L H Kuller

Korea University, Sŏul, Seoul, South Korea

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Publications (1000)6265.22 Total impact

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    ABSTRACT: Background: The Women's Health Initiative (WHI) low fat (20% kcal) diet modification (DM) trial (1993-2005) demonstrated a non-significant reduction in breast cancer, a nominally significant reduction in ovarian cancer and no effect on other cancers (mean 8.3 years intervention). Consent to non-intervention follow-up was 83% (n=37,858). This analysis was designed to assess post-intervention cancer risk in women randomized to the low-fat diet (40%) versus usual diet comparison (60%). Methods: Randomized, controlled low fat diet intervention for prevention of breast and colorectal cancers conducted in 48,835 postmenopausal U.S. women, aged 50-79 years at 40 U.S. sites. Outcomes included total invasive cancer, breast and colorectal cancer, cancer-specific and overall mortality. Results: There were no intervention effects on invasive breast 1.08 (0.94, 1.24) or colorectal cancer, other cancers, cancer-specific or overall mortality during the post-intervention period or the combined intervention and follow-up periods. For invasive breast cancer, the HRs were 0.92 (0.84, 1.01) during intervention, during the post-intervention period, and 0.97 (0.89, 1.05) during cumulative follow up. A reduced risk for estrogen receptor positive/progesterone receptor negative tumors was demonstrated during follow-up. Women with higher baseline fat intake (quartile), point estimates of breast cancer risk were HR-0.76; 0.62, 0.92 during intervention versus HR-1.11; 0.84, 1.4 during post-intervention follow-up (p-diff=.03). Conclusions: Dietary fat intake rose post-intervention in intervention women; no long-term reduction in cancer risk or mortality was shown in the WHI DM trial. Impact: Dietary advisement to reduce fat for cancer prevention after menopause generally was not supported by the WHI DM trial.
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    ABSTRACT: Cerebral white matter lesions (WMLs) are considered a reflection of cerebral and systemic small vessel disease (SVD), and are associated with reductions in brain volume. Like the brain, the kidney is also sensitive to factors that affect vasculature. Glomerular dysfunction due to renal vascular damage can be measured with different biochemical parameters, such as creatinine or cystatin C, although cystatin C is considered to be more accurate than creatinine in the elderly. The purpose of the study was to determine whether manifestations of SVD in the kidney can predict SVD-based damage to the brain. We examined the relationship between glomerular dysfunction as a measure of SVD on WMLs, gray matter (GM) volume, and cognition in 735 cognitively normal participants from the Cardiovascular Health Study Cognition Study. The multivariate analyses controlled for demographic characteristics, hypertension, heart disease, diabetes, Apolipoprotein 4 allele, C reactive protein, lipids, physical activity, smoking, and body mass index (BMI). Elevated cystatin C levels were associated with lower neuropsychological test scores, the presence of MRI-identified brain infarcts, the severity of WMLs, and GM atrophy five years later. In adjusted models, GM volume was significantly associated with cystatin-C only until BMI and severity of WMLs were added to the model, meaning that the effect of SVD on GM volume is mediated by these two variables. These findings suggest that age-related SVD is a process that leads to altered brain structure, and creates a vulnerability state for cognitive decline.
    Journal of Alzheimer's disease: JAD 09/2014; · 4.17 Impact Factor
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    ABSTRACT: The purpose of this study was to use a novel imaging biomarker to assess associations between physical activity (PA), body mass index (BMI), and brain structure in normal aging, mild cognitive impairment, and Alzheimer's dementia. We studied 963 participants (mean age: 74.1 ± 4.4 years) from the multisite Cardiovascular Health Study including healthy controls (n = 724), Alzheimer's dementia patients (n = 104), and people with mild cognitive impairment (n = 135). Volumetric brain images were processed using tensor-based morphometry to analyze regional brain volumes. We regressed the local brain tissue volume on reported PA and computed BMI, and performed conjunction analyses using both variables. Covariates included age, sex, and study site. PA was independently associated with greater whole brain and regional brain volumes and reduced ventricular dilation. People with higher BMI had lower whole brain and regional brain volumes. A PA-BMI conjunction analysis showed brain preservation with PA and volume loss with increased BMI in overlapping brain regions. In one of the largest voxel-based cross-sectional studies to date, PA and lower BMI may be beneficial to the brain across the spectrum of aging and neurodegeneration.
