Bio


Dr. Katz is board certified in both cardiovascular medicine and internal medicine. He received fellowship training in advanced heart failure and transplant cardiology. He is an instructor of medicine in the Department of Medicine, Cardiovascular Division.

He provides innovative care to patients with advanced heart failure, cardiac transplantation, or mechanical circulatory support. He sees outpatients at the Advanced Heart Failure Clinic in Pleasanton.

Dr. Katz has conducted extensive clinical and scientific research. Sponsors include the National Heart, Lung, and Blood Institute.

His research focuses on understanding the complex syndrome of heart failure using genetic, proteomic, and metabolomic data from a diverse array of patients and healthy adults. The work aims to offer patients better treatments for their unique form of heart failure.

Dr. Katz has authored articles on his research findings for peer-reviewed journals such as New England Journal of Medicine, Circulation, and many more. He also has co-authored textbook chapters on cardiovascular genetics and genomics, ischemic heart disease, and mechanical circulatory support.

He reviews articles for the Journal of the American College of Cardiology, Circulation, and Scientific Reports. He has made invited presentations to his peers on subjects including the use of proteome profiling in the analysis of heart failure.

Clinical Focus


  • Cardiovascular Disease
  • Cardiac Transplantation
  • Heart-Assist Devices
  • Heart Failure

Academic Appointments


Professional Education


  • Board Certification, American Board of Internal Medicine, Advanced Heart Failure and Transplant Cardiology (2022)
  • Fellowship: Stanford University Advanced Heart Failure and Transplant Fellowship (2022) CA
  • Board Certification: American Board of Internal Medicine, Cardiovascular Disease (2020)
  • Board Certification: American Board of Internal Medicine, Internal Medicine (2017)
  • Fellowship: Beth Israel Deaconess Medical Center Harvard Medical School (2017) MA
  • Residency: Massachusetts General Hospital Internal Medicine Residency (2017) MA
  • Medical Education: Northwestern University Feinberg School of Medicine (2014) IL

All Publications


  • Nontargeted and Targeted Metabolomic Profiling Reveals Novel Metabolite Biomarkers of Incident Diabetes in African Americans. Diabetes Chen, Z., Pacheco, J. A., Gao, Y., Deng, S., Peterson, B., Shi, X., Zheng, S., Tahir, U. A., Katz, D. H., Cruz, D. E., Ngo, D., Benson, M. D., Robbins, J. M., Guo, X., Del Rocio Sevilla Gonzalez, M., Manning, A., Correa, A., Meigs, J. B., Taylor, K. D., Rich, S. S., Goodarzi, M. O., Rotter, J. I., Wilson, J. G., Clish, C. B., Gerszten, R. E. 2022

    Abstract

    Nontargeted metabolomics methods have increased potential to identify new disease biomarkers, but assessments of the additive information provided in large human cohorts by these less biased techniques are limited. To diversify our knowledge of diabetes associated metabolites, we leveraged a method that measures 305 targeted or "known" and 2,342 nontargeted or "unknown" compounds in fasting plasma samples from 2,750 participants (315 incident cases) in the Jackson Heart Study (JHS)-a community cohort of self-identified African Americans (AAs), who are underrepresented in omics studies. We found 307 unique compounds (82 known) associated with diabetes after adjusting for age and sex at a false discovery rate (FDR) <0.05 and 124 compounds (35 known, including 11 not previously associated) after further adjustments for BMI and fasting plasma glucose (FPG). Of these, 144 and 68 associations, respectively, replicated in a multi-ethnic cohort. Among these is an apparently novel isomer of the 1-deoxyceramide Cer(m18:1/24:0) with functional geonomics and high-resolution mass spectrometry. Overall, known and unknown metabolites provided complementary information (median correlation rho=0.29) and their inclusion with clinical risk factors improved diabetes prediction modeling. Our findings highlight the importance of including nontargeted metabolomics methods to provide new insights into diabetes development in ethnically diverse cohorts.

