A meta-analysis of previous falls and subsequent fracture risk in cohort studies.

The relationship between self-reported falls and fracture risk was estimated in an international meta-analysis of individual-level data from 46 prospective cohorts. Previous falls were associated with an increased fracture risk in women and men and should be considered as an additional risk factor in the FRAX® algorithm. INTRODUCTION: Previous falls are a well-documented risk factor for subsequent fracture but have not yet been incorporated into the FRAX algorithm. The aim of this study was to evaluate, in an international meta-analysis, the association between previous falls and subsequent fracture risk and its relation to sex, age, duration of follow-up, and bone mineral density (BMD). METHODS: The resource comprised 906,359 women and men (66.9% female) from 46 prospective cohorts. Previous falls were uniformly defined as any fall occurring during the previous year in 43 cohorts; the remaining three cohorts had a different question construct. The association between previous falls and fracture risk (any clinical fracture, osteoporotic fracture, major osteoporotic fracture, and hip fracture) was examined using an extension of the Poisson regression model in each cohort and each sex, followed by random-effects meta-analyses of the weighted beta coefficients. RESULTS: Falls in the past year were reported in 21.4% of individuals. During a follow-up of 9,102,207 person-years, 87,352 fractures occurred of which 19,509 were hip fractures. A previous fall was associated with a significantly increased risk of any clinical fracture both in women (hazard ratio (HR) 1.42, 95% confidence interval (CI) 1.33-1.51) and men (HR 1.53, 95% CI 1.41-1.67). The HRs were of similar magnitude for osteoporotic, major osteoporotic fracture, and hip fracture. Sex significantly modified the association between previous fall and fracture risk, with predictive values being higher in men than in women (e.g., for major osteoporotic fracture, HR 1.53 (95% CI 1.27-1.84) in men vs. HR 1.32 (95% CI 1.20-1.45) in women, P for interaction = 0.013). The HRs associated with previous falls decreased with age in women and with duration of follow-up in men and women for most fracture outcomes. There was no evidence of an interaction between falls and BMD for fracture risk. Subsequent risk for a major osteoporotic fracture increased with each additional previous fall in women and men. CONCLUSIONS: A previous self-reported fall confers an increased risk of fracture that is largely independent of BMD. Previous falls should be considered as an additional risk factor in future iterations of FRAX to improve fracture risk prediction.

Biomarkers of cellular senescence in idiopathic pulmonary fibrosis.

BACKGROUND: Cellular senescence is a cell fate in response to diverse forms of age-related damage and stress that has been implicated in the pathogenesis of idiopathic pulmonary fibrosis (IPF). The associations between circulating levels of candidate senescence biomarkers and disease outcomes have not been specifically studied in IPF. In this study we assessed the circulating levels of candidate senescence biomarkers in individuals affected by IPF and controls and evaluated their ability to predict disease outcomes. METHODS: We measured the plasma concentrations of 32 proteins associated with senescence in Lung Tissue Research Consortium participants and studied their relationship with the diagnosis of IPF, parameters of pulmonary and physical function, health-related quality of life, mortality, and lung tissue expression of P16, a prototypical marker of cellular senescence. A machine learning approach was used to evaluate the ability of combinatorial biomarker signatures to predict disease outcomes. RESULTS: The circulating levels of several senescence biomarkers were significantly elevated in persons affected by IPF compared to controls. A subset of biomarkers accurately classified participants as having or not having the disease and was significantly correlated with measures of pulmonary function, health-related quality of life and, to an extent, physical function. An exploratory analysis revealed senescence biomarkers were also associated with mortality in IPF participants. Finally, the plasma concentrations of several biomarkers were associated with their expression levels in lung tissue as well as the expression of P16. CONCLUSIONS: Our results suggest that circulating levels of candidate senescence biomarkers are informative of disease status, pulmonary and physical function, and health-related quality of life. Additional studies are needed to validate the combinatorial biomarkers signatures that emerged using a machine learning approach.

Adult atopic eczema and the risk of dementia: A population-based cohort study.