    Neurobiology of aging. 08/2014;
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    ABSTRACT: Background/Objectives:Higher volumes of ectopic cardiovascular fat (ECF) are associated with greater risk of coronary heart disease (CHD). Identifying factors that are associated with ECF volumes may lead to new preventive efforts to reduce risk of CHD. Significant racial/ethnic differences exist for overall and central adiposity measures which are known to be associated with ECF volumes. Whether racial/ethnic differences also exist for ECF volumes and their associations with these adiposity measures remain unclear.Subjects/Methods:Body-mass index (BMI), CT-measured ECF volumes (epicardial, pericardial and their summation), and visceral adipose tissue (VAT) were examined in a community-based sample of 1,199 middle-aged men (24.2% Caucasians, 7.0% African-Americans, 23.6% Japanese-Americans, 22.0% Japanese, 23.2% Koreans).Results:Significant racial/ethnic differences existed in ECF volumes and their relationships with BMI and VAT. ECF volumes were highest among Japanese-Americans and lowest among African-Americans. The associations of BMI and VAT with ECF differed by racial/ethnic groups. Compared to Caucasians, for each 1-unit increase in BMI, African-Americans had lower whereas Koreans had higher increases in ECF volumes (P-values<0.05 for both). Meanwhile, compared to Caucasians, for each 1-unit increase in log-transformed-VAT, African-Americans, Japanese-Americans and Japanese had similar increases, whereas Koreans had a lower increase in ECF volumes (P-value<0.05).Conclusions:Racial/ethnic groups differed in their propensity to accumulate ECF at increasing level of overall and central adiposity. Future studies should evaluate whether reducing central adiposity or overall-weight will decrease ECF volumes more in certain racial/ethnic groups. Evaluating these questions might help in designing race-specific prevention strategy of CHD risk associated with higher ECF.International Journal of Obesity accepted article preview online, 11 August 2014; doi:10.1038/ijo.2014.154.
    International journal of obesity (2005) 08/2014; · 5.22 Impact Factor
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    ABSTRACT: To determine whether low vitamin D concentrations are associated with an increased risk of incident all-cause dementia and Alzheimer disease.
    Neurology 08/2014; · 8.25 Impact Factor
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    ABSTRACT: Brain health may be affected by modifiable lifestyle factors; consuming fish and antioxidative omega-3 fatty acids may reduce brain structural abnormality risk.
    American journal of preventive medicine. 07/2014;
  • Lewis H Kuller, Timothy C Wong
    Nature Reviews Cardiology 07/2014; · 10.40 Impact Factor
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    ABSTRACT: The high prevalence, incidence and mortality rates of prostate cancer in Tobago would appear to strongly indicate that screening of this population would be justified and could positively impact on mortality. We consider our approach to be consonant with the recommendations of the EAU (Heidenreich A et al, 2013) and the findings of Hugosson et al, 2014)
    BJU International 07/2014; · 3.05 Impact Factor
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    ABSTRACT: Physical activity influences inflammation, and both affect brain structure and Alzheimer's disease (AD) risk. We hypothesized that older adults with greater reported physical activity intensity and lower serum levels of the inflammatory marker tumor necrosis factor α (TNFα) would have larger regional brain volumes on subsequent magnetic resonance imaging (MRI) scans. In 43 cognitively intact older adults (79.3 ± 4.8 years) and 39 patients with AD (81.9 ± 5.1 years at the time of MRI) participating in the Cardiovascular Health Study, we examined year-1 reported physical activity intensity, year-5 blood serum TNFα measures, and year-9 volumetric brain MRI scans. We examined how prior physical activity intensity and TNFα related to subsequent total and regional brain volumes. Physical activity intensity was measured using the modified Minnesota Leisure Time Physical Activities questionnaire at year 1 of the study, when all subjects included here were cognitively intact. Stability of measures was established for exercise intensity over 9 years and TNFα over 3 years in a subset of subjects who had these measurements at multiple time points. When considered together, more intense physical activity intensity and lower serum TNFα were both associated with greater total brain volume on follow-up MRI scans. TNFα, but not physical activity, was associated with regional volumes of the inferior parietal lobule, a region previously associated with inflammation in AD patients. Physical activity and TNFα may independently influence brain structure in older adults.
