Luigi Ferrucci

National Institute on Aging, Baltimore, Maryland, United States

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Publications (977)6458.99 Total impact

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    ABSTRACT: Background: poor cognitive and motor performance predicts neurological dysfunction. Variable performance may be a subclinical indicator of emerging neurological problems. Objective: examine the cross-sectional association between a clinically accessible measure of variable walking and executive function. Methods: older adults aged 60 or older from the Baltimore Longitudinal Study of Aging (n = 811) with data on the 400-m walk test and cognition. Based on ten 40-m laps, we calculated mean lap time (MLT) and variation in time across ten 40-m laps (lap time variation, LTV). Executive function tests assessed attention and short-term memory (digit span forward and backward), psychomotor speed [Trail Making Test (TMT) part A] and multicomponent tasks requiring cognitive flexibility [TMT part B, part B-A (Delta TMT) and digit symbol substitution test (DSST)]. Multivariate linear regression analysis examined the cross-sectional association between LTV and executive function, adjusted for MLT, age, sex and education, as well as the LTV × MLT interaction. Results: the LTV was univariately associated with all executive function tests except digit span (P < 0.001); after adjustment, the association with TMT part A remained (standardised β = 0.142, P = 0.002). There was an interaction between MLT and LTV; among fast walkers, greater LTV was associated with a greater Delta TMT (β for LTV × MLT = −1.121, P = 0.016) after adjustment. Conclusion: at any walking speed, greater LTV is associated with psychomotor slowing. Among persons with faster walking speed, variation is associated with worse performance on a complex measure of cognitive flexibility. A simple measure of variability in walking time is independently associated with psychomotor slowing.
    Age and Ageing 06/2015; DOI:10.1093/ageing/afv076 · 3.11 Impact Factor
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    ABSTRACT: Chronically elevated circulating inflammatory markers are common in older persons but mechanisms are unclear. Many blood transcripts (>800 genes) are associated with interleukin-6 protein levels (IL6) independent of age. We aimed to identify gene transcripts statistically mediating, as drivers or responders, the increasing levels of IL6 protein in blood at older ages. Blood derived in-vivo RNA from the Framingham Heart Study (FHS, n=2422, ages 40-92 yrs) and InCHIANTI study (n=694, ages 30-104 yrs), with Affymetrix and Illumina expression arrays respectively (>17,000 genes tested), were tested for statistical mediation of the age-IL6 association using resampling techniques, adjusted for confounders and multiple testing. In FHS, IL6 expression was not associated with IL6 protein levels in blood. 102 genes (0.6% of 17,324 expressed) statistically mediated the age-IL6 association of which 25 replicated in InCHIANTI (including 5 of the 10 largest effect genes). The largest effect gene (SLC4A10, coding for NCBE, a sodium bicarbonate transporter) mediated 19% (adjusted CI 8.9 to 34.1%) and replicated by PCR in InCHIANTI (n=194, 35.6% mediated, p=0.01). Other replicated mediators included PRF1 (perforin, a cytolytic protein in cytotoxic T lymphocytes and NK cells) and IL1B (Interleukin 1 beta): few other cytokines were significant mediators. This transcriptome-wide study on human blood identified a small distinct set of genes that statistically mediate the age-IL6 association. Findings are robust across two cohorts and different expression technologies. Raised IL6 levels may not derive from circulating white cells in age related inflammation. Copyright © 2015. Published by Elsevier Inc.
    Experimental gerontology 06/2015; DOI:10.1016/j.exger.2015.05.012 · 3.53 Impact Factor
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    ISMRM 2015; 06/2015
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    ABSTRACT: Hip fracture is an important problem for older adults with significant functional consequences. After hip fracture, reduced muscle loading can result in muscle atrophy. We compared thigh muscle characteristics in the fractured leg with those in the nonfractured leg in participants from the Baltimore Hip Studies 7th cohort using computed tomography (CT) scan imaging. At 2 months postfracture, a single 10-mm axial CT scan was obtained at the midthigh level in 47 participants (26 men and 21 women) with a mean age of 80.4 years (range 65-96), and thigh muscle cross-sectional area (CSA), CSA of intermuscular adipose tissue (IMAT), as well as mean radiological attenuation were measured. Total thigh muscle CSA was less on the side of the fracture by 9.2 cm(2) (95% CI: 5.9, 12.4 cm(2)), whereas the CSA of IMAT was greater by 2.8 cm(2) (95% CI: 1.9, 3.8 cm(2)) on the fractured side. Mean muscle attenuation was lower on the side of the fracture by 3.61 HU (95% CI: 2.99, 4.24 HU). The observed asymmetry is consistent with the effect of disuse and inflammation in the affected limb along with training effects in the unaffected limb due to the favoring of this leg with ambulation during the postfracture period. © The Author 2015. Published by Oxford University Press on behalf of the Gerontological Society of America. All rights reserved. For permissions, please email: journals.permissions@oup.com.