    View details for DOI 10.2337/db22-0033

    View details for PubMedID 35998269

  • Whole Genome Association Study of the Plasma Metabolome Identifies Metabolites Linked to Cardiometabolic Disease in Black Individuals. Nature communications Tahir, U. A., Katz, D. H., Avila-Pachecho, J., Bick, A. G., Pampana, A., Robbins, J. M., Yu, Z., Chen, Z., Benson, M. D., Cruz, D. E., Ngo, D., Deng, S., Shi, X., Zheng, S., Eisman, A. S., Farrell, L., Hall, M. E., Correa, A., Tracy, R. P., Durda, P., Taylor, K. D., Liu, Y., Johnson, W. C., Guo, X., Yao, J., Chen, Y. I., Manichaikul, A. W., Ruberg, F. L., Blaner, W. S., Jain, D., NHLBI Trans-Omics for Precision Medicine 1 Consortium, Bouchard, C., Sarzynski, M. A., Rich, S. S., Rotter, J. I., Wang, T. J., Wilson, J. G., Clish, C. B., Natarajan, P., Gerszten, R. E., Abe, N., Abecasis, G. A., Aguet, F., Albert, C., Almasy, L., Alonso, A., Ament, S., Anderson, P., Anugu, P., Applebaum-Bowden, D., Ardlie, K., Arking, D., Arnett, D. K., Ashley-Koch, A., Aslibekyan, S., Assimes, T., Auer, P., Avramopoulos, D., Ayas, N., Balasubramanian, A., Barnard, J., Barnes, K., Barr, R. G., Barron-Casella, E., Barwick, L., Beaty, T., Beck, G., Becker, D., Becker, L., Beer, R., Beitelshees, A., Benjamin, E., Benos, T., Bezerra, M., Bielak, L., Bis, J., Blackwell, T., Blangero, J., Blue, N., Boerwinkle, E., Bowden, D. W., Bowler, R., Brody, J., Broeckel, U., Broome, J., Brown, D., Bunting, K., Burchard, E., Bustamante, C., Buth, E., Cade, B., Cardwell, J., Carey, V., Carrier, J., Carson, A., Carty, C., Casaburi, R., Romero, J. P., Casella, J., Castaldi, P., Chaffin, M., Chang, C., Chang, Y., Chasman, D., Chavan, S., Chen, B., Chen, W., Cho, M., Choi, S. H., Chuang, L., Chung, M., Chung, R., Comhair, S., Conomos, M., Cornell, E., Crandall, C., Crapo, J., Cupples, L. A., Curran, J., Curtis, J., Custer, B., Damcott, C., Darbar, D., David, S., Davis, C., Daya, M., de Andrade, M., Fuentes, L. d., de Vries, P., DeBaun, M., Deka, R., DeMeo, D., Devine, S., Dinh, H., Doddapaneni, H., Duan, Q., Dugan-Perez, S., Duggirala, R., Dutcher, S. K., Eaton, C., Ekunwe, L., El Boueiz, A., Ellinor, P., Emery, L., Erzurum, S., Farber, C., Farek, J., Fingerlin, T., Flickinger, M., Fornage, M., Franceschini, N., Frazar, C., Fu, M., Fullerton, S. M., Fulton, L., Gabriel, S., Gan, W., Gao, S., Gao, Y., Gass, M., Geiger, H., Gelb, B., Geraci, M., Germer, S., Ghosh, A., Gibbs, R., Gignoux, C., Gladwin, M., Glahn, D., Gogarten, S., Gong, D., Goring, H., Graw, S., Gray, K. J., Grine, D., Gross, C., Gu, C. C., Guan, Y., Gupta, N., Haessler, J., Han, Y., Hanly, P., Harris, D., Hawley, N. L., He, J., Heavner, B., Heckbert, S., Hernandez, R., Herrington, D., Hersh, C., Hidalgo, B., Hixson, J., Hobbs, B., Hokanson, J., Hong, E., Hoth, K., Hsiung, C., Hu, J., Hung, Y., Huston, H., Hwu, C. M., Irvin, M. R., Jackson, R., Jaquish, C., Johnsen, J., Johnson, A., Johnston, R., Jones, K., Kang, H. M., Kaplan, R., Kardia, S., Kelly, S., Kenny, E., Kessler, M., Khan, A., Khan, Z., Kim, W., Kimoff, J., Kinney, G., Konkle, B., Kooperberg, C., Kramer, H., Lange, C., Lange, E., Lange, L., Laurie, C., Laurie, C., LeBoff, M., Lee, J., Lee, S., Lee, W., LeFaive, J., Levine, D., Levy, D., Lewis, J., Li, X., Li, Y., Lin, H., Lin, H., Lin, X., Liu, S., Liu, Y., Loos, R. J., Lubitz, S., Lunetta, K., Luo, J., Magalang, U., Mahaney, M., Make, B., Manning, A., Manson, J., Martin, L., Marton, M., Mathai, S., Mathias, R., May, S., McArdle, P., McDonald, M., McFarland, S., McGarvey, S., McGoldrick, D., McHugh, C., McNeil, B., Mei, H., Meigs, J., Menon, V., Mestroni, L., Metcalf, G., Meyers, D. A., Mignot, E., Mikulla, J., Min, N., Minear, M., Minster, R. L., Mitchell, B. D., Moll, M., Momin, Z., Montasser, M. E., Montgomery, C., Muzny, D., Mychaleckyj, J. C., Nadkarni, G., Naik, R., Naseri, T., Nekhai, S., Nelson, S. C., Neltner, B., Nessner, C., Nickerson, D., Nkechinyere, O., North, K., O'Connell, J., O'Connor, T., Ochs-Balcom, H., Okwuonu, G., Pack, A., Paik, D. T., Palmer, N., Pankow, J., Papanicolaou, G., Parker, C., Peloso, G., Peralta, J. M., Perez, M., Perry, J., Peters, U., Peyser, P., Phillips, L. S., Pleiness, J., Pollin, T., Post, W., Becker, J. P., Boorgula, M. P., Preuss, M., Psaty, B., Qasba, P., Qiao, D., Qin, Z., Rafaels, N., Raffield, L., Rajendran, M., Ramachandran, V. S., Rao, D. C., Rasmussen-Torvik, L., Ratan, A., Redline, S., Reed, R., Reeves, C., Regan, E., Reiner, A., Reupena, M. A., Rice, K., Robillard, R., Robine, N., Dan Roden, R., Roselli, C., Ruczinski, I., Runnels, A., Russell, P., Ruuska, S., Sabino, E. C., Saleheen, D., Salimi, S., Salvi, S., Salzberg, S., Sandow, K., Sankaran, V. G., Santibanez, J., Schwander, K., Schwartz, D., Sciurba, F., Seidman, C., Seidman, J., Sa riA S, F. d., Sheehan, V., Sherman, S. L., Shetty, A., Shetty, A., Sheu, W. H., Shoemaker, M. B., Silver, B., Silverman, E., Skomro, R., Smith, A. V., Smith, J., Smith, J., Smith, N., Smith, T., Smoller, S., Snively, B., Snyder, M., Sofer, T., Sotoodehnia, N., Stilp, A. M., Storm, G., Streeten, E., Su, J. L., Sung, Y. J., Sylvia, J., Szpiro, A., Taliun, D., Tang, H., Taub, M., Taylor, M., Taylor, S., Telen, M., Thornton, T. A., Threlkeld, M., Tinker, L., Tirschwell, D., Tishkoff, S., Tiwari, H., Tong, C., Tsai, M., Vaidya, D., Van Den Berg, D., VandeHaar, P., Vrieze, S., Walker, T., Wallace, R., Walts, A., Wang, F. F., Wang, H., Wang, J., Watson, K., Watt, J., Weeks, D. E., Weinstock, J., Weir, B., Weiss, S. T., Weng, L., Wessel, J., Willer, C., Williams, K., Williams, L. K., Wilson, C., Winterkorn, L., Wong, Q., Wu, J., Xu, H., Yanek, L., Yang, I., Yu, K., Zekavat, S. M., Zhang, Y., Zhao, S. X., Zhao, W., Zhu, X., Ziv, E., Zody, M., Zoellner, S. 2022; 13 (1): 4923

    Abstract

    Integrating genetic information with metabolomics has provided new insights into genes affecting human metabolism. However, gene-metabolite integration has been primarily studied in individuals of European Ancestry, limiting the opportunity to leverage genomic diversity for discovery. In addition, these analyses have principally involved known metabolites, with the majority of the profiled peaks left unannotated. Here, we perform a whole genome association study of 2,291 metabolite peaks (known and unknown features) in 2,466 Black individuals from the Jackson Heart Study. We identify 519 locus-metabolite associations for 427 metabolite peaks and validate our findings in two multi-ethnic cohorts. A significant proportion of these associations are in ancestry specific alleles including findings in APOE, TTR and CD36. We leverage tandem mass spectrometry to annotate unknown metabolites, providing new insight into hereditary diseases including transthyretin amyloidosis and sickle cell disease. Our integrative omics approach leverages genomic diversity to provide novel insights into diverse cardiometabolic diseases.

    View details for DOI 10.1038/s41467-022-32275-3

    View details for PubMedID 35995766

  • Proteomic profiling platforms head to head: Leveraging genetics and clinical traits to compare aptamer- and antibody-based methods SCIENCE ADVANCES Katz, D. H., Robbins, J. M., Deng, S., Tahir, U. A., Bick, A. G., Pampana, A., Yu, Z., Ngo, D., Benson, M. D., Chen, Z., Cruz, D. E., Shen, D., Gao, Y., Bouchard, C., Sarzynski, M. A., Correa, A., Natarajan, P., Wilson, J. G., Gerszten, R. E. 2022; 8 (33): eabm5164

    Abstract

    High-throughput proteomic profiling using antibody or aptamer-based affinity reagents is used increasingly in human studies. However, direct analyses to address the relative strengths and weaknesses of these platforms are lacking. We assessed findings from the SomaScan1.3K (N = 1301 reagents), the SomaScan5K platform (N = 4979 reagents), and the Olink Explore (N = 1472 reagents) profiling techniques in 568 adults from the Jackson Heart Study and 219 participants in the HERITAGE Family Study across four performance domains: precision, accuracy, analytic breadth, and phenotypic associations leveraging detailed clinical phenotyping and genetic data. Across these studies, we show evidence supporting more reliable protein target specificity and a higher number of phenotypic associations for the Olink platform, while the Soma platforms benefit from greater measurement precision and analytic breadth across the proteome.

    View details for DOI 10.1126/sciadv.abm5164

    View details for Web of Science ID 000842064500005

    View details for PubMedID 35984888

    View details for PubMedCentralID PMC9390994

  • Proteomics and Population Biology in the Cardiovascular Health Study (CHS): design of a study with mentored access and active data sharing. European journal of epidemiology Austin, T. R., McHugh, C. P., Brody, J. A., Bis, J. C., Sitlani, C. M., Bartz, T. M., Biggs, M. L., Bansal, N., Buzkova, P., Carr, S. A., deFilippi, C. R., Elkind, M. S., Fink, H. A., Floyd, J. S., Fohner, A. E., Gerszten, R. E., Heckbert, S. R., Katz, D. H., Kizer, J. R., Lemaitre, R. N., Longstreth, W. T., McKnight, B., Mei, H., Mukamal, K. J., Newman, A. B., Ngo, D., Odden, M. C., Vasan, R. S., Shojaie, A., Simon, N., Smith, G. D., Davies, N. M., Siscovick, D. S., Sotoodehnia, N., Tracy, R. P., Wiggins, K. L., Zheng, J., Psaty, B. M. 2022

    Abstract

    BACKGROUND: In the last decade, genomic studies have identified and replicated thousands of genetic associations with measures of health and disease and contributed to the understanding of the etiology of a variety of health conditions. Proteins are key biomarkers in clinical medicine and often drug-therapy targets. Like genomics, proteomics can advance our understanding of biology.METHODS AND RESULTS: In the setting of the Cardiovascular Health Study (CHS), a cohort study of older adults, an aptamer-based method that has high sensitivity for low-abundance proteins was used to assay 4979 proteins in frozen, stored plasma from 3188 participants (61% women, mean age 74years). CHS provides active support, including central analysis, for seven phenotype-specific working groups (WGs). Each CHS WG is led by one or two senior investigators and includes 10 to 20 early or mid-career scientists. In this setting of mentored access, the proteomic data and analytic methods are widely shared with the WGs and investigators so that they may evaluate associations between baseline levels of circulating proteins and the incidence of a variety of health outcomes in prospective cohort analyses. We describe the design of CHS, the CHS Proteomics Study, characteristics of participants, quality control measures, and structural characteristics of the data provided to CHS WGs. We additionally highlight plans for validation and replication of novel proteomic associations.CONCLUSION: The CHS Proteomics Study offers an opportunity for collaborative data sharing to improve our understanding of the etiology of a variety of health conditions in older adults.

