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The independent and combined effects of aerobic exercise training (AEX) and weight loss (WL) on blood pressure (BP) and oral glucose tolerance were studied in 97 nondiabetic, sedentary, older men. The men were assigned to either a WL (n = 31), AEX (n = 35), AEX+WL (n = 20) intervention, or to a control (CON) group (n = 11). The AEX regimen consisted of 3 days/week for 9 months, whereas WL consisted of a behavioral modification weight loss program that met weekly for 9 months. Maximal oxygen uptake increased significantly (P < .05) in both the AEX and AEX+WL groups (delta change: 0.45 +/- 0.06 and 0.43 +/- 0.07 L/min, respectively; mean +/- SEM), but did not change in the WL (delta change: 0.00 +/- 0.04 L/min) and CON (-0.05 +/- 0.07 L/min) groups. The AEX+WL and WL groups had comparable reductions in body weight (-8.6 +/- 0.7 and -8.8 +/- 0.7 kg,) and %fat (-5.4 +/- 0.5 and -5.2 +/- 0.6%) that were significantly greater than the CON and AEX groups, in which neither body weight nor %fat changed. The AEX, WL, and AEX+WL groups had significant reductions in both systolic (-6.4 +/- 1.3, -9.2 +/- 1.6, and -9.7 +/- 2.2 mm Hg, respectively) and diastolic (-5.2 +/- 1.0, -6.2 +/- 1.3, and -7.2 +/- 1.5 mm Hg, respectively) BP after their respective interventions compared with the change in systolic (3.2 +/- 3.6 mm Hg) and diastolic (-0.5 +/- 1.9 mm Hg) BP in the CON group. The AEX, WL, and AEX+WL groups also had significant reductions in glucose and insulin responses to an oral glucose tolerance test compared with the CON group. The reduction in the insulin area in the AEX+WL group was significantly greater than in the AEX and WL groups. The results of this study demonstrate that AEX and WL are effective nonpharmacologic therapies to lower BP and alter glucose and insulin responses to an oral glucose challenge. However, combining the two interventions does not result in any further improvement in BP.

Both aging and grafting of whole skeletal muscle are associated with decreased specific force and resistance to fatigue. This study tested the hypothesis that the recovery of mechanical function in nerve-repair skeletal muscle grafts in senescent rats would be impaired compared with recovery in similar grafts in younger animals. Following a 120-day recovery period, the contractile properties of grafted medial gastrocnemius (MGN) muscles from young-mature (6 months), middle-aged (12 months), and senescent (24 months) Fischer 344 rats were measured and compared to age-matched controls. Although there was full recovery of muscle mass, grafting and aging alone both were associated with diminished maximum twitch and tetanic tension, maximum power, and maximum sustained power. In addition, the deleterious effect of grafting on maximum tetanic tension, specific force, and sustained power of MGN muscle was significantly greater in old animals. These findings suggest that aging limits full recovery of the quality of muscle contractions from the nerve-repair grafting procedure, possibly due to an age-related impairment of reinnervation.

Analysis of longitudinal data is one of the most challenging tasks in statistical modeling. In the analysis, it is often necessary to take into account nonlinear response to a set of parameters of interest and correlation between measurements taken from the same individual. In addition, between- and within-subject variation has to be handled properly. An example of addressing these issues is the hierarchical nonlinear model, where parameter estimation can be performed using linearization method. In this paper a new NLMEM SAS/IML macro for hierarchical nonlinear models is proposed. The program uses a portion of the code developed earlier in NLINMIX. NLMEM retains all the benefits of NLINMIX while allowing the systematic part of the model structure to be specified using IML syntax. Consequently, NLMEM allows estimation of models which are not tractable using NLINMIX. In particular, it allows us to address advanced population pharmacokinetics and pharmacodynamics models specified by ordinary differential equations.

In normal female mammals, one of the two X Chromosome (Chr) homologs per cell is silenced coordinately during early embryogenesis. The genes located on the inactivated X homolog are predicted to be influenced by the same underlying repression mechanism. To test the uniformity of cis-acting gene repression, 32 genetically identical F1 female mice were analyzed for differential expression of homologous alleles at three X-linked genes-Otc, Atp7a ( = Mottled), and Hprt. Gene expression was assayed by the single-nucleotide primer extension (SNuPE) method, thereby allowing the three genes to be quantitated from the same RNA sample. Although variable between individual animals, the relative expression of the two alleles (allelic expression ratio) of the genes is significantly correlated within each steady-state RNA pool. When examined by animal age (3 months to 12 months), no statistically significant differences were observed in the mean or variance of allelic expression ratio. Together, the results confirm that X inactivation is coordinately controlled and is stable across the early- to mid-adult life span.

Aging leads to changes in the relative proportions of several functionally distinct T cell subsets, including increases in the proportions of memory cells in the CD4 and CD8 subsets and in the proportion of T cells expressing the multiple-drug resistance pump P-glycoprotein. To see whether individual differences in T cell subset levels predict life span, we measured the levels of five age-sensitive T cell subsets, at 8 and again at 18 months of age, in the peripheral blood of genetically heterogeneous mice bred as the progeny of CB6F1 females and C3D2F1 males. The strongest immunological predictor of life span in univariate regression analyses was the proportion of CD4 memory cells measured at 18 months of age (P=0.003). CD4 memory cell levels remained strongly correlated with life span (P0.0003) in a multiple regression analysis after adjustment for sex. The proportion of CD4 cells expressing P-glycoprotein was also correlated with life span (P0.01), but only in male mice. Weaker relationships were observed between life span and 8-month tests of CD8 memory and CD8 P-glycoprotein levels, for CD4 naive cells at 18 months, and for the change in CD4 naive cells between 8 and 18 months of age; these were, however, near the margin of statistical significance and could reflect chance relationships. The relationship between CD4 memory cell levels and life span was similarly strong regardless of the cause of death in mice whose death was attributable to lymphoma, fibrosarcoma, mammary carcinoma, and other forms of terminal pathology. Additional work is needed to discriminate between two hypotheses: 1) that high levels of CD4 memory cell themselves predispose to disease and early death, particularly from neoplasia; or 2) that accumulation of CD4 memory cells is a biomarker of some underlying process-perhaps accelerated aging-that itself leads to early mortality.