    The Journals of Gerontology Series A Biological Sciences and Medical Sciences 06/2015; 70(6):753-6. DOI:10.1093/gerona/glr188 · 4.98 Impact Factor
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    ABSTRACT: Associations between subclinical thyroid dysfunction and fractures are unclear and clinical trials are lacking. To assess the association of subclinical thyroid dysfunction with hip, nonspine, spine, or any fractures. The databases of MEDLINE and EMBASE (inception to March 26, 2015) were searched without language restrictions for prospective cohort studies with thyroid function data and subsequent fractures. Individual participant data were obtained from 13 prospective cohorts in the United States, Europe, Australia, and Japan. Levels of thyroid function were defined as euthyroidism (thyroid-stimulating hormone [TSH], 0.45-4.49 mIU/L), subclinical hyperthyroidism (TSH <0.45 mIU/L), and subclinical hypothyroidism (TSH ≥4.50-19.99 mIU/L) with normal thyroxine concentrations. The primary outcome was hip fracture. Any fractures, nonspine fractures, and clinical spine fractures were secondary outcomes. Among 70 298 participants, 4092 (5.8%) had subclinical hypothyroidism and 2219 (3.2%) had subclinical hyperthyroidism. During 762 401 person-years of follow-up, hip fracture occurred in 2975 participants (4.6%; 12 studies), any fracture in 2528 participants (9.0%; 8 studies), nonspine fracture in 2018 participants (8.4%; 8 studies), and spine fracture in 296 participants (1.3%; 6 studies). In age- and sex-adjusted analyses, the hazard ratio (HR) for subclinical hyperthyroidism vs euthyroidism was 1.36 for hip fracture (95% CI, 1.13-1.64; 146 events in 2082 participants vs 2534 in 56 471); for any fracture, HR was 1.28 (95% CI, 1.06-1.53; 121 events in 888 participants vs 2203 in 25 901); for nonspine fracture, HR was 1.16 (95% CI, 0.95-1.41; 107 events in 946 participants vs 1745 in 21 722); and for spine fracture, HR was 1.51 (95% CI, 0.93-2.45; 17 events in 732 participants vs 255 in 20 328). Lower TSH was associated with higher fracture rates: for TSH of less than 0.10 mIU/L, HR was 1.61 for hip fracture (95% CI, 1.21-2.15; 47 events in 510 participants); for any fracture, HR was 1.98 (95% CI, 1.41-2.78; 44 events in 212 participants); for nonspine fracture, HR was 1.61 (95% CI, 0.96-2.71; 32 events in 185 participants); and for spine fracture, HR was 3.57 (95% CI, 1.88-6.78; 8 events in 162 participants). Risks were similar after adjustment for other fracture risk factors. Endogenous subclinical hyperthyroidism (excluding thyroid medication users) was associated with HRs of 1.52 (95% CI, 1.19-1.93) for hip fracture, 1.42 (95% CI, 1.16-1.74) for any fracture, and 1.74 (95% CI, 1.01-2.99) for spine fracture. No association was found between subclinical hypothyroidism and fracture risk. Subclinical hyperthyroidism was associated with an increased risk of hip and other fractures, particularly among those with TSH levels of less than 0.10 mIU/L and those with endogenous subclinical hyperthyroidism. Further study is needed to determine whether treating subclinical hyperthyroidism can prevent fractures.