    View details for DOI 10.1007/s10654-022-00888-z

    View details for PubMedID 35790642

  • Whole Genome Sequence Analysis of the Plasma Proteome in Black Adults Provides Novel Insights Into Cardiovascular Disease. Circulation Katz, D. H., Tahir, U. A., Bick, A. G., Pampana, A., Ngo, D., Benson, M. D., Yu, Z., Robbins, J. M., Chen, Z., Cruz, D. E., Deng, S., Farrell, L., Sinha, S., Schmaier, A. A., Shen, D., Gao, Y., Hall, M. E., Correa, A., Tracy, R. P., Durda, P., Taylor, K. D., Liu, Y., Johnson, W. C., Guo, X., Yao, J., Ida Chen, Y., Manichaikul, A. W., Jain, D., Bouchard, C., Sarzynski, M. A., Rich, S. S., Rotter, J. I., Wang, T. J., Wilson, J. G., Natarajan, P., Gerszten, R. E., National Heart, L., Abe, N., Abecasis, G., Aguet, F., Albert, C., Almasy, L., Alonso, A., Ament, S., Anderson, P., Anugu, P., Applebaum-Bowden, D., Ardlie, K., Arking, D., Arnett, D. K., Ashley-Koch, A., Aslibekyan, S., Assimes, T., Auer, P., Avramopoulos, D., Ayas, N., Balasubramanian, A., Barnard, J., Barnes, K., Barr, R. G., Barron-Casella, E., Barwick, L., Beaty, T., Beck, G., Becker, D., Becker, L., Beer, R., Beitelshees, A., Benjamin, E., Benos, T., Bezerra, M., Bielak, L., Bis, J., Blackwell, T., Blangero, J., Boerwinkle, E., Bowden, D. W., Bowler, R., Brody, J., Broeckel, U., Broome, J., Brown, D., Bunting, K., Burchard, E., Bustamante, C., Buth, E., Cade, B., Cardwell, J., Carey, V., Carrier, J., Carson, A., Carty, C., Casaburi, R., Casas Romero, J. P., Casella, J., Castaldi, P., Chaffin, M., Chang, C., Chang, Y., Chasman, D., Chavan, S., Chen, B., Chen, W., Chen, Y. I., Cho, M., Choi, S. H., Chuang, L., Chung, M., Chung, R., Clish, C., Comhair, S., Conomos, M., Cornell, E., Correa, A., Crandall, C., Crapo, J., Cupples, L. A., Curran, J., Curtis, J., Custer, B., Damcott, C., Darbar, D., David, S., Davis, C., Daya, M., de Andrade, M., de Las Fuentes, L., de Vries, P., DeBaun, M., Deka, R., DeMeo, D., Devine, S., Dinh, H., Doddapaneni, H., Duan, Q., Dugan-Perez, S., Duggirala, R., Durda, J. P., Dutcher, S. K., Eaton, C., Ekunwe, L., El Boueiz, A., Ellinor, P., Emery, L., Erzurum, S., Farber, C., Farek, J., Fingerlin, T., Flickinger, M., Fornage, M., Franceschini, N., Frazar, C., Fu, M., Fullerton, S. M., Fulton, L., Gabriel, S., Gan, W., Gao, S., Gao, Y., Gass, M., Geiger, H., Gelb, B., Geraci, M., Germer, S., Gerszten, R., Ghosh, A., Gibbs, R., Gignoux, C., Gladwin, M., Glahn, D., Gogarten, S., Gong, D., Goring, H., Graw, S., Gray, K. J., Grine, D., Gross, C., Gu, C. C., Guan, Y., Guo, X., Gupta, N., Haas, D. M., Haessler, J., Hall, M., Han, Y., Hanly, P., Harris, D., Hawley, N. L., He, J., Heavner, B., Heckbert, S., Hernandez, R., Herrington, D., Hersh, C., Hidalgo, B., Hixson, J., Hobbs, B., Hokanson, J., Hong, E., Hoth, K., Hsiung, C. A., Hu, J., Hung, Y., Huston, H., Hwu, C. M., Irvin, M. R., Jackson, R., Jain, D., Jaquish, C., Johnsen, J., Johnson, A., Johnson, C., Johnston, R., Jones, K., Kang, H. M., Kaplan, R., Kardia, S., Kelly, S., Kenny, E., Kessler, M., Khan, A., Khan, Z., Kim, W., Kimoff, J., Kinney, G., Konkle, B., Kooperberg, C., Kramer, H., Lange, C., Lange, E., Lange, L., Laurie, C., Laurie, C., LeBoff, M., Lee, J., Lee, S., Lee, W., LeFaive, J., Levine, D., Levy, D., Lewis, J., Li, X., Li, Y., Lin, H., Lin, H., Lin, X., Liu, S., Liu, Y., Liu, Y., Loos, R. J., Lubitz, S., Lunetta, K., Luo, J., Magalang, U., Mahaney, M., Make, B., Manichaikul, A., Manning, A., Manson, J., Martin, L., Marton, M., Mathai, S., Mathias, R., May, S., McArdle, P., McDonald, M., McFarland, S., McGarvey, S., McGoldrick, D., McHugh, C., McNeil, B., Mei, H., Meigs, J., Menon, V., Mestroni, L., Metcalf, G., Meyers, D. A., Mignot, E., Mikulla, J., Min, N., Minear, M., Minster, R. L., Mitchell, B. D., Moll, M., Momin, Z., Montasser, M. E., Montgomery, C., Muzny, D., Mychaleckyj, J. C., Nadkarni, G., Naik, R., Naseri, T., Natarajan, P., Nekhai, S., Nelson, S. C., Neltner, B., Nessner, C., Nickerson, D., Nkechinyere, O., North, K., O'Connell, J., O'Connor, T., Ochs-Balcom, H., Okwuonu, G., Pack, A., Paik, D. T., Palmer, N., Pankow, J., Papanicolaou, G., Parker, C., Peloso, G., Peralta, J. M., Perez, M., Perry, J., Peters, U., Peyser, P., Phillips, L. S., Pleiness, J., Pollin, T., Post, W., Powers Becker, J., Preethi Boorgula, M., Preuss, M., Psaty, B., Qasba, P., Qiao, D., Qin, Z., Rafaels, N., Raffield, L., Rajendran, M., Ramachandran, V. S., Rao, D. C., Rasmussen-Torvik, L., Ratan, A., Redline, S., Reed, R., Reeves, C., Regan, E., Reiner, A., Reupena, M. S., Rice, K., Rich, S., Robillard, R., Robine, N., Roden, D., Roselli, C., Rotter, J., Ruczinski, I., Runnels, A., Russell, P., Ruuska, S., Ryan, K., Sabino, E. C., Saleheen, D., Salimi, S., Salvi, S., Salzberg, S., Sandow, K., Sankaran, V. G., Santibanez, J., Schwander, K., Schwartz, D., Sciurba, F., Seidman, C., Seidman, J., Series, F., Sheehan, V., Sherman, S. L., Shetty, A., Shetty, A., Sheu, W. H., Shoemaker, M. B., Silver, B., Silverman, E., Skomro, R., Smith, A. V., Smith, J., Smith, J., Smith, N., Smith, T., Smoller, S., Snively, B., Snyder, M., Sofer, T., Sotoodehnia, N., Stilp, A. M., Storm, G., Streeten, E., Su, J. L., Sung, Y. J., Sylvia, J., Szpiro, A., Taliun, D., Tang, H., Taub, M., Taylor, K. D., Taylor, M., Taylor, S., Telen, M., Thornton, T. A., Threlkeld, M., Tinker, L., Tirschwell, D., Tishkoff, S., Tiwari, H., Tong, C., Tracy, R., Tsai, M., Vaidya, D., Van Den Berg, D., VandeHaar, P., Vrieze, S., Walker, T., Wallace, R., Walts, A., Wang, F. F., Wang, H., Wang, J., Watson, K., Watt, J., Weeks, D. E., Weinstock, J., Weir, B., Weiss, S. T., Weng, L., Wessel, J., Willer, C., Williams, K., Williams, L. K., Wilson, C., Wilson, J., Winterkorn, L., Wong, Q., Wu, J., Xu, H., Yanek, L., Yang, I., Yu, K., Zekavat, S. M., Zhang, Y., Zhao, S. X., Zhao, W., Zhu, X., Zody, M., Zoellner, S. 2022; 145 (5): 357-370

