Techniques to Analyze and Forecast Mortality

During the last few decades growth in life expectancy has resulted in increased pressure on personal and public finances. The increasing amount of attention paid on longevity risk and funding for old age has created the need for precise mortality models and accurate mortality forecasts. Indeed, many attempts have been made to understand mortality and there has been a rich literature on mortality modeling which goes back to the very early years. The overall aim of this PhD thesis is to have a better understanding of mortality patterns and improve the accuracy of future mortality projections. In this thesis, we apply various econometric and statistical techniques to mortality data from a wide range of developed countries including the Great Britain, the United States, Australia, Netherlands, Japan, France and Spain over the post-war period 1950–2009. Contributions have been made to the existing literature with focus given to the forecasting perspective of models and to the analysis of cohort effects. In particular we apply methods familiar to the econometrics literature to the area of mortality where they are less applied. <br>    The four main chapters of the thesis link to each other in a comprehensive way. In Chapter 2, we apply a semiparametric local linear estimation framework to stochastic mortality models which frees the commonly used Poisson assumption on number of deaths and improves upon the forecasting ability of the model. Then in Chapter 3 we introduce a flexible functional form approach aiming to capture cohort effects via the use of Legendre orthogonal polynomials in age and time dimensions. We allow for greater flexibility in the model by considering two-dimensional polynomials instead of one-dimensional polynomials in either age or time dimension. In order to further understand the nature of cohort effects and be able to evaluate and compare the strength of cohort effects across different countries, in Chapter 4 of the thesis we develop a two-dimensional kernel smoothing mortality model which enables us to analyze cohort effects in a quantitative manner. Finally, based on the empirical results from the first three main chapters, we conduct an investigation to compare the forecasting performance among different types of mortality models. We conclude that to improve forecast accuracy, more emphasis should be given to recent data over historical data during the forecasting process. <br> <br

A pivotal allocation based algorithm for solving the label switching problem in Bayesian mixture models

<div><p>In Bayesian analysis of mixture models, the label switching problem occurs as a result of the posterior distribution being invariant to any permutation of cluster indices under symmetric priors. To solve this problem, we propose a novel relabeling algorithm and its variants by investigating an approximate posterior distribution of the latent allocation variables instead of dealing with the component parameters directly. We demonstrate that our relabeling algorithm can be formulated in a rigorous framework based on information theory. Under some circumstances, it is shown to resemble the classical Kullback-Leibler relabeling algorithm and include the recently proposed Equivalence Classes Representatives relabeling algorithm as a special case. Using simulation studies and real data examples, we illustrate the efficiency of our algorithm in dealing with various label switching phenomena. Supplemental materials for this article are available online.</p></div

Table_6_Common gene signatures and molecular mechanisms of diabetic nephropathy and metabolic syndrome.XLS

BackgroundDiabetic nephropathy (DN) is the leading cause of end-stage renal disease. Multiple metabolic toxicities, redox stress, and endothelial dysfunction contribute to the development of diabetic glomerulosclerosis and DN. Metabolic syndrome (MetS) is a pathological state in which the body’s ability to process carbohydrates, fats, and proteins is compromised because of metabolic disorders, resulting in redox stress and renal remodeling. However, a causal relationship between MetS and DN has not been proven. This study aimed to provide valuable information for the clinical diagnosis and treatment of MetS with DN.MethodsHere, transcriptome data of DN and MetS patients were obtained from the Gene Expression Omnibus database, and seven potential biomarkers were screened using bioinformatics analysis. In addition, the relationship between these marker genes and metabolism and immune infiltration was explored. Among the identified marker genes, the relationship between PLEKHA1 and the cellular process, oxidative phosphorylation (OXPHOS), in DN was further investigated through single-cell analysis.ResultsWe found that PLEKHA1 may represent an important biomarker that perhaps initiates DN by activating B cells, proximal tubular cells, distal tubular cells, macrophages, and endothelial cells, thereby inducing OXPHOS in renal monocytes.ConclusionOverall, our findings can aid in further investigation of the effects of drug treatment on single cells of patients with diabetes to validate PLEKHA1 as a therapeutic target and to inform the development of targeted therapies.</p

