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1. Integrative omics identifies conserved and pathogen-specific responses of sepsis-causing bacteria.

Author

Mu, A, Klare, WP, Baines, SL, Ignatius Pang, CN, Guérillot, R, Harbison-Price, N, Keller, N, Wilksch, J, Nhu, NTK, Phan, M-D, Keller, B, Nijagal, B, Tull, D, Dayalan, S, Chua, HHC, Skoneczny, D, Koval, J, Hachani, A, Shah, AD, Neha, N, Jadhav, S, Partridge, SR, Cork, AJ, Peters, K, Bertolla, O, Brouwer, S, Hancock, SJ, Álvarez-Fraga, L, De Oliveira, DMP, Forde, B, Dale, A, Mujchariyakul, W, Walsh, CJ, Monk, I, Fitzgerald, A, Lum, M, Correa-Ospina, C, Roy Chowdhury, P, Parton, RG, De Voss, J, Beckett, J, Monty, F, McKinnon, J, Song, X, Stephen, JR, Everest, M, Bellgard, MI, Tinning, M, Leeming, M, Hocking, D, Jebeli, L, Wang, N, Ben Zakour, N, Yasar, SA, Vecchiarelli, S, Russell, T, Zaw, T, Chen, T, Teng, D, Kassir, Z, Lithgow, T, Jenney, A, Cole, JN, Nizet, V, Sorrell, TC, Peleg, AY, Paterson, DL, Beatson, SA, Wu, J, Molloy, MP, Syme, AE, Goode, RJA, Hunter, AA, Bowland, G, West, NP, Wilkins, MR, Djordjevic, SP, Davies, MR, Seemann, T, Howden, BP, Pascovici, D, Tyagi, S, Schittenhelm, RB, De Souza, DP, McConville, MJ, Iredell, JR, Cordwell, SJ, Strugnell, RA, Stinear, TP, Schembri, MA, Walker, MJ, Mu, A, Klare, WP, Baines, SL, Ignatius Pang, CN, Guérillot, R, Harbison-Price, N, Keller, N, Wilksch, J, Nhu, NTK, Phan, M-D, Keller, B, Nijagal, B, Tull, D, Dayalan, S, Chua, HHC, Skoneczny, D, Koval, J, Hachani, A, Shah, AD, Neha, N, Jadhav, S, Partridge, SR, Cork, AJ, Peters, K, Bertolla, O, Brouwer, S, Hancock, SJ, Álvarez-Fraga, L, De Oliveira, DMP, Forde, B, Dale, A, Mujchariyakul, W, Walsh, CJ, Monk, I, Fitzgerald, A, Lum, M, Correa-Ospina, C, Roy Chowdhury, P, Parton, RG, De Voss, J, Beckett, J, Monty, F, McKinnon, J, Song, X, Stephen, JR, Everest, M, Bellgard, MI, Tinning, M, Leeming, M, Hocking, D, Jebeli, L, Wang, N, Ben Zakour, N, Yasar, SA, Vecchiarelli, S, Russell, T, Zaw, T, Chen, T, Teng, D, Kassir, Z, Lithgow, T, Jenney, A, Cole, JN, Nizet, V, Sorrell, TC, Peleg, AY, Paterson, DL, Beatson, SA, Wu, J, Molloy, MP, Syme, AE, Goode, RJA, Hunter, AA, Bowland, G, West, NP, Wilkins, MR, Djordjevic, SP, Davies, MR, Seemann, T, Howden, BP, Pascovici, D, Tyagi, S, Schittenhelm, RB, De Souza, DP, McConville, MJ, Iredell, JR, Cordwell, SJ, Strugnell, RA, Stinear, TP, Schembri, MA, and Walker, MJ

Abstract

Even in the setting of optimal resuscitation in high-income countries severe sepsis and septic shock have a mortality of 20-40%, with antibiotic resistance dramatically increasing this mortality risk. To develop a reference dataset enabling the identification of common bacterial targets for therapeutic intervention, we applied a standardized genomic, transcriptomic, proteomic and metabolomic technological framework to multiple clinical isolates of four sepsis-causing pathogens: Escherichia coli, Klebsiella pneumoniae species complex, Staphylococcus aureus and Streptococcus pyogenes. Exposure to human serum generated a sepsis molecular signature containing global increases in fatty acid and lipid biosynthesis and metabolism, consistent with cell envelope remodelling and nutrient adaptation for osmoprotection. In addition, acquisition of cholesterol was identified across the bacterial species. This detailed reference dataset has been established as an open resource to support discovery and translational research.

