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.

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.

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).

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).

Apo(a) and ApoB Interact Noncovalently Within Hepatocytes: Implications for Regulation of Lp(a) Levels by Modulation of ApoB Secretion.

BACKGROUND: Elevated plasma Lp(a) (lipoprotein(a)) levels are associated with increased risk for atherosclerotic cardiovascular disease and aortic valve stenosis. However, the cell biology of Lp(a) biosynthesis remains poorly understood, with the locations of the noncovalent and covalent steps of Lp(a) assembly unclear and the nature of the apoB-containing particle destined for Lp(a) unknown. We, therefore, asked if apo(a) and apoB interact noncovalently within hepatocytes and if this impacts Lp(a) biosynthesis. METHODS: Using human hepatocellular carcinoma cells expressing 17K (17 kringle) apo(a), or a 17KΔLBS7,8 variant with a reduced ability to bind noncovalently to apoB, we performed coimmunoprecipitation, coimmunofluorescence, and proximity ligation assays to document intracellular apo(a):apoB interactions. We used a pulse-chase metabolic labeling approach to measure apo(a) and apoB secretion rates. RESULTS: Noncovalent complexes containing apo(a)/apoB are present in lysates from cells expressing 17K but not 17KΔLBS7,8, whereas covalent apo(a)/apoB complexes are absent from lysates. 17K and apoB colocalized intracellularly, overlapping with staining for markers of endoplasmic reticulum trans-Golgi, and early endosomes, and less so with lysosomes. The 17KΔLBS7,8 had lower colocalization with apoB. Proximity ligation assays directly documented intracellular 17K/apoB interactions, which were dramatically reduced for 17KΔLBS7,8. Treatment of cells with PCSK9 (proprotein convertase subtilisin/kexin type 9) enhanced, and lomitapide reduced, apo(a) secretion in a manner dependent on the noncovalent interaction between apo(a) and apoB. Apo(a) secretion was also reduced by siRNA-mediated knockdown of APOB. CONCLUSIONS: Our findings explain the coupling of apo(a) and Lp(a)-apoB production observed in human metabolic studies using stable isotopes as well as the ability of agents that inhibit apoB biosynthesis to lower Lp(a) levels.

Lipoprotein(a): A Genetically Determined, Causal, and Prevalent Risk Factor for Atherosclerotic Cardiovascular Disease: A Scientific Statement From the American Heart Association.

High levels of lipoprotein(a) [Lp(a)], an apoB100-containing lipoprotein, are an independent and causal risk factor for atherosclerotic cardiovascular diseases through mechanisms associated with increased atherogenesis, inflammation, and thrombosis. Lp(a) is predominantly a monogenic cardiovascular risk determinant, with ≈70% to ≥90% of interindividual heterogeneity in levels being genetically determined. The 2 major protein components of Lp(a) particles are apoB100 and apolipoprotein(a). Lp(a) remains a risk factor for cardiovascular disease development even in the setting of effective reduction of plasma low-density lipoprotein cholesterol and apoB100. Despite its demonstrated contribution to atherosclerotic cardiovascular disease burden, we presently lack standardization and harmonization of assays, universal guidelines for diagnosing and providing risk assessment, and targeted treatments to lower Lp(a). There is a clinical need to understand the genetic and biological basis for variation in Lp(a) levels and its relationship to disease in different ancestry groups. This scientific statement capitalizes on the expertise of a diverse basic science and clinical workgroup to highlight the history, biology, pathophysiology, and emerging clinical evidence in the Lp(a) field. Herein, we address key knowledge gaps and future directions required to mitigate the atherosclerotic cardiovascular disease risk attributable to elevated Lp(a) levels.

Diabetes complications and cognitive function in young adults with youth-onset type 1 or type 2 diabetes: the SEARCH for Diabetes in Youth Study.