    Abstract

    BACKGROUND: Plasma proteins are critical mediators of cardiovascular processes and are the targets of many drugs. Previous efforts to characterize the genetic architecture of the plasma proteome have been limited by a focus on individuals of European descent and leveraged genotyping arrays and imputation. Here we describe whole genome sequence analysis of the plasma proteome in individuals with greater African ancestry, increasing our power to identify novel genetic determinants.METHODS: Proteomic profiling of 1301 proteins was performed in 1852 Black adults from the Jackson Heart Study using aptamer-based proteomics (SomaScan). Whole genome sequencing association analysis was ascertained for all variants with minor allele count ≥5. Results were validated using an alternative, antibody-based, proteomic platform (Olink) as well as replicated in the Multi-Ethnic Study of Atherosclerosis and the HERITAGE Family Study (Health, Risk Factors, Exercise Training and Genetics).RESULTS: We identify 569 genetic associations between 479 proteins and 438 unique genetic regions at a Bonferroni-adjusted significance level of 3.8*10-11. These associations include 114 novel locus-protein relationships and an additional 217 novel sentinel variant-protein relationships. Novel cardiovascular findings include new protein associations at the APOE gene locus including ZAP70 (sentinel single nucleotide polymorphism [SNP] rs7412-T, beta=0.61±0.05, P=3.27*10-30) and MMP-3 (beta=-0.60±0.05, P=1.67*10-32), as well as a completely novel pleiotropic locus at the HPX gene, associated with 9 proteins. Further, the associations suggest new mechanisms of genetically mediated cardiovascular disease linked to African ancestry; we identify a novel association between variants linked to APOL1-associated chronic kidney and heart disease and the protein CKAP2 (rs73885319-G, beta=0.34±0.04, P=1.34*10-17) as well as an association between ATTR amyloidosis and RBP4 levels in community-dwelling individuals without heart failure.CONCLUSIONS: Taken together, these results provide evidence for the functional importance of variants in non-European populations, and suggest new biological mechanisms for ancestry-specific determinants of lipids, coagulation, and myocardial function.

    View details for DOI 10.1161/CIRCULATIONAHA.121.055117

    View details for PubMedID 34814699

  • Proteomics in Heart Failure: From Benchtop to Bedside. Journal of cardiac failure Katz, D. H., Thompson, A. D. 1800

    View details for DOI 10.1016/j.cardfail.2021.12.003

    View details for PubMedID 34933100

  • Human plasma proteomic profiles indicative of cardiorespiratory fitness (vol 3, pg 786, 2021) NATURE METABOLISM Robbins, J. M., Peterson, B., Schranner, D., Tahir, U. A., Rienmuller, T., Deng, S., Keyes, M. J., Katz, D. H., Beltran, P., Barber, J. L., Baumgartner, C., Carr, S. A., Ghosh, S., Shen, C., Jennings, L. L., Ross, R., Sarzynski, M. A., Bouchard, C., Gerszten, R. E. 2021; 3 (9): 1275

    View details for DOI 10.1038/s42255-021-00459-8

    View details for Web of Science ID 000691656400001

    View details for PubMedID 34446928

  • Multiomic Profiling in Black and White Populations Reveals Novel Candidate Pathways in Left Ventricular Hypertrophy and Incident Heart Failure Specific to Black Adults CIRCULATION-GENOMIC AND PRECISION MEDICINE Katz, D. H., Tahir, U. A., Ngo, D., Benson, M. D., Gao, Y., Shi, X., Nayor, M., Keyes, M. J., Larson, M. G., Hall, M. E., Correa, A., Sinha, S., Shen, D., Herzig, M., Yang, Q., Robbins, J. M., Chen, Z., Cruz, D. E., Peterson, B., Vasan, R. S., Wang, T. J., Wilson, J. G., Gerszten, R. E. 2021; 14 (3): 348-358

    Abstract

    Increased left ventricular (LV) mass is associated with adverse cardiovascular events including heart failure (HF). Both increased LV mass and HF disproportionately affect Black individuals. To understand the underlying mechanisms, we undertook a proteomic screen in a Black cohort and compared the findings to results from a White cohort.We measured 1305 plasma proteins using the SomaScan platform in 1772 Black participants (mean age, 56 years; 62% women) in JHS (Jackson Heart Study) with LV mass assessed by 2-dimensional echocardiography. Incident HF was assessed in 1600 participants. We then compared protein associations in JHS to those observed in White participants from FHS (Framingham Heart Study; mean age, 54 years; 56% women).In JHS, there were 110 proteins associated with LV mass and 13 proteins associated with incident HF hospitalization with false discovery rate <5% after multivariable adjustment. Several proteins showed expected associations with both LV mass and HF, including NT-proBNP (N-terminal pro-B-type natriuretic peptide; β=0.04; P=2×10-8; hazard ratio, 1.48; P=0.0001). The strongest association with LV mass was novel: LKHA4 (leukotriene-A4 hydrolase; β=0.05; P=5×10-15). This association was confirmed on an alternate proteomics platform and further supported by related metabolomic data. Fractalkine/CX3CL1 (C-X3-C Motif Chemokine Ligand 1) showed a novel association with incident HF (hazard ratio, 1.32; P=0.0002). While established biomarkers such as cystatin C and NT-proBNP showed consistent associations in Black and White individuals, LKHA4 and fractalkine were significantly different between the two groups.We identified several novel biological pathways specific to Black adults hypothesized to contribute to the pathophysiologic cascade of LV hypertrophy and incident HF including LKHA4 and fractalkine.

    View details for DOI 10.1161/CIRCGEN.120.003191

    View details for Web of Science ID 000661620500005

    View details for PubMedID 34019435

    View details for PubMedCentralID PMC8497179

  • Human plasma proteomic profiles indicative of cardiorespiratory fitness NATURE METABOLISM Robbins, J. M., Peterson, B., Schranner, D., Tahir, U. A., Rienmueller, T., Deng, S., Keyes, M. J., Katz, D. H., Beltran, P., Barber, J. L., Baumgartner, C., Carr, S. A., Ghosh, S., Shen, C., Jennings, L. L., Ross, R., Sarzynski, M. A., Bouchard, C., Gerszten, R. E. 2021; 3 (6): 786-+

    Abstract

    Maximal oxygen uptake (VO2max) is a direct measure of human cardiorespiratory fitness and is associated with health. However, the molecular determinants of interindividual differences in baseline (intrinsic) VO2max, and of increases of VO2max in response to exercise training (ΔVO2max), are largely unknown. Here, we measure ~5,000 plasma proteins using an affinity-based platform in over 650 sedentary adults before and after a 20-week endurance-exercise intervention and identify 147 proteins and 102 proteins whose plasma levels are associated with baseline VO2max and ΔVO2max, respectively. Addition of a protein biomarker score derived from these proteins to a score based on clinical traits improves the prediction of an individual's ΔVO2max. We validate findings in a separate exercise cohort, further link 21 proteins to incident all-cause mortality in a community-based cohort and reproduce the specificity of ~75% of our key findings using antibody-based assays. Taken together, our data shed light on biological pathways relevant to cardiorespiratory fitness and highlight the potential additive value of protein biomarkers in identifying exercise responsiveness in humans.

