02980nas a2200433 4500008004100000022001400041245009400055210006900149260001600218300001400234490000800248520176800256653001402024653000902038653002202047653002802069653001102097653003002108653003102138653001102169653001102180653000902191653001602200653001302216653003302229653001702262100001802279700002002297700002102317700002202338700002002360700003002380700002002410700001902430700002202449700002102471700001802492856003602510 2017 eng d a1945-719700aFibroblast Growth Factor 23, Mineral Metabolism, and Adiposity in Normal Kidney Function.0 aFibroblast Growth Factor 23 Mineral Metabolism and Adiposity in c2017 Apr 01 a1387-13950 v1023 a
Context: Obesity is associated with poor bone mineralization and quality. Fibroblast growth factor 23 (FGF23) plays an important role in skeletal physiology.
Objective: To test hypothesis that greater adiposity results in higher FGF23 levels among individuals with normal estimated glomerular filtration rate (eGFR).
Design, Setting, Participants: Cross-sectional analyses among participants with eGFR ≥60 mL/min/1.73m2. We assessed the association between crude [body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR); n = 5610] and refined (abdominal adipose tissue area by computed tomography; n = 1313) measures of adiposity and FGF23 using multivariable linear regression.
Main Outcome Measure: Serum FGF23.
Results: FGF23 was higher across BMI categories (BMI <25: 37.7; BMI 25 to 29.99: 38.7; BMI 30 to 39.99: 39.8; BMI ≥40: 40.9 pg/mL, unadjusted P trend < 0.0001). The association between BMI and FGF23 was independent of known confounders of FGF23 (adjusted β = +7.2% higher FGF23 per 10 kg/m2; P < 0.0001). Similar results were observed using WC and WHR. Abdominal adipose tissue area was also independently associated with higher FGF23 (P < 0.01). Notably, the positive associations between FGF23 and adiposity were observed despite the fact that eGFR did not decline and serum phosphate levels did not increase with adiposity.
Conclusion: In a large cohort with normal kidney function, adiposity was associated with higher FGF23 levels independent of known confounders, including eGFR and phosphate. Further studies are needed to evaluate the causes of higher FGF23 in settings of greater adiposity and the potential impact on skeletal health.
10aAdiposity10aAged10aAged, 80 and over10aCross-Sectional Studies10aFemale10aFibroblast Growth Factors10aGlomerular Filtration Rate10aHumans10aKidney10aMale10aMiddle Aged10aMinerals10aRenal Insufficiency, Chronic10aRisk Factors1 aZaheer, Sarah1 ade Boer, Ian, H1 aAllison, Matthew1 aBrown, Jenifer, M1 aPsaty, Bruce, M1 aRobinson-Cohen, Cassianne1 aMichos, Erin, D1 aIx, Joachim, H1 aKestenbaum, Bryan1 aSiscovick, David1 aVaidya, Anand uhttps://chs-nhlbi.org/node/760103411nas a2200541 4500008004100000022001400041245007900055210006900134260001600203520185300219100002202072700002002094700002102114700001502135700002102150700001902171700003102190700002202221700002202243700001802265700002002283700002302303700002102326700002102347700001902368700001502387700002702402700002002429700002002449700002302469700002102492700002002513700002402533700001902557700002102576700002202597700002202619700001702641700002502658700001902683700002202702700002202724700002302746700002402769700002002793700002002813856003602833 2017 eng d a1879-084400aPredictors and outcomes of heart failure with mid-range ejection fraction.0 aPredictors and outcomes of heart failure with midrange ejection c2017 Dec 113 aAIMS: While heart failure with preserved (HFpEF) and reduced ejection fraction (HFrEF) are well described, determinants and outcomes of heart failure with mid-range ejection fraction (HFmrEF) remain unclear. We sought to examine clinical and biochemical predictors of incident HFmrEF in the community.