    JAMA The Journal of the American Medical Association 05/2015; 313(20):2055-2065. DOI:10.1001/jama.2015.5161 · 30.39 Impact Factor
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    ABSTRACT: Neuroticism is a pervasive risk factor for psychiatric conditions. It genetically overlaps with major depressive disorder (MDD) and is therefore an important phenotype for psychiatric genetics. The Genetics of Personality Consortium has created a resource for genome-wide association analyses of personality traits in more than 63 000 participants (including MDD cases). To identify genetic variants associated with neuroticism by performing a meta-analysis of genome-wide association results based on 1000 Genomes imputation; to evaluate whether common genetic variants as assessed by single-nucleotide polymorphisms (SNPs) explain variation in neuroticism by estimating SNP-based heritability; and to examine whether SNPs that predict neuroticism also predict MDD. Genome-wide association meta-analysis of 30 cohorts with genome-wide genotype, personality, and MDD data from the Genetics of Personality Consortium. The study included 63 661 participants from 29 discovery cohorts and 9786 participants from a replication cohort. Participants came from Europe, the United States, or Australia. Analyses were conducted between 2012 and 2014. Neuroticism scores harmonized across all 29 discovery cohorts by item response theory analysis, and clinical MDD case-control status in 2 of the cohorts. A genome-wide significant SNP was found on 3p14 in MAGI1 (rs35855737; P = 9.26 × 10-9 in the discovery meta-analysis). This association was not replicated (P = .32), but the SNP was still genome-wide significant in the meta-analysis of all 30 cohorts (P = 2.38 × 10-8). Common genetic variants explain 15% of the variance in neuroticism. Polygenic scores based on the meta-analysis of neuroticism in 27 cohorts significantly predicted neuroticism (1.09 × 10-12 < P < .05) and MDD (4.02 × 10-9 < P < .05) in the 2 other cohorts. This study identifies a novel locus for neuroticism. The variant is located in a known gene that has been associated with bipolar disorder and schizophrenia in previous studies. In addition, the study shows that neuroticism is influenced by many genetic variants of small effect that are either common or tagged by common variants. These genetic variants also influence MDD. Future studies should confirm the role of the MAGI1 locus for neuroticism and further investigate the association of MAGI1 and the polygenic association to a range of other psychiatric disorders that are phenotypically correlated with neuroticism.
    JAMA Psychiatry 05/2015; DOI:10.1001/jamapsychiatry.2015.0554 · 12.01 Impact Factor
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    ABSTRACT: Obesity is highly heritable. Genetic variants showing robust associations with obesity traits have been identified through genome-wide association studies. We investigated whether a composite score representing healthy diet modifies associations of these variants with obesity traits. 32 BMI- and 14 waist-hip ratio (WHR)-associated SNPs were genotyped and genetic risk scores (GRS) calculated in 18 cohorts of European ancestry (n=68,317). Diet score was calculated based on self-reported intakes of whole grains, fish, fruits, vegetables, nuts/seeds (favorable) and red/processed meats, sweets, sugar-sweetened beverages, fried potatoes (unfavorable). Multi-variable adjusted, linear regression within each cohort, followed by inverse variance-weighted fixed-effects meta-analysis was used to characterize: a) associations of each GRS with BMI and BMI-adjusted WHR; b) diet score modification of genetic associations with BMI and BMI-adjusted WHR. Nominally significant interactions (P=0.006-0.04) were observed between the diet score and WHR-GRS (but not BMI-GRS), two WHR loci (GRB14 rs10195252; LYPLAL1 rs4846567), and two BMI loci (LRRN6C rs10968576; MTIF3 rs4771122), for the respective BMI-adjusted WHR or BMI outcomes. Although the magnitudes of these select interactions were small, our data indicated that associations between genetic predisposition and obesity traits were stronger with a healthier diet. Our findings generate interesting hypotheses; however, experimental and functional studies are needed to determine their clinical relevance. © The Author 2015. Published by Oxford University Press.