Diabetic kidney disease causes significant morbidity and mortality among people with type 1 diabetes (T1D). Intensive glucose and blood pressure control have thus far failed to adequately curb this problem and therefore a major need for novel treatment approaches exists. Multiple observations link serum uric acid levels to kidney disease development and progression in diabetes and strongly argue that uric acid lowering should be tested as one such novel intervention. A pilot of such a trial, using allopurinol, is currently being conducted by the Preventing Early Renal Function Loss (PERL) Consortium. Although the PERL trial targets T1D individuals at highest risk of kidney function decline, the use of allopurinol as a renoprotective agent may also be relevant to a larger segment of the population with diabetes. As allopurinol is inexpensive and safe, it could be cost-effective even for relatively low-risk patients, pending the completion of appropriate trials at earlier stages.

At present, there are many software procedures available enabling statisticians to fit linear mixed models (LMMs) to continuous dependent variables in clustered or longitudinal data sets. LMMs are flexible tools for analyzing relationships among variables in these types of data sets, in that a variety of covariance structures can be used depending on the subject matter under study. The explicit random effects in LMMs allow analysts to make inferences about the variability between clusters or subjects in larger hypothetical populations, and examine cluster- or subject-level variables that explain portions of this variability. These models can also be used to analyze longitudinal or clustered data sets with data that are missing at random (MAR), and can accommodate time-varying covariates in longitudinal data sets. While the software procedures currently available have many features in common, more specific analytic aspects of fitting LMMs (e.g., crossed random effects, appropriate hypothesis testing for variance components, diagnostics, incorporating sampling weights) may only be available in selected software procedures. With this article, we aim to perform a comprehensive and up-to-date comparison of the current capabilities of software procedures for fitting LMMs, and provide statisticians with a guide for selecting a software procedure appropriate for their analytic goals.

To the Editor—We thank Dr McDonald for his interest in our work and concur that the role of particular ribotypes in the clinical outcome of Clostridium difficile infection (CDI) is complex [1]. Our study identified several factors that predicted severe CDI in unadjusted analysis, including ribotype 027/078 (Table 2 in our article) [2]. We agree that including intermediate white blood cell (WBC) counts in our final model (Table 4 in our article) may have potentially attenuated direct effects of ribotype on outcome. In Table 3 of our article, we show, however, that adjustment for any of the significant predictors rendered ribotype 027/078 effect on CDI severity nonsignificant [2], indicating that WBC count was not required for the conclusions drawn in our study. To directly address the possibility that WBC count was influenced by ribotype-specific host responses requires temporal patient data, including treatment, which we did not collect. To indirectly address this issue, we performed additional analyses for our combined dataset (N = 412 cases with complete data) in the following 4 contexts: We added abnormal WBC count ( 12 000 cells/mL) to the definition of severe CDI. We determined whether ribotype 027/078 predicted an abnormal WBC count. We excluded both WBC count and albumin levels from the analysis, as is appropriate if they are potentially confounded. We again added abnormal WBC to the severe CDI definition and excluded albumin level from the analysis. Ribotype 027/078 was not significant in any of these contexts (adjusted analyses). Although these results do not exclude the possibility raised by McDonald, they do add support to our original conclusion that predictors other than ribotype may be more important in explaining the variability of CDI severity. We did not explore the influence of treatment on outcome, so the influence of ribotype was either not strong enough to overcome these effects or they were relatively minor. Why the incidence and severity of CDI increased in the early 2000s remains unclear. However, epidemic spread of clonal pathogens need not result from advantageous phenotypes (toxin production, sporulation, antibiotic resistance, etc). Such population expansions may result simply by chance, as transmission rates overcome clonal interference. Temporal fluctuations in ribotype prevalence support a “drift” scenario [3]. Such fluctuations suggest that many ribotypes reach a high local prevalence, which would increase transmission and potentiate a high global prevalence. This phenomenon does not necessitate strong selection, although increased antibiotic resistance suggests that strong selective pressure from fluoroquinolones and other antimicrobials has been important [4, 5]. As noted by McDonald, the prevalences of both 027 CDI cases and severe outcome are declining in apparent synchrony. However, both declines have occurred in light of heightened surveillance, improved diagnostics, more effective/aggressive infection control practices and therapies, and the popularization of antimicrobial stewardship. Correlations among these shifting practices, ribotype prevalence, and clinical outcome are understudied and require more data from properly designed studies that recognize the potential role of chance (null hypothesis). As 027 prevalence wanes in Europe [6], it appears that the C. difficile population is changing back to a more even distribution. These are exciting times in C. difficile epidemiology, but the complexity of ribotype-specific influences on disease progression and/or severity remains mottled.

