Vitamin D and Omega-3 Trial to Prevent and Treat Diabetic Kidney Disease
Phase: NA
Conditions: Diabetes
Sponsor: University of Washington

 
 
 
 
 
 
Randomized Clinical Trial of Vitamin D and Omega-3 Fatty Acids  
for Diabetic Kidney Disease 
 
 
Protocol 
June 28, 2010 
 
 
Short title: 
VITAL Diabetes 
  
 
Principal Investigators:   
 Overall PI:  Ian H. de Boer, MD, MS 
Brigham Women's Hospital Site PI:  Debra Schaumberg, ScD, OD, MPH 
  
  
Supported by:  
National Institutes of Health 
R01 DK088762-01  
  
 
Study Interventions and IND: 
Described separately as part of the parent Vitamin D and Omega-3 Trial (VITAL) Study 
  
  

 
2
Study Team Roster 
 
Ian H. de Boer, MD MS 
Principal Investigator 
Assistant Professor of Medicine 
Division of Nephrology and Kidney Research Institute 
University of Washington 
Telephone (206) 616-5403 
Fax (206) 685-8661 
Pager (206) 540-9789 
deboer@u.washington.edu 
 
Debra Schaumberg, ScD, OD, MPH 
Brigham Women's Hospital Site Principal Investigator 
Associate Professor of Medicine and Ophthalmology 
Division of Preventive Medicine 
Brigham & Women’s Hospital  
Harvard Medical School 
Telephone (617) 278-0849 
Fax (617) 731-3843 
dschaumberg@rics.bwh.harvard.edu  
 
JoAnn Manson, MD, DrPH 
Co-investigator 
Professor of Medicine 
Division of Preventive Medicine 
Brigham & Women’s Hospital  
Harvard Medical School 
Telephone (617) 278-0871 
Fax (617) 731-3843 
jmanson@rics.bwh.harvard.edu  
 
Julie Lin, MD 
Co-investigator 
Assistant Professor of Medicine 
Renal Division 
Brigham and Women's Hospital 
75 Francis St  
Boston, MA 02115 
Telephone 617-732-6432 
Fax 617-732-6392 
JLIN11@partners.org 
 
Robert Glynn, PhD 
Biostatistician, Co-investigator 
Associate Professor of Medicine 
Division of Preventive Medicine 
Brigham & Women’s Hospital 
Harvard Medical School 
Telephone (617) 278-0792 
Fax (617) 731-3843 
rglynn@rics.bwh.harvard.edu 
 
Elaine Zaharris 
Project Coordinator 

 
3
Division of Preventive Medicine 
Brigham & Women’s Hospital 
Telephone (617) 2780893 
Fax (617) 731-3843 
 

 
4
Abstract 
Diabetic kidney disease (DKD) is a cause of substantial morbidity and mortality.  Despite widespread use 
of intensive glycemic control and renin-angiotensin-aldosterone system inhibitors, renal and cardiovascular 
consequences of DKD remain common.  This study will evaluate whether vitamin D3 and/or omega-3 fatty 
acids are safe and effective interventions to reduce the burden of DKD among the large and growing diabetic 
population.  Specifically, we aim to test whether vitamin D3 and/or omega-3 fatty acids prevent progression of 
albuminuria and loss of glomerular filtration rate, two complementary manifestations of DKD, over 4 years of 
treatment.  To effectively and efficiently test our hypotheses, we will conduct an ancillary study to the Vitamin D 
and Omega-3 Trial (VITAL), an NIH-funded randomized clinical trial.  In the parent VITAL study, 20,000 
participants (men ages ≥ 60 years, women ages ≥ 65 years) will be randomly assigned in a 2x2 factorial design 
to vitamin D3 (cholecalciferol) 2000 IU daily versus placebo, and to eicosapentaenoic acid plus 
docosahexaenoic acid 840 mg daily versus placebo, and followed for a mean of 5 years to assess effects on 
cardiovascular disease and cancer events.  Leveraging the established infrastructure of VITAL, the ancillary 
study described herein (the VITAL Diabetes sub-study) will identify and recruit a sub-cohort of 1,500 VITAL 
participants with diabetes at baseline.  Among this VITAL subgroup, we will ascertain effects of the VITAL 
interventions on albuminuria and glomerular filtration rate by obtaining additional questionnaire data and urine 
and blood samples.  Following the simple and cost-efficient design of the parent VITAL trial, biospecimens will 
be collected locally and delivered to the VITAL central laboratory by mail.  First morning voids will be collected 
at baseline and year 4 for measurement of urine albumin-creatinine ratio.  Blood samples will be collected 
simultaneously for measurement of glomerular filtration rate (using serum creatinine and cystatin C), 25-
hydroxyvitamin D, eicosapentaenoic acid plus docosahexaenoic acid, C-reactive protein, and hemoglobin A1c. 
This ancillary study is designed to determine whether vitamin D3 and/or omega-3 fatty acids have causal and 
clinically relevant effects on the development and progression of DKD. 

 
5
I. Background 
I.a. 
Public health impact of diabetic kidney disease 
I.a.1. Definition of DKD.  Chronic kidney disease is defined by albuminuria or impaired glomerular filtration 
rate (GFR).1 Diabetic kidney disease (DKD), defined as chronic kidney disease clinically attributable to 
diabetes,1, 2 is the most common cause of kidney disease in the developed world.3 The large majority of 
persons with DKD do not undergo kidney biopsy to definitively establish a pathology-based diagnosis of 
diabetic glomerulopathy, and some persons diagnosed with DKD have a nondiabetic cause of kidney disease. 
However, biopsy series confirm that the majority of persons diagnosed clinically with DKD do have diabetic 
glomerulopathy, and diagnosis and treatment of DKD in practice is currently based on clinical assessment of 
albuminuria and GFR in the setting of diagnosed diabetes.1, 2, 4 The American Diabetes Association and 
National Kidney Foundation recommend that albuminuria be assessed as albumin-creatinine ratio (ACR) in a 
spot urine sample, with abnormal defined as ACR ≥ 30 mg albumin/g creatinine, and that GFR be calculated 
from serum creatinine, with estimated GFR < 60 mL/min/1.73m2 defined as abnormal.1, 2, 4 
I.a.2. DKD is common.  The prevalence of diabetes is increasing 
worldwide, reaching 30% among US adults ages ≥ 60 years based on 
recent NHANES data (diagnosed diabetes 15-18% prevalence).5 
Individuals with diabetes are at high risk of developing DKD.  In 
NHANES III, 42% of persons with self-reported diabetes had prevalent 
elevated urine ACR and/or elevated serum creatinine, compared with 
14% of the unselected United States population.6 In addition, the 
prevalence of kidney disease is highest and increasing most rapidly 
among older adults (Figure 1).7 Thus, from a public health perspective, 
targeting older persons with diabetes offers the highest yield 
opportunity to prevent and treat kidney disease and its complications.  
Moreover, as the United States population continues to age, grow 
more obese, and develop more diabetes, the prevalence of DKD is 
expected to rise for the foreseeable future.5, 7-10 
 I.a.3. DKD health outcomes are poor.  The major adverse health 
outcomes of DKD are end-stage renal disease (ESRD), CVD, and 
death.  The natural renal history of DKD consists of progressively 
increasing levels of urine albumin excretion and relentless loss of 
GFR.11 While it is now clear that low levels of albuminuria (“microalbuminuria”) may regress, either 
spontaneously or with treatment, many individuals progress to advanced stages of DKD.3, 11-14 In 2006, DKD 
was the attributed cause of 49,224 cases of incident ESRD (44%) in the United States alone.3 In addition, the 
presence and severity of DKD potently amplifies CVD risk.15-18 Albuminuria and impaired GFR are each 
associated with increased prevalence and severity of traditional CVD risk factors, such as hypertension and 
dyslipidemia.19-24 Kidney disease is also associated with novel CVD risk factors, including inflammation, 
oxidative stress, anemia, disordered mineral metabolism, and vascular calcification.24-29 As a result, the 
prevalence and incidence of CVD are directly proportional to the severity of DKD.  Moreover, as demonstrated 
in the United Kingdom 
Prospective Diabetes Study 
(UKPDS) and other 
longitudinal studies, 
mortality is markedly 
increased with greater 
severity of DKD (Figure 
2).14, 30-33 More specifically, 
we have demonstrated that 
albuminuria and estimated 
GFR are independently and 
additively associated with 
all-cause- and CVD-specific- 
mortality among older adults 