    Neuroscience 05/2014; · 3.12 Impact Factor
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    Arthritis & Rheumatology. 05/2014; 66(5).
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    ABSTRACT: Wrist-worn accelerometer devices measure sleep in free-living settings. Few studies, however, have investigated whether these devices can also measure waking movement behavior (e.g., total movement volume, physical activity). The purpose of this study was to investigate the ability of a wrist-worn Actiwatch-2 sleep monitor to rank total movement volume and physical activity levels compared to a waist-worn ActiGraph GT1M accelerometer and self-reported leisure-time physical activity, respectively. Additionally, we compared temporally-matched activity measured via ActiGraph GT1M and Actiwatch-2 over the study week. A subset of women from the Healthy Women Study (n=145; age 73.3±1.7y) wore an Actiwatch-2 on their non-dominant wrist and an ActiGraph GT1M on their dominant hip for 7-consecutive days. Participants recorded their leisure-time physical activity in a 7-day diary and completed the past-year version of the Modifiable Activity Questionnaire. Analyses were conducted for all wake periods, and separately for active periods, when both devices were worn. Spearman rank-order correlation coefficients for total movement volume between Actiwatch-2 and ActiGraph GT1M were significant for wake periods (r=0.47, p<0.001) and to a lesser extent for active periods (r=0.26, p<0.01). However, Actiwatch-2 did not rank participant physical activity levels similarly to self-reported leisure-time physical activity estimates (kappa≤0.05, p>0.05). Multilevel model analyses comparing temporally-matched activity measured via ActiGraph GT1M and Actiwatch-2 suggest that the two devices yielded similar levels of activity during wake periods (B=0.90, SE=0.008, p<0.001) as well as during active periods (B=0.81, SE=0.01, p<0.001). A wrist-worn Actiwatch-2 may be useful for ranking total movement volume and for assessing the pattern of activity over a day in older women. However, our data does not support using a wrist-worn Actiwatch-2 device for measuring physical activity.
    Medicine and science in sports and exercise 04/2014; · 4.48 Impact Factor
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    ABSTRACT: Sleep and physical activity are both important for cognition. However, few cognitive function studies include comprehensive measurement of both sleep and physical activity. The purpose of this study was to examine the independent and interactive associations of sleep and physical activity in relation to cognitive function in older women. A subset of 121 women from the Healthy Women Study, mean age 73.3 ± 1.7 years, wore an actigraphy sleep monitor, physical activity accelerometer, and kept sleep and physical activity diaries for 7 consecutive days. Executive function was measured with the Digit Symbol Substitution Test and the Trail Making Test B. Verbal fluency was assessed with a word generation task. In adjusted models, greater actigraphy-assessed sleep efficiency was associated with more correct responses on the Digit Symbol Substitution Test (β = 0.35, SE = 0.15, p < 0.02). Sleep was not associated with verbal fluency. A significant interaction (p < 0.05) was observed between accelerometer-assessed physical activity and actigraphy-assessed sleep efficiency. Specifically, lower sleep efficiency was associated with poorer performance on both the Digit Symbol Substitution Test and the Trail Making Test B among women with low levels of physical activity but not among women with high levels of physical activity. Our findings suggest that greater levels of physical activity may attenuate the negative impact of poor sleep on executive function in older women, with the clearest effects observed using direct measurements of sleep and physical activity.
