@article {6819, title = {Genome-wide association study of L-arginine and dimethylarginines reveals novel metabolic pathway for symmetric dimethylarginine.}, journal = {Circ Cardiovasc Genet}, volume = {7}, year = {2014}, month = {2014 Dec}, pages = {864-72}, abstract = {

BACKGROUND: Dimethylarginines (DMA) interfere with nitric oxide formation by inhibiting nitric oxide synthase (asymmetrical DMA [ADMA]) and l-arginine uptake into the cell (ADMA and symmetrical DMA [SDMA]). In prospective clinical studies, ADMA has been characterized as a cardiovascular risk marker, whereas SDMA is a novel marker for renal function and associated with all-cause mortality after ischemic stroke. The aim of the current study was to characterize the environmental and genetic contributions to interindividual variability of these biomarkers.

METHODS AND RESULTS: This study comprised a genome-wide association analysis of 3 well-characterized population-based cohorts (Framingham Heart Study [FHS; n=2992], Gutenberg Health Study [GHS; n=4354], and Multinational Monitoring of Trends and Determinants in Cardiovascular Disease Study [MONICA]/Cooperative Health Research in the Augsburg Area, Augsburg, Bavaria, Germany [KORA] F3 [n=581]) and identified replicated loci (DDAH1, MED23, Arg1, and AGXT2) associated with the interindividual variability in ADMA, l-arginine, and SDMA. Experimental in silico and in vitro studies confirmed functional significance of the identified AGXT2 variants. Clinical outcome analysis in 384 patients of the Leeds stroke study demonstrated an association between increased plasma levels of SDMA, AGXT2 variants, and various cardiometabolic risk factors. AGXT2 variants were not associated with poststroke survival in the Leeds study or were they associated with incident stroke in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium.

CONCLUSIONS: These genome-wide association study support the importance of DDAH1 and MED23/Arg1 in regulating ADMA and l-arginine metabolism, respectively, and identify a novel regulatory renal pathway for SDMA by AGXT2. AGXT2 variants might explain part of the pathogenic link between SDMA, renal function, and outcome. An association between AGXT2 variants and stroke is unclear and warrants further investigation.

}, keywords = {Adult, Aged, Amidohydrolases, Arginine, Binding Sites, Cohort Studies, Female, Genetic Loci, Genome-Wide Association Study, Genotype, HEK293 Cells, Humans, Male, Mediator Complex, Middle Aged, Polymorphism, Single Nucleotide, Protein Structure, Tertiary, Risk Factors, Stroke, Substrate Specificity, Transaminases}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.113.000264}, author = {L{\"u}neburg, Nicole and Lieb, Wolfgang and Zeller, Tanja and Chen, Ming-Huei and Maas, Renke and Carter, Angela M and Xanthakis, Vanessa and Glazer, Nicole L and Schwedhelm, Edzard and Seshadri, Sudha and Ikram, Mohammad Arfan and Longstreth, William T and Fornage, Myriam and K{\"o}nig, Inke R and Loley, Christina and Ojeda, Francisco M and Schillert, Arne and Wang, Thomas J and Sticht, Heinrich and Kittel, Anja and K{\"o}nig, J{\"o}rg and Benjamin, Emelia J and Sullivan, Lisa M and Bernges, Isabel and Anderssohn, Maike and Ziegler, Andreas and Gieger, Christian and Illig, Thomas and Meisinger, Christa and Wichmann, H-Erich and Wild, Philipp S and Schunkert, Heribert and Psaty, Bruce M and Wiggins, Kerri L and Heckbert, Susan R and Smith, Nicholas and Lackner, Karl and Lunetta, Kathryn L and Blankenberg, Stefan and Erdmann, Jeanette and M{\"u}nzel, Thomas and Grant, Peter J and Vasan, Ramachandran S and B{\"o}ger, Rainer H} } @article {8626, title = {Performance of the Pooled Cohort Equations to Estimate Atherosclerotic Cardiovascular Disease Risk by Body Mass Index.}, journal = {JAMA Netw Open}, volume = {3}, year = {2020}, month = {2020 10 01}, pages = {e2023242}, abstract = {

Importance: Obesity is a global health challenge and a risk factor for atherosclerotic cardiovascular disease (ASVCD). Performance of the pooled cohort equations (PCE) for ASCVD risk by body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) is unknown.

Objective: To assess performance of the PCE across clinical BMI categories.

Design, Setting, and Participants: This cohort study used pooled individual-level data from 8 community-based, prospective, longitudinal cohort studies with 10-year ASCVD event follow-up from 1996 to 2016. We included all adults ages 40 to 79 years without baseline ASCVD or statin use, resulting in a sample size of 37 311 participants. Data were analyzed from August 2017 to July 2020.

Exposures: Participant BMI category: underweight (<18.5), normal weight (18.5 to <25), overweight (25 to <30), mild obesity (30 to <35), and moderate to severe obesity (>=35).

Main Outcomes and Measures: Discrimination (Harrell C statistic) and calibration (Nam-D{\textquoteright}Agostino χ2 goodness-of-fit test) of the PCE across BMI categories. Improvement in discrimination and net reclassification with addition of BMI, waist circumference, and high-sensitivity C-reactive protein (hsCRP) to the PCE.