Aims/hypotheses: People with type 1 (T1D) or type 2 diabetes (T2D) who also have diabetes complications can have pronounced cognitive deficits. It remains unknown, however, whether and how multiple diabetes complications co-occur with cognitive dysfunction, particularly in youth-onset diabetes. Methods: Using data from the SEARCH for Diabetes in Youth study cohort, a prospective longitudinal cohort, we examined clustering of complications and their underlying clinical factors with performance on cognitive tests in young adults with youth-onset T1D or T2D. Cognition was assessed via the NIH Toolbox Cognition Battery. The main cognitive variables were age-corrected scores for composite fluid cognition and associated cognitive subdomains. Diabetes complications included retinopathy, microalbuminuria, and peripheral neuropathy (PN). Lipids, systolic blood pressure (SBP), hemoglobin A1c, and other clinical factors were included in the analyses. Clustering was applied separately to each group (T1D=646; T2D=165). A three-cluster(C) solution was identified for each diabetes type. Mean values and frequencies of all factors were compared between resulting clusters. Results: The average age-corrected score for composite fluid cognition differed significantly across clusters for each group (p<0.001). People with T1D and the lowest average fluid cognition scores had the highest frequency of self-reporting at least one episode of hypoglycemia in the year preceding cognitive testing and the highest prevalence of PN. Persons with T2D and the lowest average fluid cognition scores had the highest SBP, the highest central systolic and diastolic blood pressures, and highest prevalence of PN. Conclusions/interpretations: These findings highlight shared (PN) and unique factors (hypoglycemia in T1D; SBP in T2D) that could be targeted to potentially mitigate cognitive issues in young people with youth-onset diabetes.

Household Food Insecurity and Cognition in Youth and Young Adults with Youth-Onset Diabetes.

Objective: We evaluated the association of household food insecurity (FI) with cognition in youth and young adults with type 1 diabetes (T1D) or type 2 diabetes (T2D). Design: In this cross-sectional study, age-adjusted scores for composite Fluid Cognition, and sub-domain scores for Receptive Language and Inhibitory Control and Attention, were modeled stratified by diabetes-type using linear regression, with FI in the past year as the predictor, controlling for covariates. Tests for processing speed, inhibitory control/attention, working memory, episodic memory, and cognitive flexibility were administered to measure composite Fluid Cognition score. The NIHT-CB Picture Vocabulary Test was used to assess Crystallized Cognition score and rapid identification of congruent versus noncongruent items were used to assess Inhibitory Control and Attention score. Setting: The SEARCH for Diabetes in Youth study, representative of 5 U.S. states. Participants: Included 1574 youth and young adults with T1D or T2D, mean age of 21 years, mean diabetes duration of 11 years, 51% non-Hispanic white, and 47% had higher HbA1c levels (>9% HbA1c). Results: Approximately 18% of the 1,240 participants with T1D and 31% of the 334 with T2D experienced FI. The food-insecure group with T1D had a lower composite Fluid Cognition score (ß= -2.5, 95% confidence interval (CI)= -4.8, -0.1) and a lower Crystallized Cognition score (ß= -3.4, CI= -5.6, -1.3) than food-secure peers. Findings were attenuated to non-significance after adjustment for demographics. Among T2D participants, no associations were observed. In participants with T1D effect modification by glycemic levels were found in the association between FI and composite Fluid Cognition score but adjustment for socioeconomic characteristics attenuated the interaction (p=0.0531). Conclusions: Food-insecure youth and young adults with T1D or T2D did not have different cognition compared to those who were food-secure after adjustment for confounders. Longitudinal research is needed to further understand relations amongst these factors.

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.

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.

Development and validation of an isoform-independent monoclonal antibody-based ELISA for measurement of lipoprotein(a).