    Human Molecular Genetics 05/2015; DOI:10.1093/hmg/ddv186 · 6.68 Impact Factor
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    ABSTRACT: Mitochondrial dysfunction has long been considered a major contributor to aging and age-related diseases. Harman's Mitochondrial Free Radical Theory of Aging postulated that somatic mitochondrial DNA mutations that accumulate over the life span cause excessive production of reactive oxygen species that damage macromolecules and impair cell and tissue function. Indeed, studies have shown that maximal oxidative capacity declines with age while reactive oxygen species production increases. Harman's hypothesis has been seriously challenged by recent studies showing that reactive oxygen species evoke metabolic health and longevity, perhaps through hormetic mechanisms that include autophagy. The purpose of this review is to scan the ever-growing literature on mitochondria from the perspective of aging research and try to identify priority questions that should be addressed in future research. A systematic search of peer-reviewed studies was performed using PubMed. Search terms included (i) mitochondria or mitochondrial; (ii) aging, ageing, older adults or elderly; and (iii) reactive oxygen species, mitochondria dynamics, mitochondrial proteostasis, cytosol, mitochondrial-associated membranes, redox homeostasis, electron transport chain, electron transport chain efficiency, epigenetic regulation, DNA heteroplasmy. The importance of mitochondrial biology as a trait d'union between the basic biology of aging and the pathogenesis of age-related diseases is stronger than ever, although the emphasis has moved from reactive oxygen species production to other aspects of mitochondrial physiology, including mitochondrial biogenesis and turnover, energy sensing, apoptosis, senescence, and calcium dynamics. Mitochondria could play a key role in the pathophysiology of aging or in the earlier stages of some events that lead to the aging phenotype. Therefore, mitochondria will increasingly be targeted to prevent and treat chronic diseases and to promote healthy aging. Published by Oxford University Press on behalf of the Gerontological Society of America 2015.
    The Journals of Gerontology Series A Biological Sciences and Medical Sciences 05/2015; DOI:10.1093/gerona/glv070 · 4.98 Impact Factor
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    ABSTRACT: Aging is characterized by rising susceptibility to development of multiple chronic diseases and, therefore, represents the major risk factor for multimorbidity. From a gerontological perspective, the progressive accumulation of multiple diseases, which significantly accelerates at older ages, is a milestone for progressive loss of resilience and age-related multisystem homeostatic dysregulation. Because it is most likely that the same mechanisms that drive aging also drive multiple age-related chronic diseases, addressing those mechanisms may reduce the development of multimorbidity. According to this vision, studying multimorbidity may help to understand the biology of aging and, at the same time, understanding the underpinnings of aging may help to develop strategies to prevent or delay the burden of multimorbidity. As a consequence, we believe that it is time to build connections and dialogue between the clinical experience of general practitioners and geriatricians and the scientists who study aging, so as to stimulate innovative research projects to improve the management and the treatment of older patients with multiple morbidities. Copyright © 2015 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.
    Journal of the American Medical Directors Association 05/2015; DOI:10.1016/j.jamda.2015.03.013 · 4.78 Impact Factor
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    ABSTRACT: Aging is characterized by rising susceptibility to development of multiple chronic diseases and, therefore, represents the major risk factor for multimorbidity. From a gerontological perspective, the progressive accumulation of multiple diseases, which significantly accelerates at older ages, is a milestone for progressive loss of resilience and age-related multisystem homeostatic dysregulation. Because it is most likely that the same mechanisms that drive aging also drive multiple age-related chronic diseases, addressing those mechanisms may reduce the development of multimorbidity. According to this vision, studying multimorbidity may help to understand the biology of aging and, at the same time, understanding the underpinnings of aging may help to develop strategies to prevent or delay the burden of multimorbidity. As a consequence, we believe that it is time to build connections and dialogue between the clinical experience of general practitioners and geriatricians and the scientists who study aging, so as to stimulate innovative research projects to improve the management and the treatment of older patients with multiple morbidities.
    Journal of the American Medical Directors Association 05/2015; · 4.78 Impact Factor
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    ABSTRACT: Persons with diabetes have accelerated muscle loss. The association of fasting and postchallenge glucose levels per se to grip strength, a clinical marker of poor physical function, and potential sex differences in this relationship has not been previously described. Longitudinal cohort. USA. Participants were community-dwelling older adults (mean age 71.3 years) without self-reported diabetes and/or use of diabetes medication with glucose measured at baseline (1992-1996). Fasting plasma glucose (FPG) was measured in 1019 women and 636 men. Two-hour glucose (2HG) levels after a 75 g oral glucose tolerance test were also available (women, n=870; men, n=559). Dominant hand grip strength was assessed using a hand-held dynamometer at 3.0±1.6 visits over a median 7.0 years. Mixed linear models examined the association of baseline glucose levels with grip strength, accounting for repeated visits, and adjusting for covariates. Sex-specific FPG quartiles were associated with unadjusted differences in grip strength among women (p=0.03) but not men (p=0.50). However, in men, adjusting for age, education, height, weight, peripheral neuropathy, physical activity, and comorbidities, each SD (SD=17 mg/dL) higher FPG was associated with persistently lower grip strength (-0.44±0.22 kg, p=0.049); 2HG (SD=50 mg/dL) was unrelated to grip strength (-0.39±0.25 kg, p=0.13). In women, neither FPG (SD=16 mg/dL) nor 2HG (SD=45 mg/dL) was associated with grip strength (0.02±0.12 kg, p=0.90; and -0.20±0.14 kg, p=0.14; respectively) after adjustment. The rate of change in grip strength did not differ across FPG or 2HG quartiles in either sex. In age-adjusted analyses, elevated fasting glucose levels are associated with persistently lower grip strength in older men, but not women. Future studies are needed to elucidate reasons for these sex differences and may provide further insight into accelerated loss of muscle function as a complication of diabetes in older adults.