Results: Among 37 311 participants (mean [SD] age, 58.6 [11.8] years; 21 897 [58.7\%] women), 380 604 person-years of follow-up were conducted. Mean (SD) baseline BMI was 29.0 (6.2), and 360 individuals (1.0\%) were in the underweight category, 9937 individuals (26.6\%) were in the normal weight category, 13 601 individuals (36.4\%) were in the overweight category, 7783 individuals (20.9\%) were in the mild obesity category, and 5630 individuals (15.1\%) were in the moderate to severe obesity category. Median (interquartile range [IQR]) 10-year estimated ASCVD risk was 7.1\% (2.5\%-15.4\%), and 3709 individuals (9.9\%) developed ASCVD over a median (IQR) 10.8 [8.5-12.6] years. The PCE overestimated ASCVD risk in the overall cohort (estimated/observed [E/O] risk ratio, 1.22; 95\% CI, 1.18-1.26) and across all BMI categories except the underweight category. Calibration was better near the clinical decision threshold in all BMI groups but worse among individuals with moderate or severe obesity (E/O risk ratio, 1.36; 95\% CI, 1.25-1.47) and among those with the highest estimated ASCVD risk >=20\%. The PCE C statistic overall was 0.760 (95\% CI, 0.753-0.767), with lower discrimination in the moderate or severe obesity group (C statistic, 0.742; 95\% CI, 0.721-0.763) compared with the normal-range BMI group (C statistic, 0.785; 95\% CI, 0.772-0.798). Waist circumference (hazard ratio, 1.07 per 1-SD increase; 95\% CI, 1.03-1.11) and hsCRP (hazard ratio, 1.07 per 1-SD increase; 95\% CI, 1.05-1.09), but not BMI, were associated with increased ASCVD risk when added to the PCE. However, these factors did not improve model performance (C statistic, 0.760; 95\% CI, 0.753-0.767) with or without added metrics.

Conclusions and Relevance: These findings suggest that the PCE had acceptable model discrimination and were well calibrated at clinical decision thresholds but overestimated risk of ASCVD for individuals in overweight and obese categories, particularly individuals with high estimated risk. Incorporation of the usual clinical measures of obesity did not improve risk estimation of the PCE. Future research is needed to determine whether incorporation of alternative high-risk obesity markers (eg, weight trajectory or measures of visceral or ectopic fat) into the PCE may improve risk prediction.

}, keywords = {Adult, Aged, Body Mass Index, Cardiovascular Diseases, Cohort Studies, Correlation of Data, Female, Humans, Longitudinal Studies, Male, Middle Aged, Proportional Hazards Models, Prospective Studies, Risk Assessment, Risk Factors}, issn = {2574-3805}, doi = {10.1001/jamanetworkopen.2020.23242}, author = {Khera, Rohan and Pandey, Ambarish and Ayers, Colby R and Carnethon, Mercedes R and Greenland, Philip and Ndumele, Chiadi E and Nambi, Vijay and Seliger, Stephen L and Chaves, Paulo H M and Safford, Monika M and Cushman, Mary and Xanthakis, Vanessa and Vasan, Ramachandran S and Mentz, Robert J and Correa, Adolfo and Lloyd-Jones, Donald M and Berry, Jarett D and de Lemos, James A and Neeland, Ian J} } @article {9255, title = {Plasma proteomic signature of decline in gait speed and grip strength.}, journal = {Aging Cell}, volume = {21}, year = {2022}, month = {2022 Dec}, pages = {e13736}, abstract = {

The biological mechanisms underlying decline in physical function with age remain unclear. We examined the plasma proteomic profile associated with longitudinal changes in physical function measured by gait speed and grip strength in community-dwelling adults. We applied an aptamer-based platform to assay 1154 plasma proteins on 2854 participants (60\% women, aged 76 years) in the Cardiovascular Health Study (CHS) in 1992-1993 and 1130 participants (55\% women, aged 54 years) in the Framingham Offspring Study (FOS) in 1991-1995. Gait speed and grip strength were measured annually for 7 years in CHS and at cycles 7 (1998-2001) and 8 (2005-2008) in FOS. The associations of individual protein levels (log-transformed and standardized) with longitudinal changes in gait speed and grip strength in two populations were examined separately by linear mixed-effects models. Meta-analyses were implemented using random-effects models and corrected for multiple testing. We found that plasma levels of 14 and 18 proteins were associated with changes in gait speed and grip strength, respectively (corrected p~< 0.05). The proteins most strongly associated with gait speed decline were GDF-15 (Meta-analytic p~= 1.58 {\texttimes} 10 ), pleiotrophin (1.23 {\texttimes} 10 ), and TIMP-1 (5.97 {\texttimes} 10 ). For grip strength decline, the strongest associations were for carbonic anhydrase III (1.09 {\texttimes} 10 ), CDON (2.38 {\texttimes} 10 ), and SMOC1 (7.47 {\texttimes} 10 ). Several statistically significant proteins are involved in the inflammatory responses or antagonism of activin by follistatin pathway. These novel proteomic biomarkers and pathways should be further explored as future mechanisms and targets for age-related functional decline.

}, keywords = {Adult, Female, Gait, Hand Strength, Humans, Independent Living, Male, Proteomics, Walking Speed}, issn = {1474-9726}, doi = {10.1111/acel.13736}, author = {Liu, Xiaojuan and Pan, Stephanie and Xanthakis, Vanessa and Vasan, Ramachandran S and Psaty, Bruce M and Austin, Thomas R and Newman, Anne B and Sanders, Jason L and Wu, Chenkai and Tracy, Russell P and Gerszten, Robert E and Odden, Michelle C} }