Studies of Clostridium difficile outbreaks suggested that certain ribotypes (eg, 027 and 078) cause more severe disease than other ribotypes. A growing number of studies challenge the validity of this hypothesis.We conducted a cross-sectional study of C. difficile infection (CDI) to test whether ribotype predicted clinical severity when adjusted for the influence of other predictors. Toxigenic C. difficile isolates were cultured from stool samples, screened for genes encoding virulence factors by polymerase chain reaction (PCR) and ribotyped using high-throughput, fluorescent PCR ribotyping. We collected data for 15 covariates (microbiologic, epidemiologic, and laboratory variables) and determined their individual and cumulative influence on the association between C. difficile ribotype and severe disease. We then validated this influence using an independent data set.A total of 34 severe CDI cases were identified among 310 independent cases of disease (11.0%). Eleven covariates, including C. difficile ribotype, were significant predictors of severe CDI in unadjusted analysis. However, the association between ribotypes 027 and 078 and severe CDI was not significant after adjustment for any of the other covariates. After full adjustment, severe cases were significantly predicted only by patients' white blood cell count and albumin level. This result was supported by analysis of a validation data set containing 433 independent CDI cases (45 severe cases; 10.4%).Ribotype is not a significant predictor of severe CDI when adjusted for the influence of any other variables separately or in combination. White blood cell count and albumin level are the most clinically relevant predictors of severe CDI cases.

The SII Project was described in Sect.2.4. In Sect.3.4, an exploratory analysis of the data was presented. The data have a hierarchical structure, with pupils grouped in classes which, in turn, are grouped in schools. Thus, we deal with two levels of grouping in the data or, equivalently, with a three-level data hierarchy. In this chapter, we use LMMs to analyze the change in mathematics achievement-scores for pupils, MATHGAIN. In particular, we use models, which include random intercepts for schools and classes to account for the data hierarchy.

In Chap. 7, we introduced several concepts related to the LM for independent, normally distributed observations with heterogeneous variance. Compared to the classical LM ( Chap. 4), the formulation of the model included a new component, namely, the variance function, which is used to take into account heteroscedasticity of the dependent variable.

The essential assumption for the LMs considered in Part II of the book was that the observations collected during the study were independent of each other. This assumption is restrictive in studies which use sampling designs that lead to correlated data. Such data result, for example, from studies collecting measures over time, i.e., in a longitudinal fashion; in designs which involve clustering or grouping, e.g., cluster-randomization clinical trials; in studies collecting spatially correlated data, etc. Note that, in contrast to Part II, for such designs, the distinction between sampling units (e.g., subjects in a longitudinal study) and analysis units (e.g., time-specific measurements) is important

In Chap. 4, we formulated the classical LM for independent observations. The key assumptions underlying the model are that the observations are independent and normally distributed with a constant, i.e., homogeneous variance, and that the expected value of the observations can be expressed as a linear function of covariates.

In Chap. 13 we summarized the main theoretical concepts underlying the construction of LMMs. Compared to the LMs introduced in Chaps. 4, 7, and 10, LMMs allow taking the hierarchical structure of data into account in the analysis. This is achieved by introducing, in addition to the mean (fixed-effects) structure, a randomeffects structure.

In Chap. 10, we summarized the main concepts underlying the construction of the LM with fixed effects and correlated residual errors for normally distributed, grouped data. An important component of the model is the correlation function, which is used to take into account the correlation between the observations belonging to the same group.

In Chap. 9, we analyzed the ARMD data using a model that assumed independence between repeated measurements of visual acuity for an individual patient. Given the longitudinal study design, in which sampling units, i.e., subjects, are differentfrom the units of analysis, i.e., visual acuity measurements, the assumption of independence typically does not hold. This consideration is confirmed by the results of the exploratory analysis presented in Sect.3.2, which indicate that the assumption is clearly not fulfilled. Thus, in the current chapter, we further modify our analysis to account for the correlation between the repeated measurements. In particular, we use LMs with fixed effects and correlated residual errors, defined in Sect.10.2.

In this chapter, we illustrate the use of the R tools, described in Sects. 5.2–5.5.We apply them to fit an LM with independent, homoscedastic residual errors to the visual acuity measurements from the ARMD dataset. Note that the model is considered for software illustration purposes only. In view of the structure of the data and of the results of the exploratory analysis presented in Sect. 3.2, the assumptions of the independence and homoscedasticity of the visual acuity measurements are not correct. More advanced LMs, which properly take into account the structure of the data and do not require these assumptions, will be presented in Chaps. 12 and 16.

In Sect.3.3, we presented an exploratory analysis of the measurements of muscle fiber isometric- and specific force, collected in the progressive resistance training PRT study. In this chapter, we use LMMs to analyze the data. In particular, we first focus on data for the muscle fiber specific force. In Sect.17.2, we consider type-1 fibers only and fit an LMM with two correlated, heteroscedastic, occasion-specific random effects for each individual and homoscedastic independent residual errors. We subsequently modify the model for residual variation by using the power-of-the-mean variance function (Sect.17.3). In the next step, we consider models for both fiber types. In Sects.17.4 and 17.5, we construct conditional-independence LMMs with four correlated, heteroscedastic, fiber-type ×occasion-specific random effects for each individual. In Sects.17.6 and17.7, the random-effects structure of the models is simplified by considering more parsimonious structures of variance-covariance matrices of the random effects. Toward this end, we develop and use a new pdKronecker class of positive-definite matrices. Finally, in Sect.17.8, we construct the most comprehensive LMM, which takes into account the data for two dependent variables, that is the isometric and specific force, and for both fiber types. A summary of the chapter is presented in Sect.17.9.

In Chap. 4, we outlined several concepts related to the classical LM. In the current chapter, we review the tools available in R for fitting the model.

The FCAT study was described in Sect.2.5. An exploratory analysis of the data from the study was presented in Sect.3.5. In this chapter, we use LMMs with crossed random effects to analyze the data. In particular, we consider the models proposed by Tibaldi et al.[2007].

In Chap.12, we presented an analysis of the age-related macular degeneration (ARMD) data using LM with fixed effects for correlated data.