    View details for DOI 10.1038/s42255-021-00400-z

    View details for Web of Science ID 000657702900001

    View details for PubMedID 34045743

  • Proteomic profiling reveals novel biomarkers and pathways in yype 2 diabetes risk. JCI insight Ngo, D. n., Benson, M. D., Long, J. Z., Chen, Z. Z., Wang, R. n., Nath, A. K., Keyes, M. J., Shen, D. n., Sinha, S. n., Kuhn, E. n., Morningstar, J. E., Shi, X. n., Peterson, B. D., Chan, C. n., Katz, D. H., Tahir, U. A., Farrell, L. A., Melander, O. n., Mosley, J. D., Carr, S. A., Vasan, R. S., Larson, M. G., Smith, J. G., Wang, T. J., Yang, Q. n., Gerszten, R. E. 2021

    Abstract

    Recent advances in proteomic technologies have made high throughput profiling of low abundance proteins in large epidemiological cohorts increasingly feasible. We investigated whether aptamer-based proteomic profiling could identify biomarkers associated with future development of type 2 diabetes (T2DM) beyond known risk factors. We identified dozens of markers with highly significant associations with future T2DM across two large longitudinal cohorts (n=2,839) followed for up to 16 years. We leveraged proteomic, metabolomic, genetic and clinical data from humans to nominate one specific candidate to test for potential causal relationships in model systems. Our studies identified functional effects of aminoacylase 1 (ACY1), a top protein association with future T2DM risk, on amino acid metabolism and insulin homeostasis in vitro and in vivo. Further, a loss-of-function variant associated with circulating levels of the biomarker WAP, Kazal, immunoglobulin, Kunitz and NTR domain-containing protein 2 (WFIKKN2) was in turn associated with fasting glucose, hemoglobin A1c and HOMA-IR measurements in humans. In addition to identifying novel disease markers and potential pathways in T2DM, we provide publicly available data to be leveraged for new insights about gene function and disease pathogenesis in the context of human metabolism. .

    View details for DOI 10.1172/jci.insight.144392

    View details for PubMedID 33591955

  • Metabolomic Profiles and Heart Failure Risk in Black Adults: Insights From the Jackson Heart Study CIRCULATION-HEART FAILURE Tahir, U. A., Katz, D. H., Zhao, T., Ngo, D., Cruz, D. E., Robbins, J. M., Chen, Z., Peterson, B., Benson, M. D., Shi, X., Dailey, L., Andersson, C., Vasan, R. S., Gao, Y., Shen, C., Correa, A., Hall, M. E., Wang, T. J., Clish, C. B., Wilson, J. G., Gerszten, R. E. 2021; 14 (1): 28-38

    Abstract

    Heart failure (HF) is a heterogeneous disease characterized by significant metabolic disturbances; however, the breadth of metabolic dysfunction before the onset of overt disease is not well understood. The purpose of this study was to determine the association of circulating metabolites with incident HF to uncover novel metabolic pathways to disease.We performed targeted plasma metabolomic profiling in a deeply phenotyped group of Black adults from the JHS (Jackson Heart Study; n=2199). We related metabolites associated with incident HF to established etiological mechanisms, including increased left ventricular mass index and incident coronary heart disease. Furthermore, we evaluated differential associations of metabolites with HF with preserved ejection fraction versus HF with reduced ejection fraction.Metabolites associated with incident HF included products of posttranscriptional modifications of RNA, as well as polyamine and nitric oxide metabolism. A subset of metabolite-HF associations was independent of well-established HF pathways such as increased left ventricular mass index and incident coronary heart disease and included homoarginine (per 1 SD increase in metabolite level, hazard ratio, 0.77; P=1.2×10-3), diacetylspermine (hazard ratio, 1.34; P=3.4×10-3), and uridine (hazard ratio, 0.79; P, 3×10-4). Furthermore, metabolites involved in pyrimidine metabolism (orotic acid) and collagen turnover (N-methylproline) among others were part of a distinct metabolic signature that differentiated individuals with HF with preserved ejection fraction versus HF with reduced ejection fraction.The integration of clinical phenotyping with plasma metabolomic profiling uncovered novel metabolic processes in nontraditional disease pathways underlying the heterogeneity of HF development in Black adults.

    View details for DOI 10.1161/CIRCHEARTFAILURE.120.007275

    View details for Web of Science ID 000639307300005

    View details for PubMedID 33464957

  • Circulating testican-2 is a podocyte-derived marker of kidney health PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Ngo, D., Wen, D., Gao, Y., Keyes, M. J., Drury, E. R., Katz, D. H., Benson, M. D., Sinha, S., Shen, D., Farrell, L. A., Peterson, B. D., Friedman, D. J., Elmariah, S., Young, B. A., Smith, J., Yang, Q., Vasan, R. S., Vasan, R. S., Larson, M. G., Correa, A., Humphreys, B. D., Wang, T. J., Pollak, M. R., Wilson, J. G., Gerszten, R. E., Rhee, E. P. 2020; 117 (40): 25026-25035

    Abstract

    In addition to their fundamental role in clearance, the kidneys release select molecules into the circulation, but whether any of these anabolic functions provides insight on kidney health is unknown. Using aptamer-based proteomics, we characterized arterial (A)-to-renal venous (V) gradients for >1,300 proteins in 22 individuals who underwent invasive sampling. Although most of the proteins that changed significantly decreased from A to V, consistent with renal clearance, several were found to increase, the most significant of which was testican-2. To assess the clinical implications of these physiologic findings, we examined proteomic data in the Jackson Heart Study (JHS), an African-American cohort (n = 1,928), with replication in the Framingham Heart Study (FHS), a White cohort (n = 1,621). In both populations, testican-2 had a strong, positive correlation with estimated glomerular filtration rate (eGFR). In addition, higher baseline testican-2 levels were associated with a lower rate of eGFR decline in models adjusted for age, gender, hypertension, type 2 diabetes, body mass index, baseline eGFR, and albuminuria. Glomerular expression of testican-2 in human kidneys was demonstrated by immunohistochemistry, immunofluorescence, and electron microscopy, while single-cell RNA sequencing of human kidneys showed expression of the cognate gene, SPOCK2, exclusively in podocytes. In vitro, testican-2 increased glomerular endothelial tube formation and motility, raising the possibility that its secretion has a functional role within the glomerulus. Taken together, our findings identify testican-2 as a podocyte-derived biomarker of kidney health and prognosis.

    View details for DOI 10.1073/pnas.2009606117

    View details for Web of Science ID 000579045200008

    View details for PubMedID 32958645

    View details for PubMedCentralID PMC7547280

  • Proteomic Profiling in Biracial Cohorts Implicates DC-SIGN as a Mediator of Genetic Risk in COVID-19. medRxiv : the preprint server for health sciences Katz, D. H., Tahir, U. A., Ngo, D., Benson, M. D., Bick, A. G., Pampana, A., Gao, Y., Keyes, M. J., Correa, A., Sinha, S., Shen, D., Yang, Q., Robbins, J. M., Chen, Z., Cruz, D. E., Peterson, B., Natarajan, P., Vasan, R. S., Smith, G., Wang, T. J., Gerszten, R. E. 2020

    Abstract

    COVID-19 is one of the most consequential pandemics in the last century, yet the biological mechanisms that confer disease risk are incompletely understood. Further, heterogeneity in disease outcomes is influenced by race, though the relative contributions of structural/social and genetic factors remain unclear. Very recent unpublished work has identified two genetic risk loci that confer greater risk for respiratory failure in COVID-19: the ABO locus and the 3p21.31 locus. To understand how these loci might confer risk and whether this differs by race, we utilized proteomic profiling and genetic information from three cohorts including black and white participants to identify proteins influenced by these loci. We observed that variants in the ABO locus are associated with levels of CD209/DC-SIGN, a known binding protein for SARS-CoV and other viruses, as well as multiple inflammatory and thrombotic proteins, while the 3p21.31 locus is associated with levels of CXCL16, a known inflammatory chemokine. Thus, integration of genetic information and proteomic profiling in biracial cohorts highlights putative mechanisms for genetic risk in COVID-19 disease.