BACKGROUND: Chronic inflammatory conditions have been linked to dementia, but little is known about the role of atopic eczema, an inflammatory condition recently recognized to be common among older adults. OBJECTIVE: To determine whether active atopic eczema is associated with incident dementia. METHODS: A longitudinal cohort study of 1,767,667 individuals aged 60 to 99 years registered with The Health Improvement Network, a primary care cohort in the United Kingdom. The diagnoses of atopic eczema and dementia were identified using medical record codes. RESULTS: The incidence of dementia was 57 per 10,000 person-years among those with atopic eczema during follow-up (12.1% of the population) compared with 44 per 10,000 person-years in the control group. This translated to a 27% increased risk of dementia (hazard ratio, 1.27; 95% CI, 1.23-1.30) in adjusted Cox proportional hazard models. Similar associations were observed in subgroup analyses of vascular dementia and Alzheimer's disease. The association persisted after additionally adjusting for the use of systemic corticosteroids (hazard ratio, 1.29; 95% CI, 1.26-1.33) and potential mediators (hazard ratio, 1.19; 95% CI, 1.16-1.22). More severe eczema was associated with a higher risk of dementia. LIMITATIONS: Lack of detailed data on severity. CONCLUSION: Atopic eczema was associated with a small but increased risk of incident dementia. The association increased with the severity of atopic eczema.

Recent fall and high imminent risk of fracture in older men and women.

BACKGROUND: despite fall history being a well-known risk factor for falls and fractures, the association between very recent falls and imminent fracture risk is not clearly elucidated. OBJECTIVE: to study the very recent (<4 months) fall-related absolute risk of fractures in the following year. METHODS: two large prospective cohort studies of women (Study of Osteoporotic Fractures [SOF]) and men (Osteoporotic Fractures in Men Study [MrOS]) aged 65 years or older were included. Data on falls were collected every 4 months, and the primary outcomes were any non-spine and hip fractures in the next 12 months. RESULTS: a total of 9,704 women contributed 419,149, and 5,994 men contributed 223,885 four-monthly periods of observations during the 14.8-year SOF and 12.6-year MrOS follow-up. Falls within 4 months indicated a high risk of non-spine and hip fractures in the following year for both sexes; in women, a recent fall indicated an 8.1% absolute risk of a non-spine fracture within 1 year, a 2.5-fold higher risk than that in women without falls, a 2.5% absolute risk of hip fracture, and a 3.1-fold increased risk. Falls increased the risk of fractures regardless of whether a fracture occurred or not. Men had similar risk patterns, albeit with a lower absolute risk of fracture. CONCLUSIONS: in older people, a fall within 4 months indicates a high risk of fracture in the next year, regardless of fracture occurrence. A recent fall warrants urgent evaluation and consideration of treatments to reduce the imminent risk of fractures.

signatureSearch: environment for gene expression signature searching and functional interpretation.

signatureSearch is an R/Bioconductor package that integrates a suite of existing and novel algorithms into an analysis environment for gene expression signature (GES) searching combined with functional enrichment analysis (FEA) and visualization methods to facilitate the interpretation of the search results. In a typical GES search (GESS), a query GES is searched against a database of GESs obtained from large numbers of measurements, such as different genetic backgrounds, disease states and drug perturbations. Database matches sharing correlated signatures with the query indicate related cellular responses frequently governed by connected mechanisms, such as drugs mimicking the expression responses of a disease. To identify which processes are predominantly modulated in the GESS results, we developed specialized FEA methods combined with drug-target network visualization tools. The provided analysis tools are useful for studying the effects of genetic, chemical and environmental perturbations on biological systems, as well as searching single cell GES databases to identify novel network connections or cell types. The signatureSearch software is unique in that it provides access to an integrated environment for GESS/FEA routines that includes several novel search and enrichment methods, efficient data structures, and access to pre-built GES databases, and allowing users to work with custom databases.

Association of mammographic density measures and breast cancer "intrinsic" molecular subtypes.

PURPOSE: We evaluated the association of percent mammographic density (PMD), absolute dense area (DA), and non-dense area (NDA) with risk of "intrinsic" molecular breast cancer (BC) subtypes. METHODS: We pooled 3492 invasive BC and 10,148 controls across six studies with density measures from prediagnostic, digitized film-screen mammograms. We classified BC tumors into subtypes [63% Luminal A, 21% Luminal B, 5% HER2 expressing, and 11% as triple negative (TN)] using information on estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and tumor grade. We used polytomous logistic regression to calculate odds ratio (OR) and 95% confidence intervals (CI) for density measures (per SD) across the subtypes compared to controls, adjusting for age, body mass index and study, and examined differences by age group. RESULTS: All density measures were similarly associated with BC risk across subtypes. Significant interaction of PMD by age (P = 0.001) was observed for Luminal A tumors, with stronger effect sizes seen for younger women < 45 years (OR = 1.69 per SD PMD) relative to women of older ages (OR = 1.53, ages 65-74, OR = 1.44 ages 75 +). Similar but opposite trends were seen for NDA by age for risk of Luminal A: risk for women: < 45 years (OR = 0.71 per SD NDA) was lower than older women (OR = 0.83 and OR = 0.84 for ages 65-74 and 75 + , respectively) (P < 0.001). Although not significant, similar patterns of associations were seen by age for TN cancers. CONCLUSIONS: Mammographic density measures were associated with risk of all "intrinsic" molecular subtypes. However, findings of significant interactions between age and density measures may have implications for subtype-specific risk models.