Development of an NADPH-Dependent Homophenylalanine Dehydrogenase by Protein Engineering

l-Homophenylalanine is a nonproteinogenic amino acid and can be used as a versatile pharmaceutical intermediate. Production of l-homophenylalanine involves amination of the keto acid precursor 2-oxo-4-phenylbutyric acid (2-OPBA), which can be accomplished by bioenzymatic processes. Current biocatalysts for this reaction include transaminases and NADH-dependent phenylalanine dehydrogenases, which are not optimal for metabolic engineering of whole-cell biocatalysis. Here, we report the development of an NADPH-dependent homophenylalanine dehydrogenase by engineering the NADPH-dependent glutamate dehydrogenase (GDH) from <i>Escherichia coli</i>, which provides a new tool for <i>in vitro</i> catalysis and <i>in vivo</i> metabolic engineering. We took a stepwise substrate walking strategy: the first round directed evolution switched GDH’s substrate specificity from its natural substrate 2-ketoglutarate to the intermediate target phenylpyruvate, which has similar structure as 2-OPBA; and the second round further improved the enzyme’s catalytic efficiency toward the final target 2-OPBA. Compared to wild type GDH, the catalytic efficiency (<i>k</i>_cat/<i>K</i>_m) of the final mutant was ∼100 fold higher for 2-OPBA and ∼3000 fold lower for the original substrate 2-ketoglutarate. When overexpressed in <i>E. coli</i>, the engineered GDH aminated 2-OPBA to l-homophenylalanine more effectively than the transaminases and NADH-dependent phenylalanine dehydrogenase, possibly because it utilizes the strong anabolic driving force NADPH under aerobic condition

A Synthetic Anhydrotetracycline-Controllable Gene Expression System in <i>Ralstonia eutropha</i> H16

Controllable gene expression systems that are orthogonal to the host’s native gene regulation network are invaluable tools for synthetic biology. In <i>Ralstonia eutropha</i> H16, such systems are extremely limited despite the importance of this organism in microbiological research and biotechnological application. Here we developed an anhydrotetracycline (aTc)-inducible gene expression system, which is composed of a synthetic promoter containing the operator <i>tetO</i>, the repressor TetR, and the inducer aTc. Using a reporter-activity based promoter library screen, we first identified the active hybrids between the <i>tetO</i> operators and the <i>R. eutropha</i> native <i>rrsC</i> promoter (<i>P</i>_<i>rrsC</i>). Next, we showed that the hybrid promoters are repressable by TetR. To optimize the dynamic range of the system, a high-throughput screening of 300 mutants of <i>R. eutropha phaC1</i> promoter was conducted to identify suitable promoters to tune the <i>tetR</i> expression level. The final controllable expression system contains the modified <i>P</i>_<i>rrsC</i> with two copies of the <i>tetO1</i> operator integrated and the <i>tetR</i> driven by the mutated <i>P</i>_<i>phaC1</i>. The system has decreased basal expression level and can be tuned by different aTc concentrations with greater than 10-fold dynamic range. The system was used to alleviate cellular toxicity caused by AlsS overexpression, which impeded our metabolic engineering work on isobutanol and 3-methyl-1-butanol production in <i>R. eutropha</i> H16

Image_7_Common gene signatures and molecular mechanisms of diabetic nephropathy and metabolic syndrome.TIF