Published
2023

2. Developing clinical indicators for oncology: the inaugural cancer care indicator set for the Australian Council on Healthcare Standards

Author

Segelov, E, Carrington, C, Aranda, S, Currow, D, Zalcberg, JR, Heriot, AG, Mileshkin, L, Coutsouvelis, J, Millar, JL, Collopy, BT, Emery, JD, Zhang, P, Cooper, S, O'Kane, C, Wale, J, Hancock, SJ, Sulkowski, A, Bashford, J, Segelov, E, Carrington, C, Aranda, S, Currow, D, Zalcberg, JR, Heriot, AG, Mileshkin, L, Coutsouvelis, J, Millar, JL, Collopy, BT, Emery, JD, Zhang, P, Cooper, S, O'Kane, C, Wale, J, Hancock, SJ, Sulkowski, A, and Bashford, J

Abstract

INTRODUCTION: The Australian Council on Healthcare Standards (ACHS) sponsored an expert-led, consensus-driven, four-stage process, based on a modified Delphi methodology, to determine a set of clinical indicators as quality measures of cancer service provision in Australia. This was done in response to requests from institutional health care providers seeking accreditation, which were additional and complementary to the existing radiation oncology set. The steering group members comprised multidisciplinary key opinion leaders and a consumer representative. Five additional participants constituted the stakeholder group, who deliberated on the final indicator set. METHODS AND RECOMMENDATIONS: An initial meeting of the steering group scoped the high level nature of the desired set. In stage 2, 65 candidate indicators were identified by a literature review and a search of international metrics. These were ranked by survey, based on ease of data accessibility and collectability and clinical relevance. The top 27 candidates were debated by the stakeholder group and culled to a final set of 16 indicators. A user manual was created with indicators mapped to clinical codes. The indicator set was ratified by the Clinical Oncology Society of Australia and is now available for use by health care organisations participating in the ACHS Clinical Indicator Program. This inaugural cancer clinical indicator set covers high level assessment of various critical processes in cancer service provision in Australia. Regular reviews and updates will ensure usability. CHANGES IN MANAGEMENT AS A RESULT OF THIS STATEMENT: This is the inaugural indicator set for cancer care for use across Australia and internationally under the ACHS Clinical Indicator Program. Multidisciplinary involvement through a modified Delphi process selected indicators representing both generic and specific aspects of care across the cancer journey pathway and will provide a functional tool to compare health care delive

Published
2021

3. Developing clinical indicators for oncology: the inaugural cancer care indicator set for the Australian Council on Healthcare Standards.

Author

Segelov, E, Carrington, C, Aranda, S, Currow, D, Zalcberg, JR, Heriot, AG, Mileshkin, L, Coutsouvelis, J, Millar, JL, Collopy, BT, Emery, JD, Zhang, P, Cooper, S, O'Kane, C, Wale, J, Hancock, SJ, Sulkowski, A, Bashford, J, Segelov, E, Carrington, C, Aranda, S, Currow, D, Zalcberg, JR, Heriot, AG, Mileshkin, L, Coutsouvelis, J, Millar, JL, Collopy, BT, Emery, JD, Zhang, P, Cooper, S, O'Kane, C, Wale, J, Hancock, SJ, Sulkowski, A, and Bashford, J

Abstract

INTRODUCTION: The Australian Council on Healthcare Standards (ACHS) sponsored an expert-led, consensus-driven, four-stage process, based on a modified Delphi methodology, to determine a set of clinical indicators as quality measures of cancer service provision in Australia. This was done in response to requests from institutional health care providers seeking accreditation, which were additional and complementary to the existing radiation oncology set. The steering group members comprised multidisciplinary key opinion leaders and a consumer representative. Five additional participants constituted the stakeholder group, who deliberated on the final indicator set. METHODS AND RECOMMENDATIONS: An initial meeting of the steering group scoped the high level nature of the desired set. In stage 2, 65 candidate indicators were identified by a literature review and a search of international metrics. These were ranked by survey, based on ease of data accessibility and collectability and clinical relevance. The top 27 candidates were debated by the stakeholder group and culled to a final set of 16 indicators. A user manual was created with indicators mapped to clinical codes. The indicator set was ratified by the Clinical Oncology Society of Australia and is now available for use by health care organisations participating in the ACHS Clinical Indicator Program. This inaugural cancer clinical indicator set covers high level assessment of various critical processes in cancer service provision in Australia. Regular reviews and updates will ensure usability. CHANGES IN MANAGEMENT AS A RESULT OF THIS STATEMENT: This is the inaugural indicator set for cancer care for use across Australia and internationally under the ACHS Clinical Indicator Program. Multidisciplinary involvement through a modified Delphi process selected indicators representing both generic and specific aspects of care across the cancer journey pathway and will provide a functional tool to compare health care delive