Risks of Hip and Nonvertebral Fractures in Patients With CKD G3a-G5D: A Systematic Review and Meta-analysis.

RATIONALE & OBJECTIVE: Disordered mineral metabolism complicates chronic kidney disease (CKD), but the effect of reduced kidney function on fracture risk has not been fully established. We conducted a systematic review and meta-analysis of the risks for hip and nonvertebral fractures in people with CKD. We also investigated the effects of age, sex, and CKD stage. STUDY DESIGN: Systematic review and meta-analysis. STUDY POPULATION: Adults with CKD glomerular filtration rate (GFR) categories 3a-5D (G3a-G5D) compared with adults without CKD G3a-G5D. SELECTION CRITERIA FOR STUDIES: Observational studies. DATA EXTRACTION: Data extraction was conducted by 1 reviewer and checked by a second reviewer. ANALYTICAL APPROACH: MEDLINE, EMBASE, and Cochrane databases were searched in March 2018 and an update was conducted in November 2019. We used random-effects models to calculate pooled risk estimates and 95% CIs. RESULTS: 17 studies met the inclusion criteria. We included 13 studies in the hip fracture systematic review and 10 studies in the meta-analysis. Studies reported data from 250,440,035 participants; 5,798,566 with CKD G3a-G5D and 363,410 with hip fractures. 4 studies were included in the nonvertebral fracture analysis, reporting data from 1,396,976 participants; 464,978 with CKD G3a-G5D and 115,284 fractures. Studies reported data from participants aged 18 to older than 90 years. We found a significant increase in fracture risk both for hip (relative risk [RR], 2.36; 95% CI, 1.64-3.39) and nonvertebral fractures (RR, 1.47; 95% CI, 1.15-1.88). For hip fractures, younger patients (<65 years) had higher relative risk (RR, 7.66; 95% CI, 2.76-21.26) than older patients (>65 years; RR, 2.11; 95% CI, 1.41-3.16). Greater GFR loss was associated with higher relative risk for fractures. LIMITATIONS: We could not assess the effects of bone mineral density, biochemical abnormalities, renal osteodystrophy, frailty, falls, or medications on risk for fractures. CONCLUSIONS: Risks for hip and nonvertebral fractures are increased in CKD G3a-G5D. The relative risk of hip fracture is greater in the younger than the older population and increases progressively with loss of GFR. We suggest that fracture prevention should be a consideration in CKD at any age.

Individual and joint trajectories of change in bone, lean mass and physical performance in older men.

BACKGROUND: Declines in bone, muscle and physical performance are associated with adverse health outcomes in older adults. However, few studies have described concurrent age-related patterns of change in these factors. The purpose of this study was to characterize change in four properties of muscle, physical performance, and bone in a prospective cohort study of older men. METHODS: Using repeated longitudinal data from up to four visits across 6.9 years from up to 4681 men (mean age at baseline 72.7 yrs. ±5.3) participating in the Osteoporotic Fractures in Men (MrOS) Study, we used group-based trajectory models (PROC TRAJ in SAS) to identify age-related patterns of change in four properties of muscle, physical performance, and bone: total hip bone mineral (BMD) density (g/m2) and appendicular lean mass/ht2 (kg/m2), by DXA; grip strength (kg), by hand dynamometry; and walking speed (m/s), by usual walking pace over 6 m. We also described joint trajectories in all pair-wise combinations of these measures. Mean posterior probabilities of placement in each trajectory (or joint membership in latent groups) were used to assess internal reliability of the model. The number of trajectories for each individual factor was limited to three, to ensure that the pair-wise determination of joint trajectories would yield a tractable number of groups as well as model fit considerations. RESULTS: The patterns of change identified were generally similar for all measures, with three district groups declining over time at roughly similar rates; joint trajectories revealed similar patterns with no cross-over or convergence between groups. Mean posterior probabilities for all trajectories were similar and consistently above 0.8 indicating reasonable model fit to the data. CONCLUSIONS: Our description of trajectories of change with age in bone mineral density, grip strength, walking speed and appendicular lean mass found that groups identified by these methods appeared to have little crossover or convergence of change with age, even when considering joint trajectories of change in these factors.