This study was designed to define the effect of human aging on hypoglycemia counterregulatory mechanisms. A hyperinsulinemic (2 mU.kg-1.min-1) glucose clamp procedure was used to control glucose and insulin levels during stepwise lowering of plasma glucose. Counterregulatory hormones, hepatic glucose production (HGP), glucose utilization, and symptoms of hypoglycemia were studied in 13 healthy young [age 24 +/- 1 (SE) yr] and 11 healthy old (age 65 +/- 1 yr) nondiabetic volunteers on two occasions: 1) at matched euglycemia and 70 and 60 mg/dl (study 1) and 2) at matched euglycemia and 60 and 50 mg/dl (study 2). The old had consistently lower epinephrine (P < 0.005), glucagon (P < 0.02), cortisol (P < 0.05), and pancreatic polypeptide (P < 0.02) responses at the 60-mg/dl glucose step in study 1. However, these differences were no longer detectable at the more severe hypoglycemic stimulus of 50 mg/dl in study 2. A consistent increase in HGP occurred in both groups only at the 50-mg/dl glucose step (study 2) and was not different between young and old. There were also no differences in symptom responses between young and old. In summary, we found that elderly individuals have a subtle impairment of the glucose counterregulatory response during moderate hypoglycemia, but this impairment is no longer detectable during more severe hypoglycemia.

The main difficulty in parametric analysis of longitudinal data lies in specifying covariance structure. Several covariance structures, which usually reflect one series of measurements collected over time, have been presented in the literature. However there is a lack of literature on covariance structures designed for repeated measures specified by more than one repeated factor. In this paper a new, general method of modelling covariance structure based on the Kronecker product of underlying factor specific covariance profiles is presented. The method has an attractive interpretation in terms of independent factor specific contribution to overall within subject covariance structure and can be easily adapted to standard software.

A genetically heterogeneous population of mice was tested for hearing at 8, 18, and 22 months by auditory brainstem response (ABR), and genotyped at 128 markers to identify loci that modulate late life hearing loss. Half of the test mice were exposed to noise for 2 hours at age 20 months. Polymorphisms affecting hearing at 18 months were noted on chromosomes 2, 3, 7, 10, and 15. Most of these loci had effects only on responses to 48 kHz stimuli, but a subset also influenced the auditory brainstem response at lower frequencies. Loci on chromosomes 4, 10, 12, and 14 had significant effects on hearing at 22 months in noise-exposed mice, and loci on chromosomes 10 and 11 had effects on mice not exposed to noise. Outer hair cell loss was modulated by polymorphisms on chromosomes 10, 11, 12, 17, and 19. Resistance to age-related hearing loss is thus modulated by a set of genetic effects, some age-specific, some frequency specific, some dependent on prior exposure to noise, and some of which compromise survival of cochlear hair cells.

Elite sprinters offer insights into the fastest whole body auditory reaction times. When, however, is a reaction so fast that it represents a false start? Currently, a false start is awarded if an athlete increases the force on their starting block above a given threshold before 100 ms has elapsed after the starting gun. To test the hypothesis that the fastest valid reaction times of sprinters really is 100 ms and that no sex difference exists in that time, we analyzed the fastest reaction times achieved by each of the 425 male and female sprinters who competed at the 2008 Beijing Olympics. After power transformation of the skewed data, a fixed effects ANOVA was used to analyze the effects of sex, race, round and lane position. The lower bounds of the 95, 99 and 99.9% confidence intervals were then calculated and back transformed. The mean fastest reaction time recorded by men was significantly faster than women (p

We previously described a cross-sectional association between serum uric acid and reduced glomerular filtration rate (GFR) in nonproteinuric patients with type 1 diabetes. Here, we prospectively investigated whether baseline uric acid impacts the risk of early progressive renal function loss (early GFR loss) in these patients.Patients with elevated urinary albumin excretion (n = 355) were followed for 4-6 years for changes in urinary albumin excretion and GFR. The changes were estimated by multiple determinations of albumin-to-creatinine ratios (ACRs) and serum cystatin C (GFRcystatin).At baseline, the medians (25th-75th percentiles) for uric acid, ACR, and GFRcystatin values were 4.6 mg/dl (3.8-5.4), 26.2 mg/g (15.1-56.0), and 129 ml/min per 1.73 m(2) (111-145), respectively. During the 6-year follow-up, significant association (P0.0002) was observed between serum uric acid and development of early GFR loss, defined as GFRcystatin decline exceeding 3.3% per year. In baseline uric acid concentration categories (in mg/dl:3.0, 3.0-3.9, 4.0-4.9, 5.0-5.9, andor=6), the risk of early GFR loss increased linearly (9, 13, 20, 29, and 36%, respectively). This linear increase corresponds to odds ratio 1.4 (95% CI 1.1-1.8) per 1 mg/dl increase of uric acid. The progression and regression of urinary albumin excretion were not associated with uric acid.We found a clear dose-response relation between serum uric acid and risk of early GFR loss in patients with type 1 diabetes. Clinical trials are warranted to determine whether uric acid-lowering drugs can halt renal function decline before it becomes clinically significant.

A Poisson regression model is proposed for the analysis of incidence rates presented in a two-way table classified by two categorical variables. It is shown that the likelihood function is the same as that using Glasser’s exponential covariate model. An algorithm is given to solve the maximum likelihood estimates of the regression parameters. The model is evaluated via deviance and the method is illustrated with an example. Some extensions of the model are discussed.

