Larson, Nicholas B.

Key Points Common kidney stones are unlikely to be an independent and direct cause of CKD in the general population. CKD may protect against kidney stones because of changes in key urinary factors critical for stone formation. Background Kidney stones and CKD are common disorders with a substantial interaction. Although observational studies have suggested a potential for enhanced CKD risk after prior kidney stones, the exact relationship remains ambiguous. Methods Shared comorbidities between two diseases were identified using unbiased screening. Genome-wide association study summary statistics were obtained from the UK Biobank (UKBB), FinnGen, and CKDGen, followed by genetic association analyses across various traits. Bidirectional Mendelian randomization (MR) analyses were performed to define causal links, complemented by multivariable MR that included the shared comorbidities including hypertension, diabetes, and obesity. Observational analyses were undertaken using cohorts from the Mayo Clinic and a UKBB subset. Results Despite identifying a total of 123 conditions as shared comorbidities, there was no significant genetic correlation between kidney stones and CKD. Unadjusted MR analysis revealed no significant association between kidney stones and CKD risk (UKBB [exposure]/FinnGen [outcome]: odds ratio [OR]=0.97, 95% confidence interval [CI], 0.88 to 1.06; FinnGen/UKBB: OR=1.17, 95% CI, 0.98 to 1.39). Kidney stones did significantly associate with a higher urinary albumin-creatinine ratio ( β =0.014, 95% CI, 0.002 to –0.025), but this association disappeared in the multivariable MR model ( β =0.009, 95% CI, −0.003 to 0.020). Furthermore, in a cross-sectional analysis limited to the UKBB cohort, a robust regression model did not detect an independent association between kidney stones and urinary albumin-creatinine ratio ( β =0.16, 95% CI, −0.04 to 0.35) or eGFR ( β =0.10, 95% CI, −0.07 to 0.28). Conversely, CKD associated with a diminished risk of kidney stones in multivariable MR models (UKBB/FinnGen: OR=0.77, 95% CI, 0.69 to 0.87; FinnGen/UKBB: OR=0.73, 95% CI, 0.66 to 0.81). Furthermore, in the Mayo Clinic cohort with available urinary biochemistries, lower eGFR was associated with lower urinary calcium excretion and urinary calcium oxalate/phosphate supersaturation. Conclusions In this study, kidney stones were not independently associated with CKD. Conversely, CKD was associated with a lower risk of calcium kidney stones likely via changes in key urinary traits, including lower calcium excretion.

PURPOSE The autosomal dominant cancer predisposition disorders hereditary breast and ovarian cancer (HBOC) and Lynch syndrome (LS) are genetic conditions for which early identification and intervention have a positive effect on the individual and public health. The goals of this study were to determine whether germline genetic screening using exome sequencing could be used to efficiently identify carriers of HBOC and LS. METHODS Participants were recruited from three geographically and racially diverse sites in the United States (Rochester, MN; Phoenix, AZ; Jacksonville, FL). Participants underwent Exome+ sequencing (Helix Inc, San Mateo, CA) and return of results for specific genetic findings: HBOC ( BRCA1 and BRCA1) and LS ( MLH1, MSH2, MSH6, PMS2, and EPCAM). Chart review was performed to collect demographics and personal and family cancer history. RESULTS To date, 44,306 participants have enrolled in Tapestry. Annotation and interpretation of all variants in genes for HBOC and LS resulted in the identification of 550 carriers (prevalence, 1.24%), which included 387 with HBOC (27.2% BRCA1, 42.8% BRCA2) and 163 with LS (12.3% MSH6, 8.8% PMS2, 4.5% MLH1, 3.8% MSH2, and 0.2% EPCAM). More than half of these participants (52.1%) were newly diagnosed carriers with HBOC and LS. In all, 39.2% of HBOC/LS carriers did not satisfy National Comprehensive Cancer Network (NCCN) criteria for genetic evaluation. NCCN criteria were less commonly met in underrepresented minority populations versus self-reported White race (51.5% v 37.5%, P = .028). CONCLUSION Our results emphasize the need for wider utilization of germline genetic sequencing for enhanced screening and detection of individuals who have LS and HBOC cancer predisposition syndromes.