Deep Learning With Electronic Health Records for Short-Term Fracture Risk Identification: Crystal Bone Algorithm Development and Validation.

BACKGROUND: Fractures as a result of osteoporosis and low bone mass are common and give rise to significant clinical, personal, and economic burden. Even after a fracture occurs, high fracture risk remains widely underdiagnosed and undertreated. Common fracture risk assessment tools utilize a subset of clinical risk factors for prediction, and often require manual data entry. Furthermore, these tools predict risk over the long term and do not explicitly provide short-term risk estimates necessary to identify patients likely to experience a fracture in the next 1-2 years. OBJECTIVE: The goal of this study was to develop and evaluate an algorithm for the identification of patients at risk of fracture in a subsequent 1- to 2-year period. In order to address the aforementioned limitations of current prediction tools, this approach focused on a short-term timeframe, automated data entry, and the use of longitudinal data to inform the predictions. METHODS: Using retrospective electronic health record data from over 1,000,000 patients, we developed Crystal Bone, an algorithm that applies machine learning techniques from natural language processing to the temporal nature of patient histories to generate short-term fracture risk predictions. Similar to how language models predict the next word in a given sentence or the topic of a document, Crystal Bone predicts whether a patient's future trajectory might contain a fracture event, or whether the signature of the patient's journey is similar to that of a typical future fracture patient. A holdout set with 192,590 patients was used to validate accuracy. Experimental baseline models and human-level performance were used for comparison. RESULTS: The model accurately predicted 1- to 2-year fracture risk for patients aged over 50 years (area under the receiver operating characteristics curve [AUROC] 0.81). These algorithms outperformed the experimental baselines (AUROC 0.67) and showed meaningful improvements when compared to retrospective approximation of human-level performance by correctly identifying 9649 of 13,765 (70%) at-risk patients who did not receive any preventative bone-health-related medical interventions from their physicians. CONCLUSIONS: These findings indicate that it is possible to use a patient's unique medical history as it changes over time to predict the risk of short-term fracture. Validating and applying such a tool within the health care system could enable automated and widespread prediction of this risk and may help with identification of patients at very high risk of fracture.

Automated volumetric breast density measures: differential change between breasts in women with and without breast cancer.

BACKGROUND: Given that breast cancer and normal dense fibroglandular tissue have similar radiographic attenuation, we examine whether automated volumetric density measures identify a differential change between breasts in women with cancer and compare to healthy controls. METHODS: Eligible cases (n = 1160) had unilateral invasive breast cancer and bilateral full-field digital mammograms (FFDMs) at two time points: within 2 months and 1-5 years before diagnosis. Controls (n = 2360) were matched to cases on age and date of FFDMs. Dense volume (DV) and volumetric percent density (VPD) for each breast were assessed using Volpara™. Differences in DV and VPD between mammograms (median 3 years apart) were calculated per breast separately for cases and controls and their difference evaluated by using the Wilcoxon signed-rank test. To simulate clinical practice where cancer laterality is unknown, we examined whether the absolute difference between breasts can discriminate cases from controls using area under the ROC curve (AUC) analysis, adjusting for age, BMI, and time. RESULTS: Among cases, the VPD and DV between mammograms of the cancerous breast decreased to a lesser degree (- 0.26% and - 2.10 cm3) than the normal breast (- 0.39% and - 2.74 cm3) for a difference of 0.13% (p value < 0.001) and 0.63 cm3 (p = 0.002), respectively. Among controls, the differences between breasts were nearly identical for VPD (- 0.02 [p = 0.92]) and DV (0.05 [p = 0.77]). The AUC for discriminating cases from controls using absolute difference between breasts was 0.54 (95% CI 0.52, 0.56) for VPD and 0.56 (95% CI, 0.54, 0.58) for DV. CONCLUSION: There is a small relative increase in volumetric density measures over time in the breast with cancer which is not found in the normal breast. However, the magnitude of this difference is small, and this measure alone does not appear to be a good discriminator between women with and without breast cancer.

Reduced contrast sensitivity among older women is associated with increased risk of cognitive impairment.