Importance Indwelling devices (eg, urinary catheters and feeding tubes) are often used in nursing homes (NHs). Inadequate care of residents with these devices contributes to high rates of multidrug-resistant organisms (MDROs) and device-related infections in NHs. Objective To test whether a multimodal targeted infection program (TIP) reduces the prevalence of MDROs and incident device-related infections. Design, setting, and participants Randomized clinical trial at 12 community-based NHs from May 2010 to April 2013. Participants were high-risk NH residents with urinary catheters, feeding tubes, or both. Interventions Multimodal, including preemptive barrier precautions, active surveillance for MDROs and infections, and NH staff education. Main outcomes and measures The primary outcome was the prevalence density rate of MDROs, defined as the total number of MDROs isolated per visit averaged over the duration of a resident's participation. Secondary outcomes included new MDRO acquisitions and new clinically defined device-associated infections. Data were analyzed using a mixed-effects multilevel Poisson regression model (primary outcome) and a Cox proportional hazards model (secondary outcome), adjusting for facility-level clustering and resident-level variables. Results In total, 418 NH residents with indwelling devices were enrolled, with 34,174 device-days and 6557 anatomic sites sampled. Intervention NHs had a decrease in the overall MDRO prevalence density (rate ratio, 0.77; 95% CI, 0.62-0.94). The rate of new methicillin-resistant Staphylococcus aureus acquisitions was lower in the intervention group than in the control group (rate ratio, 0.78; 95% CI, 0.64-0.96). Hazard ratios for the first and all (including recurrent) clinically defined catheter-associated urinary tract infections were 0.54 (95% CI, 0.30-0.97) and 0.69 (95% CI, 0.49-0.99), respectively, in the intervention group and the control group. There were no reductions in new vancomycin-resistant enterococci or resistant gram-negative bacilli acquisitions or in new feeding tube-associated pneumonias or skin and soft-tissue infections. Conclusions and relevance Our multimodal TIP intervention reduced the overall MDRO prevalence density, new methicillin-resistant S aureus acquisitions, and clinically defined catheter-associated urinary tract infection rates in high-risk NH residents with indwelling devices. Further studies are needed to evaluate the cost-effectiveness of this approach as well as its effects on the reduction of MDRO transmission to other residents, on the environment, and on referring hospitals. Trial registration clinicaltrials.gov Identifier: NCT01062841.

Fibroblast cell lines were developed from skin biopsies of eight species of wild-trapped rodents, one species of bat, and a group of genetically heterogeneous laboratory mice. Each cell line was tested in vitro for their resistance to six varieties of lethal stress, as well as for resistance to the nonlethal metabolic effects of the mitochondrial inhibitor rotenone and of culture at very low glucose levels. Standard linear regression of species-specific lifespan against each species mean stress resistance showed that longevity was associated with resistance to death induced by cadmium and hydrogen peroxide, as well as with resistance to rotenone inhibition. A multilevel regression method supported these associations, and suggested a similar association for resistance to heat stress. Regressions for resistance to cadmium, peroxide, heat, and rotenone remained significant after various statistical adjustments for body weight. In contrast, cells from longer-lived species did not show significantly greater resistance to ultraviolet light, paraquat, or the DNA alkylating agent methylmethanesulfonate. There was a strong correlation between species longevity and resistance to the metabolic effects of low-glucose medium among the rodent cell lines, but this test did not distinguish mice and rats from the much longer-lived little brown bat. These results are consistent with the idea that evolution of long-lived species may require development of cellular resistance to several forms of lethal injury, and provide justification for evaluation of similar properties in a much wider range of mammals and bird species.

The aim of this study was to examine effects of polymorphic genes on vertebral bone morphology and mechanical properties. Genotypes from 525, 18 month old female mice were compared to geometric traits obtained from micro-computed tomography and mechanical properties from compression testing. Genetic markers were associated with traits on at least 13 different chromosomes, demonstrating the complexity of genetic control over vertebral form, function and aging.

Context: Studies in older people have shown inconsistent agreement between homeostasis model assessment of insulin resistance (HOMA-IR) and dynamic measures of insulin action and have not evaluated HOMA β-cell. Objective: We compared measures of insulin sensitivity and β-cell function from the frequently sampled iv glucose tolerance test (FSIGT) to HOMA models. Design/Patients/Setting/Intervention: Two hundred fourteen young and old with normal glucose tolerance (NGT) and old with impaired glucose tolerance (IGT) participated in a retrospective analysis of FSIGT data in a university medical setting. Main Outcome Measure: Sensitivity to insulin (SI) and acute insulin response to glucose (AIRg) from FSIGT were compared with HOMA models. Results: SI and HOMA-IR measures identified similar patterns of increasing insulin resistance in the two older groups, compared with younger people with NGT, with the greatest degree of insulin resistance in older people with IGT (P < 0.05 vs. young and old NGT for both SI and HOMA-IR). Agreement between HOMA-IR and SI was moderate (weighted kappa = 0.51). AIRg was similar in young and old NGT but was markedly decreased in old IGT (P < 0.05 vs. young and old NGT). HOMA-β-cell was similar in the three groups. Agreement between HOMA β-cell and AIRg was weak (weighted kappa = 0.35). Conclusions: HOMA-IR may detect age-related insulin resistance when comparing large populations of older people. However, dynamic testing appears to be necessary to quantitate diminished insulin secretion in older people.

A genome scan was conducted to seek evidence for polymorphic genes that influence cause of death in mice produced by a cross between CB6F1 females and C3D2F1 males. Loci on chromosomes 1 and 4 were found to modulate risk of lymphoma. A locus on chromosome 4 influenced risk of mammary adenocarcinoma among multiparous female mice, but had no significant effect in virgin females. A chromosome 4 locus was found to modulate risk of death from either hemangiosarcoma or fibrosarcoma. A suggestive linkage was noted (at p =.09) between a marker on chromosome 11 and hepatocellular carcinoma. Lastly, a locus on chromosome 6 was noted to influence the likelihood that pulmonary adenocarcinoma would be present at death. The collection of normal and neoplastic tissues from 1004 terminal necropsies, together with genetic information, provides a valuable resource for further studies of the genetic influences on late-life diseases in mice.