 
6
with diabetes who participated in the Cardiovascular Health 
Study (Figure 3).34 In randomized clinical trials of renin-
angiotensin-aldosterone system (RAAS) antagonists, 
reduction of albuminuria on therapy correlated with 
improved renal and CVD outcomes.35, 36 Taken together, 
these observations suggest that reducing the burden of 
DKD in its early stages will help prevent ESRD, CVD, and 
death.  Because diabetes and kidney disease are 
particularly strong risk factors for mortality among older 
adults, for whom other CVD risk factors such as 
hyperlipidemia have reduced prognostic utility, prevention 
and treatment of DKD may have particularly beneficial 
effects in this age group.18, 34, 37, 38 
I.a.4. Novel interventions for DKD prevention and 
treatment are urgently needed.  Current interventions to 
prevent and treat DKD are limited.  The Diabetes Control 
and Complications Trial (DCCT) and the UKPDS clearly 
demonstrated that intensive glycemic control decreases the 
incidence of DKD, and perhaps its progression.39-41 Despite 
these exceptionally important findings, however, the 
incidence of DKD in these studies remained high even in 
the intensive glycemic control treatment arms.  For 
example, of DCCT participants assigned to intensive 
diabetes therapy, 5% had prevalent microalbuminuria (albumin excretion rate ≥ 28 μg/min) at baseline, 16% 
developed incident microalbuminuria during the DCCT, and an additional 7% developed incident 
microalbuminuria over the subsequent 8 years of follow-up.39, 40 In addition, effects of glycemic control on 
prevention of CVD remain unclear:  while intensive glycemic control in the DCCT resulted in a modest 
reduction in CVD events (myocardial infarction, stroke, CVD death, angina, coronary revascularization) over 
long-term follow-up, the ACCORD, ADVANCE and Veterans Affairs Diabetes Trial did not demonstrate 
benefits of tight glycemic control on CVD events.41-45 In addition to glycemic control, blood pressure control is 
clearly important for DKD prevention and treatment.  In particular, angiotensin coverting enzyme (ACE) 
inhibitors and angiotensin II receptor blockers are proven to prevent the development and progression of 
DKD.46-51 Again, however, DKD incidence and progression remain high despite treatment with these RAAS 
antagonists.  Therefore, glycemic control and RAAS inhibition on their own do not meet the clinical need for 
DKD prevention and treatment, and novel approaches to therapy are needed.  Given the high incidence of 
DKD among persons with diabetes, ideal new interventions would be sufficiently accessible, inexpensive, safe, 
and effective to apply to large numbers of persons with diabetes. 
I.b. 
Vitamin D is a promising therapeutic intervention for DKD prevention and treatment. 
I.b.1. Overview of vitamin D metabolism.  Vitamin D is a critical regulator of calcium, phosphorous, and bone 
homeostasis.52-55  Humans derive substrate forms of vitamin D (cholecalciferol and ergocalciferol) from 
cutaneous synthesis and dietary intake.  Cholecalciferol and ergocalciferol have little inherent biologic activity 
and require two hydroxylation steps for full hormonal activity.  25-hydroxylation occurs in the liver and is 
unregulated and non-rate-limiting.  Circulating 25-hydroxyvitamin D [25(OH)D] concentration increases in 
proportional to UV light exposure and dietary supplement intake, has a half-life of 10-21 days, and is widely 
accepted as a summary measure of vitamin D intake from cutaneous and dietary sources.56-62  Further 
hydroxylation to 1,25-dihydroxyvitamin D (calcitriol) occurs predominantly in the kidney and is dependent upon 
sufficient 25(OH)D availability, particularly among persons with kidney disease.28, 63-68 1,25-dihydroxyvitamin D 
is a pleiotropic steroid hormone that binds to the vitamin D receptor and regulates gene expression in a diverse 
array of target tissues.69  
I.b.2. Vitamin D and the kidney.  Traditional effects of 1,25-dihydroxyvitamin D include stimulation of dietary 
calcium and phosphorous absorption, suppression of parathyroid hormone, and maintenance of bone mineral 
density.  Recently, the potential impact of vitamin D on metabolic and cell regulatory pathways other than those 
related to traditional mineral homeostasis has attracted increased attention.55, 69-71 As one of these potential 

 
7
pleiotropic actions, 1,25-dihydroxyvitamin D appears to have direct renoprotective effects – this evidence is 
described below and forms the rationale for Specific Aim 1.  It is also possible that calcitriol deficiency due to 
impaired renal synthesis is a mechanism through which kidney disease leads to CVD and other adverse health 
outcomes – this latter hypothesis is not the focus of the current application. 
 I.b.3. Mechanisms through which vitamin D may 
prevent DKD.  Vitamin D may prevent kidney damage 
by suppressing the RAAS, reducing renal inflammation, 
and exerting direct pro-survival effects on podocytes 
(Figure 4).  First, vitamin D deficiency stimulates the 
transcription and release of renin in experimental 
animals, thus activating the RAAS, and renin is potently 
downregulated by administration of 1,25-
dihydroxyvitamin D.72, 73 RAAS stimulation leads to 
vasoconstriction, oxidative stress, and 
glomerulosclerosis through both hemodynamic and 
nonhemodynamic (e.g. fibrotic) mechanisms.74-77 In 
humans, circulating 1,25-dihydroxyvitamin D 
concentrations are inversely correlated with blood 
pressure,78-80 and lower circulating 25-hydroxyvitamin D 
concentrations have been associated with increased risk of incident hypertension.81 Second, in vitro cell culture 
studies and in vivo animal-experimental models demonstrate potent immunomodulatory functions of vitamin 
D.82 In antigen presenting cells (including monocytes), vitamin D therapy alters cytokine expression (decreased 
IL-1, IL-6, IL-8, IL-12, and TNF-α; increased IL-10) and regulates cell growth and cell-cell interaction 
(decreased differentiation, maturation, MHC-II expression, costimulatory molecule expression, and interferon-γ; 
increased apoptosis).83-86 Net effects of vitamin D on immune function include inhibition of cell-mediated 
immunity, which contributes to the tubulointersitial fibrosis responsible for progression of DKD.71, 87, 88 In 
support of this hypothesis, circulating 25(OH)D concentration is inversely correlated with renal inflammation in 
human kidney biopsies.89 Third, vitamin D is known to affect cell proliferation, differentiation, and survival 
through regulation of cell cycle progression and modulation of apoptosis.90-94 In animal models of kidney injury, 
1,25-dihydroxyvitamin D has direct pro-survival effects on kidney podocytes, preventing damage and 
apoptosis.95-100 Podocytes form a critical component of the glomerular barrier to albumin filtration, and 
dysfunction and loss of podocytes is a seminal feature of proteinuric kidney diseases including DKD.101  
 I.b.4. Vitamin D reduces albuminuria and glomerulosclerosis in animal-experimental models.  In animal-
experimental models, vitamin D deficiency promotes and 1,25-dihydroxyvitamin D therapy reduces 
albuminuria, glomerulosclerosis, and loss of GFR.96, 100, 102 These actions have been observed in animal 
models of DKD as well as the nondiabetic 5/6 nephrectomy model.  Effects are mediated, at least in part, 
through mechanisms described in Section B2c and Figure 4.  One particularly provocative study suggested 
that treatment with an angiotensin-II receptor blocker (losartan) and paricalcitol (an activated analogue of 1,25-
dihydroxyvitamin D) acted synergistically to completely abrogate the development of albuminuria in the 
streptozotocin model of DKD (Figure 5), in part 
because paricalcitol prevented the compensatory 
increase in renal renin production normally stimulated 
by RAAS blockade.102 These data raise the possibility 
that vitamin D interventions may prove to be particularly 
valuable when added to current standard DKD 
therapies. 
I.b.5. Epidemiologic studies of vitamin D and kidney 
disease.  Human studies examining the relationship of 
vitamin D with clinical manifestations of kidney disease 
suggest that effects observed in animal models may 
have clinical relevance.  Comparing Italian subjects with 
type 1 diabetes and persistent microalbuminuria to 
those with normal albumin excretion rate, lower levels 
of both 25(OH)D (27±5 vs 36±5 ng/mL, p<0.01) and 

 
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1,25-dihydroxy vitamin D (25±6 vs 39±9 pg/mL, p<0.01) were reported.103 Among 100 Japanese persons with 
type 2 diabetes, 1,25-dihydroxyvitamin D concentration was inversely correlated with urine ACR (r=-0.21, 
p<0.05).104 We have demonstrated an inverse association of serum 25(OH)D concentration with albuminuria 
prevalence in the United States population, as represented by NHANES III (preliminary data Section C2a).105 
Among 168 persons with moderate-severe CKD (mean estimated GFR 34 mL/min/1.73m2), 25(OH)D 
concentration was directly correlated with estimated GFR.28 
I.b.6. Clinical trials of vitamin D agents in kidney disease.  Two small studies reported that paricalcitol (an 
activated analogue of 1,25-dihydroxyvitamin D) significantly reduced albuminuria in stage 3-4 chronic kidney 
disease (estimated GFR 15-59 mL/min/1.73m2).  In the first study, among 118 participants with dipstick 
positive albuminuria at baseline, urine dipstick results improved among 51% of participants assigned to 
paricalcitol versus 25% of participants assigned to placebo after 24 weeks of therapy (p=0.004).106 In the 
second study, 24-hour urine albumin excretion rate increase by 35% over 1 month among participants 
assigned to placebo and decreased by 48% and 46% among participants assigned to paricalcitol 1 mcg and 2 
mcg daily, respectively (8 participants per group, p<0.001).107 An industry-sponsored clinical trial is currently 
recruited to follow up on these data by testing whether paricalcitol reduces albuminuria among participants with 
advanced DKD (diabetes with urine ACR 100-3000 mg/g and estimated GFR 15-90 mL/min/1.73m2) over 1 
year.108 While results of this trial may have important implications for the studies proposed in this application, 
they will not determine whether cholecalciferol prevents the development or progression of DKD among 
persons with early or inapparent DKD, for whom renal activation of 25(OH)D to 1,25-dihydroxyvitamin D is 
largely preserved (thus abrogating the need for an activated form of vitamin D) and for whom activated vitamin 
D analogues may be associated with unnecessary risk and cost.  Currently, there are no published clinical 
trials data examining effects of cholecalciferol or ergocalciferol treatment on the presence or severity of 
diabetic or other forms of kidney disease. 
I.b.7. Race/ethnicity, vitamin D, and DKD.  25-hydroxyvitamin D concentration varies strongly by 
race/ethnicity due to differences in skin pigmentation and cutaneous cholecalciferol synthesis, being highest in 
Caucasian populations, intermediate in Hispanic and Asian populations, and lowest in African American 
populations.68, 105, 109 The prevalence and incidence of chronic kidney disease in general and DKD specifically 
also vary strongly by race/ethnicity, with higher rates among minority populations.3, 110-113 Given these 
observations, and the biologic hypothesis that vitamin D helps prevent DKD, it is possible to speculate that 
vitamin D deficiency mediates, in part, the increased prevalence and incidence of DKD in non-Caucasian 
populations.  If so, vitamin D supplementation may reduce this racial and ethnic disparity. 
I.c. 
Omega-3 fatty acids are a promising therapeutic intervention for DKD prevention and treatment. 
I.c.1. 
Omega-3 fatty acids (ω-3 FA).  Eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) are 
omega-3 long chain polyunsaturated fatty acids which are found mainly in fatty fish.  Diets rich in ω-3 FA or 
supplemented with ω-3 FA have been associated with diverse health benefits, including prevention of type 2 
diabetes, CVD, dyslipidemia, and thrombosis.114-116 Recently, it was reported that EPA 1.8 grams daily reduced 
the incidence of major CVD events by 19% among persons with 
elevated LDL cholesterol, compared with placebo (JELIS 
trial).117 
I.c.2. 
Potential reno-protective actions of ω-3 FA.  Intervention 
studies in humans suggest that ω-3 FA have a number of 
actions that may directly help prevent the development and 
progression of kidney disease.  These include suppression of 
endothelial activation, reduction of renal inflammation and 
oxidative stress, and modest blood pressure lowering (Figure 
6).  First, at least 7 human intervention studies suggest that ω-3 
FA improve vasodilation and/or decrease markers of endothelial 
cell activation.114 For example, in a cross-over trial among 23 
participants with type 2 diabetes, six weeks of ω-3 FA 
administration improved forearm blood flow responses to 
acetylcholine, when compared to the vasodilator responses 
recorded at baseline or after olive oil administration.118 Another study reported that ω-3 FA significantly 
reduced soluble cell adhesion molecules, particularly among persons with type 2 diabetes.119 Endothelial 

