Modeling hematopoietic system response caused by chronic exposure to ionizing radiation.

A new model of the hematopoietic system response in humans chronically exposed to ionizing radiation describes the dynamics of the hematopoietic stem cell compartment as well as the dynamics of each of the four blood cell types (lymphocytes, neutrophiles, erythrocytes, and platelets). The required model parameters were estimated based on available results of human and experimental animal studies. They include the steady-state number of hematopoietic stem cells and peripheral blood cell lines in an unexposed organism, amplification parameters for each blood line, parameters describing proliferation and apoptosis, parameters of feedback functions regulating the steady-state numbers, and characteristics of radiosensitivity related to cell death and non-lethal cell damage. The model predictions were tested using data on hematological measurements (e.g., blood counts) performed in 1950-1956 in the Techa River residents chronically exposed to ionizing radiation since 1949. The suggested model of hematopoiesis is capable of describing experimental findings in the Techa River Cohort, including: (1) slopes of the dose-effect curves reflecting the inhibition of hematopoiesis due to chronic ionizing radiation, (2) delay in effect of chronic exposure and accumulated character of the effect, and (3) dose-rate patterns for different cytopenic states (e.g., leukopenia, thrombocytopenia).

Modeling deterministic effects in hematopoietic system caused by chronic exposure to ionizing radiation in large human cohorts.

A new model of the hematopoietic system for humans chronically exposed to ionizing radiation allows for quantitative description of the initial hematopoiesis inhibition and subsequent increase in the risks of late stochastic effects such as leukemia. This model describes the dynamics of the hematopoietic stem cell compartment as well as the dynamics of each of the three blood cell types (leukocytes, erythrocytes, and platelets). The model parameters are estimated from the results of other experiments. They include the steady-state numbers of hematopoietic stem cells and peripheral blood cell lines for an unexposed organism, amplification parameters for each blood cell line, parameters describing the proliferation and apoptosis, parameters of feedback functions regulating the steady-state numbers, and characteristics of radiosensitivity in respect to cell death and non-lethal cell damages. The dynamic model of hematopoiesis is applied to the data on a subcohort of the Techa River residents with hematological measurements (e.g., blood counts) performed in 1950-1956 (which totals to about 3,500 exposed individuals). Among well-described effects observed in these data are the slope values of the dose-effect curves describing the hematopoietic inhibition and the dose rate patterns of the fractions of cytopenic states (e.g., leukopenia, thrombocytopenia). The model has been further generalized by inclusion of the component describing the risk of late stochastic effects. The risks of the development of late effects (such as leukemia) in population groups with specific patterns of early reactions in hematopoiesis (such as leukopenia induced by ionizing radiation) are investigated using simulation studies and compared to data.

Early hematopoietic effects of chronic radiation exposure in humans.

The major goal of this study is to investigate and quantitatively describe the nature of the relationship between the characteristics of chronic exposure to ionizing radiation and specific patterns of hematopoiesis reduction. The study is based on about 3,200 hemograms taken for inhabitants of the Techa riverside villages over the years 1951-1956, i.e., the period characterized by a gradual decrease in dose rates. The mean cumulative red bone marrow dose was 333.6 + or - 4.6 mGy. The approach to statistical analyses involved both empirical methods and modeling (generalized linear models and logistic regressions). The results of the analyses highlighted a gradual increase in the frequency of cytopenias with dose rate. The impact of exposure on hematopoiesis reduction patterns was found to be more substantial than that of age and health status. Dose rates resulting in a two-fold increase in the frequency of cytopenias have been estimated.

Early hematopoiesis inhibition under chronic radiation exposure in humans.