METHODS AND RESULTS: We pooled data from four community-based longitudinal cohorts, with ascertainment of new heart failure (HF) classified into HFmrEF [ejection fraction (EF) 41-49%], HFpEF (EF ≥50%), and HFrEF (EF ≤40%). Predictors of incident HF subtypes were assessed using multivariable Cox models. Among 28 820 participants free of HF followed for a median of 12 years, there were 200 new HFmrEF cases, compared with 811 HFpEF and 1048 HFrEF. Clinical predictors of HFmrEF included age, male sex, systolic blood pressure, diabetes mellitus, and prior myocardial infarction (multivariable adjusted P ≤ 0.003 for all). Biomarkers that predicted HFmrEF included natriuretic peptides, cystatin-C, and high-sensitivity troponin (P ≤ 0.0004 for all). Natriuretic peptides were stronger predictors of HFrEF [hazard ratio (HR) 2.00 per 1 standard deviation increase, 95% confidence interval (CI) 1.81-2.20] than of HFmrEF (HR 1.51, 95% CI 1.20-1.90, P = 0.01 for difference), and did not differ in their association with incident HFmrEF and HFpEF (HR 1.56, 95% CI 1.41-1.73, P = 0.68 for difference). All-cause mortality following the onset of HFmrEF was worse than that of HFpEF (50 vs. 39 events per 1000 person-years, P = 0.02), but comparable to that of HFrEF (46 events per 1000 person-years, P = 0.78).
CONCLUSIONS: We found overlap in predictors of incident HFmrEF with other HF subtypes. In contrast, mortality risk after HFmrEF was worse than HFpEF, and similar to HFrEF.
1 aBhambhani, Vijeta1 aKizer, Jorge, R1 aLima, João, A C1 aHarst, Pim1 aBahrami, Hossein1 aNayor, Matthew1 ade Filippi, Christopher, R1 aEnserro, Danielle1 aBlaha, Michael, J1 aCushman, Mary1 aWang, Thomas, J1 aGansevoort, Ron, T1 aFox, Caroline, S1 aGaggin, Hanna, K1 aKop, Willem, J1 aLiu, Kiang1 aVasan, Ramachandran, S1 aPsaty, Bruce, M1 aLee, Douglas, S1 aBrouwers, Frank, P1 aHillege, Hans, L1 aBartz, Traci, M1 aBenjamin, Emelia, J1 aChan, Cheeling1 aAllison, Matthew1 aGardin, Julius, M1 aJanuzzi, James, L1 aLevy, Daniel1 aHerrington, David, M1 aGilst, Wiek, H1 aBertoni, Alain, G1 aLarson, Martin, G1 ade Boer, Rudolf, A1 aGottdiener, John, S1 aShah, Sanjiv, J1 aHo, Jennifer, E uhttps://chs-nhlbi.org/node/754904686nas a2200541 4500008004100000022001400041245011900055210006900174260001600243520308900259100002303348700001903371700003003390700002203420700002203442700002003464700002203484700002303506700001803529700002103547700002103568700001503589700002003604700002303624700002103647700002103668700001903689700001503708700002703723700002003750700002003770700002103790700002003811700002403831700001903855700002103874700002203895700002203917700002003939700001703959700002503976700002204001700001904023700002404042700002204066700002004088856003604108 2018 eng d a2380-659100aAssociation of Cardiovascular Biomarkers With Incident Heart Failure With Preserved and Reduced Ejection Fraction.0 aAssociation of Cardiovascular Biomarkers With Incident Heart Fai c2018 Jan 103 aImportance: Nearly half of all patients with heart failure have preserved ejection fraction (HFpEF) as opposed to reduced ejection fraction (HFrEF), yet associations of biomarkers with future heart failure subtype are incompletely understood.
Objective: To evaluate the associations of 12 cardiovascular biomarkers with incident HFpEF vs HFrEF among adults from the general population.
Design, Setting, and Participants: This study included 4 longitudinal community-based cohorts: the Cardiovascular Health Study (1989-1990; 1992-1993 for supplemental African-American cohort), the Framingham Heart Study (1995-1998), the Multi-Ethnic Study of Atherosclerosis (2000-2002), and the Prevention of Renal and Vascular End-stage Disease study (1997-1998). Each cohort had prospective ascertainment of incident HFpEF and HFrEF. Data analysis was performed from June 25, 2015, to November 9, 2017.
Exposures: The following biomarkers were examined: N-terminal pro B-type natriuretic peptide or brain natriuretic peptide, high-sensitivity troponin T or I, C-reactive protein (CRP), urinary albumin to creatinine ratio (UACR), renin to aldosterone ratio, D-dimer, fibrinogen, soluble suppressor of tumorigenicity, galectin-3, cystatin C, plasminogen activator inhibitor 1, and interleukin 6.
Main Outcomes and Measures: Development of incident HFpEF and incident HFrEF.