 
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function regulates intraglomerular pressure, and the endothelium is a critical barrier to urinary albumin filtration.  
Second, at least 3 studies of persons with type 2 diabetes found that ω-3 FA reduced measures of oxidative 
stress, such as urine F2-isoprostane excretion.120-122 Oxidative stress is closely linked with tissue inflammation 
(Section B2c) and may contribute to the pathogenesis of albuminuria and DKD progression.25, 88 Third, ω-3 FA 
appear to have modest effects lowering systemic blood pressure, perhaps related to the mechanisms 
described above.114 
I.c.3. 
ω-3 FA reduce albuminuria and tubulo-interstitial fibrosis in animal-experimental models.  Effects of ω-3 
FA have recently been studied in several animal models of kidney disease.  In the diabetic KKay/Ta mouse, 
intraperitoneal EPA reduced mesangial expansion, albuminuria, and tubulo-interstitial fibrosis.123 It was 
postulated that these effects were mediated by suppression of monocyte chemoattractant protein-1 (MCP-1), a 
protein which regulates macrophage recruitment, is increased in experimental DKD, and was suppressed by 
EPA administration.  In the stretozotocin model of DKD, ω-3 FA prevented the development of albuminuria 
(urine albumin excretion approximately 10 mg/d, versus 95 mg/day in untreated and 17 mg/day in non-diabetic 
control animals), reduced glomerulsclerosis, and downregulated MCP-1, interleukin-6, transforming growth 
factor-β (TGF- β), and collagen type I and type IV.124 In the 5/6 nephrectomy model of nondiabetic kidney 
disease, ω-3 FA suppressed markers of renal inflammation, including MCP-1; downregulated tissue-level 
NAD(P)H oxidase; and reduced expression of fibrotic markers including TGF-β.125 Together, these studies 
suggest that ω-3 FA reduce kidney disease in animals by reducing renal oxidative stress and inflammation. 
I.c.4. 
Epidemiologic studies of ω-3 FA and kidney disease.  Observational data suggest that effects of ω-3 
FA on the diabetic kidney may have clinical relevance.  A cross-sectional study of 22,384 individuals in the 
European Prospective Investigation of Cancer-Norfolk population cohort demonstrated that greater dietary fish 
intake was associated with decreased risk of macroalbuminuria (urine ACR ≥ 220 mg/g) among participants 
with diabetes.126 In the InCHIANTI study, a population-based Tuscan cohort, higher baseline plasma total 
polyunsaturated fatty acids, ω-3 FA, and ω-6 FA were each strong independent predictors of slower loss of 
creatinine clearance over 3 years of follow-up (P <0.0001).127 
 I.c.5. Clinical trials of ω-3 FA for 
the treatment of kidney disease.  
ω-3 FA have been studied in small 
clinical trials to treat established 
DKD, IgA nephropathy, and other 
glomerular diseases.  Individually, 
these trials have not generated 
consistent findings.  However, a 
recent meta-analysis of 17 clinical 
trials (626 total participants) 
reported that ω-3 FA significantly 
reduced albuminuria.128 Effects on 
albuminuria in 7 clinical trials of 
persons with diabetes (222 
participants) were consistent with 
the overall estimate of ω-3 FA 
effect (Figure 7).129-135 12 of 17 
clinical trials additionally reported 
effects on GFR; in these, ω-3 FA resulted in a preservation of GFR, relative to control groups, which was not 
statistically significant.  Studies included in the meta-analysis were heterogenous with regard to population, 
precise nature and dose of intervention, follow-up, and outcome ascertainment, such that results require 
confirmation in adequately powered, high-quality clinical trials.  No definitive large clinical trials of ω-3 FA in 
diabetic or other forms of kidney disease have been published.   
I.d. 
Summary of background and current gaps in knowledge.  DKD is highly prevalent, particularly 
among older adults, and leads to substantial morbidity and mortality due to progressive kidney and 
cardiovascular disease.  While tight glycemic control and RAAS inhibitors help prevent the incidence and 
progression of DKD, rates of adverse renal and cardiovascular consequences remain unacceptably high.  
Cholecalciferol and ω-3 FA are promising interventions for the prevention and treatment of DKD, because 

 
10
animal-experimental data suggest they have substantial reno-protective effects, early human data suggest 
these effects have clinical relevance, and each intervention is relatively accessible, inexpensive, and safe.  
Thus, it is possible that cholecalciferol and/or ω-3 FA are appropriate for wide-spread use to prevent and treat 
DKD in the large and growing population of older persons with diabetes.  This hypothesis requires rigorous 
testing in well-controlled clinical trials. 

 
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II. SPECIFIC AIMS 
Diabetic kidney disease (DKD) is a common and morbid complication of diabetes mellitus.  Preventing the 
development and progression of DKD is a critical goal for improving long-term health outcomes of the growing 
diabetes population and for reducing the overall burden of kidney disease in the United States.  Therefore, 
there is an urgent need for additional, complementary interventions to prevent and treat DKD.  This need is 
greatest among older adults because diabetes and kidney disease are highly prevalent among older adults and 
kidney disease is among the strongest risk factors for mortality in this group.  Vitamin D and omega-3 fatty 
acids (ω-3 FA) are two of the most promising interventions for DKD prevention and treatment.  Because 
cholecalciferol and ω-3 FA are relatively safe, inexpensive, and widely available, they may offer opportunity to 
substantially reduce the burden of DKD in large populations.  Prior to widespread implementation, however, 
these hypothesized benefits should be rigorously tested in well-powered clinical trials.  Therefore, among older 
adults with diabetes, we aim: 
SPECIFIC AIM 1:  To test whether cholecalciferol (vitamin D3, 2000 IU per day) prevents the development 
and progression of DKD, compared with placebo. 
Hypothesis 1a:  Cholecalciferol slows progression of albuminuria over 4 years of therapy. 
Hypothesis 1b:  Cholecalciferol reduces loss of GFR over 4 years of therapy. 
Hypothesis 1c:  Beneficial effects of cholecalciferol are strongest among persons who at baseline have low 
plasma 25-hydroxyvitamin D concentration, albuminuria, and/or impaired GFR. 
SPECIFIC AIM 2:  To test whether marine omega-3 fatty acids (ω-3 FA, eicosapentaenoic acid plus 
docosahexaenoic acid, 840 mg per day) prevent the development and progression of DKD, compared with 
placebo. 
Hypothesis 2a:  ω-3 FA acids slow progression of albuminuria over 4 years of therapy. 
Hypothesis 2b:  ω-3 FA reduce loss of GFR over 4 years of therapy. 
Hypothesis 2c:  Beneficial effects of ω-3 FA are strongest among persons with low baseline levels of 
plasma eicosapentaenoic acid and docosahexaenoic acid and/or high baseline levels of C-reactive protein. 
To test these hypotheses effectively and efficiently, we propose an ancillary study to the Vitamin D and 
Omega-3 Trial (VITAL).  The parent VITAL trial will be a randomized, double-blind, placebo-controlled trial of 
the benefits and risks of cholecalciferol and ω-3 FA in the primary prevention of cardiovascular disease and 
cancer.  Funded by the NIH (R01 CA138962), 20,000 participants (men ages ≥ 60 years, women ages ≥ 65 
years) will be randomly assigned in a 2x2 factorial design to cholecalciferol 2000 IU daily versus placebo, and 
to eicosapentaenoic acid plus docosahexaenoic acid 840 mg daily versus placebo.  Planned mean follow-up is 
5 years.  Leveraging the established infrastructure of VITAL, we propose to ascertain effects of cholecalciferol 
and ω-3 FA on albuminuria and GFR among 1,500 participants with diabetes at baseline.  Following the simple 
and cost-efficient design of the parent VITAL trial, biospecimens will be collected locally and delivered to the 
VITAL central laboratory by mail.  First morning voids will be collected at baseline and year 4 for measurement 
of urine albumin-creatinine ratio.  Blood samples will be collected simultaneously for measurement of GFR 
(using plasma creatinine and cystatin C), 25-hydroxyvitamin D, eicosapentaenoic acid plus docosahexaenoic 
acid, C-reactive protein, and hemoglobin A1c.   
This VITAL Diabetes ancillary study is designed to determine whether cholecalciferol and ω-3 FA have 
causal and clinically relevant effects on the development of DKD.  Null results of the studies proposed herein 
would suggest that salutary effects of vitamin D and/or ω-3 FA observed in animal-experimental studies do not 
translate to meaningful clinical benefits in early DKD.  Positive results would support wide-spread use of 
cholecalciferol and/or ω-3 FA interventions among the growing and high-risk population of persons with 
diabetes.