OBJECTIVE: Several cross-sectional studies have reported an association between visual contrast sensitivity (a functional measure of low contrast vision) and poor cognitive performance or dementia, but no studies have investigated this association prospectively in a population-based cohort with final adjudication of mild cognitive impairment (MCI)/dementia. METHODS: In a prospective, community-based study of aging women (Study of Osteoporotic Fractures), we analyzed whether visual contrast sensitivity was associated with increased risk of MCI or dementia and/or worse performance on various cognitive tests assessed 10 years later. Contrast sensitivity was assessed at baseline in each eye using a VISTECH VCTS 6500 wall chart. MCI/dementia was adjudicated by an expert panel. Multivariate logistic and linear regression models were analyzed. RESULTS: Of 1,352 white (88.2%) and African American (11.8%) women with a mean age of 77.7 years (standard deviation = 3.3), 536 (39.6%) went on to develop MCI/dementia over 10 years. MCI/dementia risk was more than doubled (odds ratio = 2.16, 95% confidence interval = 1.58-2.96) in women with the lowest quartile of contrast sensitivity compared to the highest (p < 0.0001 for the linear trend). Reduced baseline contrast sensitivity was also associated with lower performance on several cognitive measures assessed 10 years later. INTERPRETATION: Among older women, reduced contrast sensitivity is associated with a greater risk of MCI/dementia. These findings suggest that visual system neurodegeneration or dysfunction may parallel or precede dementia-related cortical or subcortical degeneration, and that contrast sensitivity testing may be useful in identifying aging adults at high risk for dementia. Ann Neurol 2018;83:730-738.

Automated and Clinical Breast Imaging Reporting and Data System Density Measures Predict Risk for Screen-Detected and Interval Cancers: A Case-Control Study.

Background: In 30 states, women who have had screening mammography are informed of their breast density on the basis of Breast Imaging Reporting and Data System (BI-RADS) density categories estimated subjectively by radiologists. Variation in these clinical categories across and within radiologists has led to discussion about whether automated BI-RADS density should be reported instead. Objective: To determine whether breast cancer risk and detection are similar for automated and clinical BI-RADS density measures. Design: Case-control. Setting: San Francisco Mammography Registry and Mayo Clinic. Participants: 1609 women with screen-detected cancer, 351 women with interval invasive cancer, and 4409 matched control participants. Measurements: Automated and clinical BI-RADS density assessed on digital mammography at 2 time points from September 2006 to October 2014, interval and screen-detected breast cancer risk, and mammography sensitivity. Results: Of women whose breast density was categorized by automated BI-RADS more than 6 months to 5 years before diagnosis, those with extremely dense breasts had a 5.65-fold higher interval cancer risk (95% CI, 3.33 to 9.60) and a 1.43-fold higher screen-detected risk (CI, 1.14 to 1.79) than those with scattered fibroglandular densities. Associations of interval and screen-detected cancer with clinical BI-RADS density were similar to those with automated BI-RADS density, regardless of whether density was measured more than 6 months to less than 2 years or 2 to 5 years before diagnosis. Automated and clinical BI-RADS density measures had similar discriminatory accuracy, which was higher for interval than screen-detected cancer (c-statistics: 0.70 vs. 0.62 [P < 0.001] and 0.72 vs. 0.62 [P < 0.001], respectively). Mammography sensitivity was similar for automated and clinical BI-RADS categories: fatty, 93% versus 92%; scattered fibroglandular densities, 90% versus 90%; heterogeneously dense, 82% versus 78%; and extremely dense, 63% versus 64%, respectively. Limitation: Neither automated nor clinical BI-RADS density was assessed on tomosynthesis, an emerging breast screening method. Conclusion: Automated and clinical BI-RADS density similarly predict interval and screen-detected cancer risk, suggesting that either measure may be used to inform women of their breast density. Primary Funding Source: National Cancer Institute.

Fine-mapping, novel loci identification, and SNP association transferability in a genome-wide association study of QRS duration in African Americans.