    05/2015; 3(1):e000086. DOI:10.1136/bmjdrc-2015-000086
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    ABSTRACT: The functional consequences of trait associated SNPs are often investigated using expression quantitative trait locus (eQTL) mapping. While trait-associated variants may operate in a cell-type specific manner, eQTL datasets for such cell-types may not always be available. We performed a genome-environment interaction (GxE) meta-analysis on data from 5,683 samples to infer the cell type specificity of whole blood cis-eQTLs. We demonstrate that this method is able to predict neutrophil and lymphocyte specific cis-eQTLs and replicate these predictions in independent cell-type specific datasets. Finally, we show that SNPs associated with Crohn's disease preferentially affect gene expression within neutrophils, including the archetypal NOD2 locus.
    PLoS Genetics 05/2015; 11(5):e1005223. DOI:10.1371/journal.pgen.1005223 · 8.17 Impact Factor
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    ABSTRACT: Few medical therapies improve lower extremity functioning in people with lower extremity peripheral artery disease (PAD). Among people with PAD, we studied whether a group-mediated cognitive behavioral intervention promoting home-based unsupervised exercise prevented mobility loss and improved functional performance compared to control. One hundred ninety-four PAD participants were randomized. During months 1 to 6, the intervention group met weekly with other PAD participants and a facilitator. Group support and self-regulatory skills were used to help participants adhere to walking exercise. Ninety-percent of exercise was conducted at or near home. The control group attended weekly lectures. During months 6 to 12, each group received telephone contact only. Primary outcomes have been reported. Here we compare changes in exploratory outcomes of mobility loss (the inability to climb a flight of stairs or walk one-quarter mile without assistance), walking velocity, and the Short Physical Performance Battery. Compared to controls, fewer participants randomized to the intervention experienced mobility loss at 6-month follow-up: 6.3% versus 26.5%, P=0.002, odds ratio=0.19 (95% CI=0.06 to 0.58) and at 12-month follow-up: 5.2% versus 18.5%, P=0.029, odds ratio=0.24 (95% CI=0.06 to 0.97). The intervention improved fast-paced 4-m walking velocity at 6-month follow-up (P=0.005) and the Short Physical Performance Battery at 12-month follow-up (P=0.027), compared to controls. In exploratory analyses, a group-mediated cognitive behavioral intervention promoting unsupervised walking exercise prevented mobility loss and improved functioning at 6- and 12-month follow-up in PAD patients. URL: http://clinicaltrials.gov. Unique identifier: NCT00693940. © 2015 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.