    View details for DOI 10.1101/2020.06.09.20125690

    View details for PubMedID 32577670

  • Mining a GWAS of Severe Covid-19 New England Journal of Medicine Katz, D. H., Wilson, J. G., Gerszten, R. E. 2020; 383: 2588-2589

    View details for DOI 10.1056/NEJMc2025747

  • In the Clinic Stable Ischemic Heart Disease ANNALS OF INTERNAL MEDICINE Katz, D., Gavin, M. C. 2019; 171 (3): ITC17-U136

    Abstract

    Stable ischemic heart disease (SIHD) is a leading cause of death in the United States and many other countries. The defining pathobiology is an imbalance between the metabolic demands of the myocardium and its oxygen supply, which most often results from coronary artery atherosclerosis. The classic presenting symptom of SIHD is angina, but clinical presentation varies greatly among patients. Since the last In the Clinic on SIHD in 2014, several new drugs have been approved to reduce ischemic complications, such as myocardial infarction and congestive heart failure.

    View details for DOI 10.7326/AITC201908060

    View details for Web of Science ID 000478809000001

    View details for PubMedID 31382288

  • A Role for Branched-Chain Amino Acids in the Pathophysiology of Diabetes: Using Data to Guide Discovery CLINICAL CHEMISTRY Katz, D. H., Gerszten, R. E. 2018; 64 (8): 1250-1251

    View details for DOI 10.1373/clinchem.2017.273516

    View details for Web of Science ID 000448296800014

    View details for PubMedID 29506975

  • Phenomapping for the Identification of Hypertensive Patients with the Myocardial Substrate for Heart Failure with Preserved Ejection Fraction JOURNAL OF CARDIOVASCULAR TRANSLATIONAL RESEARCH Katz, D. H., Deo, R. C., Aguilar, F. G., Selvaraj, S., Martinez, E. E., Beussink-Nelson, L., Kim, K. A., Peng, J., Irvin, M. R., Tiwari, H., Rao, D. C., Arnett, D. K., Shah, S. J. 2017; 10 (3): 275-284

    Abstract

    We sought to evaluate whether unbiased machine learning of dense phenotypic data ("phenomapping") could identify distinct hypertension subgroups that are associated with the myocardial substrate (i.e., abnormal cardiac mechanics) for heart failure with preserved ejection fraction (HFpEF). In the HyperGEN study, a population- and family-based study of hypertension, we studied 1273 hypertensive patients utilizing clinical, laboratory, and conventional echocardiographic phenotyping of the study participants. We used machine learning analysis of 47 continuous phenotypic variables to identify mutually exclusive groups constituting a novel classification of hypertension. The phenomapping analysis classified study participants into 2 distinct groups that differed markedly in clinical characteristics, cardiac structure/function, and indices of cardiac mechanics (e.g., phenogroup #2 had a decreased absolute longitudinal strain [12.8 ± 4.1 vs. 14.6 ± 3.5%] even after adjustment for traditional comorbidities [p < 0.001]). The 2 hypertension phenogroups may represent distinct subtypes that may benefit from targeted therapies for the prevention of HFpEF.

    View details for DOI 10.1007/s12265-017-9739-z

    View details for Web of Science ID 000405852400005

    View details for PubMedID 28258421

  • Archeological Echocardiography: Digitization and Speckle Tracking Analysis of Archival Echocardiograms in the HyperGEN Study ECHOCARDIOGRAPHY-A JOURNAL OF CARDIOVASCULAR ULTRASOUND AND ALLIED TECHNIQUES Aguilar, F. G., Selvaraj, S., Martinez, E. E., Katz, D. H., Beussink, L., Kim, K. A., Ping, J., Rasmussen-Torvik, L., Goyal, A., Sha, J., Irvin, M. R., Arnett, D. K., Shah, S. J. 2016; 33 (3): 386-397

    Abstract

    Several large epidemiologic studies and clinical trials have included echocardiography, but images were stored in analog format and these studies predated tissue Doppler imaging (TDI) and speckle tracking echocardiography (STE). We hypothesized that digitization of analog echocardiograms, with subsequent quantification of cardiac mechanics using STE, is feasible, reproducible, accurate, and produces clinically valid results.In the NHLBI HyperGEN study (N = 2234), archived analog echocardiograms were digitized and subsequently analyzed using STE to obtain tissue velocities/strain. Echocardiograms were assigned quality scores and inter-/intra-observer agreement was calculated. Accuracy was evaluated in: (1) a separate second study (N = 50) comparing prospective digital strain versus post hoc analog-to-digital strain, and (2) in a third study (N = 95) comparing prospectively obtained TDI e' velocities with post hoc STE e' velocities. Finally, we replicated previously known associations between tissue velocities/strain, conventional echocardiographic measurements, and clinical data.Of the 2234 HyperGEN echocardiograms, 2150 (96.2%) underwent successful digitization and STE analysis. Inter/intra-observer agreement was high for all STE parameters, especially longitudinal strain (LS). In accuracy studies, LS performed best when comparing post hoc STE to prospective digital STE for strain analysis. STE-derived e' velocities correlated with, but systematically underestimated, TDI e' velocity. Several known associations between clinical variables and cardiac mechanics were replicated in HyperGEN. We also found a novel independent inverse association between fasting glucose and LS (adjusted β = -2.4 [95% CI -3.6, -1.2]% per 1-SD increase in fasting glucose; P < 0.001).Archeological echocardiography, the digitization and speckle tracking analysis of archival echocardiograms, is feasible and generates indices of cardiac mechanics similar to contemporary studies.

    View details for DOI 10.1111/echo.13095

    View details for Web of Science ID 000371719600007

    View details for PubMedID 26525308

    View details for PubMedCentralID PMC4775325

  • Association of Chronic Kidney Disease With Chronotropic Incompetence in Heart Failure With Preserved Ejection Fraction AMERICAN JOURNAL OF CARDIOLOGY Klein, D. A., Katz, D. H., Beussink-Nelson, L., Sanchez, C. L., Strzelczyk, T. A., Shah, S. J. 2015; 116 (7): 1093-1100

    Abstract

    Chronotropic incompetence (CI) is common in heart failure with preserved ejection fraction (HFpEF) and may be a key reason underlying exercise intolerance in these patients. However, the determinants of CI in HFpEF are unknown. We prospectively studied 157 patients with consecutive HFpEF who underwent cardiopulmonary exercise testing and defined CI according to specific thresholds of the percent heart rate reserve (%HRR). CI was diagnosed as present if %HRR <80 if not taking a β blocker and <62 if taking β blockers. Participants who achieved inadequate exercise effort (respiratory exchange ratio ≤1.05) on cardiopulmonary exercise testing were excluded. Multivariable-adjusted logistic regression was used to determine the factors associated with CI. Of the 157 participants, 108 (69%) achieved a respiratory exchange ratio >1.05 and were included in the final analysis. Of these 108 participants, 70% were women, 62% were taking β blockers, and 38% had chronic kidney disease. Most patients with HFpEF met criteria for CI (81 of 108; 75%). Lower estimated glomerular filtration rate (GFR), higher B-type natriuretic peptide, and higher pulmonary artery systolic pressure were each associated with CI. A 1-SD decrease in GFR was independently associated with CI after multivariable adjustment (adjusted odds ratio 2.2, 95% confidence interval 1.1 to 4.4, p = 0.02). The association between reduced GFR and CI persisted when considering a variety of measures of chronotropic response. In conclusion, reduced GFR is the major clinical correlate of CI in patients with HFpEF, and further study of the relation between chronic kidney disease and CI may provide insight into the pathophysiology of CI in HFpEF.