The study aims were to develop a new isoform-independent enzyme-linked immunoassay (ELISA) for the measurement of lipoprotein(a) [Lp(a)], validate its performance characteristics, and demonstrate its accuracy by comparison with the gold-standard ELISA method and an LC-MS/MS candidate reference method, both developed at the University of Washington. The principle of the new assay is the capture of Lp(a) with monoclonal antibody LPA4 primarily directed to an epitope in apolipoprotein(a) KIV2 and its detection with monoclonal antibody LPA-KIV9 directed to a single antigenic site present on KIV9. Validation studies were performed following the guidelines of the Clinical Laboratory Improvement Amendments and the College of American Pathologists. The analytical measuring range of the LPA4/LPA-KIV9 ELISA is 0.27-1,402 nmol/L, and the method meets stringent criteria for precision, linearity, spike and recovery, dilutability, comparison of plasma versus serum, and accuracy. Method comparison with both the gold-standard ELISA and the LC-MS/MS method performed in 64 samples with known apolipoprotein(a) isoforms resulted in excellent correlation with both methods (r=0.987 and r=0.976, respectively). Additionally, the variation in apolipoprotein(a) size accounted for only 0.2% and 2.2% of the bias variation, respectively, indicating that the LPA4/LPA-KIV9 ELISA is not affected by apolipoprotein(a) size polymorphism. Peptide mapping and competition experiments demonstrated that the measuring monoclonal antibodies used in the gold-standard ELISA (a-40) and in the newly developed ELISA (LPA-KIV9) are directed to the same epitope, 4076LETPTVV4082, on KIV9. In conclusion, no statistically or clinically significant bias was observed between Lp(a) measurements obtained by the LPA4/LPA-KIV9 ELISA and those obtained by the gold-standard ELISA or LC-MS/MS, and therefore, the methods are considered equivalent.

Sortilin enhances secretion of apolipoprotein(a) through effects on apolipoprotein B secretion and promotes uptake of lipoprotein(a).

Elevated plasma lipoprotein(a) (Lp(a)) is an independent, causal risk factor for atherosclerotic cardiovascular disease and calcific aortic valve stenosis. Lp(a) is formed in or on hepatocytes from successive noncovalent and covalent interactions between apo(a) and apoB, although the subcellular location of these interactions and the nature of the apoB-containing particle involved remain unclear. Sortilin, encoded by the SORT1 gene, modulates apoB secretion and LDL clearance. We used a HepG2 cell model to study the secretion kinetics of apo(a) and apoB. Overexpression of sortilin increased apo(a) secretion, while siRNA-mediated knockdown of sortilin expression correspondingly decreased apo(a) secretion. Sortilin binds LDL but not apo(a) or Lp(a), indicating that its effect on apo(a) secretion is likely indirect. Indeed, the effect was dependent on the ability of apo(a) to interact noncovalently with apoB. Overexpression of sortilin enhanced internalization of Lp(a), but not apo(a), by HepG2 cells, although neither sortilin knockdown in these cells or Sort1 deficiency in mice impacted Lp(a) uptake. We found several missense mutations in SORT1 in patients with extremely high Lp(a) levels; sortilin containing some of these mutations was more effective at promoting apo(a) secretion than WT sortilin, though no differences were found with respect to Lp(a) internalization. Our observations suggest that sortilin could play a role in determining plasma Lp(a) levels and corroborate in vivo human kinetic studies which imply that secretion of apo(a) and apoB are coupled, likely within the hepatocyte.

PCSK9 inhibition with alirocumab decreases plasma lipoprotein(a) concentration by a dual mechanism of action in statin-treated patients with very high apolipoprotein(a) concentration.

BACKGROUND: Inhibition of proprotein convertase subtilisin/kexin type 9 with alirocumab decreases plasma lipoprotein(a) [Lp(a)] levels. The kinetic mechanism for lowering Lp(a) by alirocumab may differ according to pre-treatment apolipoprotein(a) [apo(a)] levels. METHODS: The effect of 12-week alirocumab (150 mg subcutaneously fortnightly) on the kinetics of apo(a) was compared in statin-treated patients with high (n = 10) and very high Lp(a) concentrations (n = 11). RESULTS: In patients with high apo(a) concentrations, alirocumab lowered plasma apo(a) pool size (-17%, p < 0.01) chiefly by increasing the fractional catabolic rate (FCR) of apo(a) (+27%, p < 0.001). By contrast in patients with very high apo(a) concentrations, alirocumab significantly lowered plasma apo(a) pool size (-32%, p < 0.001) by both increasing apo(a) FCR (+30%, p < 0.001) and lowering production rate (-11%, p < 0.05). CONCLUSIONS: In statin-treated patients with very high apo(a) concentrations, alirocumab lowers plasma Lp(a) concentration by a dual mode of action that increases the clearance and decreases the production of Lp(a) particles.

A longitudinal assessment of diabetes autoantibodies in the SEARCH for diabetes in youth study.