 
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III. Study Population 
III.a. 
Parent VITAL study population.  The 
study described herein is an ancillary study 
to the NIH-funded VITAL study.  Therefore, 
all participants in our ancillary study must be 
existing participants in the parent VITAL 
study.  The parent VITAL study will be 
conducted among 20,000 apparently healthy 
participants.  The study population is 
restricted to older individuals (men ages ≥ 60 
years, women ages ≥ 65 years), because 
rates of chronic disease (including CVD, 
cancer, and kidney disease) increase 
substantially with age.  VITAL will exclude 
persons with clinically apparent CVD or 
cancer (except non-melanoma skin cancer), 
because it is a trial for the primary prevention 
of these conditions.  Other eligibility criteria, 
which focus largely on safety, are listed in 
Table 1.  VITAL will oversample for 
participants of black and Hispanic 
race/ethnicity. 
The VITAL study population will be 
recruited entirely by mail.  A master mailing 
tape containing 1.2 million names and 
addresses will be assembled by Listmart, a 
list broker with access to all commercially 
available U.S. mailing lists.  This master 
mailing tape will be compiled from the same 
age-selected source tapes as the VITAL pilot study (i.e., licensed health professionals, other professionals, 
AARP members, and Essence subscribers), as well as subscription lists of magazines that appeal to 
professionals and college-educated individuals (e.g., National Geographic and Time) and a subset of Listmart’s 
executive database that includes black business professionals.  Each of the 1.2 million persons on the master 
mailing tape will be mailed a letter explaining the rationale for VITAL, an informed consent form, a brief 
questionnaire, and a self-addressed, pre-paid envelope for returning study forms.  The letter will outline what 
participation would entail and provide sources for further information on relevant scientific issues.  Persons 
identified as black with a high degree of certainty (e.g., Essence subscribers) will receive a special invitation 
letter emphasizing that blacks are at higher risk for vitamin D deficiency, as well as heart disease, stroke, and 
certain cancers.  The initial questionnaire will focus only on VITAL eligibility criteria, containing items related to 
demographics, specific medical history (including diabetes), relevant allergies, and dietary intakes of vitamin D 
and fish, as well as contact information.  Based on the completed pilot mailing, it is anticipated that roughly 
40,000 individuals (25% minority race/ethnicity) will be willing and eligible for the placebo run-in.   
III.b. 
VITAL Diabetes ancillary study population.  Eligibility criteria specific to this proposed ancillary study 
are listed along with parent VITAL trial eligibility criteria in Table 1.  We aim to recruit a diabetes sub-cohort 
with prevalent diagnosed type 2 diabetes.  Persons with known diabetes are at high risk of DKD and comprise 
a targetable population for clinical intervention.  For the purpose of this VITAL Diabetes ancillary study, we will 
define diabetes as a self-reported physician diagnosis of diabetes.  Specificities of self-reported diabetes 
diagnosis were 97.5% and 98.9% in the WHS and NHS, respectively, using self-report alone.136 We will 
exclude (a) persons who report a diagnosis of diabetes only during pregnancy (presumed gestational 
diabetes), and (b) persons who report diabetes diagnosis prior to age 30 and first treated with insulin (likely 
type 1 diabetes).  Persons who are likely to have type 1 diabetes will be excluded because DKD in this 
population generally develops prior to older age among susceptible individuals, thus leading to disease 
heterogeneity compared with the much larger proportion of participants with type 2 diabetes.  To focus on 
DKD, we will also exclude (a) participants who report a physician diagnosis of kidney disease caused by a 
Table 1.  Eligibility criteria 
Inclusion criteria 
* Age ≥ 60 years (men) or ≥ 65 years (women) 
* High school education or higher (for questionnaires) 
* Willing to limit nonstudy vitamin D intake to ≤ 800 IU/d 
* Willing to limit calcium intake to ≤ 1200 mg/d 
* Willing to forego fish oil supplements 
* Adherence to placebo run-in study medication > 67% 
Self-reported history of diabetes 
Blood and urine specimens returned during placebo run-in 
Exclusion criteria 
* Known CVD:  MI, stroke, TIA, angina pectoris, CABG, PCI 
* History of cancer, except non-melanoma skin cancer 
* History of kidney stones 
* Kidney failure or dialysis 
* Hypercalcemia 
* Hypo- or hyperparathyroidism 
* Cirrhosis of the liver 
* Granulomatous diseases (sarcoidosis, tuberculosis) 
* Fish allergy (for EPA + DHA) 
* Other serious illnesses which preclude participation 
Diagnosis of diabetes only during pregnancy 
Diabetes diagnosis prior to age 30 and first treated with insulin 
Known cause of kidney disease other than diabetes 
Kidney transplant 
* Parent VITAL study eligibility criteria 

 
13
condition other than diabetes, and (b) participants who have had a kidney transplant. 
III.c. 
Recruitment of the VITAL Diabetes ancillary study.  To conduct the VITAL Diabetes ancillary study 
outlined in this application, we will identify, recruit, and study a sub-cohort of 1,500 VITAL participants with pre-
existing diabetes at baseline.  The VITAL Diabetes ancillary study sub-cohort will be recruited during the 3- to 
6-month placebo run-in phase of the parent VITAL trial.  VITAL will utilize a 3-6 month placebo run-in phase to 
maximize the proportion of randomized participants who adhere to study medications.  Maximizing adherence 
increases the power of the study, because study outcomes will be analyzed according to treatment assignment 
(intention to treat).137 During the run-in phase, all participants will be asked to take placebo cholecalciferol and 
placebo ω-3 FA.  Participants will receive a follow-up questionnaire reevaluating eligibility criteria and 
assessing willingness to continue in the trial, pill adherence, and potential adverse effects.  Parent VITAL 
investigators estimate that, of the 40,000 initially willing and eligible individuals enrolled in the run-in, 50% 
(n=20,000) will be adherent and remain willing and eligible for randomization.  The placebo run-in phase 
provides a critical window of opportunity for ancillary study recruitment.  
Persons willing to participate in the parent VITAL trial will return a screening medical history form 
concurrent with their parent VITAL trial consent form.  Those who respond “YES” to the question “Have you 
EVER been diagnosed as having diabetes?” and who indicate "YES" or "MAYBE" to the question "Are you 
willing to give a blood sample" (in addition to meeting initial parent VITAL trial eligibility criteria) will be targeted 
for VITAL Diabetes ancillary study recruitment.  With their placebo run-in materials, we will send these persons 
a DKD ancillary study packet, which includes:   
 
Letter explaining the rationale for the VITAL DKD ancillary study,  
 
DKD ancillary study informed consent form,  
 
DKD ancillary study questionnaire, 
 
Urine collection kit, and  
 
Self-addressed, pre-paid FedEx box for returning study materials.   
The VITAL Diabetes ancillary study letter will outline what participation in the VITAL Diabetes ancillary study 
would entail and will provide sources for further information on relevant scientific issues.  It will explain that 
participation in the ancillary study is optional and that it will not affect participation in the parent VITAL trial.  
The VITAL Diabetes ancillary study questionnaire will include items which clarify the self-reported diagnosis of 
diabetes and further define diabetes and kidney disease history.  All persons will have the option to decline 
VITAL Diabetes ancillary study participation by checking a single box on their initial contact letter and returning 
this by mail to the VITAL coordinating center, or by calling the toll-free VITAL telephone number.  Persons who 
do not respond to the first mailing of VITAL Diabetes ancillary study materials will be sent a reminder mailing 
and/or contacted by telephone.   
Recent NHANES estimates suggest that 15-18% of the US population in the VITAL study age range have 
been diagnosed with diabetes, not including 13% with undiagnosed diabetes.5 Based on VITAL recruiting 
strategies and selective response to mailings, it is possible that the VITAL population will be somewhat 
healthier than the general US population.  This may have competing effects on the number of VITAL 
participants with diagnosed diabetes, with a lower prevalence of diabetes overall but a higher proportion of 
diabetes being diagnosed.  Accordingly, of the 20,000 participants who will be enrolled in VITAL, we 
conservatively estimate that 3,000 participants will have prevalent diagnosed diabetes.  VITAL Diabetes 
ancillary study participant burden is modest compared with parent VITAL trial activities (including study 
interventions), and VITAL participants with diabetes may be further motivated to contribute to scientific 
advancement in a disease with which they have personal experience.  Thus, we anticipate that the majority of 
VITAL participants with diabetes will consent to VITAL Diabetes ancillary study participation, allowing quick 
and successful recruitment of the VITAL Diabetes ancillary study population (n=1,500). 

 
14
IV. 
Subject enrollment 
IV.a. 
Methods of Enrollment.  All potential participants who return a valid VITAL Diabetes ancillary study 
consent form will be evaluated for enrollment in the VITAL Diabetes ancillary study.  First, in collaboration with 
study staff for the parent VITAL study, we will assess whether each potential participant qualifies for the parent 
trial.  Second, we will screen responses to the initial diabetes questionnaire using computer algorithms, 
excluding potential participants who report a diagnosis of diabetes only during pregnancy, diabetes diagnosis 
prior to age 30 and first treated with insulin, a known cause of kidney disease other than diabetes of 
hypertension, or kidney transplantation.  Follow-up telephone calls will be used to clarify incomplete or 
inconsistent responses.  Finally, we will include only participants who during the placebo run-in period return 
samples of both blood (for the parent VITAL trial) and urine (for this VITAL Diabetes ancillary study).  Follow-up 
telephone calls will be used to remind potential participants to complete blood and urine collections, if needed.  
The first 1,500 VITAL participants who meet these VITAL Diabetes ancillary study eligibility criteria (Table 1) 
will be fully enrolled in the VITAL Diabetes ancillary study.  Persons who meet eligibility criteria only for the 
parent VITAL trial will continue in the parent trial only. 
IV.b. 
Informed Consent.  A VITAL Diabetes consent form will be mailed to each potential participant as part 
of their initial VITAL Diabetes ancillary study packet.  All persons will have the option to decline VITAL 
Diabetes ancillary study participation by checking a single box on their initial contact letter and returning this by 
mail to the VITAL coordinating center, or by calling the toll-free VITAL telephone number.  The initial contact 
letter and consent form will encourage participants to ask questions or address concerns by calling the toll-free 
VITAL telephone number to speak with study staff in person.  Willing potential participants will return their 
consent forms to the VITAL coordinating center by mail.  Study staff will contact potential participants by 
telephone to clarify ambiguous or invalid consent forms. 
IV.c. 
Treatment Assignment.  Upon enrollment in the VITAL Diabetes ancillary study and/or parent VITAL 
trial, participants will be randomly assigned to vitamin D and omega-3 fatty acid treatment groups by the parent 
VITAL trial.  Assignment to treatment groups will be accomplished using a computer-generated table of 
random numbers, stratified by 5-year age group.  Within each age group, treatment assignments will be 
generated in blocks of eight individuals, with two individuals in each of the four treatment combinations:  
cholecalciferol + ω-3 FA, cholecalciferol + placebo, placebo + ω-3 FA, or placebo + placebo. 