    View details for DOI 10.1016/j.amjcard.2015.06.038

    View details for Web of Science ID 000362382400017

    View details for PubMedID 26260398

    View details for PubMedCentralID PMC4567946

  • Phenomapping for Novel Classification of Heart Failure With Preserved Ejection Fraction CIRCULATION Shah, S. J., Katz, D. H., Selvaraj, S., Burke, M. A., Yancy, C. W., Gheorghiade, M., Bonow, R. O., Huang, C., Deo, R. C. 2015; 131 (3): 269-+

    Abstract

    Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous clinical syndrome in need of improved phenotypic classification. We sought to evaluate whether unbiased clustering analysis using dense phenotypic data (phenomapping) could identify phenotypically distinct HFpEF categories.We prospectively studied 397 patients with HFpEF and performed detailed clinical, laboratory, ECG, and echocardiographic phenotyping of the study participants. We used several statistical learning algorithms, including unbiased hierarchical cluster analysis of phenotypic data (67 continuous variables) and penalized model-based clustering, to define and characterize mutually exclusive groups making up a novel classification of HFpEF. All phenomapping analyses were performed by investigators blinded to clinical outcomes, and Cox regression was used to demonstrate the clinical validity of phenomapping. The mean age was 65±12 years; 62% were female; 39% were black; and comorbidities were common. Although all patients met published criteria for the diagnosis of HFpEF, phenomapping analysis classified study participants into 3 distinct groups that differed markedly in clinical characteristics, cardiac structure/function, invasive hemodynamics, and outcomes (eg, phenogroup 3 had an increased risk of HF hospitalization [hazard ratio, 4.2; 95% confidence interval, 2.0-9.1] even after adjustment for traditional risk factors [P<0.001]). The HFpEF phenogroup classification, including its ability to stratify risk, was successfully replicated in a prospective validation cohort (n=107).Phenomapping results in a novel classification of HFpEF. Statistical learning algorithms applied to dense phenotypic data may allow improved classification of heterogeneous clinical syndromes, with the ultimate goal of defining therapeutically homogeneous patient subclasses.

    View details for DOI 10.1161/CIRCULATIONAHA.114.010637

    View details for Web of Science ID 000348126800012

    View details for PubMedID 25398313

    View details for PubMedCentralID PMC4302027

  • Albuminuria Is Independently Associated With Cardiac Remodeling, Abnormal Right and Left Ventricular Function, and Worse Outcomes in Heart Failure With Preserved Ejection Fraction JACC-HEART FAILURE Katz, D. H., Burns, J. A., Aguilar, F. G., Beussink, L., Shah, S. J. 2014; 2 (6): 586-596

    Abstract

    The purpose of this study was to determine the relationship between albuminuria and cardiac structure/function in heart failure with preserved ejection fraction (HFpEF).Albuminuria, a marker of endothelial dysfunction, has been associated with adverse cardiovascular outcomes in HFpEF. However, the relationship between albuminuria and cardiac structure/function in HFpEF has not been well studied.We measured urinary albumin-to-creatinine ratio (UACR) and performed comprehensive echocardiography, including tissue Doppler imaging and right ventricular (RV) evaluation, in a prospective study of 144 patients with HFpEF. Multivariable-adjusted linear regression was used to determine the association between UACR and echocardiographic parameters. Cox proportional hazards analyses were used to determine the association between UACR and outcomes.The mean age was 66 ± 11 years, 62% were female, and 42% were African American. Higher UACR was associated with greater left ventricular mass, lower preload-recruitable stroke work, and lower global longitudinal strain. Higher UACR was also significantly associated with RV remodeling (for each doubling of UACR, RV wall thickness was 0.9 mm higher [95% confidence interval: 0.05 to 0.14 mm; p = 0.001, adjusted p = 0.01]) and worse RV systolic function (for each doubling of UACR, RV fractional area change was 0.56% lower [95% confidence interval: 0.14 to 0.98%; p = 0.01, adjusted p = 0.03]. The association between UACR and RV parameters persisted after the exclusion of patients with macroalbuminuria (UACR >300 mg/g). Increased UACR was also independently associated with worse outcomes.In HFpEF, increased UACR is a prognostic marker and is associated with increased RV and left ventricular remodeling and longitudinal systolic dysfunction. (Classification of Heart Failure With Preserved Ejection Fraction; NCT01030991).

    View details for DOI 10.1016/j.jchf.2014.05.016

    View details for Web of Science ID 000365649100006

    View details for PubMedID 25282032

    View details for PubMedCentralID PMC4256131

  • Addressing Statin Adverse Effects in the Clinic: The 5 Ms JOURNAL OF CARDIOVASCULAR PHARMACOLOGY AND THERAPEUTICS Katz, D. H., Intwala, S. S., Stone, N. J. 2014; 19 (6): 533-542

    Abstract

    With the release of the 2013 American College of Cardiology/American Heart Association (ACC/AHA) Guideline on the Treatment of Blood Cholesterol to Reduce Atherosclerotic Cardiovascular Risk in Adults, emphasis has been placed on using evidence-based intensity of therapy to reduce atherosclerotic cardiovascular disease (ASCVD) risk, rather than focusing on goal cholesterol levels. Before initiating therapy, however, it is critical that physicians and patients discuss 4 key topics: (1) the benefit of ASCVD risk reduction, (2) medication adverse effects, (3) drug-drug interactions, and (4) patient preferences. To facilitate discussion of statin adverse effects, we present here an evidence-based review of the 5 Ms of statin adverse effects: metabolism, muscle, medication interactions, major organ effects, and memory. "Metabolism" represents the small risk of new-onset diabetes that comes with statins, which is highest in those with diabetes risk factors. "Muscle" requires discussion of the wide range of muscle symptoms that occur with statins but emphasizes that these have been no more prevalent than those experienced with placebo in randomized controlled trials (RCTs). "Medication interactions" emphasize that statins interact with numerous medications. Interaction profiles vary widely between statins, and patients should be made aware of the most common interactions with their prescription. "Major organ effects" prompt the physician to review the possibility of a transient transaminitis as well as the recent observation of rare acute kidney injury with statin use. Both are rare and do not require routine monitoring. Finally, "memory" references the recent observational data suggesting statins may contribute to memory loss and confusion, both of which have not been observed in RCTs and resolve with drug cessation. Reviewing these common effects has the possibility to strengthen the doctor-patient relationship and boost both medication adherence and patient satisfaction.

    View details for DOI 10.1177/1074248414529622

    View details for Web of Science ID 000343614600004

    View details for PubMedID 24770611

  • Phenotypic Spectrum of Heart Failure with Preserved Ejection Fraction HEART FAILURE CLINICS Shah, S. J., Katz, D. H., Deo, R. C. 2014; 10 (3): 407-+

    Abstract

    Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome, with several underlying etiologic and pathophysiologic factors. The heterogeneity of the HFpEF syndrome may explain why (1) diagnosing and treating HFpEF is so challenging and (2) clinical trials in HFpEF have failed thus far. Here we describe 4 ways of categorizing HFpEF based on pathophysiology, clinical/etiologic subtype, type of clinical presentation, and quantitative phenomics (phenomapping analysis). Regardless of the classification method used, improved phenotypic characterization of HFpEF, and matching targeted therapies with specific HFpEF subtypes, will be a critical step towards improving outcomes in this increasingly prevalent syndrome.