    Journal of the American Heart Association 04/2015; 4(5). DOI:10.1161/JAHA.114.001659 · 2.88 Impact Factor
  • Archives of Gerontology and Geriatrics 04/2015; 61(1). DOI:10.1016/j.archger.2015.04.004 · 1.53 Impact Factor
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    ABSTRACT: Some experts suggest that serum thyrotropin levels in the upper part of the current reference range should be considered abnormal, an approach that would reclassify many individuals as having mild hypothyroidism. Health hazards associated with such thyrotropin levels are poorly documented, but conflicting evidence suggests that thyrotropin levels in the upper part of the reference range may be associated with an increased risk of coronary heart disease (CHD). To assess the association between differences in thyroid function within the reference range and CHD risk. Individual participant data analysis of 14 cohorts with baseline examinations between July 1972 and April 2002 and with median follow-up ranging from 3.3 to 20.0 years. Participants included 55 412 individuals with serum thyrotropin levels of 0.45 to 4.49 mIU/L and no previously known thyroid or cardiovascular disease at baseline. Thyroid function as expressed by serum thyrotropin levels at baseline. Hazard ratios (HRs) of CHD mortality and CHD events according to thyrotropin levels after adjustment for age, sex, and smoking status. Among 55 412 individuals, 1813 people (3.3%) died of CHD during 643 183 person-years of follow-up. In 10 cohorts with information on both nonfatal and fatal CHD events, 4666 of 48 875 individuals (9.5%) experienced a first-time CHD event during 533 408 person-years of follow-up. For each 1-mIU/L higher thyrotropin level, the HR was 0.97 (95% CI, 0.90-1.04) for CHD mortality and 1.00 (95% CI, 0.97-1.03) for a first-time CHD event. Similarly, in analyses by categories of thyrotropin, the HRs of CHD mortality (0.94 [95% CI, 0.74-1.20]) and CHD events (0.97 [95% CI, 0.83-1.13]) were similar among participants with the highest (3.50-4.49 mIU/L) compared with the lowest (0.45-1.49 mIU/L) thyrotropin levels. Subgroup analyses by sex and age group yielded similar results. Thyrotropin levels within the reference range are not associated with risk of CHD events or CHD mortality. This finding suggests that differences in thyroid function within the population reference range do not influence the risk of CHD. Increased CHD risk does not appear to be a reason for lowering the upper thyrotropin reference limit.
    JAMA Internal Medicine 04/2015; 175(6). DOI:10.1001/jamainternmed.2015.0930 · 13.25 Impact Factor
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    ABSTRACT: Abstract Background. Higher cardiorespiratory fitness (CRF) is cross-sectionally associated with more conserved brain volume in older age, but longitudinal studies are rare. This study examined whether higher midlife CRF was prospectively associated with slower atrophy, which in turn was associated with higher late-life CRF. Methods. Brain volume by magnetic resonance imaging was determined annually from 1994 to 2003 in 146 participants (M baseline age = 69.6 years). Peak oxygen uptake on a treadmill yielded estimated midlife CRF in 138 and late-life CRF in 73 participants. Results. Higher midlife CRF was associated with greater middle temporal gyrus, perirhinal cortex, and temporal and parietal white matter, but was not associated with atrophy progression. Slower atrophy in middle frontal and angular gyri was associated with higher late-life CRF, independent of CRF at baseline magnetic resonance imaging. Conclusions. Higher midlife CRF may play a role in preserving middle and medial temporal volumes in late adulthood. Slower atrophy in middle frontal and angular gyri may predict late-life CRF.
    The Journals of Gerontology Series A Biological Sciences and Medical Sciences 04/2015; DOI:10.1093/gerona/glv041 · 4.98 Impact Factor
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    PLoS ONE 04/2015; 10(4):e0122541. DOI:10.1371/journal.pone.0122541 · 3.53 Impact Factor
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    ABSTRACT: To determine the risk of stroke associated with subclinical hypothyroidism. Data Sources and Study Selection Published prospective cohort studies were identified through a systematic search through November 2013 without restrictions in several databases. Unpublished studies were identified through the Thyroid Studies Collaboration. We collected individual participant data (IPD) on thyroid function and stroke outcome. Euthyroidism was defined as thyrotropin (TSH) levels 0.45-4.49 mIU/L, subclinical hypothyroidism as TSH levels 4.5-19.9 mIU/L with normal thyroxin levels. Data Extraction and Synthesis We collected IPD on 47,573 adults (3451 subclinical hypothyroidism) from 17 cohorts, followed-up 1972-2014 (489,192 person-years). Age- and sex-adjusted pooled hazard ratio (HR) for participants with subclinical hypothyroidism compared to euthyroidism was 1.05 (95% CI, 0.91-1.21) for stroke events (combined fatal and non-fatal stroke) and 1.07 (95% CI, 0.80-1.42) for fatal stroke. Stratified by age, the HR for stroke events was 3.32 (95% CI, 1.25-8.80) for individuals aged 18-49 years. There was an increased risk of fatal stroke in the age groups 18-49 and 50-64 years with a HR of 4.22 (95% CI, 1.08-16.55) and 2.86 (95% CI, 1.31-6.26), respectively (p trend 0.04). We found no increased risk for those 65-79 years (HR 1.00, 95% CI, 0.86-1.18) or ≥80 years (HR 1.31, 95% CI, 0.79-2.18). There was a pattern of increased risk of fatal stroke with higher TSH concentrations. Although no overall effect of subclinical hypothyroidism on stroke could be demonstrated, an increased risk in subjects younger than 65 years and those with higher TSH concentrations was observed.