 
15
V. 
Study Procedures 
V.a. 
Approach to Data Collection.  We will to collect all study data via mail, including questionnaires and 
urine and blood samples.  The BWH Division of Preventive Medicine research group has extensive experience 
collecting and analyzing questionnaires and collecting, processing, and storing biospecimens using the mail-
based collection procedures to be used in this study.  We will utilize these established, standardized protocols, 
described below, for all data collection. 
V.b. 
Questionnaire Data.  All participants will be asked to complete diabetes questionnaires at baseline and 
after 4 years of study participation.  Questionnaires will address diabetes diagnosis, diabetes history, history of 
kidney disease, and medication use related to diabetes and kidney disease. 
V.c. 
Urine Collection.  Each participant will be sent a standardized urine collection kit at baseline (pre-
randomization) and again after 4 years of study participation.  The kit will include instructions for proper 
collection of a clean-catch first morning void; a urine cup; a plastic single-use pipette; two 5-mL screw-top 
cryovials; a gel-filled freezer pack; and an overnight courier air bill.  Participants will be instructed to fill each 5 
mL cryovial with urine using the pipette, to securely close each cryovial, and to immediately mail both vials to 
the VITAL laboratory at the BWH Division of Preventive Medicine in the freezer packs provided.  Upon receipt, 
any precipitate in the urine will be removed by centrifugation, and the urine will be aliquoted without 
preservative into six 2-ml Nunc vials.  Urine samples will be thawed for measurements of albumin and 
creatinine. 
V.d. 
Blood Collection.  Each participant will be sent a standardized blood collection kit after 4 years of study 
participation.  This kit will be identical to the blood collection kit used by the parent VITAL trial for collection of 
baseline (pre-randomization) blood samples.  (Baseline blood samples will be collected only by the parent 
VITAL trial under the parent VITAL trial IRB approval and with separate informed consent.  These samples will 
be made available for use in the VITAL Diabetes ancillary study.)  The kit will include supplies and instructions 
for having blood drawn into two EDTA tubes, one heparin tube, and one citrate tube; a gel-filled freezer pack; 
and an overnight courier air bill.  We anticipate that most participants will have their blood drawn by their own 
healthcare providers or in another healthcare or blood-drawing facility.  Participants will be instructed to record 
the time of venipuncture and the time of their last meal.  They will be instructed to immediately send their 
sample to the VITAL laboratory at the BWH Division of Preventive Medicine in the freezer packs.  Upon 
receipt, samples will be processed using the same protocols as the parent VITAL trial, in order to avoid 
laboratory errors.  Blood samples will be centrifuged to separate plasma and red blood cells, each aliquoted 
into 2-ml Nunc vials.  EDTA-plasma samples will be thawed for measurements of creatinine, cystatin C, C-
reactive protein, 25-hydroxyvitamin D, and eicosapentaenoic acid and docosahexaenoic acid.  Red blood cells 
will be thawed for measurement of hemoglobin A1c. 
V.e. 
Interventions.  All interventions will be provided by the parent VITAL trial and are included in the IRB 
application for the parent VITAL trial.  For completeness, these are described below. 
V.e.1. Cholecalciferol intervention.  Active cholecalciferol (vitamin D3) and matching inert placebo will be 
provided by Pharmavite LLC.  Cholecalciferol is recommended by many experts as the optimal form of vitamin 
D supplementation based on its known dose-response effects on 25(OH)D concentration, documented long-
term safety, and proven benefits in fracture reduction when used with calcium in the setting of osteoporosis.61, 
62, 138 Each active cholecalciferol study pill will contain 2000 IU (40 µg) cholecalciferol.  This dose was chosen 
to maximize the separation in 25-hydroxyvitamin D concentration attained between treatment groups while 
maintaining safety.  Specifically, cholecalciferol 2000 IU daily is conservatively anticipated to raise mean 25-
hydroxyvitamin D concentration by approximately 16 ng/mL, while maintaining total daily cholecalciferol intake 
at or below the no-observed-adverse-effect level (NOAEL) specified by the Institute of Medicine, and well 
below the 4000 IU NOAEL specified by the European Commission Scientific Committee on Food, with 
allowance for nonstudy use up to 800 IU/d.62, 138-140 Study medications will be dispensed in calendar packs, with 
participants asked to take one pill (cholecalciferol or placebo) each day.  Participants will be instructed to 
discontinue their study pills if, during follow-up, they receive a diagnosis of kidney stones or hypercalcemia. 
V.e.2. Omega-3 fatty acid intervention.  Active fish oil (1000 mg capsule containing 840 mg EPA + DHA) and 
matching inert placebo will be provided by Pronova BioPharma ASA of Norway. Each active soft-gel capsule 
will contain a total EPA+DHA dose of 840 mg/d, the highest dose of EPA + DHA currently available in a 1000 
mg capsule.  We believe that this dose provides the best balance of feasibility, efficacy and safety. We seek to 

 
16
obtain a large-enough difference in omega-3 fatty acid status between the treatment and placebo groups to 
detect health benefits, and there appear to be few safety issues associated with this dose. Health authorities 
recommend 400 mg to 1 g/d for cardioprotection.141 A total dose of 840 mg/d was used in the GISSI-
Prevenzione Trial (EPA to DHA ratio, 1:2) and AREDS 2 (EPA to DHA ratio, 2:1), while a dose of 1.8 g/d of 
EPA was used in JELIS. For this trial, we have selected a total dose of omega-3 fatty acids recommended by 
the American Heart Association for cardioprotection and demonstrated to be beneficial in one secondary 
prevention population with minimal side effects.142 Because the optimal ratio of EPA to DHA is unknown, we 
have selected a 40:30 ratio of EPA to DHA. The ratio of omega-3 to omega-6 fatty acid intake is between 1:10 
and 1:20 in most Western countries, including the U.S., whereas the optimal ratio for disease prevention has 
been hypothesized to be closer to 1:1 or 1:2, although this is controversial.  Indeed, there is growing 
consensus that the absolute intake of omega-3 is a more important predictor of health than is the ratio of 
omega-3 to omega-6 intake, at least for cardiovascular outcomes.  However, given that the average intake of 
EPA+DHA is 100-200 mg/d among U.S. adults, the proposed intervention of 840 mg/d would be expected to 
increase the average participant’s omega-3 intake by a factor of 4 to 8. Assuming no concurrent change in 
omega-6 intake, the proposed omega-3 dose would thus have the effect of achieving the purported optimal 
omega-3 to omega-6 ratio and providing intakes associated with benefits in previous studies. 
As with vitamin D, potential side effects of omega-3 fatty acids are rare.  They include gastrointestinal (GI) 
symptoms (stomach upset or pain, nausea, constipation, diarrhea), bleeding (any GI bleed, GI bleeding 
requiring transfusion, hematuria, easy bruising, epistaxis), skin rash, colds or upper respiratory tract infection, 
flu-like symptoms, bad taste in mouth, and physician diagnosis of atrial fibrillation or other irregular rhythms.  
The FDA has concluded that marine omega-3 fatty acid doses of up to 3 g/d are “Generally Recognized as 
Safe.”  The AHA also has concluded that these risks are very low or low at doses of up to 1 g/d and low to 
moderate at doses of 1-3 g/d.  Because they undergo an extensive purification process, high-quality fish oil 
supplements are free of environmental toxins (e.g., methylmercury, polychlorinated biphenyls [PCBs], and 
dioxins) found in some fish.  The ω-3 FA supplement contains no vitamin D. 
 