The electrocardiographic QRS duration, a measure of ventricular depolarization and conduction, is associated with cardiovascular mortality. While single nucleotide polymorphisms (SNPs) associated with QRS duration have been identified at 22 loci in populations of European descent, the genetic architecture of QRS duration in non-European populations is largely unknown. We therefore performed a genome-wide association study (GWAS) meta-analysis of QRS duration in 13,031 African Americans from ten cohorts and a transethnic GWAS meta-analysis with additional results from populations of European descent. In the African American GWAS, a single genome-wide significant SNP association was identified (rs3922844, P = 4 × 10-14) in intron 16 of SCN5A, a voltage-gated cardiac sodium channel gene. The QRS-prolonging rs3922844 C allele was also associated with decreased SCN5A RNA expression in human atrial tissue (P = 1.1 × 10-4). High density genotyping revealed that the SCN5A association region in African Americans was confined to intron 16. Transethnic GWAS meta-analysis identified novel SNP associations on chromosome 18 in MYL12A (rs1662342, P = 4.9 × 10-8) and chromosome 1 near CD1E and SPTA1 (rs7547997, P = 7.9 × 10-9). The 22 QRS loci previously identified in populations of European descent were enriched for significant SNP associations with QRS duration in African Americans (P = 9.9 × 10-7), and index SNP associations in or near SCN5A, SCN10A, CDKN1A, NFIA, HAND1, TBX5 and SETBP1 replicated in African Americans. In summary, rs3922844 was associated with QRS duration and SCN5A expression, two novel QRS loci were identified using transethnic meta-analysis, and a significant proportion of QRS-SNP associations discovered in populations of European descent were transferable to African Americans when adequate power was achieved.

Does mammographic density mediate risk factor associations with breast cancer? An analysis by tumor characteristics.

BACKGROUND: Though mammographic density (MD) has been proposed as an intermediate marker of breast cancer risk, few studies have examined whether the associations between breast cancer risk factors and risk are mediated by MD, particularly by tumor characteristics. METHODS: Our study population included 3392 cases (1105 premenopausal) and 8882 (3192 premenopausal) controls from four case-control studies. For established risk factors, we estimated the percent of the total risk factor association with breast cancer that was mediated by percent MD (secondarily, by dense area and non-dense area) for invasive breast cancer as well as for subtypes defined by the estrogen receptor (ER+/ER-), progesterone receptor (PR+/PR-), and HER2 (HER2+/HER2-). Analyses were conducted separately in pre- and postmenopausal women. RESULTS: Positive associations between prior breast biopsy and risk of invasive breast cancer as well as all subtypes were partially mediated by percent MD in pre- and postmenopausal women (percent mediated = 11-27%, p ≤ 0.02). In postmenopausal women, nulliparity and hormone therapy use were positively associated with invasive, ER+ , PR+ , and HER2- breast cancer; percent MD partially mediated these associations (percent mediated ≥ 31%, p ≤ 0.02). Further, among postmenopausal women, percent MD partially mediated the positive association between later age at first birth and invasive as well as ER+ breast cancer (percent mediated = 16%, p ≤ 0.05). CONCLUSION: Percent MD partially mediated the associations between breast biopsy, nulliparity, age at first birth, and hormone therapy with risk of breast cancer, particularly among postmenopausal women, suggesting that these risk factors at least partially influence breast cancer risk through changes in breast tissue composition.

Urinary Biomarkers of Kidney Tubular Damage and Risk of Cardiovascular Disease and Mortality in Elders.

RATIONALE & OBJECTIVE: Novel urinary biomarkers have enabled earlier detection of kidney tubular damage, but their prognostic value for adverse cardiovascular outcomes is uncertain. We hypothesized that tubular damage, measured by urine α1-microglobulin (A1M), amino-terminal propeptide of type III procollagen (PIIINP), and neutrophil gelatinase-associated lipocalin (NGAL), would be associated with higher risks for cardiovascular events and mortality among elders. STUDY DESIGN: Case-cohort study. SETTING & PARTICIPANTS: This study included a randomly selected subcohort (n=502), cardiovascular disease (CVD) cases (n=245), and heart failure cases (n=220) from the Health, Aging, and Body Composition (Health ABC) Study. PREDICTORS: Baseline urine A1M, PIIINP, and NGAL concentrations. OUTCOMES: Incident CVD, heart failure, and all-cause mortality. ANALYTICAL APPROACH: Cox proportional hazards models were used to evaluate biomarker associations with each outcome. RESULTS: At baseline, mean age was 74 years and estimated glomerular filtration rate was 73mL/min/1.73m2. After adjustment for demographics, estimated glomerular filtration rate, albumin-creatinine ratio, and other cardiovascular risk factors, each doubling in biomarker concentration was associated with the following adjusted HRs for CVD: A1M, 1.51 (95% CI, 1.16-1.96); PIIINP, 1.21 (95% CI, 1.00-1.46); and NGAL, 1.12 (95% CI, 1.05-1.20). There were 248 deaths in the subcohort during a median follow-up of 12.4 years. Adjusted associations of each biomarker (HR per doubling) with all-cause mortality were: A1M, 1.29 (95% CI, 1.10-1.51); PIIINP, 1.05 (95%, 0.94-1.18); and NGAL, 1.07 (95% CI, 1.02-1.12). Biomarker concentrations did not have statistically significant associations with heart failure after multivariable adjustment. LIMITATIONS: Urine biomarkers were measured at a single time point; no validation cohort available. CONCLUSIONS: Kidney tubular damage is an independent risk factor for CVD and death among elders. Future studies should investigate mechanisms by which kidney tubular damage may adversely affect cardiovascular risk.

