title: Potentially modifiable factors affecting the progression of autosomal dominant polycystic kidney disease.
abstract: OBJECTIVE
  The Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP) was created to identify markers of disease progression in patients with autosomal dominant polycystic kidney disease (ADPKD).
  
  
  METHODS
  Linear mixed models were utilized to model effects of baseline parameters on changes in natural-log (ln)-transformed total kidney volume (TKV) and iothalamate clearance (GFR) across time in CRISP participants (creatinine clearance at entry >70 ml/min). Stepwise selection was used to obtain a final main effect model.
  
  
  RESULTS
  TKV increased from year to year, whereas GFR uncorrected for body surface area (BSA) decreased only at year 6. Higher lnTKV and urine sodium excretion (U(Na)V), lower serum HDL-cholesterol, and younger age at baseline associated with greater lnTKV growth from baseline to year 3 and to year 6. Higher lnTKV at baseline associated with greater GFR decline from year 1 to year 3 and to year 6. Higher BSA and 24-hour urine osmolality at baseline associated with greater GFR decline from year 1 to year 6. Higher U(Na)V and lower serum HDL-cholesterol at baseline associated with greater GFR decline from year 1 to year 6 by univariate analysis only. Associations seen during year 1 to year 6 (not seen during year 1 to year 3) reflect the time lag between structural and functional disease progression.
  
  
  CONCLUSIONS
  Serum HDL-cholesterol, U(Na)V, and 24-hour urine osmolality likely affect ADPKD progression. To what extent their modification may influence the clinical course of ADPKD remains to be determined.
authors.affiliation: Mayo Clinic College of Medicine, Rochester, Minnesota, MN, USA. torres.vicente@mayo.edu
authors.forename: Vicente E
authors.initials: VE
authors.lastname: Torres
authors.forename: Jared J
authors.initials: JJ
authors.lastname: Grantham
authors.forename: Arlene B
authors.initials: AB
authors.lastname: Chapman
authors.forename: Michal
authors.initials: M
authors.lastname: Mrug
authors.forename: Kyongtae T
authors.initials: KT
authors.lastname: Bae
authors.forename: Bernard F
authors.initials: BF
authors.lastname: King
authors.forename: Louis H
authors.initials: LH
authors.lastname: Wetzel
authors.forename: Diego
authors.initials: D
authors.lastname: Martin
authors.forename: Mark E
authors.initials: ME
authors.lastname: Lockhart
authors.forename: William M
authors.initials: WM
authors.lastname: Bennett
authors.forename: Marva
authors.initials: M
authors.lastname: Moxey-Mims
authors.forename: Kaleab Z
authors.initials: KZ
authors.lastname: Abebe
authors.forename: Yan
authors.initials: Y
authors.lastname: Lin
authors.forename: James E
authors.initials: JE
authors.lastname: Bost
mesh_terms: D000328:Adult; D000367:Age Factors; D008076:Cholesterol, HDL / Q000097:blood; D018450:Disease Progression; D005260:Female; D005500:Follow-Up Studies; D005919:Glomerular Filtration Rate; D006801:Humans; D007483:Iothalamic Acid; D007668:Kidney / Q000378:metabolism / Q000473:pathology / Q000503:physiopathology; D016014:Linear Models; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D009318:Natriuresis; D009929:Organ Size; D009994:Osmolar Concentration; D010641:Phenotype; D016891:Polycystic Kidney, Autosomal Dominant / Q000175:diagnosis* / Q000378:metabolism / Q000503:physiopathology; D011379:Prognosis; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors; D014481:United States
chemical_list: D008076:Cholesterol, HDL; D007483:Iothalamic Acid