Published
2021

4. Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function

Author

Pattaro, C, Teumer, A, Gorski, M, Chu, AY, Li, M, Mijatovic, V, Garnaas, M, Tin, A, Sorice, R, Li, Y, Taliun, D, Olden, M, Foster, M, Yang, Q, Chen, M-H, Pers, TH, Johnson, AD, Ko, Y-A, Fuchsberger, C, Tayo, B, Nalls, M, Feitosa, MF, Isaacs, A, Dehghan, A, d'Adamo, P, Adeyemo, A, Dieffenbach, AK, Zonderman, AB, Nolte, IM, van der Most, PJ, Wright, AF, Shuldiner, AR, Morrison, AC, Hofman, A, Smith, AV, Dreisbach, AW, Franke, A, Uitterlinden, AG, Metspalu, A, Tonjes, A, Lupo, A, Robino, A, Johansson, A, Demirkan, A, Kollerits, B, Freedman, BI, Ponte, B, Oostra, BA, Paulweber, B, Kraemer, BK, Mitchell, BD, Buckley, BM, Peralta, CA, Hayward, C, Helmer, C, Rotimi, CN, Shaffer, CM, Mueller, C, Sala, C, van Duijn, CM, Saint-Pierre, A, Ackermann, D, Shriner, D, Ruggiero, D, Toniolo, D, Lu, Y, Cusi, D, Czamara, D, Ellinghaus, D, Siscovick, DS, Ruderfer, D, Gieger, C, Grallert, H, Rochtchina, E, Atkinson, EJ, Holliday, EG, Boerwinkle, E, Salvi, E, Bottinger, EP, Murgia, F, Rivadeneira, F, Ernst, F, Kronenberg, F, Hu, FB, Navis, GJ, Curhan, GC, Ehret, GB, Homuth, G, Coassin, S, Thun, G-A, Pistis, G, Gambaro, G, Malerba, G, Montgomery, GW, Eiriksdottir, G, Jacobs, G, Li, G, Wichmann, H-E, Campbell, H, Schmidt, H, Wallaschofski, H, Voelzke, H, Brenner, H, Kroemer, HK, Kramer, H, Lin, H, Leach, IM, Ford, I, Guessous, I, Rudan, I, Prokopenko, I, Borecki, I, Heid, IM, Kolcic, I, Persico, I, Jukema, JW, Wilson, JF, Felix, JF, Divers, J, Lambert, J-C, Stafford, JM, Gaspoz, J-M, Smith, JA, Faul, JD, Wang, JJ, Ding, J, Hirschhorn, JN, Attia, J, Whitfield, JB, Chalmers, J, Viikari, J, Coresh, J, Denny, JC, Karjalainen, J, Fernandes, JK, Endlich, K, Butterbach, K, Keene, KL, Lohman, K, Portas, L, Launer, LJ, Lyytikaeinen, L-P, Yengo, L, Franke, L, Ferrucci, L, Rose, LM, Kedenko, L, Rao, M, Struchalin, M, Kleber, ME, Cavalieri, M, Haun, M, Cornelis, MC, Ciullo, M, Pirastu, M, de Andrade, M, McEvoy, MA, Woodward, M, Adam, M, Cocca, M, Nauck, M, Imboden, M, Waldenberger, M, Pruijm, M, Metzger, M, Stumvoll, M, Evans, MK, Sale, MM, Kaehoenen, M, Boban, M, Bochud, M, Rheinberger, M, Verweij, N, Bouatia-Naji, N, Martin, NG, Hastie, N, Probst-Hensch, N, Soranzo, N, Devuyst, O, Raitakari, O, Gottesman, O, Franco, OH, Polasek, O, Gasparini, P, Munroe, PB, Ridker, PM, Mitchell, P, Muntner, P, Meisinger, C, Smit, JH, Kovacs, P, Wild, PS, Froguel, P, Rettig, R, Maegi, R, Biffar, R, Schmidt, R, Middelberg, RPS, Carroll, RJ, Penninx, BW, Scott, RJ, Katz, R, Sedaghat, S, Wild, SH, Kardia, SLR, Ulivi, S, Hwang, S-J, Enroth, S, Kloiber, S, Trompet, S, Stengel, B, Hancock, SJ, Turner, ST, Rosas, SE, Stracke, S, Harris, TB, Zeller, T, Zemunik, T, Lehtimaeki, T, Illig, T, Aspelund, T, Nikopensius, T, Esko, T, Tanaka, T, Gyllensten, U, Voelker, U, Emilsson, V, Vitart, V, Aalto, V, Gudnason, V, Chouraki, V, Chen, W-M, Igl, W, Maerz, W, Koenig, W, Lieb, W, Loos, RJF, Liu, Y, Snieder, H, Pramstaller, PP, Parsa, A, O'Connell, JR, Susztak, K, Hamet, P, Tremblay, J, de