Background Clinical risk scores are used to identify those at high risk of atherosclerotic cardiovascular disease (ASCVD). Despite preventative efforts, residual risk remains for many individuals. Very low‐density lipoprotein cholesterol (VLDL‐C) and lipid discordance could be contributors to the residual risk of ASCVD. Methods and Results Cardiovascular disease–free residents, aged ≥40 years, living in Olmsted County, Minnesota, were identified through the Rochester Epidemiology Project. Low‐density lipoprotein cholesterol (LDL‐C) and VLDL‐C were estimated from clinically ordered lipid panels using the Sampson equation. Participants were categorized into concordant and discordant lipid pairings based on clinical cut points. Rates of incident ASCVD, including percutaneous coronary intervention, coronary artery bypass grafting, stroke, or myocardial infarction, were calculated during follow‐up. The association of LDL‐C and VLDL‐C with ASCVD was assessed using Cox proportional hazards regression. Interaction between LDL‐C and VLDL‐C was assessed. The study population (n=39 098) was primarily White race (94%) and female sex (57%), with a mean age of 54 years. VLDL‐C (per 10‐mg/dL increase) was significantly associated with an increased risk of incident ASCVD (hazard ratio, 1.07 [95% CI, 1.05–1.09]; P <0.001]) after adjustment for traditional risk factors. The interaction between LDL‐C and VLDL‐C was not statistically significant ( P =0.11). Discordant individuals with high VLDL‐C and low LDL‐C experienced the highest rate of incident ASCVD events, 16.9 per 1000 person‐years, during follow‐up. Conclusions VLDL‐C and lipid discordance are associated with a greater risk of ASCVD and can be estimated from clinically ordered lipid panels to improve ASCVD risk assessment.

BACKGROUND Diagnosis of PMM2-CDG, the most common congenital disorder of glycosylation (CDG), relies on measuring carbohydrate-deficient transferrin (CDT) and genetic testing. CDT tests have false negatives and may normalize with age. Site-specific changes in protein N-glycosylation have not been reported in sera in PMM2-CDG. METHODS Using multistep mass spectrometry–based N-glycoproteomics, we analyzed sera from 72 individuals to discover and validate glycopeptide alterations. We performed comprehensive tandem mass tag–based discovery experiments in well-characterized patients and controls. Next, we developed a method for rapid profiling of additional samples. Finally, targeted mass spectrometry was used for validation in an independent set of samples in a blinded fashion. RESULTS Of the 3,342 N-glycopeptides identified, patients exhibited decrease in complex-type N-glycans and increase in truncated, mannose-rich, and hybrid species. We identified a glycopeptide from complement C4 carrying the glycan Man 5 GlcNAc 2 , which was not detected in controls, in 5 patients with normal CDT results, including 1 after liver transplant and 2 with a known genetic variant associated with mild disease, indicating greater sensitivity than CDT. It was detected by targeted analysis in 2 individuals with variants of uncertain significance in PMM2 . CONCLUSION Complement C4–derived Man 5 GlcNAc 2 glycopeptide could be a biomarker for accurate diagnosis and therapeutic monitoring of patients with PMM2-CDG and other CDGs. FUNDING U54NS115198 (Frontiers in Congenital Disorders of Glycosylation: NINDS; NCATS; Eunice Kennedy Shriver NICHD; Rare Disorders Consortium Disease Network); K08NS118119 (NINDS); Minnesota Partnership for Biotechnology and Medical Genomics; Rocket Fund; R01DK099551 (NIDDK); Mayo Clinic DERIVE Office; Mayo Clinic Center for Biomedical Discovery; IA/CRC/20/1/600002 (Center for Rare Disease Diagnosis, Research and Training; DBT/Wellcome Trust India Alliance)