To assess changes in diabetes autoantibodies (DAs) over time in children and young adults with diabetes and determine whether observed changes were associated with demographic characteristics, clinical parameters and diabetes complications. Participants had DAs measured at baseline (10.3 ± 7.1 months after diabetes diagnosis) and at 12, 24 months and ≥5 years after the baseline measurement. At the ≥5-year follow-up, the presence of diabetes complications was assessed. We examined the associations between change in number of positive DAs and changes in individual DA status with the participants' characteristics and clinical parameters over time. Out of 4179 participants, 62% had longitudinal DA data and 51% had complications and longitudinal DA data. In participants with ≥1 baseline positive DA (n = 1699), 83.4% remained positive after 7.3 ± 2.3 years duration of diabetes. Decrease in number of positive DAs was associated with longer diabetes duration (p = 0.003 for 1 baseline positive DA; p < 0.001 for 2 baseline positive DAs) and younger age at diagnosis (p < 0.001 for 2 baseline positive DAs). No associations were found between change in number of positive DAs in participants with ≥1 baseline positive DA (n = 1391) and HbA1c, insulin dose, acute, or chronic complications after 7.7 ± 1.9 years duration of diabetes. DA status likely remains stable in the first 7 years after diabetes diagnosis. Younger age at diabetes diagnosis and longer duration were associated with less persistence of DAs. Measuring DAs after initial presentation may aid in diabetes classification but not likely in predicting the clinical course.

Household food insecurity is associated with diabetic ketoacidosis but not severe hypoglycemia or glycemic control in youth and young adults with youth-onset type 2 diabetes.

OBJECTIVE: To examine the association between household food insecurity (HFI), glycemic control, severe hypoglycemia and diabetic ketoacidosis (DKA) among youth and young adults (YYA) with youth-onset type 2 diabetes. RESEARCH DESIGN AND METHODS: This cross-sectional study included 395 YYA with type 2 diabetes from the SEARCH for Diabetes in Youth Study (2015-2019). HFI was reported by young adult participants or parents of minor participants via the US Household Food Security Survey Module. Glycemic control was assessed by HbA1c and analyzed as a continuous and categorical variable (optimal: <7.0%, suboptimal: ≥7.0%-9.0%, poor: >9.0%). Acute complications included self-reported severe hypoglycemia or DKA in the last 12 months. Adjusted logistic and linear regression were used for binary and continuous outcomes, respectively. RESULTS: Approximately 31% reported HFI in the past 12 months. Mean HbA1c among those with HFI was 9.2% compared to 9.5% without HFI. Of those with HFI, 56% had an HbA1c >9.0% compared to 55% without HFI. Adjusted models showed no associations between HFI and glycemic control. Of those with HFI, 14.4% reported experiencing DKA and 4.7% reported severe hypoglycemia. YYA with HFI had 3.08 times (95% CI: 1.18-8.06) the odds of experiencing DKA as those without HFI. There was no association between HFI and severe hypoglycemia. CONCLUSIONS: HFI was associated with markedly increased odds of DKA but not with glycemic control or severe hypoglycemia. Future research among YYA with type 2 diabetes should evaluate longitudinally whether alleviating HFI reduces DKA.

Quantification of LDL-Cholesterol Corrected for Molar Concentration of Lipoprotein(a).

PURPOSE: Cholesterol in lipoprotein(a) [Lp(a)-C] is commonly estimated as 30% of the measured Lp(a) mass. However, difficulties in the accurate measurement of Lp(a) mass, along with the inaccuracy of the 30% assumption, produce erroneous values when LDL-C is corrected for Lp(a) [LDL-CLp(a)corr]. Our aim was to develop a new formula for LDL-CLp(a)corr to reduce this error. METHODS: We developed a new formula to calculate Lp(a)-C from the molar measurement of Lp(a), which is Lp(a) nmol/L × 0.077 = Lp(a)-C mg/dL. The calculated Lp(a)-C is subtracted from LDL-C to obtain LDL-CLp(a)corr. The results obtained with our novel formula versus the conventional formula were compared in 440 samples from 239 participants enrolled in the BANTING study. RESULTS: With the conventional formula, approximately 7% of samples with low LDL-C resulted in negative LDL-CLp(a)corr values. With the new formula, no negative LDL-CLp(a)corr values occurred. Among groups with the highest Lp(a)/apoB ratio (p < 0.001) and smaller apolipoprotein(a) isoform size (p < 0.006), LDL-CLp(a)corr was significantly underestimated by the conventional formula, which may result in the undertreatment of some patients. CONCLUSION: The new formula provides more reliable estimates of LDL-CLp(a)corr than the conventional formula. TRIAL REGISTRATION: ClinicalTrials.gov NCT02739984.

