@article {1399, title = {Lipid-related markers and cardiovascular disease prediction.}, journal = {JAMA}, volume = {307}, year = {2012}, month = {2012 Jun 20}, pages = {2499-506}, abstract = {

CONTEXT: The value of assessing various emerging lipid-related markers for prediction of first cardiovascular events is debated.

OBJECTIVE: To determine whether adding information on apolipoprotein B and apolipoprotein A-I, lipoprotein(a), or lipoprotein-associated phospholipase A2 to total cholesterol and high-density lipoprotein cholesterol (HDL-C) improves cardiovascular disease (CVD) risk prediction.

DESIGN, SETTING, AND PARTICIPANTS: Individual records were available for 165,544 participants without baseline CVD in 37 prospective cohorts (calendar years of recruitment: 1968-2007) with up to 15,126 incident fatal or nonfatal CVD outcomes (10,132 CHD and 4994 stroke outcomes) during a median follow-up of 10.4 years (interquartile range, 7.6-14 years).

MAIN OUTCOME MEASURES: Discrimination of CVD outcomes and reclassification of participants across predicted 10-year risk categories of low (<10\%), intermediate (10\%-<20\%), and high (>=20\%) risk.

RESULTS: The addition of information on various lipid-related markers to total cholesterol, HDL-C, and other conventional risk factors yielded improvement in the model{\textquoteright}s discrimination: C-index change, 0.0006 (95\% CI, 0.0002-0.0009) for the combination of apolipoprotein B and A-I; 0.0016 (95\% CI, 0.0009-0.0023) for lipoprotein(a); and 0.0018 (95\% CI, 0.0010-0.0026) for lipoprotein-associated phospholipase A2 mass. Net reclassification improvements were less than 1\% with the addition of each of these markers to risk scores containing conventional risk factors. We estimated that for 100,000 adults aged 40 years or older, 15,436 would be initially classified at intermediate risk using conventional risk factors alone. Additional testing with a combination of apolipoprotein B and A-I would reclassify 1.1\%; lipoprotein(a), 4.1\%; and lipoprotein-associated phospholipase A2 mass, 2.7\% of people to a 20\% or higher predicted CVD risk category and, therefore, in need of statin treatment under Adult Treatment Panel III guidelines.

CONCLUSION: In a study of individuals without known CVD, the addition of information on the combination of apolipoprotein B and A-I, lipoprotein(a), or lipoprotein-associated phospholipase A2 mass to risk scores containing total cholesterol and HDL-C led to slight improvement in CVD prediction.

}, keywords = {Aged, Biomarkers, Cardiovascular Diseases, Cholesterol, HDL, Cohort Studies, Female, Humans, Lipoproteins, Male, Middle Aged, Risk Assessment}, issn = {1538-3598}, doi = {10.1001/jama.2012.6571}, author = {Di Angelantonio, Emanuele and Gao, Pei and Pennells, Lisa and Kaptoge, Stephen and Caslake, Muriel and Thompson, Alexander and Butterworth, Adam S and Sarwar, Nadeem and Wormser, David and Saleheen, Danish and Ballantyne, Christie M and Psaty, Bruce M and Sundstr{\"o}m, Johan and Ridker, Paul M and Nagel, Dorothea and Gillum, Richard F and Ford, Ian and Ducimetiere, Pierre and Kiechl, Stefan and Koenig, Wolfgang and Dullaart, Robin P F and Assmann, Gerd and D{\textquoteright}Agostino, Ralph B and Dagenais, Gilles R and Cooper, Jackie A and Kromhout, Daan and Onat, Altan and Tipping, Robert W and G{\'o}mez-de-la-C{\'a}mara, Agust{\'\i}n and Rosengren, Annika and Sutherland, Susan E and Gallacher, John and Fowkes, F Gerry R and Casiglia, Edoardo and Hofman, Albert and Salomaa, Veikko and Barrett-Connor, Elizabeth and Clarke, Robert and Brunner, Eric and Jukema, J Wouter and Simons, Leon A and Sandhu, Manjinder and Wareham, Nicholas J and Khaw, Kay-Tee and Kauhanen, Jussi and Salonen, Jukka T and Howard, William J and Nordestgaard, B{\o}rge G and Wood, Angela M and Thompson, Simon G and Boekholdt, S Matthijs and Sattar, Naveed and Packard, Chris and Gudnason, Vilmundur and Danesh, John} } @article {6238, title = {Age- and sex-dependent upper reference limits for the high-sensitivity cardiac troponin T assay.}, journal = {J Am Coll Cardiol}, volume = {63}, year = {2014}, month = {2014 Apr 15}, pages = {1441-8}, abstract = {

OBJECTIVES: The study sought to determine the 99th percentile upper reference limit for the high-sensitivity cardiac troponin T assay (hs-cTnT) in 3 large independent cohorts.

BACKGROUND: The presently recommended 14 ng/l cut point for the diagnosis of myocardial infarction using the hs-cTnT assay was derived from small studies of presumably healthy individuals, with relatively little phenotypic characterization.