Results: Among the 22 756 participants in these 4 cohorts (12 087 women and 10 669 men; mean [SD] age, 60 [13] years) in the study, during a median follow-up of 12 years, 633 participants developed incident HFpEF, and 841 developed HFrEF. In models adjusted for clinical risk factors of heart failure, 2 biomarkers were significantly associated with incident HFpEF: UACR (hazard ratio [HR], 1.33; 95% CI, 1.20-1.48; P < .001) and natriuretic peptides (HR, 1.27; 95% CI, 1.16-1.40; P < .001), with suggestive associations for high-sensitivity troponin (HR, 1.11; 95% CI, 1.03-1.19; P = .008), plasminogen activator inhibitor 1 (HR, 1.22; 95% CI, 1.03-1.45; P = .02), and fibrinogen (HR, 1.12; 95% CI, 1.03-1.22; P = .01). By contrast, 6 biomarkers were associated with incident HFrEF: natriuretic peptides (HR, 1.54; 95% CI, 1.41-1.68; P < .001), UACR (HR, 1.21; 95% CI, 1.11-1.32; P < .001), high-sensitivity troponin (HR, 1.37; 95% CI, 1.29-1.46; P < .001), cystatin C (HR, 1.19; 95% CI, 1.11-1.27; P < .001), D-dimer (HR, 1.22; 95% CI, 1.11-1.35; P < .001), and CRP (HR, 1.19; 95% CI, 1.11-1.28; P < .001). When directly compared, natriuretic peptides, high-sensitivity troponin, and CRP were more strongly associated with HFrEF compared with HFpEF.
Conclusions and Relevance: Biomarkers of renal dysfunction, endothelial dysfunction, and inflammation were associated with incident HFrEF. By contrast, only natriuretic peptides and UACR were associated with HFpEF. These findings highlight the need for future studies focused on identifying novel biomarkers of the risk of HFpEF.
1 ade Boer, Rudolf, A1 aNayor, Matthew1 adeFilippi, Christopher, R1 aEnserro, Danielle1 aBhambhani, Vijeta1 aKizer, Jorge, R1 aBlaha, Michael, J1 aBrouwers, Frank, P1 aCushman, Mary1 aLima, João, A C1 aBahrami, Hossein1 aHarst, Pim1 aWang, Thomas, J1 aGansevoort, Ron, T1 aFox, Caroline, S1 aGaggin, Hanna, K1 aKop, Willem, J1 aLiu, Kiang1 aVasan, Ramachandran, S1 aPsaty, Bruce, M1 aLee, Douglas, S1 aHillege, Hans, L1 aBartz, Traci, M1 aBenjamin, Emelia, J1 aChan, Cheeling1 aAllison, Matthew1 aGardin, Julius, M1 aJanuzzi, James, L1 aShah, Sanjiv, J1 aLevy, Daniel1 aHerrington, David, M1 aLarson, Martin, G1 aGilst, Wiek, H1 aGottdiener, John, S1 aBertoni, Alain, G1 aHo, Jennifer, E uhttps://chs-nhlbi.org/node/760305314nas a2201501 4500008004100000022001400041245010000055210006900155260001600224520106300240100002301303700001801326700002801344700002001372700002101392700002401413700002301437700002101460700002301481700002101504700002501525700001801550700001701568700002101585700002001606700001801626700001601644700001901660700003401679700001901713700002101732700002101753700001701774700002801791700002101819700002401840700002401864700002001888700002001908700001901928700002301947700001601970700001701986700002002003700002202023700002102045700001802066700002202084700002102106700002302127700002902150700002802179700001902207700002202226700002302248700002202271700001702293700002202310700001902332700002302351700002102374700002402395700002202419700002102441700002002462700002002482700002202502700002202524700001202546700001502558700001802573700001802591700002102609700002102630700002702651700002802678700002902706700002202735700002302757700002002780700002302800700002202823700002202845700002002867700002302887700002102910700001602931700002402947700002002971700002202991700002803013700001303041700001303054700001703067700001903084700001803103700002003121700002303141700002003164700001703184700001803201700002003219700002003239700002203259700002503281700002203306700002003328700002203348700002503370700002103395700002203416700002003438700002103458700002003479700002003499700001903519700002603538700002503564700002203589700002403611700002503635700002503660700002103685700002303706700001903729700002803748856003603776 2020 eng d a1939-327X00aGenetic Studies of Leptin Concentrations Implicate Leptin in the Regulation of Early Adiposity.0 aGenetic Studies of Leptin Concentrations Implicate Leptin in the c2020 Sep 113 aLeptin influences food intake by informing the brain about the status of body fat stores. Rare mutations associated with congenital leptin deficiency cause severe early-onset obesity that can be mitigated by administering leptin. However, the role of genetic regulation of leptin in polygenic obesity remains poorly understood. We performed an exome-based analysis in up to 57,232 individuals of diverse ancestries to identify genetic variants that influence adiposity-adjusted leptin concentrations. We identify five novel variants, including four missense variants, in , and , and one intergenic variant near The missense variant Val94Met (rs17151919) in was common in individuals of African ancestry only and its association with lower leptin concentrations was specific to this ancestry (P=2x10, n=3,901). Using analyses, we show that the Met94 allele decreases leptin secretion. We also show that the Met94 allele is associated with higher BMI in young African-ancestry children but not in adults, suggesting leptin regulates early adiposity.