Association of serum albumin levels with kidney function decline and incident chronic kidney disease in elders.

Background: Previous studies in HIV-infected individuals have demonstrated serum albumin to be strongly associated with kidney function decline, independent of urine albumin and inflammatory markers. Lower serum albumin concentrations may be an under-appreciated risk factor for kidney function decline in elders. Methods: We performed a cohort analysis in the Health Aging and Body Composition Study, a cohort of well-functioning, bi-racial, community-dwelling elders between the age of 70 and 79 years. We examined the associations of serum albumin concentration with longitudinal kidney function decline by estimated glomerular filtration rate (eGFR). Outcomes included linear eGFR decline, rapid kidney function decline defined as >30% decrease in eGFR, defined as a final eGFR <60 mL/min/1.73 m2 in those with an eGFR >60 mL/min/1.73 m2 at baseline. Cystatin C-based eGFR was calculated at baseline, Year 3 and Year 10. Results: Mean age was 74 years, and mean eGFR was 73 mL/min/1.73 m2 at baseline. The mean rate of eGFR change was 1.81 mL/min/1.73 m2 per year. After multivariate adjustment, lower serum albumin concentrations were strongly and independently associated with kidney function decline (-0.11 mL/min/1.73 m2 per year for each standard deviation decrease serum albumin; -0.01 to - 0.20) with no attenuation after adjustment for urine albumin and inflammatory markers (-0.12, -0.03 to - 0.22). When divided into quartiles, serum albumin levels ≤3.80 g/dL were associated with increased odds of rapid kidney function decline (odds ratio 1.59; 1.12-2.26) and increased risk of incident chronic kidney disease (incident rate ratio 1.29; 1.03-1.62) relative to levels >4.21g/dL. Urine albumin to creatinine ratio (ACR) was also significantly and independently associated with kidney function decline (-0.08 mL/min/1.73 m2 per year for urine ACR >30 mg/g; -0.82 to - 0.13). Conclusions: Lower serum albumin levels are strongly and independently associated with kidney function decline in elders, independent of clinical risk factors, urine albumin and measured inflammatory markers.

Mitochondrial DNA m.13514G>A heteroplasmy is associated with depressive symptoms in the elderly.

OBJECTIVES: Mitochondrial DNA (mtDNA) heteroplasmy is a mixture of normal and mutated mtDNA molecules in a cell. High levels of heteroplasmy at several mtDNA sites in complex I lead to inherited neurological neurologic diseases and brain magnetic resonance imaging (MRI) abnormalities. Here, we test the hypothesis that mtDNA heteroplasmy at these complex I sites is associated with depressive symptoms in the elderly. METHODS: We examined platelet mtDNA heteroplasmy for associations with depressive symptoms among 137 participants over age 70 from the community-based Health, Aging and Body Composition Study. Depressive symptoms were assessed using the 10-point version of the Center for Epidemiologic Studies Depression Scale (CES-D 10). Complete mtDNA sequencing was performed and heteroplasmy derived for 5 mtDNA sites associated with neurologic mitochondrial diseases and tested for associations with depressive symptoms. RESULTS: Of 5 candidate complex I mtDNA mutations examined for effects on depressive symptoms, increased heteroplasmy at m.13514A>G, ND5, was significantly associated with higher CES-D score (P = .01). A statistically significant interaction between m.13514A > G heteroplasmy and sex was detected (P = .04); in sex-stratified analyses, the impact of m.13514A>G heteroplasmy was stronger in male (P = .003) than in female (P = .98) participants. Men in highest tertile of mtDNA heteroplasmy exhibited significantly higher (P = .0001) mean ± SE CES-D 10 scores, 5.37 ± 0.58, when compared with those in the middle, 2.13 ± 0.52, and lowest tertiles, 2.47 ± 0.58. No associations between the 4 other candidate sites and depressive symptoms were observed. CONCLUSIONS: Increased mtDNA heteroplasmy at m.13514A>G is associated with depressive symptoms in older men. Heteroplasmy may represent a novel biological risk factor for depression.