Development of an LC-MS/MS Proposed Candidate Reference Method for the Standardization of Analytical Methods to Measure Lipoprotein(a).

BACKGROUND: Use of lipoprotein(a) concentrations for identification of individuals at high risk of cardiovascular diseases is hampered by the size polymorphism of apolipoprotein(a), which strongly impacts immunochemical methods, resulting in discordant values. The availability of a reference method with accurate values expressed in SI units is essential for implementing a strategy for assay standardization. METHOD: A targeted LC-MS/MS method for the quantification of apolipoprotein(a) was developed based on selected proteotypic peptides quantified by isotope dilution. To achieve accurate measurements, a reference material constituted of a human recombinant apolipoprotein(a) was used for calibration. Its concentration was assigned using an amino acid analysis reference method directly traceable to SI units through an unbroken traceability chain. Digestion time-course, repeatability, intermediate precision, parallelism, and comparability to the designated gold standard method for lipoprotein(a) quantification, a monoclonal antibody-based ELISA, were assessed. RESULTS: A digestion protocol providing comparable kinetics of digestion was established, robust quantification peptides were selected, and their stability was ascertained. Method intermediate imprecision was below 10% and linearity was validated in the 20-400 nmol/L range. Parallelism of responses and equivalency between the recombinant and endogenous apo(a) were established. Deming regression analysis comparing the results obtained by the LC-MS/MS method and those obtained by the gold standard ELISA yielded y = 0.98*ELISA +3.18 (n = 64). CONCLUSIONS: Our method for the absolute quantification of lipoprotein(a) in plasma has the required attributes to be proposed as a candidate reference method with the potential to be used for the standardization of lipoprotein(a) assays.

Glycemic control is associated with dyslipidemia over time in youth with type 2 diabetes: The SEARCH for diabetes in youth study.

BACKGROUND: Dyslipidemia has been documented in youth with type 2 diabetes. There is a paucity of studies examining dyslipidemia over time in youth with type 2 diabetes and associated risk factors. OBJECTIVE: To evaluate lipids at baseline and follow-up and associated risk factors in youth with type 2 diabetes. METHODS: We studied 212 youth with type 2 diabetes at baseline and after an average of 7 years of follow-up in the SEARCH for Diabetes in Youth Study. Abnormal lipids were defined as high-density lipoprotein cholesterol (HDL-C) < 35, low-density lipoprotein cholesterol (LDL-C) > 100, or triglycerides >150 (all mg/dl). We evaluated participants for progression to abnormal lipids (normal lipids at baseline and abnormal at follow-up), regression (abnormal lipids at baseline and normal at follow-up), stable normal, and stable abnormal lipids over time for HDL-C, LDL-C, and triglycerides. Associations between hemoglobin A1c (HbA1c) and adiposity over time (area under the curve [AUC]) with progression and stable abnormal lipids were evaluated. RESULTS: HDL-C progressed, regressed, was stable normal, and stable abnormal in 12.3%, 11.3%, 62.3%, and 14.2% of participants, respectively. Corresponding LDL-C percentages were 15.6%, 12.7%, 42.9%, and 28.8% and triglycerides were 17.5%, 10.8%, 55.7%, and 16.0%. Each 1% increase in HbA1c AUC was associated with a 13% higher risk of progression and stable abnormal triglycerides and a 20% higher risk of progression and stable abnormal LDL-C. Higher adiposity AUC was marginally (p = 0.049) associated with abnormal HDL-C. CONCLUSIONS: Progression and stable abnormal LDL-C and triglycerides occur in youth with type 2 diabetes and are associated with higher HbA1c.

The relationship between traffic-related air pollution exposures and allostatic load score among youth with type 1 diabetes in the SEARCH cohort.