 
 

 
17
VI. 
Analysis plan 
VI.a. 
Descriptive analyses.  We will describe creation of the VITAL diabetes sub-cohort according to 
CONSORT guidelines, including numbers of participants who consent to VITAL participation; self-identify a 
diagnosis of diabetes; consent to participation in the DKD ancillary study; complete baseline urine and blood 
collections; and complete year 4 urine and/or blood collections.  We will document reasons that participants do 
not complete the proposed studies, e.g. death, withdrawal of consent, or loss to follow-up.  Among participants 
recruited into the DKD ancillary study, we will compare baseline characteristics of those who do and do not 
complete year 4 biospecimen collections in order to assess the potential impact of loss to follow-up.  Among 
participants who complete year 4 biospecimens, we will describe by treatment assignment baseline 
characteristics and changes in clinical characteristics over the course of the study. 
VI.b. 
Primary study outcome.  The primary outcome of this study is change in urine albumin-creatinine ratio 
(ACR) from baseline to year 4, analyzed as a continuous variable.  We will examine percent change in urine 
ACR, because relative increases in urine ACR have been roughly linearly associated with adverse health 
parameters and outcomes in the published literature, and because the distribution of urine ACR and its change 
over time are normalized by log transformation.21, 38, 143, 144 Percent change in urine ACR will be calculated and 
summarized by treatment group as [(ACR4 – ACR0) / ACR0], where ACR4 represents urine ACR at follow-up 
(year 4) and ACR0 represents urine ACR at baseline. 
VI.c. 
Secondary study outcomes.  As a secondary dichotomous outcome, we will examine change in 
estimated glomerular filtration rate (eGFR) from baseline to year 4, analyzed as a continuous variable.  We will 
measure plasma concentrations of both creatinine and cystatin C to estimate GFR using the most precise 
serologic methods available.  Specifically, data from multiple community-based studies have been combined to 
create and validate an equation which calculates estimated GFR from serum creatinine and cystatin C, along 
with demographic variables.145 
Equation 1:  Estimated GFR = 177.6 x SCr-0.65 x CysC-0.57 x age-0.20 x (0.82 if female) x (1.11 if black) 
where SCr is serum creatinine (mg/dL) and CysC is cystatin C (mg/L).  GFR estimated using this equation 
captures 89% of variation in GFR measured using radionucleotide methods.  In addition, use of serum 
creatinine and serum cystatin C in combination to estimate GFR offers important theoretical advantages.  
Serum cystatin C concentration appears to be more sensitive to mild decrements in kidney function than serum 
creatinine, such that inclusion of cystatin C may aid detection of changes in GFR within the “normal” range.146-
148   However, some reports suggest that serum cystatin C concentration may be affected by systemic 
inflammation.149, 150 This influence may be moderated by combination with creatinine.  We will examine change 
in eGFR without transformation, because absolute differences in eGFR have been roughly linearly associated 
with adverse health parameters and outcomes in the published literature, and because the distribution of eGFR 
and its change over time is roughly normal.18, 34, 37 Change in eGFR will be calculated and summarized by 
treatment group as [eGFR4 – eGFR0]. 
As an additional secondary outcomes, we will examine the proportion of participants who develop a 
composite outcome of albuminuria progression (100% increase in urine ACR and a year 4 urine ACR ≥ 30 
mg/g), rapid loss of eGFR (loss of eGFR ≥ 12 mL/min over the 4-year interval), ESRD (maintenance dialysis or 
kidney transplant verified by medical records review), and/or death.  This composite outcome serves two 
purposes.  First, it addresses large changes in DKD which have particularly high clinical impact.  Second, the 
composite outcome reduces the potential impact of competing risks that preclude assessment of urine ACR 
and/or eGFR at follow-up.  Accounting for competing risks will be particularly important if the incidence of 
ESRD and/or death differs by treatment assignment.  The composite endpoint is scientifically important, 
because each component is a clinically relevant diabetes outcome and progression of DKD is strongly 
associated with ESRD and death.  A 100% increase in urine ACR is generally considered to have clinical 
relevance, and additional inclusion of a threshold (30 mg/g) will reduce the potential impact of measurement 
error among persons with “normal” levels of albuminuria near the limits of assay reliability.  Loss of eGFR 
exceeding 12 mL/min over the 4-year interval (3mL/min/year) has been associated with increased risk of 
mortality among older adults with and without diabetes.34, 37 
VI.d. 
Interaction of cholecalciferol and ω-3 FA.  We will assess for interaction of the study interventions 
(vitamin D and ω-3 FA) for each of the primary and secondary study outcomes.  First, we will assess for 
interaction on the additive scale.  Differences in each study outcome comparing the treatment group which 

 
18
receives both active study medications (vitamin D + ω-3 FA) to the treatment group which receives neither 
(placebo + placebo) will be compared to the sum of differences comparing treatment groups receiving only one 
medication (vitamin D + placebo, or placebo + ω-3 FA) to the treatment group which receives neither (placebo 
+ placebo).  Interaction on the additive scale exists if the former difference differs significantly from the sum of 
the latter two differences.151 Second, we will assess for interaction on the multiplicative scale by testing the 
joint effect of assigned treatment on each study outcome using ANCOVA.  For urine ACR: 
Equation 2:  log(ACR4) = β0 + β1log(ACR0) + β2(vitamin D) + β3(ω-3 FA) + β4(vitamin D + ω-3 FA) + e 
where log(ACR4) represents the natural log of urine ACR at follow-up (year 4), log(ACR0) represents the 
natural log of urine ACR at baseline, (vitamin D) is active vitamin D treatment assignment (yes/no), (ω-3 FA) is 
active ω-3 FA treatment assignment (yes/no), and (vitamin D + ω-3 FA) is an interaction indicator variable for 
assignment to both active vitamin D and active ω-3 FA.  A p value < 0.05 for β4 will be interpreted as evidence 
of interaction on the multiplicative scale. 
If we observe evidence of interaction on either the additive or relative scale for either study outcome, all 
analyses of that outcome will separately compare each of the 3 treatment groups which include at least one 
active study medication (i.e. cholecacliferol + placebo, placebo + ω-3 FA, and cholecalciferol + ω-3 FA) to the 
treatment group which receives (placebo + placebo).  In contrast, if there is no evidence of interaction, as 
hypothesized, all participants assigned to any active vitamin D (i.e. vitamin D + placebo or vitamin D + ω-3 FA) 
will be compared to all participants assigned to no vitamin D (i.e. placebo + placebo or placebo + ω-3 FA).  In 
parallel, participants assigned to any active ω-3 FA (i.e. placebo + ω-3 FA or vitamin D + ω-3 FA) will be 
compared to all participants assigned to no ω-3 FA (i.e. placebo + placebo or vitamin D + placebo). 
VI.e. 
Hypothesis testing.  Change in urine ACR and eGFR are continuous variables which will be tested 
using ANCOVA.  To test the effect of vitamin D on percent change in urine ACR in the absence of interaction 
with ω-3 FA, we will test the following equation: 
Equation 3:  log(ACR4) = β0 + β1log(ACR0) + β2(vitamin D) + e 
where [exp(β2) – 1] represents the relative difference in percent change in albuminuria comparing active 
vitamin D3 to placebo, and the corresponding 95% confidence interval and p-value reflect statistical 
significance of the treatment effect.  To test the effect of vitamin D on change in eGFR in the absence of 
interaction with ω-3 FA, we will test the following equation: 
Equation 4:  eGFR4 = β0 + β1eGFR0 + β2(vitamin D) + e 
where β2 represents the difference in eGFR comparing active vitamin D3 to placebo, and the corresponding 
95% confidence interval and p-value reflect statistical significance of the treatment effect.  Parallel equations 
will be used to test effects of ω-3 FA on changes in albuminuria and eGFR in the absence of interaction with 
vitamin D3.  An alpha level of 0.05 will be taken to represent statistical significance, without correction for 
multiple comparisons.  We will examine the distributions of change in urine ACR and eGFR and substitute 
rank-sum comparisons if indicated.152 We will test differences in proportions of participants attaining the 
composite dichotomous outcome using the chi2 test.   
Analyses will be performed in accordance with the intent-to-treat principle.  For analyses of change in urine 
ACR and eGFR as continuous variables, only participants who complete study measurements at baseline and 
year 4 will be included in analyses (complete case analysis).  Maximum effort will be made to ensure that all 
possible participants supply follow-up biospecimens, and all available participants will be included in 
continuous outcome analyses regardless of adherence to study medications.  The relatively large sample size 
makes it likely that few or no substantial differences in baseline characteristics will be present.  In the event 
that any baseline characteristics are not balanced between treatment groups, however, secondary analyses 
will add to the ANCOVA model additional terms for such baseline characteristics.  If we observe differences by 
treatment group in medication use (e.g. glucose-lowering or antihypertensive medications) or laboratory 
covariates (e.g. hemoglobin A1c, CRP) over follow-up, we will explore whether such differences may mediate 
or obscure effects of study interventions on study outcomes by including additional covariate(s) in the 
ANCOVA model to assess change in β2 (treatment effect) toward or away from zero, respectively. 
VI.f. 
Subgroup analyses.  For the vitamin D intervention, prespecified subgroup analyses will be based on 
baseline plasma 25(OH)D concentration, baseline urine ACR, baseline eGFR, and race/ethnicity.  We 
hypothesize that beneficial effects of cholecalciferol on urine ACR and eGFR will be greater among 