Biophysical measurements indicative of protein stability and function were performed on crude extracts from liver, muscle, and lens of a genetically heterogeneous mouse population. Genetic information was used to search for quantitative trait loci (QTL) that influenced the biophysical traits, with emphasis on phenotypes that previously have been shown to be altered in aged animals. Spectroscopic and enzymatic assays of crude liver and muscle tissue extracts from ∼600 18-month-old mice, the progeny of (BALB/cJ × C57BL/6J)F1 females and (C3H/HeJ × DBA/2J)F1 males, were used to measure the susceptibility of a ubiquitous glycolytic enzyme, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), to thermal denaturation. The rate constant for thermal inactivation of GAPDH correlated with markers on chromosome 5 (D5Mit79 and D5Mit251) for muscle lysates and chromosome 15 (D15Mit63 and D15Mit100) for liver tissue. The degree of variability of inactivation rate constants, a measure of the heterogeneity of muscle GAPDH in tissue extracts, was also associated with markers on chromosome 5 (D5Mit79 and D5Mit205). In addition, spectroscopic characteristics of extracted eye lens proteins were evaluated for their susceptibility to photooxidative stress. Absorbance and fluorescence emission characteristics of the lens proteins were mapped to QTL on chromosomes 5 and 15 (D5Mit25 and D15Mit171) while the degree of heterogeneity in photochemical oxidation kinetics was associated with a marker on the chromosome 8 (D8Mit42). Recent work has shown that GAPDH possesses a number of non-glycolytic functions including DNA/RNA binding and regulation of protein expression. Tissue specific differences in GAPDH stability may have significant consequences to these alternate functions during aging.

Glucose tolerance declines with age, resulting in a high prevalence of diabetes and impaired glucose tolerance (IGT) in the older population. Hyperglycemia per se can lead to impaired β-cell function (glucose toxicity). We tested the role of glucose toxicity in age-related β-cell dysfunction in older people (65 ± 8 yr) with IGT treated with the α-glucosidase inhibitor acarbose ( n = 14) or placebo ( n = 13) for 6 wk in a randomized, double-blind study. Baseline and posttreatment studies included 1) an oral glucose tolerance test (OGTT), 2) 1-h postprandial glucose monitoring, 3) a frequently sampled intravenous glucose tolerance test (insulin sensitivity, or SI), and 4) glucose ramp clamp (insulin secretion rates, or ISR), in which a variable glucose infusion increases plasma glucose from 5 to 10 mM. The treatment groups had similar baseline body mass index; fasting, 2-h OGTT, and 1-h postprandial glucose levels; and SI. In these carefully matched older people with IGT, both fasting (5.7 ± 0.2 vs. 6.3 ± 0.2 mM, P = 0.002) and 1-h postprandial glucose levels (6.9 ± 0.3 vs. 8.2 ± 0.4 mM, P = 0.02) were significantly lower in the acarbose than in the placebo group. Despite this reduction of chronic hyperglycemia in the acarbose vs. placebo group, measures of insulin secretion (ISR area under the curve: 728 ± 55 vs. 835 ± 81 pmol/kg, P = 0.9) and acute insulin response to intravenous glucose (329 ± 67 vs. 301 ± 54 pM, P = 0.4) remained unchanged and impaired. Thus short-term improvement of chronic hyperglycemia does not reverse β-cell dysfunction in older people with IGT.

PURPOSE. The goal of this study was to map mouse quantitative trait loci (QTL) that influence the development of murine age-related cataract and synechia, by using a genetically heterogeneous mouse population bred by a four-way cross. METHODS. The test population consisted initially of 510 mice bred as the progeny of (BALB/cJ x C57BL/6J)F1 females and (C3H/HeJ x DBA/2J)F1 males. Each mouse was examined by slit lamp at 18 and 24 months of age and scored for degree of lens opacity o na0t o 4 scale, and the presence or absence of additional anterior chamber disease was noted. The presence of synechia was confirmed by histology. Each mouse was genotyped at 96 maternal and 92 paternal loci, and the significance of association between genotype and eye lesions was tested by permutation analysis. RESULTS. Significant QTL with effects on lens opacity at 24 months were detected on mouse chromosomes 4, 11, and 12. The effects were additive, and severe cataracts were seen in 80% of the mice with all three high-risk alleles, but in only 28% of the mice with all three low-risk alleles. The risk of synechia was associated with paternal chromosome 1 and on both the maternal and paternally inherited chromosome 4. Mice with all three high-risk alleles had a 68% risk of synechia, compared with a 0% incidence in mice with all three counteralleles. CONCLUSIONS. A four-way cross population of mice can be used to map polymorphic loci that influence cataract severity and synechia prevalence in late life. The results provide a first step toward identification of the individual genes involved and may help to guide the search for homologous human genes. (Invest Ophthalmol Vis Sci. 2004;45:1922‐1929) DOI:10.1167/iovs.030435

Many diseases show dichotomous phenotypic variation but do not follow a simple Mendelian pattern of inheritance. Variances of these binary diseases are presumably controlled by multiple loci and environmental variants. A least-squares method has been developed for mapping such complex disease loci by treating the binary phenotypes (0 and 1) as if they were continuous. However, the least-squares method is not recommended because of its ad hoc nature. Maximum Likelihood (ML) and Bayesian methods have also been developed for binary disease mapping by incorporating the discrete nature of the phenotypic distribution. In the ML analysis, the likelihood function is usually maximized using some complicated maximization algorithms (e.g. the Newton–Raphson or the simplex algorithm). Under the threshold model of binary disease, we develop an Expectation Maximization (EM) algorithm to solve for the maximum likelihood estimates (MLEs). The new EM algorithm is developed by treating both the unobserved genotype and the disease liability as missing values. As a result, the EM iteration equations have the same form as the normal equation system in linear regression. The EM algorithm is further modified to take into account sexual dimorphism in the linkage maps. Applying the EM-implemented ML method to a four-way-cross mouse family, we detected two regions on the fourth chromosome that have evidence of QTLs controlling the segregation of fibrosarcoma, a form of connective tissue cancer. The two QTLs explain 50–60% of the variance in the disease liability. We also applied a Bayesian method previously developed (modified to take into account sex-specific maps) to this data set and detected one additional QTL on chromosome 13 that explains another 26% of the variance of the disease liability. All the QTLs detected primarily show dominance effects.