    The Journal of Clinical Endocrinology and Metabolism 04/2015; DOI:10.1210/jc.2015-1438 · 6.31 Impact Factor

Publication Stats

40k Citations
6,458.99 Total Impact Points

Institutions

  • 2000–2015
    • National Institute on Aging
      • • Clinical Research Branch (CRB)
      • • Laboratory of Epidemiology, Demography and Biometry (LEDB)
      Baltimore, Maryland, United States
  • 2014
    • Universiteit Twente
      • Group of Behavioural Sciences
      Enschede, Overijssel, Netherlands
    • California Pacific Medical Center Research Institute
      • Research Institute
      San Francisco, California, United States
  • 2003–2014
    • National Institutes of Health
      • • Clinical Research Branch (CRB)
      • • Laboratory of Immunology
      • • Laboratory of Epidemiology, Demography, and Biometry (LEDB)
      베서스다, Maryland, United States
    • University of Iowa
      Iowa City, Iowa, United States
    • Texas A&M University - Galveston
      Galveston, Texas, United States
    • Catholic University of the Sacred Heart
      • School of Geriatrics
      Milano, Lombardy, Italy
    • AMC Health
      New York City, New York, United States
    • INRIM Istituto Nazionale di Ricerca Metrologica
      Torino, Piedmont, Italy
  • 2013
    • Universita degli studi di Ferrara
      • Section of Internal Medicine, Gerontology and Geriatrics
      Ferrare, Emilia-Romagna, Italy
    • Northern Inyo Hospital
      BIH, California, United States
    • Harvard Medical School
      • Department of Medicine
      Boston, Massachusetts, United States
    • Università degli Studi di Salerno
      Fisciano, Campania, Italy
    • Florida State University
      • Department of Geriatrics
      Tallahassee, Florida, United States
  • 2010–2013
    • Queen's University
      • School of Rehabilitation Therapy
      Kingston, Ontario, Canada
    • Northwestern University
      • Feinberg School of Medicine
      Evanston, IL, United States
    • University Hospital of Parma
      Parma, Emilia-Romagna, Italy
    • Kent State University
      • Department of Psychology
      Kent, OH, United States
    • University of California, San Francisco
      • Division of Hospital Medicine
      San Francisco, CA, United States
    • University of Lausanne
      • Faculté de biologie et de médecine (FBM)
      Lausanne, VD, Switzerland
  • 2004–2013
    • Università degli studi di Parma
      • Department of Clinical and Experimental Medicine
      Parma, Emilia-Romagna, Italy
    • Università degli Studi di Sassari
      Sassari, Sardinia, Italy
  • 2012
    • University-Hospital of Padova
      Padua, Veneto, Italy
    • William Penn University
      Filadelfia, Pennsylvania, United States
    • University of Missouri - St. Louis
      Saint Louis, Michigan, United States
    • National Institute of Aerospace
      Hampton, Virginia, United States
    • McGill University
      • Department of Epidemiology, Biostatistics and Occupational Health
      Montréal, Quebec, Canada
  • 2009–2012
    • University of Pittsburgh
      • Division of Geriatric Medicine
      Pittsburgh, Pennsylvania, United States
    • National Eye Institute
      Maryland, United States
    • MedStar Health Research Institute
      Maryland, United States
    • Case Western Reserve University
      • School of Medicine
      Cleveland, Ohio, United States
    • University Hospital Regensburg
      Ratisbon, Bavaria, Germany
  • 2004–2012
    • Johns Hopkins University
      • • Department of Medicine
      • • Welch Center for Prevention, Epidemiology, and Clinical Research
      • • Division of Geriatric Medicine and Gerontology
      Baltimore, Maryland, United States
  • 2003–2012
    • University of Maryland, Baltimore
      • • Department of Epidemiology and Public Health
      • • Department of Medicine
      Baltimore, Maryland, United States
  • 2002–2012
    • Johns Hopkins Medicine
      • • Department of Otolaryngology - Head and Neck Surgery
      • • Department of Urology
      Baltimore, Maryland, United States