1 aYaghootkar, Hanieh1 aZhang, Yiying1 aSpracklen, Cassandra, N1 aKaraderi, Tugce1 aHuang, Lam, Opal1 aBradfield, Jonathan1 aSchurmann, Claudia1 aFine, Rebecca, S1 aPreuss, Michael, H1 aKutalik, Zoltán1 aWittemans, Laura, Bl1 aLu, Yingchang1 aMetz, Sophia1 aWillems, Sara, M1 aLi-Gao, Ruifang1 aGrarup, Niels1 aWang, Shuai1 aMolnos, Sophie1 aSandoval-Zárate, América, A1 aNalls, Mike, A1 aLange, Leslie, A1 aHaesser, Jeffrey1 aGuo, Xiuqing1 aLyytikäinen, Leo-Pekka1 aFeitosa, Mary, F1 aSitlani, Colleen, M1 aVenturini, Cristina1 aMahajan, Anubha1 aKacprowski, Tim1 aWang, Carol, A1 aChasman, Daniel, I1 aAmin, Najaf1 aBroer, Linda1 aRobertson, Neil1 aYoung, Kristin, L1 aAllison, Matthew1 aAuer, Paul, L1 aBlüher, Matthias1 aBorja, Judith, B1 aBork-Jensen, Jette1 aCarrasquilla, Germán, D1 aChristofidou, Paraskevi1 aDemirkan, Ayse1 aDoege, Claudia, A1 aGarcia, Melissa, E1 aGraff, Mariaelisa1 aGuo, Kaiying1 aHakonarson, Hakon1 aHong, Jaeyoung1 aChen, Yii-Der, Ida1 aJackson, Rebecca1 aJakupović, Hermina1 aJousilahti, Pekka1 aJustice, Anne, E1 aKähönen, Mika1 aKizer, Jorge, R1 aKriebel, Jennifer1 aLeDuc, Charles, A1 aLi, Jin1 aLind, Lars1 aLuan, Jian'an1 aMackey, David1 aMangino, Massimo1 aMännistö, Satu1 aCarli, Jayne, F Martin1 aMedina-Gómez, Carolina1 aMook-Kanamori, Dennis, O1 aMorris, Andrew, P1 ade Mutsert, Renée1 aNauck, Matthias1 aNedeljkovic, Ivana1 aPennell, Craig, E1 aPradhan, Arund, D1 aPsaty, Bruce, M1 aRaitakari, Olli, T1 aScott, Robert, A1 aSkaaby, Tea1 aStrauch, Konstantin1 aTaylor, Kent, D1 aTeumer, Alexander1 aUitterlinden, André, G1 aWu, Ying1 aYao, Jie1 aWalker, Mark1 aNorth, Kari, E1 aKovacs, Peter1 aIkram, Arfan, M1 aDuijn, Cornelia, M1 aRidker, Paul, M1 aLye, Stephen1 aHomuth, Georg1 aIngelsson, Erik1 aSpector, Tim, D1 aMcKnight, Barbara1 aProvince, Michael, A1 aLehtimäki, Terho1 aAdair, Linda, S1 aRotter, Jerome, I1 aReiner, Alexander, P1 aWilson, James, G1 aHarris, Tamara, B1 aRipatti, Samuli1 aGrallert, Harald1 aMeigs, James, B1 aSalomaa, Veikko1 aHansen, Torben1 avan Dijk, Ko, Willems1 aWareham, Nicholas, J1 aGrant, Struan, Fa1 aLangenberg, Claudia1 aFrayling, Timothy, M1 aLindgren, Cecilia, M1 aMohlke, Karen, L1 aLeibel, Rudolph, L1 aLoos, Ruth, Jf1 aKilpeläinen, Tuomas, O uhttps://chs-nhlbi.org/node/849104184nas a2200829 4500008004100000022001400041245017700055210006900232260001600301300001200317490000800329520172300337653001202060653001502072653002802087653002602115653002502141653001702166100002202183700002102205700002002226700001602246700001902262700002002281700002202301700001802323700001902341700002302360700002102383700002002404700002002424700002202444700002002466700002002486700001902506700002302525700002402548700002102572700002502593700001802618700002402636700002002660700002102680700002602701700002202727700001902749700001902768700001702787700002702804700002502831700001602856700002102872700002402893700001802917700002402935700002402959700001902983700002003002700002203022700002503044700002103069700002003090700002503110700001803135700002003153700002303173700002103196700002503217700001903242710005703261856003603318 2024 eng d a1524-453900aRole of Polyunsaturated Fat in Modifying Cardiovascular Risk Associated With Family History of Cardiovascular Disease: Pooled De Novo Results From 15 Observational Studies.0 aRole of Polyunsaturated Fat in Modifying Cardiovascular Risk Ass c2024 Jan 23 a305-3160 v1493 aBACKGROUND: It is unknown whether dietary intake of polyunsaturated fatty acids (PUFA) modifies the cardiovascular disease (CVD) risk associated with a family history of CVD. We assessed interactions between biomarkers of low PUFA intake and a family history in relation to long-term CVD risk in a large consortium.