Background Frailty is common in heart failure (HF) and is associated with death but not routinely captured clinically. Frailty is linked with inflammation and malnutrition, which can be assessed by a novel plasma multimarker score: the metabolic vulnerability index (MVX). We sought to evaluate the associations between frailty and MVX and their prognostic impact. Methods and Results In an HF community cohort (2003–2012), we measured frailty as a proportion of deficits present out of 32 physical limitations and comorbidities, MVX by nuclear magnetic resonance spectroscopy, and collected extensive longitudinal clinical data. Patients were categorized by frailty score (≤0.14, >0.14 and ≤0.27, >0.27) and MVX score (≤50, >50 and ≤60, >60 and ≤70, >70). Cox models estimated associations of frailty and MVX with death, adjusted for Meta‐Analysis Global Group in Chronic Heart Failure (MAGGIC) score and NT‐proBNP (N‐terminal pro‐B‐type natriuretic peptide). Uno's C‐statistic measured the incremental value of MVX beyond frailty and clinical factors. Weibull's accelerated failure time regression assessed whether MVX mediated the association between frailty and death. We studied 985 patients (median age, 77; 48% women). Frailty and MVX were weakly correlated (Spearman's ρ=0.21). The highest frailty group experienced an increased rate of death, independent of MVX, MAGGIC score, and NT‐proBNP (hazard ratio, 3.3 [95% CI, 2.5–4.2]). Frailty improved Uno's c‐statistic beyond MAGGIC score and NT‐proBNP (0.69–0.73). MVX only mediated 3.3% and 4.5% of the association between high and medium frailty groups and death, respectively. Conclusions In this HF cohort, frailty and MVX are weakly correlated. Both independently contribute to stratifying the risk of death, suggesting that they capture distinct domains of vulnerability in HF.

BACKGROUND: Heart failure is heterogeneous syndrome with persistently high mortality. Nuclear magnetic resonance spectroscopy enables high-throughput metabolomics, suitable for precision phenotyping. We aimed to use targeted metabolomics to derive a metabolic risk score (MRS) that improved mortality risk stratification in heart failure. METHODS: Nuclear magnetic resonance was used to measure 21 metabolites (lipoprotein subspecies, branched-chain amino acids, alanine, GlycA (glycoprotein acetylation), ketone bodies, glucose, and citrate) in plasma collected from a heart failure community cohort. The MRS was derived using least absolute shrinkage and selection operator penalized Cox regression and temporal validation. The association between the MRS and mortality and whether risk stratification was improved over the Meta-Analysis Global Group in Chronic Heart Failure clinical risk score and NT-proBNP (N-terminal pro-B-type natriuretic peptide) levels were assessed. RESULTS: The study included 1382 patients (median age, 78 years, 52% men, 43% reduced ejection fraction) with a 5-year survival rate of 48% (95% CI, 46%–51%). The MRS included 9 metabolites measured. In the validation data set, a 1 standard deviation increase in the MRS was associated with a large increased rate of death (hazard ratio, 2.2 [95% CI, 1.9–2.5]) that remained after adjustment for Meta-Analysis Global Group in Chronic Heart Failure score and NT-proBNP (hazard ratio, 1.6 [95% CI, 1.3–1.9]). These associations did not differ by ejection fraction. The integrated discrimination and net reclassification indices, and Uno’s C statistic, indicated that the addition of the MRS improved discrimination over Meta-Analysis Global Group in Chronic Heart Failure and NT-proBNP. CONCLUSIONS: This MRS developed in a heart failure community cohort was associated with a large excess risk of death and improved risk stratification beyond an established risk score and clinical markers.