OBJECTIVE: We investigated the effects of chronic exposures to particulate and traffic-related air pollution on allostatic load (AL) score, a marker of cumulative biological risk, among youth with type 1 diabetes. RESEARCH DESIGN AND METHODS: Participants were drawn from five clinical sites of the SEARCH for Diabetes in Youth (SEARCH) study (n = 2338). Baseline questionnaires, anthropometric measures, and a fasting blood test were taken at a clinic visit between 2001 and 2005. AL was operationalized using 10 biomarkers reflecting cardiovascular, metabolic, and inflammatory risk. Annual residential exposures to PM2.5 and proximity to heavily-trafficked major roadways were estimated for each participant. Poisson regression models adjusted for sociodemographic and lifestyle factors were conducted for each exposure. RESULTS: No significant associations were observed between exposures to PM2.5 or proximity to traffic and AL score, however analyses were suggestive of effect modification by race for residential distance to heavily-trafficked major roadways (p = 0.02). In stratified analyses, residing <100, 100-<200 and 200-<400 m compared to 400 m or more from heavily-trafficked major roadways was associated with 11%, 26% and 14% increases in AL score, respectively (95% CIs: -4, 29; 9, 45; -1, 30) for non-white participants compared to 6%, -2%, and -2% changes (95% CIs: -2, 15; -10, 7; -8, 6) for white participants. CONCLUSIONS: Among this population of youth with type 1 diabetes, we did not observe consistent relationships between chronic exposures to particulate and traffic-related air pollution and changes in AL score, however associations for traffic-related pollution exposures may differ by race/ethnicity and warrant further examination.

Trends in Prevalence of Type 1 and Type 2 Diabetes in Children and Adolescents in the US, 2001-2017.

Importance: Changes in the prevalence of youth-onset diabetes have previously been observed. Objective: To estimate changes in prevalence of type 1 and type 2 diabetes in youths in the US from 2001 to 2017. Design, Setting, and Participants: In this cross-sectional observational study, individuals younger than 20 years with physician-diagnosed diabetes were enumerated from 6 areas in the US (4 geographic areas, 1 health plan, and select American Indian reservations) for 2001, 2009, and 2017. Exposures: Calendar year. Main Outcomes and Measures: Estimated prevalence of physician-diagnosed type 1 and type 2 diabetes overall and by race and ethnicity, age, and sex. Results: Among youths 19 years or younger, 4958 of 3.35 million had type 1 diabetes in 2001, 6672 of 3.46 million had type 1 diabetes in 2009, and 7759 of 3.61 million had type 1 diabetes in 2017; among those aged 10 to 19 years, 588 of 1.73 million had type 2 diabetes in 2001, 814 of 1.85 million had type 2 diabetes in 2009, and 1230 of 1.85 million had type 2 diabetes in 2017. The estimated type 1 diabetes prevalence per 1000 youths for those 19 years or younger increased significantly from 1.48 (95% CI, 1.44-1.52) in 2001 to 1.93 (95% CI, 1.88-1.98) in 2009 to 2.15 (95% CI, 2.10-2.20) in 2017, an absolute increase of 0.67 per 1000 youths (95%, CI, 0.64-0.70) and a 45.1% (95% CI, 40.0%-50.4%) relative increase over 16 years. The greatest absolute increases were observed among non-Hispanic White (0.93 per 1000 youths [95% CI, 0.88-0.98]) and non-Hispanic Black (0.89 per 1000 youths [95% CI, 0.88-0.98]) youths. The estimated type 2 diabetes prevalence per 1000 youths aged 10 to 19 years increased significantly from 0.34 (95% CI, 0.31-0.37) in 2001 to 0.46 (95% CI, 0.43-0.49) in 2009 to 0.67 (95% CI, 0.63-0.70) in 2017, an absolute increase of 0.32 per 1000 youths (95% CI, 0.30-0.35) and a 95.3% (95% CI, 77.0%-115.4%) relative increase over 16 years. The greatest absolute increases were observed among non-Hispanic Black (0.85 per 1000 youths [95% CI, 0.74-0.97]) and Hispanic (0.57 per 1000 youths [95% CI, 0.51-0.64]) youths. Conclusions and Relevance: In 6 areas of the US from 2001 to 2017, the estimated prevalence of diabetes among children and adolescents increased for both type 1 and type 2 diabetes.