METHODS: Data were included from 3 well-characterized population-based studies: the Dallas Heart Study (DHS), the Atherosclerosis Risk in Communities (ARIC) Study, and the Cardiovascular Health Study (CHS). Within each cohort, reference subcohorts were defined excluding individuals with recent hospitalization, overt cardiovascular disease, and kidney disease (subcohort 1), and further excluding those with subclinical structural heart disease (subcohort 2). Data were analyzed stratified by age, sex, and race.

RESULTS: The 99th percentile values for the hs-cTnT assay in DHS, ARIC, and CHS were 18, 22, and 36 ng/l (subcohort 1) and 14, 21, and 28 ng/l (subcohort 2), respectively. These differences in 99th percentile values paralleled age differences across cohorts. Analyses within sex/age strata yielded similar results between cohorts. Within each cohort, 99th percentile values increased with age and were higher in men. More than 10\% of men 65 to 74 years of age with no cardiovascular disease in our study had cardiac troponin T values above the current myocardial infarction threshold.

CONCLUSIONS: Use of a uniform 14 ng/l cutoff for the hs-cTnT assay may lead to over-diagnosis of myocardial infarction, particularly in men and the elderly. Clinical validation is needed of new age- and sex-specific cutoff values for this assay.

}, keywords = {Adult, Age Factors, Aged, Biological Assay, Biomarkers, Blood Chemical Analysis, Cohort Studies, Cross-Sectional Studies, Female, Humans, Male, Middle Aged, Myocardial Infarction, Reference Values, Risk Assessment, Sensitivity and Specificity, Severity of Illness Index, Sex Factors, Troponin T}, issn = {1558-3597}, doi = {10.1016/j.jacc.2013.12.032}, author = {Gore, M Odette and Seliger, Stephen L and deFilippi, Christopher R and Nambi, Vijay and Christenson, Robert H and Hashim, Ibrahim A and Hoogeveen, Ron C and Ayers, Colby R and Sun, Wensheng and McGuire, Darren K and Ballantyne, Christie M and de Lemos, James A} } @article {6577, title = {Whole-exome sequencing identifies rare and low-frequency coding variants associated with LDL cholesterol.}, journal = {Am J Hum Genet}, volume = {94}, year = {2014}, month = {2014 Feb 06}, pages = {233-45}, abstract = {

Elevated low-density lipoprotein cholesterol (LDL-C) is a treatable, heritable risk factor for cardiovascular disease. Genome-wide association studies (GWASs) have identified 157 variants associated with lipid levels but are not well suited to assess the impact of rare and low-frequency variants. To determine whether rare or low-frequency coding variants are associated with LDL-C, we exome sequenced 2,005 individuals, including 554 individuals selected for extreme LDL-C (>98(th) or <2(nd) percentile). Follow-up analyses included sequencing of 1,302 additional individuals and genotype-based analysis of 52,221 individuals. We observed significant evidence of association between LDL-C and the burden of rare or low-frequency variants in PNPLA5, encoding a phospholipase-domain-containing protein, and both known and previously unidentified variants in PCSK9, LDLR and APOB, three known lipid-related genes. The effect sizes for the burden of rare variants for each associated gene were substantially higher than those observed for individual SNPs identified from GWASs. We replicated the PNPLA5 signal in an independent large-scale sequencing study of 2,084 individuals. In conclusion, this large whole-exome-sequencing study for LDL-C identified a gene not known to be implicated in LDL-C and provides unique insight into the design and analysis of similar experiments.