Background Although VCAM‐1 (vascular cell adhesion molecule‐1) and ICAM‐1 (intercellular adhesion molecule‐1) have been associated with incident heart failure with preserved ejection fraction (HFpEF) and atrial fibrillation (AF), the associations of VCAM‐1 and ICAM‐1 with sensitive measures of cardiac structure/function are unclear. The objective of this study is to evaluate associations between VCAM‐1, ICAM‐1, and measures of cardiac structure and function as potential pathways through which cellular adhesion molecules promote HFpEF and AF risk. Methods and Results In MESA (Multi‐Ethnic Study of Atherosclerosis), we evaluated the associations of circulating VCAM‐1 and ICAM‐1 at examination 2 (2002–2004) with measures of cardiac structure/function on cardiac magnetic resonance imaging at examination 5 (2010–2011) after multivariable adjustment. Mediation analysis of left atrial (LA) strain on the association between VCAM‐1 or ICAM‐1 and AF or HFpEF was also performed. Overall, 2304 individuals (63±10 years; 47% men) with VCAM‐1 or ICAM‐1, cardiac magnetic resonance imaging, and covariate data were included in analysis. Higher VCAM‐1 and ICAM‐1 were associated with lower LA peak longitudinal strain and worse global circumferential left ventricular strain but were not associated with left ventricular myocardial scar or interstitial fibrosis. Lower LA peak longitudinal strain mediated 8% (95% CI, 2–30) of the relationship between VCAM‐1 and HFpEF and 9% (95% CI, 2–21) of the relationship between VCAM‐1 and AF. Conclusions Higher VCAM‐1 and ICAM‐1 were associated with lower LA function and left ventricular systolic function but were not associated with myocardial scar or interstitial fibrosis. VCAM‐1 and ICAM‐1 may promote HFpEF and AF risk through impaired LA reservoir function.

Abstract Background Accurate assessment of axillary lymph nodes (ALNs) is a critical step for timely diagnosis of metastasis and proper subsequent intervention in breast cancer patients. Herein, we compare the diagnostic utility of quantitative high-definition microvasculature imaging (qHDMI), shear wave elastography (SWE) and their combination for differentiation of metastatic ALNs from reactive. Methods A total of 85 female patients with suspicious ALNs recommended for fine needle aspiration biopsy (FNAB) were included in the study, and the pathology results were used as the gold standard for labeling the status of each ALN. Three SWE metrics and ten qHDMI-derived biomarkers were used in our analyses. Additionally, age, as well as clinical ultrasound features such as nodal size and cortical thickness were included as clinical factors. The Wilcoxon rank-sum test was utilized to analyze distributional differences in biomarkers between metastatic and reactive ALNs. Multiple elastic-net logistic regression models were developed based on varying combinations of clinical, qHDMI, and SWE feature sets. A 70%/30% train/test split was adopted, and ROC curve analyses were performed to evaluate and compare classification performance. Moreover, distributional differences in qHDMI and SWE biomarkers between ALNs corresponding to breast cancer immunohistochemical subtypes luminal A and B were investigated. Results Of the total of 85 ALNs included in the analysis, 42 were metastatic. Statistically significant (p-value < 0.05) differences were observed in all but one of the qHDMI biomarkers, as well as all the SWE metrics. Test-set discrimination defined by area under ROC curve (AUC) was low for the model using only clinical features (0.62; 95% CI = [0.39,0.84]), with higher performance observed for models using SWE only (0.93; [0.82,1.00]), qHDMI only (0.97; [0.91,1.00]), qHDMI-SWE (0.97; [0.92,1.00]), and qHDMI-SWE plus clinical biomarkers (0.98; [0.94,1.00]). No statistically significant improvements were seen in the combined SWE-qHDMI and SWE-qHDMI-C classification models relative to the qHDMI-only model, although power for comparison was limited. Four qHDMI biomarkers and two SWE measures exhibited statistically significant distributions among breast cancer luminal A and B subtypes. Conclusions qHDMI classification model was able to separate metastatic from reactive ALNs with high accuracy. qHDMI, SWE, and the combined models had improved classification performance over the baseline Clinical model. qHDMI biomarkers can be valuable in determining the malignancy status of suspicious ALNs, providing helpful information regarding breast cancer prognosis.