    View details for DOI 10.1016/j.hfc.2014.04.008

    View details for Web of Science ID 000339540400006

    View details for PubMedID 24975905

    View details for PubMedCentralID PMC4076705

  • Aggressive Lipid Management in Very Elderly Adults: Less Is More Response JOURNAL OF THE AMERICAN GERIATRICS SOCIETY Stone, N. J., Intwala, S., Katz, D. 2014; 62 (5): 947-948

    View details for DOI 10.1111/jgs.12788_3

    View details for Web of Science ID 000336385300024

    View details for PubMedID 24801252

  • Statins in Very Elderly Adults (Debate) JOURNAL OF THE AMERICAN GERIATRICS SOCIETY Stone, N. J., Intwala, S., Katz, D. 2014; 62 (5): 943-945

    View details for DOI 10.1111/jgs.12788_1

    View details for Web of Science ID 000336385300022

    View details for PubMedID 24800984

  • Prognostic Importance of Pathophysiologic Markers in Patients With Heart Failure and Preserved Ejection Fraction CIRCULATION-HEART FAILURE Burke, M. A., Katz, D. H., Beussink, L., Selvaraj, S., Gupta, D. K., Fox, J., Chakrabarti, S., Sauer, A. J., Rich, J. D., Freed, B. H., Shah, S. J. 2014; 7 (2): 288-299

    Abstract

    Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome associated with multiple pathophysiologic abnormalities, including left ventricular (LV) diastolic dysfunction, longitudinal LV systolic dysfunction, abnormal ventricular-arterial coupling, pulmonary hypertension, and right ventricular (RV) remodeling/dysfunction. However, the relative prognostic significance of each of these pathophysiologic abnormalities in HFpEF is unknown.We prospectively studied 419 patients with HFpEF using echocardiography and sphygmomanometry to assess HFpEF pathophysiologic markers. Cox proportional hazards analyses were used to determine the associations between pathophysiologic markers and outcomes. Mean age was 65±12 years; 62% were women; 39% were black; comorbidities were common; and study participants met published criteria for HFpEF. RV abnormalities were frequent: 28% had abnormal tricuspid annular plane systolic excursion, 15% had reduced RV fractional area change, and 34% had RV hypertrophy. During a median follow-up time of 18 months, 102 (24%) were hospitalized for HF and 175 (42%) experienced the composite end point of cardiovascular hospitalization or death. Decreased LV compliance, measured as reduced LV end-diastolic volume at an idealized LV end-diastolic pressure of 20 mm Hg (EDV20), and RV remodeling, as indicated by increased RV wall thickness, were the 2 pathophysiologic markers most predictive of worse outcomes: adjusted hazard ratio per 1 SD decrease in EDV20=1.39 (95% confidence interval [CI], 1.10-1.75; P=0.006), and hazard ratio per 1 SD increase in RV wall thickness=1.37 (95% CI, 1.16-1.61; P<0.001). These associations persisted after additional adjustment for markers of HF severity. By contrast, markers of LV relaxation, longitudinal LV systolic dysfunction, and ventricular-arterial coupling were not significantly associated with adverse outcomes.In patients with HFpEF, reduced LV compliance and RV remodeling are the strongest pathophysiologic predictors of adverse outcomes.

    View details for DOI 10.1161/CIRCHEARTFAILURE.113.000854

    View details for Web of Science ID 000333759600008

    View details for PubMedID 24365774

    View details for PubMedCentralID PMC5947992

  • Association of Low-Grade Albuminuria With Adverse Cardiac Mechanics Findings From the Hypertension Genetic Epidemiology Network (HyperGEN) Study CIRCULATION Katz, D. H., Selvaraj, S., Aguilar, F. G., Martinez, E. E., Beussink, L., Kim, K. A., Peng, J., Sha, J., Irvin, M. R., Eckfeldt, J. H., Turner, S. T., Freedman, B. I., Arnett, D. K., Shah, S. J. 2014; 129 (1): 42-+

    Abstract

    Albuminuria is a marker of endothelial dysfunction and has been associated with adverse cardiovascular outcomes. The reasons for this association are unclear but may be attributable to the relationship between endothelial dysfunction and intrinsic myocardial dysfunction.In the Hypertension Genetic Epidemiology Network (HyperGEN) Study, a population- and family-based study of hypertension, we examined the relationship between urine albumin-to-creatinine ratio (UACR) and cardiac mechanics (n=1894, all of whom had normal left ventricular ejection fraction and wall motion). We performed speckle-tracking echocardiographic analysis to quantify global longitudinal, circumferential, and radial strain, and early diastolic (e') tissue velocities. We used E/e' ratio as a marker of increased left ventricular filling pressures. We used multivariable-adjusted linear mixed effect models to determine independent associations between UACR and cardiac mechanics. The mean age was 50±14 years, 59% were female, and 46% were black. Comorbidities were increasingly prevalent among higher UACR quartiles. Albuminuria was associated with global longitudinal strain, global circumferential strain, global radial strain, e' velocity, and E/e' ratio on unadjusted analyses. After adjustment for covariates, UACR was independently associated with lower absolute global longitudinal strain (multivariable-adjusted mean global longitudinal strain [95% confidence interval] for UACR Quartile 1 = 15.3 [15.0-15.5]% versus UACR Q4 = 14.6 [14.3-14.9]%, P for trend <0.001) and increased E/e' ratio (Q1 = 25.3 [23.5-27.1] versus Q4 = 29.0 [27.0-31.0], P=0.003). The association between UACR and global longitudinal strain was present even in participants with UACR < 30 mg/g (P<0.001 after multivariable adjustment).Albuminuria, even at low levels, is associated with adverse cardiac mechanics and higher E/e' ratio.

    View details for DOI 10.1161/CIRCULATIONAHA.113.003429

    View details for Web of Science ID 000336726300009

    View details for PubMedID 24077169

    View details for PubMedCentralID PMC3888488

  • Prevalence, Clinical Characteristics, and Outcomes Associated With Eccentric Versus Concentric Left Ventricular Hypertrophy in Heart Failure With Preserved Ejection Fraction AMERICAN JOURNAL OF CARDIOLOGY Katz, D. H., Beussink, L., Sauer, A. J., Freed, B. H., Burke, M. A., Shah, S. J. 2013; 112 (8): 1158-1164

    Abstract

    Although concentric remodeling (CR) and concentric hypertrophy (CH) are common forms of left ventricular (LV) remodeling in heart failure with preserved ejection fraction (HFpEF), eccentric hypertrophy (EH) can also occur in these patients. However, clinical characteristics and outcomes of EH have not been well described in HFpEF. We prospectively studied 402 patients with HFpEF, divided into 4 groups based on LV structure: normal geometry (no LV hypertrophy [LVH] and relative wall thickness [RWT] ≤0.42); CR (no LVH and RWT >0.42); CH (LVH and RWT >0.42); and EH (LVH and RWT ≤0.42). We compared clinical, laboratory, echocardiographic, invasive hemodynamic, and outcome data among groups. Of 402 patients, 48 (12%) had EH. Compared with CH, patients with EH had lower systolic blood pressure and less renal impairment despite similar rates of hypertension. After adjustment for covariates, EH was associated with reduced LV contractility compared with CH: lower LVEF (β coefficient = -3.2; 95% confidence interval [CI] -5.4 to -1.1%) and ratio of systolic blood pressure to end-systolic volume (β coefficient = -1.0; 95% CI -1.5 to -0.5 mm Hg/ml). EH was also associated with increased LV compliance compared with CH (LV end-diastolic volume at an idealized LV end-diastolic pressure of 20 mm Hg β coefficient = 14.2; 95% CI 9.4 to 19.1 ml). Despite these differences, EH and CH had similarly elevated cardiac filling pressures and equivalent adverse outcomes. In conclusion, the presence of EH denotes a distinct subset of HFpEF that is pathophysiologically similar to HF with reduced EF (HFrEF) and may benefit from HFrEF therapy.

    View details for DOI 10.1016/j.amjcard.2013.05.061

    View details for Web of Science ID 000325833700017

    View details for PubMedID 23810323

    View details for PubMedCentralID PMC3788852