}, keywords = {Adult, Aged, Apolipoproteins E, Cholesterol, LDL, Cohort Studies, Dyslipidemias, Exome, Female, Follow-Up Studies, Gene Frequency, Genetic Code, Genome-Wide Association Study, Genotype, Humans, Lipase, Male, Middle Aged, Phenotype, Polymorphism, Single Nucleotide, Proprotein Convertase 9, Proprotein Convertases, Receptors, LDL, Sequence Analysis, DNA, Serine Endopeptidases}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2014.01.010}, author = {Lange, Leslie A and Hu, Youna and Zhang, He and Xue, Chenyi and Schmidt, Ellen M and Tang, Zheng-Zheng and Bizon, Chris and Lange, Ethan M and Smith, Joshua D and Turner, Emily H and Jun, Goo and Kang, Hyun Min and Peloso, Gina and Auer, Paul and Li, Kuo-Ping and Flannick, Jason and Zhang, Ji and Fuchsberger, Christian and Gaulton, Kyle and Lindgren, Cecilia and Locke, Adam and Manning, Alisa and Sim, Xueling and Rivas, Manuel A and Holmen, Oddgeir L and Gottesman, Omri and Lu, Yingchang and Ruderfer, Douglas and Stahl, Eli A and Duan, Qing and Li, Yun and Durda, Peter and Jiao, Shuo and Isaacs, Aaron and Hofman, Albert and Bis, Joshua C and Correa, Adolfo and Griswold, Michael E and Jakobsdottir, Johanna and Smith, Albert V and Schreiner, Pamela J and Feitosa, Mary F and Zhang, Qunyuan and Huffman, Jennifer E and Crosby, Jacy and Wassel, Christina L and Do, Ron and Franceschini, Nora and Martin, Lisa W and Robinson, Jennifer G and Assimes, Themistocles L and Crosslin, David R and Rosenthal, Elisabeth A and Tsai, Michael and Rieder, Mark J and Farlow, Deborah N and Folsom, Aaron R and Lumley, Thomas and Fox, Ervin R and Carlson, Christopher S and Peters, Ulrike and Jackson, Rebecca D and van Duijn, Cornelia M and Uitterlinden, Andr{\'e} G and Levy, Daniel and Rotter, Jerome I and Taylor, Herman A and Gudnason, Vilmundur and Siscovick, David S and Fornage, Myriam and Borecki, Ingrid B and Hayward, Caroline and Rudan, Igor and Chen, Y Eugene and Bottinger, Erwin P and Loos, Ruth J F and S{\ae}trom, P{\r a}l and Hveem, Kristian and Boehnke, Michael and Groop, Leif and McCarthy, Mark and Meitinger, Thomas and Ballantyne, Christie M and Gabriel, Stacey B and O{\textquoteright}Donnell, Christopher J and Post, Wendy S and North, Kari E and Reiner, Alexander P and Boerwinkle, Eric and Psaty, Bruce M and Altshuler, David and Kathiresan, Sekar and Lin, Dan-Yu and Jarvik, Gail P and Cupples, L Adrienne and Kooperberg, Charles and Wilson, James G and Nickerson, Deborah A and Abecasis, Goncalo R and Rich, Stephen S and Tracy, Russell P and Willer, Cristen J} } @article {9804, title = {Sociodemographic, lifestyle, and medical factors associated with calculated free testosterone concentrations in men: individual participant data meta-analyses.}, journal = {Eur J Endocrinol}, volume = {191}, year = {2024}, month = {2024 Oct 29}, pages = {523-534}, abstract = {

OBJECTIVE: Sociodemographic, lifestyle, and medical variables influence total testosterone (T) and sex hormone-binding globulin (SHBG) concentrations. The relationship between these factors and "free" T remains unclear. We examined 21 sociodemographic, lifestyle, and medical predictors influencing calculated free T (cFT) in community-dwelling men across ages.

DESIGN: This is a cross-sectional analysis in 20 631 participants in the Androgens in Men Study.

METHODS: Individual participant data (IPD) were provided by 9 cohorts. Total T was determined using mass spectrometry, SHBG using immunoassays, and cFT using the Vermeulen formula. Associations were analyzed using 2-stage random effects IPD meta-analyses.

RESULTS: Cohort median ages ranged from 40 to 76 years and median cFT concentrations from 174.3 to 422.8 pmol/L. In men aged 17-99 years, there was a linear inverse association of cFT with age (-57.2 pmol/L [95\% confidence interval, -69.4, -44.9] per 1 SD increase in age). Calculated free T increased with increasing baseline body mass index (BMI) among men with BMI < 23.6 kg/m2, but decreased among men with BMI > 23.6 kg/m2 (-24.7 pmol/L [-29.1, -20.3] per 1 SD increase in the 25.4-29.6 kg/m2 BMI range). Calculated free T was lower in younger men, who were married or in a de facto relationship (-18.4 pmol/L [-27.6, -9.3]) and in men who formerly smoked (-5.7 pmol/L [-8.9, -2.6]), were in poor general health (-14.0 pmol/L [-20.1, -7.8]), and had diabetes (-19.6 pmol/L [-23.0, -16.3]), cardiovascular disease (-5.8 pmol/L [-8.3, -3.2]), or cancer (-19.2 pmol/L [-24.4, -14.1]).

CONCLUSIONS: Calculated free T was most prominently associated with age and BMI. The linear, inverse association with age, nonlinear association with BMI, and presence of diabetes, cancer, and sociodemographic factors should be considered when interpreting cFT values.

}, keywords = {Adolescent, Adult, Age Factors, Aged, Aged, 80 and over, Body Mass Index, Cohort Studies, Cross-Sectional Studies, Humans, Life Style, Male, Middle Aged, Sex Hormone-Binding Globulin, Sociodemographic Factors, Socioeconomic Factors, Testosterone, Young Adult}, issn = {1479-683X}, doi = {10.1093/ejendo/lvae133}, author = {Narinx, Nick and Marriott, Ross J and Murray, Kevin and Adams, Robert J and Ballantyne, Christie M and Bauer, Douglas C and Bhasin, Shalender and Biggs, Mary L and Cawthon, Peggy M and Couper, David J and Dobs, Adrian S and Flicker, Leon and Hankey, Graeme J and Hannemann, Anke and Wilkening, Robin and Martin, Sean A and Matsumoto, Alvin M and Ohlsson, Claes and O{\textquoteright}Neill, Terence W and Orwoll, Eric S and Shores, Molly M and Steveling, Antje and Travison, Thomas G and Wittert, Gary A and Wu, Frederick C W and Antonio, Leen and Vanderschueren, Dirk and Yeap, Bu B} }