The major goal of this study was to identify and quantitatively describe the association between the characteristics of chronic (low-dose rate) exposure to (low LET) ionizing radiation and cellularity of peripheral blood cell lines. About 3,200 hemograms (i.e., spectra of blood counts) obtained over the years of maximal exposure to ionizing radiation (1950-1956) for inhabitants of the Techa River were used in analyses. The mean cumulative red bone marrow dose (with standard errors), calculated using Techa River Dosimetry System-2000, was 333.6 +/- 4.6 mGy (SD = 259.9 mGy, max = 1151 mGy) to the year 1956. The statistical approach included both empirical methods for estimating frequencies of cytopenic states of the investigated blood cell lines (e.g. neutrophile, platelets, erythrocyte, etc.), and regression methods, including generalized linear models and logistic regressions which allowed taking into account confounding factors (e.g., attained age, age at maximal exposure, presence of concomitant diseases, and demographic characteristics). The results of the analyses demonstrated hematopoiesis inhibition manifested by a decrease in peripheral blood cellularity and an increase in the frequency of cytopenia in all blood cell lines (leukocytes, including lymphocytes, monocytes, neutrophiles, as well as platelets and erythrocytes). The intensity of hematopoiesis inhibition in the period of maximal exposures is determined by the combined influence of the dose rate and cumulative dose. The contribution of specific confounding factors was quantified and shown to be much less important than dose characteristics. The best predictor among dose characteristics was identified for each blood cell line. A 2-fold increase in dose rate is assumed to be a characteristic of radiosensitivity and a quantitative characteristic of the effect.

Trade-off between cancer and aging: what role do other diseases play? Evidence from experimental and human population studies.

The potential gain in life expectancy which could result from the complete elimination of mortality from cancer in the U.S. would not exceed 3 years if one were to consider cancer independently of other causes of death. In this paper, we review evidence of trade-offs between cancer and aging as well as between cancer and other diseases, which, if taken into account, may substantially increase estimates of gain in life expectancy resulting from cancer eradication. We also used the Multiple Causes of Death (MCD) data to evaluate correlations among mortalities from cancer and other major disorders including heart disease, stroke, diabetes, Alzheimer's, Parkinson's diseases, and asthma. Our analyses revealed significant negative correlations between cancer and other diseases suggesting stronger population effects of cancer eradication. Possible mechanisms of the observed dependencies and emerging perspectives of using dependent competing risks models for evaluating the effects of reduction of mortality from cancer on life expectancy are discussed.

Cumulative index of health deficiencies as a characteristic of long life.

OBJECTIVES: To describe the accumulation of aging-associated health disorders using a cumulative measure known as a frailty index (FI) and to evaluate its ability to differentiate long- and short-life phenotypes as well as the FI's connection to aging-associated processes in older people. DESIGN: Retrospective cross-sectional and longitudinal studies. SETTING: The National Long-Term Care Survey (NLTCS) data that assessed health and functioning of U.S. older individuals (> or =65) in 1982, 1984, 1989, 1994, and 1999 were analyzed. The NLTCS sample in each survey represents a mixture of longitudinal and cross-sectional components. PARTICIPANTS: Approximately 5,000 individuals in each survey. MEASUREMENTS: A cumulative index of health and well-being deficiencies (disabilities, signs, diseases) was calculated as a count of deficits observed in an individual divided by the total number of all considered deficits. RESULTS: Men and women who died before the age of 75 and those who died after the age of 85 exhibited remarkably similar FI frequency patterns despite the 10-year age difference between age profiles in these samples. Long life is consistently characterized in longitudinal analyses by lower FIs. FI dynamics are found to be strongly sex sensitive. CONCLUSION: The FI appears to be a sensitive age-independent indicator of sex-specific physiological decline in aging individuals and a sex-specific discriminator of survival chances. The FI is a promising characteristic suitable for improving sex-sensitive forecasts of risks of adverse health outcomes in older people.

Insights on aging and exceptional longevity from longitudinal data: novel findings from the Framingham Heart Study.

Age trajectories of physiological indices contain important information about aging-related changes in the human organism and therefore may help us understand human longevity. The goal of this study is to investigate whether shapes of such trajectories earlier in life affect the residual life span distribution. We used longitudinal limited access data from seven physiological indices and life spans of respective individuals collected in the Framingham Heart Study (FHS). These include: diastolic blood pressure (DBP), pulse pressure (PP), body mass index (BMI), serum cholesterol (SCH), blood glucose (BG), hematocrit (HC), and pulse rate (PR). We developed a method for assigning individuals to groups of potentially long-lived (PLL) and potentially medium-lived (PML) groups using age trajectories of physiological indices at the age interval between 40 and 60 years. The analysis shows that the longevity of individuals who survived to age of 65 depends on the behavior of the physiological indices between 40 and 60 years of age.