question survey assessed frequency of perceived diabetes-related stigma, generating a total diabetes stigma score. We used multivariable linear modeling, stratified by diabetes type, to examine the association of diabetes stigma with clinical factors, adjusting for sociodemographic characteristics, clinic site, diabetes duration, health insurance, treatment plan, and HbA1c. RESULTS: Of 1,608 respondents, 78% had type 1 diabetes, 56% were female, and 48% were non-Hispanic White. The mean (SD) age at study visit was 21.7 (5.1) years (range, 10-24.9). The mean (SD) HbA1c was 9.2% (2.3%; 77 mmol/mol [2.0 mmol/mol]). Higher diabetes stigma scores were associated with female sex and higher HbA1c (P < 0.01) for all participants. No significant association between diabetes stigma score and technology use was observed. In participants with type 2 diabetes, higher diabetes stigma scores were associated with insulin use (P = 0.04). Independent of HbA1c, higher diabetes stigma scores were associated with some acute complications for AYAs with type 1 diabetes and some chronic complications for AYAs with type 1 or type 2 diabetes. CONCLUSIONS: Diabetes stigma in AYAs is associated with worse diabetes outcomes and is important to address when providing comprehensive diabetes care.

Striving for a pragmatic contribution of biomarkers results to lifelong health care.

BACKGROUND: The increased role of preventive medicine in healthcare and the rapid technological advancements, have deeply changed the landscape of laboratory medicine. In particular, increased investments in newborn screening tests and policies have been observed. Aim of this paper is to characterize how laboratory professionals engaged in clinical chemistry or newborn screening, in collaboration with experts in econometric, bioinformatics, and biostatistics may address a pragmatic use of laboratory results in the decision-making process oriented toward improvement of health care outcomes. CONTENT: The effectiveness of biomarkers on healthcare depends on several factors such as analytical performance, prevalence of the disease, integration of the test within the diagnostic algorithm, associated costs, and social/economic impact of false positive and false negative results. Cost-effectiveness analysis needs to be performed and reliability achieved, by overcoming analytical pitfalls and by improving interpretative criteria. These are challenging issues common to clinical chemistry and newborn screening tests. Following the experience in clinical chemistry, one of the main issues to be approached in newborn screening tests, is the lack of harmonization of results obtained by different methods and the limited healthcare effectiveness. SUMMARY: The focus on prevention is a crucial opportunity for laboratory medicine to change how to approach the effectiveness of biomarkers on healthcare. The consolidation within clinical laboratories of professionals with different technical and methodological expertise coupled with the need to produce and manage large sets of data, require the cooperation of professionals from other disciplines to characterize the impact of the tests on epidemiological outcomes for health care policy making process.