Boer, IH, Boeger, CA, Goessling, W, Chasman, DI, Koettgen, A, Kao, WHL, Fox, CS, Pattaro, C, Teumer, A, Gorski, M, Chu, AY, Li, M, Mijatovic, V, Garnaas, M, Tin, A, Sorice, R, Li, Y, Taliun, D, Olden, M, Foster, M, Yang, Q, Chen, M-H, Pers, TH, Johnson, AD, Ko, Y-A, Fuchsberger, C, Tayo, B, Nalls, M, Feitosa, MF, Isaacs, A, Dehghan, A, d'Adamo, P, Adeyemo, A, Dieffenbach, AK, Zonderman, AB, Nolte, IM, van der Most, PJ, Wright, AF, Shuldiner, AR, Morrison, AC, Hofman, A, Smith, AV, Dreisbach, AW, Franke, A, Uitterlinden, AG, Metspalu, A, Tonjes, A, Lupo, A, Robino, A, Johansson, A, Demirkan, A, Kollerits, B, Freedman, BI, Ponte, B, Oostra, BA, Paulweber, B, Kraemer, BK, Mitchell, BD, Buckley, BM, Peralta, CA, Hayward, C, Helmer, C, Rotimi, CN, Shaffer, CM, Mueller, C, Sala, C, van Duijn, CM, Saint-Pierre, A, Ackermann, D, Shriner, D, Ruggiero, D, Toniolo, D, Lu, Y, Cusi, D, Czamara, D, Ellinghaus, D, Siscovick, DS, Ruderfer, D, Gieger, C, Grallert, H, Rochtchina, E, Atkinson, EJ, Holliday, EG, Boerwinkle, E, Salvi, E, Bottinger, EP, Murgia, F, Rivadeneira, F, Ernst, F, Kronenberg, F, Hu, FB, Navis, GJ, Curhan, GC, Ehret, GB, Homuth, G, Coassin, S, Thun, G-A, Pistis, G, Gambaro, G, Malerba, G, Montgomery, GW, Eiriksdottir, G, Jacobs, G, Li, G, Wichmann, H-E, Campbell, H, Schmidt, H, Wallaschofski, H, Voelzke, H, Brenner, H, Kroemer, HK, Kramer, H, Lin, H, Leach, IM, Ford, I, Guessous, I, Rudan, I, Prokopenko, I, Borecki, I, Heid, IM, Kolcic, I, Persico, I, Jukema, JW, Wilson, JF, Felix, JF, Divers, J, Lambert, J-C, Stafford, JM, Gaspoz, J-M, Smith, JA, Faul, JD, Wang, JJ, Ding, J, Hirschhorn, JN, Attia, J, Whitfield, JB, Chalmers, J, Viikari, J, Coresh, J, Denny, JC, Karjalainen, J, Fernandes, JK, Endlich, K, Butterbach, K, Keene, KL, Lohman, K, Portas, L, Launer, LJ, Lyytikaeinen, L-P, Yengo, L, Franke, L, Ferrucci, L, Rose, LM, Kedenko, L, Rao, M, Struchalin, M, Kleber, ME, Cavalieri, M, Haun, M, Cornelis, MC, Ciullo, M, Pirastu, M, de Andrade, M, McEvoy, MA, Woodward, M, Adam, M, Cocca, M, Nauck, M, Imboden, M, Waldenberger, M, Pruijm, M, Metzger, M, Stumvoll, M, Evans, MK, Sale, MM, Kaehoenen, M, Boban, M, Bochud, M, Rheinberger, M, Verweij, N, Bouatia-Naji, N, Martin, NG, Hastie, N, Probst-Hensch, N, Soranzo, N, Devuyst, O, Raitakari, O, Gottesman, O, Franco, OH, Polasek, O, Gasparini, P, Munroe, PB, Ridker, PM, Mitchell, P, Muntner, P, Meisinger, C, Smit, JH, Kovacs, P, Wild, PS, Froguel, P, Rettig, R, Maegi, R, Biffar, R, Schmidt, R, Middelberg, RPS, Carroll, RJ, Penninx, BW, Scott, RJ, Katz, R, Sedaghat, S, Wild, SH, Kardia, SLR, Ulivi, S, Hwang, S-J, Enroth, S, Kloiber, S, Trompet, S, Stengel, B, Hancock, SJ, Turner, ST, Rosas, SE, Stracke, S, Harris, TB, Zeller, T, Zemunik, T, Lehtimaeki, T, Illig, T, Aspelund, T, Nikopensius, T, Esko, T, Tanaka, T, Gyllensten, U, Voelker, U, Emilsson, V, Vitart, V, Aalto, V, Gudnason, V, Chouraki, V, Chen, W-M, Igl, W, Maerz, W, Koenig, W, Lieb, W, Loos, RJF, Liu, Y, Snieder, H, Pramstaller, PP, Parsa, A, O'Connell, JR, Susztak, K, Hamet, P, Tremblay, J, de Boer, IH, Boeger, CA, Goessling, W, Chasman, DI, Koettgen, A, Kao, WHL, and Fox, CS