Previous studies have shown that T cell subset levels, early life body weight, and levels of leptin and thyroid hormones can each serve, independently, as predictors of life span in populations of genetically heterogeneous mice. New data now confirm, in a replicate cohort, that T cell subset patterns predict longevity, and show that they can do so when measured in mice as young as 8 months of age. Individual T cell subsets, as well as composite indices that combine data from two or more T cell measures at 8 or 18 months, can be combined with 3- and 9-month body weight data to provide better prediction of life span than either immune or weight measures alone. Mice whose immune and weight measures are both in the lowest quartile have mean and maximal life spans that are 18% and 16-25% higher, respectively, than mice in the opposite quartiles for both traits. Thyroxine levels measured at 4 months lead to further improvement over models that combine weight and immune data only. A genome scan provided evidence for loci on chromosomes 2, 12, 13, and 17 that modulate age-sensitive T cell subset patterns at both 8 and 18 months of age. These data show that late-life mortality risks are influenced to a measurable degree by factors that modulate growth trajectory and hormone and immune status in the first third of the life span, and provide clues as to which early life systems deserve further scrutiny as potential mediators of late life disease risk.

The goal of this study was to investigate genetic effects on mechanical properties of the mouse femur. We found evidence for QTL on eight chromosomes that affect mechanical traits. Some of these QTL may have primary effects on body weight or femoral geometry, and others seem to affect bone quality directly. Introduction: Previous studies have shown a dependence of fragility-related fracture risk on genetic background. Although many of these studies investigated the effect of genetics on BMD, basic measures of bone geometry and mechanical integrity may provide a more comprehensive characterization of the genetic effects on bone fragility. The purpose of this study was to identify quantitative trait loci (QTL) that affect mechanical and material properties of cortical bone in a genetically heterogeneous mouse population. Materials and Methods: A total of 486 female UM-HET3 mice was used for this study. UM-HET3 mice are produced as the offspring of (BALB/cJ × C57BL/6J) F1 females and (C3H/HeJ × DBA/2J) F1 males. Femurs from 18-month-old mice were tested to failure in four-point bending to assess mechanical properties of cortical bone; these properties were compared with genotype data from 185 biallelic loci. A permutation-based test was used to detect significant associations between genetic markers and mechanical traits. This test generates p values that account for the effect of testing multiple hypotheses. Throughout the experiment, p ≤ 0.05 was considered statistically significant. Analysis of covariance was used to examine possible effects of body weight and femoral geometry. Results: We found evidence for genes on maternal chromosomes 11 and 13 and paternal chromosomes 2, 4, 7, 10, 11, and 17 that affect mechanical and material properties of femoral bone. The total variance explained by genetic effects on each mechanical trait ranges from 2.9% to 15.4%. Most of the identified polymorphisms influence mechanical traits even after adjustment for body weight. Adjustment for femoral geometry reduces the effects of some of the QTL, but those on chromosomes 2 and 10 do not seem to be influenced by femoral geometry. Conclusions:Many genes and chromosomes are involved in the genetic control over mechanical integrity of cortical bone. QTL on paternal chromosomes 4 and 11 may mediate mechanical properties, at least in part, by modulation of femoral geometry. Other QTL identified here may directly affect bone tissue quality.

The aim of this study was to examine the genetic effects on cortical bone geometry. Genotypes from 487 mice were compared with geometric traits obtained from μCT. We found 14 genetic markers that associate with geometric traits, showing the complexity of genetic control over bone geometry. Introduction: Previous studies have shown that genetic background affects bone characteristics, particularly bone mineral density, in both mouse and human populations. Much less is known, however, about the effects of polymorphic genes on bone size, shape, and mechanical integrity. In this study, we investigated the genetic determinants of geometric properties of cortical bone in mice. Materials and Methods: This study used a genetically heterogeneous mouse population, which is denoted UM-HET3 stock and is derived as the progeny of (BALB/cJ × C57BL/6J) F1 females and (C3H/HeJ × DBA/2J) F1 males. The experimental group consisted of 487 female UM-HET3 mice. Genotypic data from 99 polymorphic genetic loci was obtained from the mice at 4 weeks of age. At 18 months of age, the mice were humanely killed, and the right femurs were scanned with microcomputed tomography to assess geometric properties of cortical bone. A permutation-based test was used to detect significant associations between genetic markers and geometric traits. This test generates experimentwise p values, which account for the effect of testing multiple hypotheses. An experiment-wise p ≤ 0.05 was considered statistically significant. Results: Fourteen genetic markers were found to significantly associate with one or more geometric traits. Two markers (D3Mit62 and D4Mit155) were associated with traits describing bone size; 2 (D12Mit167 and D14Mit170) were linked with traits describing bone shape; and 10 (D1Nds2, D5Mit95, D6Mit216, D7Mit91, D8Mit51, D9Mit110, D11Mit83, D15Mit100, D15Mit171, and D17Mit46) were associated with both size and shape. Conclusions: Our results indicate that the genetic control of cortical bone geometry is complex and that femoral size and shape may be influenced by different, although overlapping, groups of polymorphic loci.