A genome-wide interaction analysis of tricyclic/tetracyclic antidepressants and RR and QT intervals: a pharmacogenomics study from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium.

BACKGROUND: Increased heart rate and a prolonged QT interval are important risk factors for cardiovascular morbidity and mortality, and can be influenced by the use of various medications, including tricyclic/tetracyclic antidepressants (TCAs). We aim to identify genetic loci that modify the association between TCA use and RR and QT intervals. METHODS AND RESULTS: We conducted race/ethnic-specific genome-wide interaction analyses (with HapMap phase II imputed reference panel imputation) of TCAs and resting RR and QT intervals in cohorts of European (n=45 706; n=1417 TCA users), African (n=10 235; n=296 TCA users) and Hispanic/Latino (n=13 808; n=147 TCA users) ancestry, adjusted for clinical covariates. Among the populations of European ancestry, two genome-wide significant loci were identified for RR interval: rs6737205 in BRE (ß=56.3, pinteraction=3.9e-9) and rs9830388 in UBE2E2 (ß=25.2, pinteraction=1.7e-8). In Hispanic/Latino cohorts, rs2291477 in TGFBR3 significantly modified the association between TCAs and QT intervals (ß=9.3, pinteraction=2.55e-8). In the meta-analyses of the other ethnicities, these loci either were excluded from the meta-analyses (as part of quality control), or their effects did not reach the level of nominal statistical significance (pinteraction>0.05). No new variants were identified in these ethnicities. No additional loci were identified after inverse-variance-weighted meta-analysis of the three ancestries. CONCLUSIONS: Among Europeans, TCA interactions with variants in BRE and UBE2E2 were identified in relation to RR intervals. Among Hispanic/Latinos, variants in TGFBR3 modified the relation between TCAs and QT intervals. Future studies are required to confirm our results.

Combining quantitative and qualitative breast density measures to assess breast cancer risk.

BACKGROUND: Accurately identifying women with dense breasts (Breast Imaging Reporting and Data System [BI-RADS] heterogeneously or extremely dense) who are at high breast cancer risk will facilitate discussions of supplemental imaging and primary prevention. We examined the independent contribution of dense breast volume and BI-RADS breast density to predict invasive breast cancer and whether dense breast volume combined with Breast Cancer Surveillance Consortium (BCSC) risk model factors (age, race/ethnicity, family history of breast cancer, history of breast biopsy, and BI-RADS breast density) improves identifying women with dense breasts at high breast cancer risk. METHODS: We conducted a case-control study of 1720 women with invasive cancer and 3686 control subjects. We calculated ORs and 95% CIs for the effect of BI-RADS breast density and Volpara™ automated dense breast volume on invasive cancer risk, adjusting for other BCSC risk model factors plus body mass index (BMI), and we compared C-statistics between models. We calculated BCSC 5-year breast cancer risk, incorporating the adjusted ORs associated with dense breast volume. RESULTS: Compared with women with BI-RADS scattered fibroglandular densities and second-quartile dense breast volume, women with BI-RADS extremely dense breasts and third- or fourth-quartile dense breast volume (75% of women with extremely dense breasts) had high breast cancer risk (OR 2.87, 95% CI 1.84-4.47, and OR 2.56, 95% CI 1.87-3.52, respectively), whereas women with extremely dense breasts and first- or second-quartile dense breast volume were not at significantly increased breast cancer risk (OR 1.53, 95% CI 0.75-3.09, and OR 1.50, 95% CI 0.82-2.73, respectively). Adding continuous dense breast volume to a model with BCSC risk model factors and BMI increased discriminatory accuracy compared with a model with only BCSC risk model factors (C-statistic 0.639, 95% CI 0.623-0.654, vs. C-statistic 0.614, 95% CI 0.598-0.630, respectively; P < 0.001). Women with dense breasts and fourth-quartile dense breast volume had a BCSC 5-year risk of 2.5%, whereas women with dense breasts and first-quartile dense breast volume had a 5-year risk ≤ 1.8%. CONCLUSIONS: Risk models with automated dense breast volume combined with BI-RADS breast density may better identify women with dense breasts at high breast cancer risk than risk models with either measure alone.