 
19
participants who at baseline (a) have low levels of plasma 25(OH)D, because vitamin D insufficiency may be 
particularly detrimental below a threshold vitamin D level; (b) have urine ACR ≥ 30 mg/g and/or eGFR < 60 
mL/min/m2, because persons with DKD may be particularly dependent on adequate 25(OH)D availability for 
renal synthesis of 1,25dihydroxyvitamin D; and/or (c) are non-Caucasian, i.e. differences in albuminuria and 
eGFR by race/ethnicity will narrow with vitamin D treatment.  For the ω-3 FA intervention, prespecified 
subgroup analyses will be based on baseline levels of EPA+DHA and CRP.  We hypothesize that beneficial 
effects of ω-3 FA on urine ACR and eGFR will be greater among participants who at baseline have (a) low 
levels of EPA+DHA, because ω-3 FA insufficiency may be particularly detrimental below a threshold 
EPA+DHA level; and/or (b) high levels of CRP, because inflammation at baseline will provide opportunity for 
anti-inflammatory actions of ω-3 FA.  Effect modification will be tested by including interaction terms of 
treatment assignment with subgroup in ANCOVA models (Equations 3 & 4).   
VI.g. 
Exploratory adherence and efficacy analyses.  All primary analyses will be performed according to the 
intent-to-treat principle.  We plan secondary, exploratory analyses for the following limited purposes:  (a) to 
evaluate whether null findings, if observed, are robust (i.e. not readily attributable to defects in the study 
interventions or their administration); and/or (b) to more comprehensively evaluate the potential range of 
treatment effects, if treatment effects are observed.  We understand and acknowledge that these analyses, 
which are based on data collected after randomization, may introduce bias into study results.  We will therefore 
use great caution to limit their interpretation.  To conduct these efficacy-based explorations, we will first repeat 
analyses among the subset of participants who report adherence to ≥ 80% of study medications.  In addition, 
we will assess whether changes in 25(OH)D and EPA+DHA levels are associated with changes in urine ACR 
and eGFR.  For the latter analyses, change in 25(OH)D concentrations or change in EPA+DHA concentration 
(continuous variables) will replace treatment assignment in ANCOVA models. 
VI.h. 
Power.  The following assumptions are made for power calculations:  (1) independent and equal 
allocation of participants to each treatment; (2) variation in urine ACR as observed in the Multi-Ethnic Study of 
Atherosclerosis (MESA), including follow-up log(ACR) mean 3.085, standard deviation 1.59, and correlation 
with baseline 0.78; (3) variation in eGFR as observed in the Cardiovascular Health Study (CHS), including 
follow-up eGFR mean 70 mL/min/1.73m2, standard deviation 25 mL/min/1.73m2; and correlation with baseline 
0.834; and (4) 20% loss to follow-up.  These assumptions are conservative, in that we anticipate follow-up 
greater than 80% using planned participant recruiting and retention techniques, and that we will collect first-
morning voids which yield lower intra-individual variation in urine ACR than the random voids collected in 
MESA.153 Statistical confidence is tested using ANCOVA (Equations 3 & 4), with a significance level of 0.05.   
Applying these assumptions, 1,500 enrolled participants (1,200 returning for follow-up) will provide 90% 
power to detect observed differences by treatment group of 17% in follow-up urine ACR and 2.6 
mL/min/1.73m2 in follow-up eGFR.  These differences are modest compared with observed changes in urine 
ACR and eGFR over time in comparable MESA and CHS participants, similar to the difference in  
eGFR expected with the 
cholecalcierol intervention based 
on observational 25(OH)D data, 
and substantially more modest 
than the point estimate for change 
in urine ACR observed in our 
short-term cholecalciferol 
intervention study.  Powers to 
detect other observed differences 
in the co-primary continuous 
outcomes are shown in Table 2.  It 
is likely that an observed treatment 
effect, if present, will be due to a 
larger effect among adherent 
participants “diluted” by little or no effect among nonadherent participants.  If adherence to study medications is 
80% in each treatment group, observed differences in urine ACR and eGFR of 17% and 2.6 mL/min/1.73m2 
correspond to differences of 21% and 3.2 mL/min/1.73m2, respectively, among adherent participants.154 A 
decrease in loss to follow-up to 10% (1,350 participants returning for follow-up) will increase power to 93% for 
Table 2.  Study power for co-primary study outcomes, by effect size 
Urine ACR 
Estimated GFR 
% Difference 
Power 
Difference (mL/min/1.73m2) 
Power 
15% 
81% 
2.0 
71% 
17% 
90% 
2.2 
79% 
19% 
96% 
2.4 
85% 
21% 
98% 
2.6 
90% 
23% 
>99% 
2.8 
94% 
25% 
>99% 
3.0 
97% 
Differences are assessed after four years total follow-up (not per year) 

 
20
the detection of differences by treatment group of 17% in follow-up urine ACR and 2.6 mL/min/1.73m2 in 
follow-up eGFR, while an increase in loss to follow-up to 30% (1,050 participants returning for follow-up) will 
decrease power to 86% for the detection of these differences.  If interaction of the study interventions is 
present, requiring separate testing of each treatment combination against the group assigned to 
(placebo+placebo), we will have 80% power to detect differences in follow-up urine ACR and eGFR of 20% 
and 3.2 mL/min/1.73m2, respectively, comparing any one treatment combination (e.g. active cholecalciferol + 
active ω-3 FA) to (placebo + placebo). 
Power for the secondary composite outcome is shown in Figure 11, given an enrolled sample size of 1,500 
participants and other assumptions listed above (including 20% loss to follow-up).  Power depends on the 
observed 4-year incidence of the composite outcome.  Based on observational data from MESA and CHS, we 
expect the incidences of albuminuria progression and rapid loss of eGFR to be approximately 17% each 
(Section C1), the 4-year cumulative incidence of ESRD to be <1%, and the 4-year cumulative incidence of 
death to be ~4.6% (cumulative incidence during the first 4 years of observation for CHS participants with self-
reported diabetes), for groups assigned to placebo.  The joint cumulative incidence of these outcomes will 
likely be at least 20-30%, yielding 80% power to detect observed relative risks of 0.69-0.76 (or lower) and 90% 
power to detect observed relative risks of 0.65-0.73 
(or lower).  A higher cumulative incidence of the 
composite outcome would allow detection of relative 
risks closer to 1. 
It is important to acknowledge that both 
albuminuria and eGFR have substantial biologic 
variation over time, such that single measurements of 
albuminuria and eGFR at baseline and year 4 can 
lead to substantial misclassification of change in 
these outcomes (“noise”).  This misclassification is 
unlikely to be biased by treatment assignment, so 
that it will bias results toward the null and decrease 
power to detect effects of study interventions.  Our 
power calculations are based on real-world 
distributions of albuminuria, eGFR, and their change 
over time.  Thus, our power calculations account for 
known variability in study outcomes, with the 
relatively large proposed sample size of 1,500 
participants essentially overcoming misclassification 
to permit detection of relatively modest changes in 
study outcomes with high levels of power. 
 

 
21
VII. 
Risks and Discomforts 
VII.a. Potential adverse effects of study interventions.  The main risks of this study arise from the 
interventions of the parent VITAL trial, not the VITAL Diabetes ancillary study described herein.  The parent 
VITAL trial will test a dose of 2000 IU (40 µg) per day of vitamin D3 (cholecalciferol) and 840 mg/d of EPA+DHA 
in VITAL. We believe that these doses provide the best balance of efficacy and safety, based on careful review 
of the literature and extensive consultation with numerous nutritional experts. We seek to obtain an adequate 
difference in vitamin D and EPA+DHA levels between the treatment and placebo groups to detect health 
benefits, and there appear to be few safety issues associated with these doses. For vitamin D, the selected 
dose is lower than the tolerable upper intake level (UL) for vitamin D3 (50 µg, or 2000 IU) set by the Food and 
Nutrition Board of the Institute of Medicine (IOM) and the European Commission Scientific Committee on Food 
(EC SCF).  Also, because we will exclude from the trial persons who report supplemental vitamin D intakes 
>800 IU/d, the selected dose ensures that no participants will be taking a supplemental vitamin D dose above 
2800 IU, which is well below the 4000 IU NOAEL specified by the EC SCF. To further ensure participants’ 
safety, we will exclude from the trial persons with a history of kidney stones, hypercalcemia, renal failure, 
cirrhosis, or sarcoidosis or other granulomatous disease, and will obtain calcium and PTH levels in a random 
subsample of participants. For fish oil, there are no specific exclusions necessary except for those currently 
taking the supplement and unwilling to forego use during the trial.   
Potential side effects of the study agents will be assessed on each follow-up questionnaire. For fish oil, 
these side effects include gastrointestinal (GI) upset (presence or absence of symptoms of peptic ulcer, 
nausea, constipation, diarrhea); bleeding (any GI bleed, GI bleeding requiring transfusion, hematuria, easy 
bruising, epistaxis); skin eruptions; and physician diagnosis of atrial fibrillation or other irregular rhythms. For 
vitamin D, these side effects include GI symptoms as listed above, and physician diagnosis of hypercalcemia 
or kidney stones.  Participants who self-report one of the parent VITAL trial study endpoints will be asked to 
sign a medical release form authorizing VITAL staff to obtain hospital/physician records.  VITAL Diabetes 
ancillary study participants who report a kidney biopsy prior to or during VITAL participation will also be asked 
to sign a medical release form authorizing VITAL staff to obtain hospital/physician records.  The Data and 
Safety Monitoring Board will compare the incidence of potential side effects in the active v. placebo groups for 
each agent, including the incidence of kidney stones with vitamin D assignment and the incidence of GI 
symptoms, skin abnormalities, and bleeding with fish oil assignment. 
VII.b. Psychosocial risks.  There is also the possibility of social/psychological risk that could result from 
inadvertent disclosure of confidential information from the questionnaires or blood tests. However, we have 
many safeguards in place to avoid this possibility, and the experienced team leading the parent VITAL trial has 
never had an inadvertent breach of confidentiality in prior trials.  Each name on the mailing tape will be 
assigned a study identification number and sent a package containing: a letter explaining the rationale for 
VITAL and what participation would entail; an informed consent form; and a brief questionnaire with items on 
demographics; medical history; current use of supplements containing vitamin D or fish oil; current use of other 
supplements or medications; dietary intake of vitamin D and consumption of fish; cancer and vascular risk 
factors; and potential effect modifiers. Those who are initially willing and eligible will be entered into the 3-
month run-in phase. Those who remain willing and eligible, and who are compliant with pill-taking during the 
run-in phase, will be randomized into the parent VITAL trial. Participants who are additionally eligible for the 
VITAL Diabetes ancillary study proposed herein will be additionally entered into this ancillary study. 
The potential risk of disclosure of confidential information is guarded against by maintaining completed 
questionnaires and blood test results in locked files accessible by authorized personnel only. In these files, 
participants are identified only by study ID. Subject identifiers are stored in separate computer files with 
password protection, and results will be presented only in the aggregate. In addition, employees involved with 
the proposed study will be asked to sign a form agreeing not to disclose any information to which they might 
have access, regardless of their personal perception about its confidentiality. Each employee of the study with 
human subject contact participates in an institutional (Brigham and Women’s Hospital) human subjects 
educational program, which consists of reviewing regulatory and informational documents pertaining to human 
subjects research; passing a test on ethical principles and regulations governing human subjects research; and 
signing a statement of commitment to the protection of human subjects.  Finally, all such employees are 
required to participate in HIPAA training.  