Small body size has been associated with long life span in four stocks of mutant dwarf mice, and in two varieties of dietary restriction in rodents. In this study, small body size at ages 2-24 months was shown to be a significant predictor of life span in a genetically heterogeneous mouse population derived from four common inbred mouse strains. The association was strongest for weights measured early in adult life, and somewhat weaker, though still statistically significant, at later ages. The effect was seen both in males and females, and was replicated in an independent population of the same genetic background. Body size at ages 2-4 months was correlated with levels of serum leptin in both males and females, and with levels of IGF-I and thyroid hormone in females only. A genome scan showed the presence of polymorphic alleles on chromosomes 2, 6, 7 and 15 with significant effects on body weight at 2-4 months, at 10-12 months, or at both age ranges, showing that weight gain trajectory in this stock is under complex genetic control. Because it provides the earliest known predictor of life span, body weight may be usefully included in screens for induced mutations that alter aging. The evidence that weight in 2-month-old mice is a significant predictor of life span suggests that at least some of the lethal diseases of old age can be timed by factors that influence growth rate in juvenile rodents.

Serum levels of thyroxine (T4), leptin, and insulin-like growth factor-I (IGF-I), as well as cataract severity, were evaluated as predictors of life span in a population of genetically heterogeneous mice (UM-HET3). Long life span was predicted by low levels of leptin at age 4 months in females, and by low levels of IGF-I at age 15 months and high levels of T4 at age 4 months, in males. Cataract severity at either 18 or 24 months was also a significant predictor of life span in females only, but in contrast to what has been reported in human studies, relatively severe cataract was correlated with longer life span. Additional work is needed to evaluate the role of these hormones as potential modulators of the aging process, and to resolve the conflicting data obtained for cataract severity as a predictor of life span.

To see whether genetic polymorphisms regulate inter-individual differences in T cell subset levels, we have conducted a genome scan in two populations of mice, bred as the progeny of a cross between CB6F1 females and C3D2F1 males. The data document quantitative trait loci (QTL) with statistically significant effects on CD4, CD8, and CD8 memory T cells, and on subsets of CD4 and CD8 T cells that express P-glycoprotein. Some of the loci detected were robust, in the sense that they produced effects of similar size both in mated female mice, and in a population that included male and female virgin animals. Some of the effects were stable, in that they were apparent at both 8 and 18 months of age, but others were age-specific, showing effects either at 8 or at 18 months but not at both ages. Genes that had an effect on the same T cell subset were in almost all cases additive rather than epistatic, and their combined effects could produce large overall effects, leading in the most dramatic case to a two-fold difference in CD8 memory cells. The analysis also documented two QTL, on chromosomes 4 and 13, that regulate an age-sensitive composite index of T cell subset pattern which has been shown previously to be a predictor of life expectancy in these mice. The analysis thus reveals both subset-specific genes and others which modulate the overall pattern of age-sensitive changes in T cell subset distributions.

Some models of aging imply that late-life diseases, though roughly synchronous, are the result of distinct pathophysiological processes, each in turn influenced by polymorphisms at multiple loci. Other models suggest that the dramatic increase in later life of multiple forms of illness might reflect the outcome of a unitary process, of so-far unknown biochemical nature, that proceeds at a species-specific rate to increase the risk of many forms of disease and disability in parallel. We have previously reported the results of genetic linkage analyses documenting the ability of alleles at D9Mit110, D10Mit15, and D12Mit167, and an allele pair at D2Mit58 and D16Mit182 to predict longevity in mice bred as the progeny of (BALB/cJ x C57BL/6J)F1 mothers and (C3H/HeJ x DBA/2J)F1 fathers (the UM-HET3 stock). Here we report the results of post hoc analyses to test the hypothesis that the genes that extend the life span of mice dying of neoplastic diseases also extend the life span of mice that die of nonneoplastic causes. In all four cases we find that the genotype associated with increased survival in mice dying of cancer is also associated for a similar degree of life span extension in mice dying of other causes. For D9Mit110 and the combination of D2Mit58 and D16Mit182, the difference is statistically significant in both the neoplastic and nonneoplastic mouse groups. The data support the hypothesis that many forms of late-life disease may be influenced by shared pathophysiologic mechanisms that are under coordinated genetic control.

Background. The population aged 65 and older is often analyzed in three categories: young-old (65‐74), middle-old (75‐84), and oldest-old ( $ 85). This may blind heterogeneity within the oldest category. New, large data sets allow examination of the very oldest-old (e.g., aged $ 95) and contrasts with those who are younger. Methods. We determined the annual change of prevalence of physical and cognitive function, and of disease problems in the old to very oldest-old, using data from existing Resident Assessment Instrument records from nursing homes in seven states during 1992‐1994. We used data from 193,467 unique residents aged 80 or older, including 6,556 residents aged 100 or older. We computed the prevalence, by age, of selected conditions: physical and cognitive function, diseases, problem behavior, mood disturbance, restraint use, falls, weight loss, eating less, body mass index, chewing and swallowing problems, incontinence (bowel and bladder), catheter use, and selected diagnoses. Results. Prevalence of all measures of physical and cognitive dysfunction increased most rapidly with each year of age among the very oldest-old. Most of the slope changes occurred from 95 to 100 years of age. Such changes are less pronounced or not seen in measures of disease prevalence. Conclusions. Accelerated change in prevalence of dysfunction seen in the nursing home population may suggest a change in the mechanisms of aging that occur after the mid-nineties. Examination of the very oldest-old may provide new insight into the nature of the aging process. HE population of the United States, as of virtually all the world, is aging rapidly and with the greatest relative change in the oldest-old group. From 1960 to 1990, when the total U.S. population grew by 39%, the number of persons aged 65 or older increased by 89%, and those aged 85 or older increased by 232% (1). By 2030, older Americans aged 65 or older could represent 25% (12% currently) of the population, because the size of younger populations will have declined (2,3).