    The Journals of Gerontology Series A Biological Sciences and Medical Sciences 04/2014; · 4.31 Impact Factor
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    ABSTRACT: ABSTRACT Background: The purpose of this study was to describe the longitudinal trajectories and bidirectional relationships of the physical-social and emotional functioning (EF) dimensions of positive aging and to identify their baseline characteristics. Methods: Women age 65 and older who enrolled in one or more Women's Health Initiative clinical trials (WHI CTs) and who had positive aging indicators measured at baseline and years 1, 3, 6, and 9 were included in these analyses (N = 2281). Analytic strategies included latent class growth modeling to identify longitudinal trajectories and multinomial logistic regression to examine the effects of baseline predictors on these trajectories. Results: A five-trajectory model was chosen to best represent the data. For Physical-Social Functioning (PSF), trajectory groups included Low Maintainer (8.3%), Mid-Low Improver (10.4%), Medium Decliner (10.7%), Mid-High Maintainer (31.2%), and High Maintainer (39.4%); for EF, trajectories included Low Maintainer (3%), Mid-Low Improver (9%), Medium Decliner (7.7%), Mid-High Maintainer (22.8%), and High Maintainer (57.5%). Cross-classification of the groups of trajectories demonstrated that the impact of a high and stable EF on PSF might be greater than the reverse. Low depression symptoms, low pain, and high social support were the most consistent predictors of high EF trajectories. Conclusion: Aging women are heterogeneous in terms of positive aging indicators for up to 9 years of follow-up. Interventions aimed at promoting sustainable EF might have diffused effects on other domains of healthy aging.
    International Psychogeriatrics 04/2014; · 2.19 Impact Factor
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    ABSTRACT: To examine the association between 6-min walk test (6 MWT) performance and all-cause mortality, coronary heart disease mortality, and incident coronary heart disease in older adults. We conducted a time-to-event analysis of 1,665 Cardiovascular Health Study participants without prevalent cardiovascular disease with a 6 MWT. During a mean follow-up of 8 years, there were 305 incident coronary heart disease events, and 504 deaths of which 100 were coronary heart disease-related deaths. The 6 MWT performance in the shortest two distance quintiles was associated with increased risk of all-cause mortality (290-338 m: hazard ratio [HR] = 1.7; 95% confidence interval [CI] = [1.2, 2.5]; <290 m: HR = 2.1; 95% CI = [1.4, 3.0]). The adjusted risk of coronary heart disease mortality incident events among those with a 6 MWT < 290 m was not significant. Performance on the 6 MWT is independently associated with all-cause mortality and is of prognostic utility in community-dwelling older adults.
    Journal of Aging and Health 04/2014; · 1.56 Impact Factor
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    ABSTRACT: IMPORTANCE Recent studies show that cerebral β-amyloid (Aβ) deposition is associated with blood pressure and measures of arterial stiffness in nondemented individuals. OBJECTIVE To examine the association between measures of arterial stiffness and change in Aβ deposition over time. DESIGN, SETTING, AND PARTICIPANTS Deposition of Aβ was determined in a longitudinal observational study of aging by positron emission tomography using the Pittsburgh compound B twice 2 years apart in 81 nondemented individuals 83 years and older. Arterial stiffness was measured with a noninvasive and automated waveform analyzer at the time closest to the second positron emission tomography scan. All measures were performed under standardized conditions. Pulse wave velocity (PWV) was measured in the central (carotid-femoral and heart-femoral PWV), peripheral (femoral-ankle PWV), and mixed (brachial-ankle PWV) vascular beds. MAIN OUTCOMES AND MEASURES The change in Aβ deposition over 2 years was calculated from the 81 individuals with repeat Aβ-positron emission tomography. RESULTS The proportion of Aβ-positive individuals increased from 48% at baseline to 75% at follow-up. Brachial-ankle PWV was significantly higher among Aβ-positive participants at baseline and follow-up. Femoral-ankle PWV was only higher among Aβ-positive participants at follow-up. Measures of central stiffness and blood pressure were not associated with Aβ status at baseline or follow-up, but central stiffness was associated with a change in Aβ deposition over time. Each standard deviation increase in central stiffness (carotid-femoral PWV, P = .001; heart-femoral PWV, P = .004) was linked with increases in Aβ deposition over 2 years. CONCLUSIONS AND RELEVANCE This study showed that Aβ deposition increases with age in nondemented individuals and that arterial stiffness is strongly associated with the progressive deposition of Aβ in the brain, especially in this age group. The association between Aβ deposition changes over time and generalized arterial stiffness indicated a relationship between the severity of subclinical vascular disease and progressive cerebral Aβ deposition.