Abstract

Reduced glomerular filtration rate defines chronic kidney disease and is associated with cardiovascular and all-cause mortality. We conducted a meta-analysis of genome-wide association studies for estimated glomerular filtration rate (eGFR), combining data across 133,413 individuals with replication in up to 42,166 individuals. We identify 24 new and confirm 29 previously identified loci. Of these 53 loci, 19 associate with eGFR among individuals with diabetes. Using bioinformatics, we show that identified genes at eGFR loci are enriched for expression in kidney tissues and in pathways relevant for kidney development and transmembrane transporter activity, kidney structure, and regulation of glucose metabolism. Chromatin state mapping and DNase I hypersensitivity analyses across adult tissues demonstrate preferential mapping of associated variants to regulatory regions in kidney but not extra-renal tissues. These findings suggest that genetic determinants of eGFR are mediated largely through direct effects within the kidney and highlight important cell types and biological pathways.

Published
2016

5. Genetics of hand grip strength in mid to late life

Author

Chan, JPL, Thalamuthu, A, Oldmeadow, C, Armstrong, NJ, Holliday, EG, McEvoy, M, Kwok, JB, Assareh, AA, Peel, R, Hancock, SJ, Reppermund, S, Menant, J, Trollor, JN, Brodaty, H, Schofield, PR, Attia, JR, Sachdev, PS, Scott, RJ, Mather, KA, Chan, JPL, Thalamuthu, A, Oldmeadow, C, Armstrong, NJ, Holliday, EG, McEvoy, M, Kwok, JB, Assareh, AA, Peel, R, Hancock, SJ, Reppermund, S, Menant, J, Trollor, JN, Brodaty, H, Schofield, PR, Attia, JR, Sachdev, PS, Scott, RJ, and Mather, KA

Abstract

Hand grip strength (GS) is a predictor of mortality in older adults and is moderately to highly heritable, but no genetic variants have been consistently identified. We aimed to identify single nucleotide polymorphisms (SNPs) associated with GS in middle-aged to older adults using a genome-wide association study (GWAS). GS was measured using handheld dynamometry in community-dwelling men and women aged 55-85 from the Hunter Community Study (HCS, N = 2088) and the Sydney Memory and Ageing Study (Sydney MAS, N = 541). Genotyping was undertaken using Affymetrix microarrays with imputation to HapMap2. Analyses were performed using linear regression. No genome-wide significant results were observed in HCS nor were any of the top signals replicated in Sydney MAS. Gene-based analyses in HCS identified two significant genes (ZNF295, C2CD2), but these results were not replicated in Sydney MAS. One out of eight SNPs previously associated with GS, rs550942, located near the CNTF gene, was significantly associated with GS (p = 0.005) in the HCS cohort only. Study differences may explain the lack of consistent results between the studies, including the smaller sample size of the Sydney MAS cohort. Our modest sample size also had limited power to identify variants of small effect. Our results suggest that similar to various other complex traits, many genetic variants of small effect size may influence GS. Future GWAS using larger samples and consistent measures may prove more fruitful at identifying genetic contributors for GS in middle-aged to older adults.

Published
2015

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