 
22
VIII. 
Potential Benefits 
VIII.a. Potential Benefits to Participants.  For the majority of participants, there will be few direct benefits from 
participating in this primary prevention study other than the awareness of being involved in a large endeavor to 
answer relevant and timely questions regarding the possible benefit of vitamin D and fish oil. During the trial 
itself, we will receive inquiries from the participants regarding both specific and general health concerns. We 
will respond to each of those questions, primarily directing participants to published sources or recommending 
that they see their local health provider who is familiar with their medical history.  
VIII.b. Potential Benefits to Society.  The potential benefits to society relate to the increasing use of both 
vitamin D and fish oil, with data not yet clearly indicating efficacy in the general population with respect to 
prevention of cancer and CVD (parent VITAL trial outcomes) or with respect to albuminuria and glomerular 
filtration rate (VITAL Diabetes ancillary study outcomes). Such data will help guide individual decisions, clinical 
recommendations, and public health guidelines. 

 
23
IX. 
Monitoring and Quality Assurance 
An independent Data and Safety Monitoring Board (DSMB) has been assembled for the parent VITAL trial, 
consisting of experts in clinical trials, epidemiology, biostatistics, relevant clinical areas of cancer and CVD, 
and NIH representatives. The DSMB will annually examine the progress of the trial and the unblinded data on 
study endpoints and possible adverse effects to recommend continuation, alteration of study design, or early 
termination, as appropriate. Interim trial results will be assessed with the Haybittle-Peto rule,155, 156 adjusting for 
multiple looks. In this method, interim results are compared to a z-score of 3 standard deviations (p=0.0027) 
throughout the trial. The final results may then be interpreted as having close to nominal significance levels. 
This rule appropriately requires very strong evidence for early stopping, is more conservative than the 
Pocock157 and O’Brien-Fleming158 rules and the alpha-spending function,159 and can be conducted at 
convenient times without inducing statistical complexity.160 
While these rules are intended for the primary endpoints, the goal of VITAL is to assess the overall balance 
of benefits and risks of the two agents in the primary prevention of cancer and CVD. Thus, consideration will 
also be given to the secondary endpoints that are needed in the interpretation of overall results. In addition, the 
monitoring rules will serve solely as guidelines in decisions regarding continuation or stopping of treatment 
arms. All decisions must be made after examining the totality of evidence, including other trial data, on these 
agents. 

 
24
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Randomized Clinical Trial of Vitamin D and Omega-3 Fatty Acids  
for Diabetic Kidney Disease 
 
 
Protocol Addendum 
Changes to analytic plan 
Submitted in NIH grant renewal application 3/2/2015 
Implemented upon funding 2/24/2016 
 
 
 
  

 
2
15. Data analysis  
15a. Descriptive analyses. We will describe creation of the VITAL diabetes sub-cohort according to 
CONSORT guidelines, including numbers of participants who consent to VITAL participation; report a 
diagnosis of diabetes; are approached for the DKD ancillary study; enroll in the DKD ancillary study; and 
complete year 2 and 5 year biosample collections. We will document reasons that participants do not complete 
the proposed studies. Among participants recruited into the DKD ancillary study, we will compare baseline 
characteristics of those who do and do not return at least one follow-up biosample collection. Among 
participants who return a follow-up biospecimen, we will describe by treatment assignment baseline 
characteristics and changes in clinical characteristics over the course of the study. 
15b. Study outcomes. With an extension of follow-up from 2 to 5 years, we will have sufficient time to 
effectively evaluate change in estimated GFR (eGFR), a clinically relevant outcome.175-179 Therefore, if this 
competitive renewal is funded, change in eGFR from baseline to year 5 will supplant 2-year changes in 
albuminuria and eGFR as our primary study outcome. Change in eGFR will be calculated and summarized by 
treatment group as [eGFR5 – eGFR0], where eGFR5 represents eGFR at follow-up (year 5) and eGFR0 
represents eGFR at baseline. As secondary outcomes, we will examine changes in urine ACR from baseline to 
years 2 and 5, time to the development of rapid eGFR loss (loss of eGFR ≥40% from baseline to year 2 or 
5),175-179 and time to a composite of rapid eGFR loss, end stage renal disease (maintenance dialysis or kidney 
transplant verified by medical records review), or death. The composite outcome addresses large changes in 
eGFR which have particularly high clinical importance and reduces the potential impact of competing risks that 
preclude assessment of eGFR at follow-up. 
15c. Intention to treat and missing data. Analyses will be performed in accordance with the intent-to-treat 
principle, meaning that all participants who return at least one follow-up biosample will be included in analyses, 
regardless of adherence or other characteristics observed after randomization. Multiple imputation for study 
participants missing year 5 eGFR will be conducted using chained equations, utilizing baseline data as well as 
eGFR and urine ACR data available at year 2.180 Results from 10 imputation datasets will be combined using 
Rubin’s rules.181  
15d. Treatment interaction. We will assess for interaction of the study interventions (vitamin D and omega-3 
fatty acids) for the primary outcome.182 We will use a linear mixed model to test for interaction:183 
Equation 1:  eGFRij = β0 + β1(vitamin Di) + β2(ω-3 FAi) + β3(vitamin Di × ω-3 FAi) + β4(vitamin Di × tij) 
+ β5(ω-3 FAi × tij) + β6(vitamin Di × ω-3 FAi x tij) + ai + eij 
where i denotes the ith participant and j=0,2,5 represents the time period, t is time modeled categorically, 
(vitamin D) is active vitamin D treatment assignment (yes/no), (ω-3 FA) is active omega-3 treatment 
assignment (yes/no), ai is a random effect for patient, and ε is statistical error. A p value < 0.05 for β6 will be 
interpreted as evidence of interaction. If we observe interaction, all analyses will separately compare each of 
the 3 active treatment groups to the treatment group which receives (placebo + placebo). If there is no 
evidence of interaction, as hypothesized, all participants assigned to any active vitamin D will be compared to 
all participants assigned to placebo vitamin D, and all participants assigned to any active omega-3 fatty acids 
will be compared to all participants assigned to placebo omega-3 fatty acids. 
15e. Hypothesis testing. The primary outcome is a continuous variable which will be tested using a linear 
mixed model with random intercepts. To test whether the change in eGFR differs by vitamin D treatment 
assignment in the absence of interaction with omega-3 fatty acids, we will test: 
Equation 2:  eGFRij = β0 + β1(vitamin Di) + β2(tij) + β3(vitamin Di × tij) + ai + eij 
where β3 represents the difference in change in eGFR over time, comparing those on active vitamin D3 to 
those on placebo. The corresponding 95% confidence interval and p-value reflect statistical significance of the 
treatment effect. We will use this model to describe treatment effects at years 2 and 5 but reserve statistical 
inference for year 5 alone. Corresponding equations will test the effect of omega-3 treatment assignment on 
eGFR as well as treatment effects on urine ACR, analyzed as a log-transformed continuous variable. The 
relatively large sample size makes it likely that few or no substantial differences in baseline characteristics will 
be present. In the event that any baseline characteristics are not balanced between treatment groups, 
sensitivity analyses will add to the model additional terms for such baseline characteristics. If we observe 
differences by treatment group in medication use (e.g. glucose-lowering or antihypertensive medications) or 

 
3
laboratory covariates (e.g. hemoglobin A1c, CRP, IL-6) over follow-up, 
we will explore whether such differences may mediate or attenuate 
treatment effects by adding terms for these covariates to the model. 
We will assess secondary categorical outcomes using discrete Cox 
proportional hazards models.184 
15f. Subgroup analyses.  For the vitamin D intervention, prespecified 
subgroup analyses will be based on baseline total and bioavailable 
serum 25(OH)D concentrations, urine ACR, and eGFR as well as 
race/ethnicity: we hypothesize that effects will be greater among 
participants who have low 25(OH)D at baseline, who have DKD (urine 
ACR ≥ 30 mg/g or eGFR < 60 mL/min/m2) at baseline, or are 
Caucasian.185,186 For the omega-3 fatty acid intervention, prespecified 
subgroup analyses will be based on baseline levels of EPA+DHA and 
hsCRP: we hypothesize that effects will be greater among participants 
who low levels of EPA+DHA or high concentrations of hsCRP at 
baseline. Effect modification will be tested by including interaction 
terms of treatment assignment with subgroup in linear mixed models 
(Equation 2). 
15g. Exploratory adherence and efficacy analyses.  All primary analyses will be performed according to the 
intent-to-treat principle (Section D15e). We plan secondary, exploratory analyses for the following limited 
purposes: (a) to evaluate whether null findings, if observed, are robust (i.e. not readily attributable to defects in 
the study interventions or their administration); and/or (b) to more comprehensively evaluate the potential 
range of treatment effects, if treatment effects are observed. We understand and acknowledge that these 
analyses, which are based on data collected after randomization, may introduce bias into study results. We will 
therefore use caution to limit their interpretation. We will first repeat analyses among the subset of participants 
who report continuous adherence to ≥ 80% of study medications.  In addition, we will assess whether changes 
in 25(OH)D and EPA+DHA levels are associated with changes in urine ACR and eGFR. For the latter 
analyses, change in 25(OH)D concentrations or change in EPA+DHA concentration (continuous variables) will 
replace treatment assignment in linear mixed models. 
D16. Power. We calculated power using simulation (2000 replications) and the following assumptions: 
independent and equal allocation of participants to each treatment; 1,058 participants (80%) contributing at 
least one follow-up blood sample (as supported in Section D10); variation in eGFR and its change over time as 
observed in the preliminary data from our study population (Section D12); and no interaction between 
treatments. With these assumptions, we have 80% power (two-sided alpha=0.05) to detect a 2.3 
mL/min/1.73m2 difference in eGFR at year 5, comparing each active treatment to placebo. Power for 
alternative effect sizes is shown in Figure 7. We do not present power for secondary outcomes because the 
incidence of these outcomes is difficult to predict with available data.