    JAMA neurology. 03/2014;
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    ABSTRACT: The value of measuring levels of glycated hemoglobin (HbA1c) for the prediction of first cardiovascular events is uncertain. To determine whether adding information on HbA1c values to conventional cardiovascular risk factors is associated with improvement in prediction of cardiovascular disease (CVD) risk. Analysis of individual-participant data available from 73 prospective studies involving 294,998 participants without a known history of diabetes mellitus or CVD at the baseline assessment. Measures of risk discrimination for CVD outcomes (eg, C-index) and reclassification (eg, net reclassification improvement) of participants across predicted 10-year risk categories of low (<5%), intermediate (5% to <7.5%), and high (≥7.5%) risk. During a median follow-up of 9.9 (interquartile range, 7.6-13.2) years, 20,840 incident fatal and nonfatal CVD outcomes (13,237 coronary heart disease and 7603 stroke outcomes) were recorded. In analyses adjusted for several conventional cardiovascular risk factors, there was an approximately J-shaped association between HbA1c values and CVD risk. The association between HbA1c values and CVD risk changed only slightly after adjustment for total cholesterol and triglyceride concentrations or estimated glomerular filtration rate, but this association attenuated somewhat after adjustment for concentrations of high-density lipoprotein cholesterol and C-reactive protein. The C-index for a CVD risk prediction model containing conventional cardiovascular risk factors alone was 0.7434 (95% CI, 0.7350 to 0.7517). The addition of information on HbA1c was associated with a C-index change of 0.0018 (0.0003 to 0.0033) and a net reclassification improvement of 0.42 (-0.63 to 1.48) for the categories of predicted 10-year CVD risk. The improvement provided by HbA1c assessment in prediction of CVD risk was equal to or better than estimated improvements for measurement of fasting, random, or postload plasma glucose levels. In a study of individuals without known CVD or diabetes, additional assessment of HbA1c values in the context of CVD risk assessment provided little incremental benefit for prediction of CVD risk.
    JAMA The Journal of the American Medical Association 03/2014; 311(12):1225-33. · 29.98 Impact Factor
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    ABSTRACT: Paradoxically, a breast cancer risk reduction with conjugated equine estrogens (CEE) and a risk elevation with CEE plus medroxyprogesterone acetate (CEE + MPA) were observed in the Women's Health Initiative (WHI) randomized controlled trials. The effects of hormone therapy on serum sex hormone levels, and on the association between baseline sex hormones and disease risk, may help explain these divergent breast cancer findings. Serum sex hormone concentrations were measured for 348 breast cancer cases in the CEE + MPA trial and for 235 cases in the CEE trial along with corresponding pair-matched controls, nested within the WHI trials of healthy postmenopausal women. Association and mediation analyses, to examine the extent to which sex hormone levels and changes can explain the breast cancer findings, were conducted using logistic regression. Following CEE treatment, breast cancer risk was associated with higher concentrations of baseline serum estrogens, and with lower concentrations of sex hormone binding globulin. However, following CEE + MPA, there was no association of breast cancer risk with baseline sex hormone levels. The sex hormone changes from baseline to year 1 provided an explanation for much of the reduced breast cancer risk with CEE. Specifically, the treatment odds ratio (95% confidence interval) increased from 0.71 (0.43, 1.15) to 0.92 (0.41, 2.09) when the year 1 measures were included in the logistic regression analysis. In comparison, the CEE + MPA odds ratio was essentially unchanged when these year 1 measures were included. Breast cancer risk remains low following CEE use among women having favorable baseline sex hormone profiles, but CEE + MPA evidently produces a breast cancer risk for all women similar to that for women having an unfavorable baseline sex hormone profile. These patterns could reflect breast ductal epithelial cell stimulation by CEE + MPA that is substantially avoided with CEE, in conjunction with relatively more favorable effects of either regimen following a sustained period of estrogen deprivation. These findings may have implications for other hormone therapy formulations and routes of delivery.Trial registration: clinicaltrials.gov identifier: NCT00000611.