METHODS: Blood and tissue PUFA data from 40 885 CVD-free adults were assessed. PUFA levels ≤25th percentile were considered to reflect low intake of linoleic, alpha-linolenic, and eicosapentaenoic/docosahexaenoic acids (EPA/DHA). Family history was defined as having ≥1 first-degree relative who experienced a CVD event. Relative risks with 95% CI of CVD were estimated using Cox regression and meta-analyzed. Interactions were assessed by analyzing product terms and calculating relative excess risk due to interaction.
RESULTS: After multivariable adjustments, a significant interaction between low EPA/DHA and family history was observed (product term pooled RR, 1.09 [95% CI, 1.02-1.16]; =0.01). The pooled relative risk of CVD associated with the combined exposure to low EPA/DHA, and family history was 1.41 (95% CI, 1.30-1.54), whereas it was 1.25 (95% CI, 1.16-1.33) for family history alone and 1.06 (95% CI, 0.98-1.14) for EPA/DHA alone, compared with those with neither exposure. The relative excess risk due to interaction results indicated no interactions.
CONCLUSIONS: A significant interaction between biomarkers of low EPA/DHA intake, but not the other PUFA, and a family history was observed. This novel finding might suggest a need to emphasize the benefit of consuming oily fish for individuals with a family history of CVD.
10aAnimals10aBiomarkers10aCardiovascular Diseases10aDocosahexaenoic Acids10aFatty Acids, Omega-310aRisk Factors1 aLaguzzi, Federica1 aÅkesson, Agneta1 aMarklund, Matti1 aQian, Frank1 aGigante, Bruna1 aBartz, Traci, M1 aBassett, Julie, K1 aBirukov, Anna1 aCampos, Hannia1 aHirakawa, Yoichiro1 aImamura, Fumiaki1 aJäger, Susanne1 aLankinen, Maria1 aMurphy, Rachel, A1 aSenn, Mackenzie1 aTanaka, Toshiko1 aTintle, Nathan1 aVirtanen, Jyrki, K1 aYamagishi, Kazumasa1 aAllison, Matthew1 aBrouwer, Ingeborg, A1 ade Faire, Ulf1 aEiriksdottir, Gudny1 aFerrucci, Luigi1 aForouhi, Nita, G1 aGeleijnse, Johanna, M1 aHodge, Allison, M1 aKimura, Hitomi1 aLaakso, Markku1 aRiserus, Ulf1 avan Westing, Anniek, C1 aBandinelli, Stefania1 aBaylin, Ana1 aGiles, Graham, G1 aGudnason, Vilmundur1 aIso, Hiroyasu1 aLemaitre, Rozenn, N1 aNinomiya, Toshiharu1 aPost, Wendy, S1 aPsaty, Bruce, M1 aSalonen, Jukka, T1 aSchulze, Matthias, B1 aTsai, Michael, Y1 aUusitupa, Matti1 aWareham, Nicholas, J1 aOh, Seung-Won1 aWood, Alexis, C1 aHarris, William, S1 aSiscovick, David1 aMozaffarian, Dariush1 aLeander, Karin1 aFatty Acids and Outcomes Research Consortium (FORCE) uhttps://chs-nhlbi.org/node/9587