    • IRCCS Centro San Giovanni di Dio, Fatebenefratelli, Brescia
      Brescia, Lombardy, Italy
  • 2011
    • National Institute for Health and Welfare, Finland
      • Department of Health, Functional Capacity and Welfare
      Helsinki, Province of Southern Finland, Finland
    • Università degli Studi di Brescia
      • Department of Clinical and Experimental Sciences
      Brescia, Lombardy, Italy
    • Yale University
      New Haven, Connecticut, United States
    • Boston University
      • Department of Biostatistics
      Boston, Massachusetts, United States
    • University of Leicester
      • Department of Health Sciences
      Leicester, ENG, United Kingdom
  • 2009–2011
    • University of Exeter
      • • Peninsula College of Medicine and Dentistry
      • • Department of Biosciences
      Exeter, England, United Kingdom
  • 2005–2011
    • University of Naples Federico II
      • Department of Molecular Medicine and Medical Biotechnology
      Napoli, Campania, Italy
    • Johnson & Johnson
      New Brunswick, New Jersey, United States
    • Università Vita-Salute San Raffaele
      Milano, Lombardy, Italy
  • 2009–2010
    • IRCCS Ospedale Casa Sollievo della Sofferenza
      • Department of Medical Sciences
      Giovanni Rotondo, Apulia, Italy
  • 2006–2010
    • Azienda Sanitaria di Firenze
      Florens, Tuscany, Italy
    • Università degli Studi di Palermo
      Palermo, Sicily, Italy
    • Fondazione Don Carlo Gnocchi
      Milano, Lombardy, Italy
    • University of Florida
      • Department of Aging and Geriatric Research
      Gainesville, FL, United States
    • University of Maryland, College Park
      • Department of Kinesiology
      College Park, MD, United States
    • University of Pennsylvania
      • Center for Clinical Epidemiology and Biostatistics
      Philadelphia, Pennsylvania, United States
  • 2005–2009
    • Università degli Studi di Perugia
      • Department of Clinical and Experimental Medicine
      Perugia, Umbria, Italy
    • Second University of Naples
      Caserta, Campania, Italy
  • 2004–2009
    • Johns Hopkins Bloomberg School of Public Health
      • • Department of Biostatistics
      • • Department of Health Policy and Management
      Baltimore, MD, United States
  • 1996–2009
    • INRCA Istituto Nazionale di Ricovero e Cura per Anziani
      • Gerontological Research Department
      Ancona, The Marches, Italy
  • 2008
    • Grays Harbor Community Hospital
      Aberdeen, Washington, United States
    • Boston Medical Center
      Boston, Massachusetts, United States
    • Saint Louis University
      Saint Louis, Michigan, United States
    • Universidade Federal do Rio Grande do Sul
      Pôrto de São Francisco dos Casaes, Rio Grande do Sul, Brazil
  • 2006–2008
    • University of California, San Diego
      • Department of Family and Preventive Medicine
      San Diego, CA, United States
  • 2003–2008
    • Università degli Studi G. d'Annunzio Chieti e Pescara
      Chieta, Abruzzo, Italy
  • 2002–2008
    • University of Washington Seattle
      • Department of Rehabilitation Medicine
      Seattle, Washington, United States
  • 2007
    • VU University Medical Center
      • Department of Psychiatry
      Amsterdamo, North Holland, Netherlands
    • The Peninsula College of Medicine and Dentistry
      Plymouth, England, United Kingdom
    • Duke University Medical Center
      Durham, North Carolina, United States
    • Unità Locale Socio Sanitaria Padova ULSS 16
      Padua, Veneto, Italy
  • 2005–2007
    • Cornell University
      • Department of Nutritional Sciences
      Итак, New York, United States
  • 2000–2004
    • Wake Forest School of Medicine
      • Sticht Center on Aging
      Winston-Salem, NC, United States
  • 2002–2003
    • Italian National Research Council
      Oristany, Sardinia, Italy
  • 1995
    • Azienda Ospedaliera Fatebenefratelli e Oftalmico Milano
      Brescia, Lombardy, Italy
  • 1986–1995
    • University of Florence
      • Dipartimento di Chirurgia e Medicina Traslazionale (DCMT)
      Florens, Tuscany, Italy