    Breast cancer research: BCR 03/2014; 16(2):R30. · 5.87 Impact Factor
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    ABSTRACT: Kidney cancer incidence is increasing globally. Reasons for this rise are unclear but could relate to obesity and hypertension. We analyzed longitudinal relationships between hypertension and obesity and kidney cancer incidence in 156 774 participants of the Women's Health Initiative clinical trials and observational studies over 10.8 years. In addition, we examined the effect of blood pressure (BP) on kidney cancer deaths for over 25 years among the 353 340 men screened for the Multiple Risk Factor Intervention Trial (MRFIT). In the Women's Health Initiative, systolic BP (SBP) was categorized in 6 groups from <120 to >160 mm Hg, and body mass index was categorized using standard criteria. In age-adjusted analyses, kidney cancer risk increased across SBP categories (P value for trend <0.0001) and body mass index categories (P value for trend <0.0001). In adjusted Cox proportional hazards models, both SBP levels and body mass index were predictors of kidney cancer. In the MRFIT sample, there were 906 deaths after an average of 25 years of follow-up attributed to kidney cancer among the 353 340 participants aged 35 to 57 years at screening. The risk of death from kidney cancer increased in a dose-response fashion with increasing SBP (hazard ratio, 1.87 for SBP>160 versus <120 mm Hg; 95% confidence interval, 1.38-2.53). Risk was increased among cigarette smokers. Further research is needed to determine the pathophysiologic basis of relationships between both higher BP and the risk of kidney cancer, and whether specific drug therapies for hypertension can reduce kidney cancer risk.
    Hypertension 03/2014; · 6.87 Impact Factor
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    ABSTRACT: Rheumatoid arthritis (RA) patients have an increased risk of cardiovascular disease (CVD) and mortality. We measured anti-cyclic citrullinated peptide (anti-CCP) antibody levels and determined use of disease-modifying antirheumatic drugs (DMARDs) among women in the Women's Health Initiative (WHI). Using these data, we undertook this study to assess total mortality over 10 years of followup among white, black, or Hispanic women with self-reported RA in the WHI. Using stored baseline serum, we measured anti-CCP, rheumatoid factor (RF), and antinuclear antibodies (ANAs) in 9,988 women who reported having RA. Based on a previous chart review study, probable RA was defined as either self-reported RA and anti-CCP positivity, or anti-CCP negativity and DMARD use. Cox proportional hazards regression was used to model the relationship of self-reported RA, DMARD exposure, and anti-CCP positivity to total mortality, using followup data through April 2009. At baseline, the mean age was 62.8 years; 24.5% of subjects were black and 10% were Hispanic. Prevalence of anti-CCP positivity was 8.1% (n = 812), and 217 women were anti-CCP negative but had reported use of DMARDs; therefore, 1,029 women (of 9,988) were classified as having probable RA, and 8,958 were classified as unlikely to have RA (with data on DMARD use missing for 1 subject). Age-adjusted mortality rates were ∼2-fold higher for anti-CCP-positive women, with 20.2 deaths per 1,000 person-years, as compared to 11.4 deaths per 1,000 person-years among anti-CCP-negative women with self-reported RA who never used DMARDs. Among women who did not report any arthritis at baseline, we found 8.3 deaths per 1,000 person-years. The increased risk among anti-CCP-positive women with RA was not explained by age, RF positivity, ANA positivity, or DMARD use. Anti-CCP-positive RA was associated with substantial excess mortality among postmenopausal women in the WHI. This result was not explained by the risk factors we measured.
    Arthritis & rheumatology (Hoboken, N.J.). 03/2014; 66(3):497-507.
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    ABSTRACT: Second-generation assays for anti-cyclic citrullinated peptide (anti-CCP), a highly sensitive and specific marker for rheumatoid arthritis (RA), have redefined the epidemiology of RA. In the Women's Health Initiative (WHI) RA study (2009-2011), we evaluated the prevalence of anti-CCP positivity among 15,691 (10.2% of 161,808) WHI participants aged 50-79 years who reported RA. Using stored baseline specimens, we measured serum anti-CCP, rheumatoid factor (RF), and antinuclear antibody in a defined sample of 9,988 of black, white, and Hispanic women. In a subset of women, we measured plasma cytokine levels and number of copies of the human leukocyte antigen (HLA)-DRB1 (HLA-DRB1) shared epitope in DNA by means of Luminex polymerase chain reaction typing (Luminex Corporation, Austin, Texas). We validated classification of probable clinical RA in 2 clinics as anti-CCP positivity or self-reported validated use of disease-modifying antirheumatic drugs (DMARDs). The prevalence of anti-CCP positivity was 8.1%, and the prevalence of RF positivity was approximately 16.0%. DMARD use including prednisone was reported by 1,140 (11.4%) participants (841 excluding prednisone) but by 57.5% of anti-CCP-positive women. The prevalence of 2 shared epitopes was also much higher for anti-CCP-positive women (18.2%, as opposed to only 5.5% for women with anti-CCP-negative DMARD-positive RA and 6.6% for anti-CCP-negative, RF-negative DMARD nonusers). Median cytokine levels were much higher for anti-CCP-positive/RF-positive women. Women with anti-CCP-positive RA and anti-CCP-negative RA had different characteristics with regard to HLA shared epitope, cigarette smoking, and inflammation (cytokines).
    American journal of epidemiology 02/2014; · 5.59 Impact Factor

Publication Stats

41k Citations
6,265.22 Total Impact Points


  • 2010–2014
    • Korea University
      • College of Nursing
      Sŏul, Seoul, South Korea
    • University of Minnesota Duluth
      Duluth, Minnesota, United States
    • Medical University of South Carolina
      Charleston, South Carolina, United States
  • 1975–2014
    • University of Pittsburgh
      • • Department of Epidemiology
      • • School of Medicine
      • • Department of Psychiatry
      Pittsburgh, Pennsylvania, United States
  • 2013
    • Wake Forest University
      • Department of Internal Medicine
      Winston-Salem, North Carolina, United States
    • Keio University
      Edo, Tōkyō, Japan
  • 2006–2013
    • Shiga University of Medical Science
      • • Department of Health Science
      • • Department of Medicine
      Ōtu, Shiga, Japan
    • University at Buffalo, The State University of New York
      • Department of Social and Preventive Medicine
      Buffalo, NY, United States
  • 2012
    • University of Maryland, Baltimore
      • Department of Medicine
      Baltimore, MD, United States
  • 2011
    • Autonomous University of Barcelona
      Cerdanyola del Vallès, Catalonia, Spain
    • United States Department of Agriculture
      Washington, Washington, D.C., United States
    • Cornell University
      • Department of Medicine
      Ithaca, NY, United States
    • Alpert Medical School - Brown University
      Providence, Rhode Island, United States
  • 2010–2011
    • University of Texas Health Science Center at Tyler
      Tyler, Texas, United States
  • 2007–2011
    • University of California, Los Angeles
      • • Department of Neurology
      • • Laboratory of Neuro Imaging
      • • Department of Medicine
      • • Department of Epidemiology
      Los Angeles, CA, United States
    • Inje University
      • College of Medicine
      Kimhae, South Gyeongsang, South Korea
    • University of Michigan
      • Department of Internal Medicine
      Ann Arbor, MI, United States
    • Arizona State University
      Phoenix, Arizona, United States
    • Albert Einstein College of Medicine
      • Department of Epidemiology & Population Health
      New York City, NY, United States
  • 1991–2011
    • University of Minnesota Twin Cities
      • • Division of Cardiology
      • • Division of Biostatistics
      Minneapolis, MN, United States
  • 2009
    • Boston Children's Hospital
      • Department of Radiology
      Boston, MA, United States
    • National Cerebral and Cardiovascular Center
      Ōsaka, Ōsaka, Japan
    • Beth Israel Medical Center
      New York City, New York, United States
  • 2007–2009
    • CHA University
      • Department of Internal Medicine
      Seoul, Seoul, South Korea
  • 2003–2009
    • National Institute on Aging
      • Laboratory of Epidemiology, Demography and Biometry (LEDB)
      Baltimore, MD, United States
    • University of California, San Diego
      San Diego, California, United States
    • San Diego State University
      San Diego, California, United States
    • Philadelphia University
      Philadelphia, Pennsylvania, United States
    • National Institutes of Health
      • Laboratory of Epidemiology, Demography, and Biometry (LEDB)
      Bethesda, MD, United States
  • 1997–2009
    • Western Psychiatric Institute and Clinic
      Pittsburgh, Pennsylvania, United States
  • 1996–2009
    • University of Vermont
      • • Department of Pathology
      • • Department of Medicine
      Burlington, VT, United States
  • 2008
    • Johns Hopkins Bloomberg School of Public Health
      Baltimore, Maryland, United States
    • Kaiser Permanente
      Oakland, California, United States
    • Tufts University
      Georgia, United States
    • George Washington University
      • Department of Medicine
      Washington, D. C., DC, United States
  • 2003–2008
    • Beth Israel Deaconess Medical Center
      • • Department of Medicine
      • • Division of General Medicine and Primary Care
      Boston, MA, United States
  • 1999–2007
    • University of Helsinki
      • Department of Psychology
      Helsinki, Province of Southern Finland, Finland
    • North Carolina Department of Health and Human Services
      Raleigh, North Carolina, United States
  • 1990–2007
    • University of California, Davis
      • • Center for Neuroscience
      • • Department of Neurology
      • • School of Medicine
      Davis, CA, United States
  • 2002–2006
    • University of Washington Seattle
      • • Department of Medicine
      • • Department of Biostatistics
      Seattle, WA, United States
  • 2005
    • University of Bristol
      Bristol, England, United Kingdom
    • University of Nevada, Las Vegas
      Las Vegas, Nevada, United States
    • Harvard Medical School
      • Department of Medicine
      Boston, MA, United States
  • 1994–2004
    • Tulane University
      • • Department of Epidemiology
      • • School of Public Health and Tropical Medicine
      New Orleans, LA, United States
    • University of Melbourne
      • Department of Ophthalmology
      Melbourne, Victoria, Australia
  • 1991–2004
    • Johns Hopkins University
      • Department of Medicine
      Baltimore, Maryland, United States
  • 2001
    • Emory University
      • Division of Endocrinology
      Atlanta, GA, United States
  • 2000
    • Slippery Rock University of Pennsylvania
      Slippery Rock, Pennsylvania, United States
    • University of California, San Francisco
      San Francisco, California, United States
  • 1998
    • Maine Medical Center
      Portland, Maine, United States
    • London School of Hygiene and Tropical Medicine
      • Faculty of Epidemiology and Population Health
      Londinium, England, United Kingdom
  • 1994–1996
    • University of Alabama at Birmingham
      • Department of Medicine
      Birmingham, Alabama, United States
  • 1995
    • University of Benin
      • Department of Community Health
      Benim, Edo, Nigeria
  • 1993
    • University of Tennessee
      Knoxville, Tennessee, United States
  • 1992–1993
    • University of Delaware
      Delaware, United States
    • National Heart, Lung, and Blood Institute
      Maryland, United States
    • Pittsburg State University
      Kansas, United States
    • Oklahoma City University
      Oklahoma City, Oklahoma, United States
  • 1991–1992
    • Childrens Hospital of Pittsburgh
      • Department of Pediatrics
      Pittsburgh, Pennsylvania, United States
  • 1988
    • Pennsylvania Department of Health
      Harrisburg, Pennsylvania, United States
  • 1986
    • Georgia Health Sciences University
      • Department of Medicine
      Augusta, Georgia, United States