BackgroundDiabetic nephropathy (DN) is the leading cause of end-stage renal disease. Multiple metabolic toxicities, redox stress, and endothelial dysfunction contribute to the development of diabetic glomerulosclerosis and DN. Metabolic syndrome (MetS) is a pathological state in which the body’s ability to process carbohydrates, fats, and proteins is compromised because of metabolic disorders, resulting in redox stress and renal remodeling. However, a causal relationship between MetS and DN has not been proven. This study aimed to provide valuable information for the clinical diagnosis and treatment of MetS with DN.MethodsHere, transcriptome data of DN and MetS patients were obtained from the Gene Expression Omnibus database, and seven potential biomarkers were screened using bioinformatics analysis. In addition, the relationship between these marker genes and metabolism and immune infiltration was explored. Among the identified marker genes, the relationship between PLEKHA1 and the cellular process, oxidative phosphorylation (OXPHOS), in DN was further investigated through single-cell analysis.ResultsWe found that PLEKHA1 may represent an important biomarker that perhaps initiates DN by activating B cells, proximal tubular cells, distal tubular cells, macrophages, and endothelial cells, thereby inducing OXPHOS in renal monocytes.ConclusionOverall, our findings can aid in further investigation of the effects of drug treatment on single cells of patients with diabetes to validate PLEKHA1 as a therapeutic target and to inform the development of targeted therapies.</p

DataSheet4_Hydrogen sulfide alleviates uremic cardiomyopathy by regulating PI3K/PKB/mTOR-mediated overactive autophagy in 5/6 nephrectomy mice.PDF

The gasotransmitter hydrogen sulfide (H2S) plays important physiological and pathological roles in the cardiovascular system. However, the involvement of H2S in recovery from uremic cardiomyopathy (UCM) remains unclear. This study aimed to determine the therapeutic efficacy and elucidate the underlying mechanisms of H2S in UCM. A UCM model was established by 5/6 nephrectomy in 10-week-old C57BL/6 mice. Mice were treated with sodium hydrosulfide (NaHS, H2S donor), L-cysteine [L-Cys, cystathionine gamma-lyase (CSE) substrate], and propargylglycine (PPG, CSE inhibitor). Treatment of H9C2 cardiomyocytes utilized different concentrations of uremic serum, NaHS, PPG, and PI3K inhibitors (LY294002). Mouse heart function was assessed by echocardiography. Pathological changes in mouse myocardial tissue were identified using hematoxylin and eosin and Masson’s trichrome staining. Cell viability was assessed using the Cell Counting Kit-8. The protein expressions of CSE, p-PI3K, PI3K, p-PKB, PKB, p-mTOR, mTOR, and autophagy-related markers (Beclin-1, P62, and LC3) were detected using Western blotting. We found that NaHS and L-Cys treatment attenuated myocardial disarray, fibrosis, and left ventricular dysfunction in UCM mice. These abnormalities were further aggravated by PPG supplementation. Enhanced autophagy and decreased phosphorylation of PI3K, PKB, and mTOR protein expression by UCM were altered by NaHS and L-Cys treatment. In vitro, uremic serum increased overactive autophagy and decreased the phosphorylation levels of PI3K, PKB, and mTOR in cardiomyocytes, which was substantially exacerbated by endogenous H2S deficiency and attenuated by pre-treatment with 100 µm NaHS. However, the protective effects of NaHS were completely inhibited by LY294002. These findings support a protective effect of H2S exerted against UCM by reducing overactive autophagy through activation of the PI3K/PKB/mTOR pathway.</p

DataSheet2_Hydrogen sulfide alleviates uremic cardiomyopathy by regulating PI3K/PKB/mTOR-mediated overactive autophagy in 5/6 nephrectomy mice.PDF

The gasotransmitter hydrogen sulfide (H2S) plays important physiological and pathological roles in the cardiovascular system. However, the involvement of H2S in recovery from uremic cardiomyopathy (UCM) remains unclear. This study aimed to determine the therapeutic efficacy and elucidate the underlying mechanisms of H2S in UCM. A UCM model was established by 5/6 nephrectomy in 10-week-old C57BL/6 mice. Mice were treated with sodium hydrosulfide (NaHS, H2S donor), L-cysteine [L-Cys, cystathionine gamma-lyase (CSE) substrate], and propargylglycine (PPG, CSE inhibitor). Treatment of H9C2 cardiomyocytes utilized different concentrations of uremic serum, NaHS, PPG, and PI3K inhibitors (LY294002). Mouse heart function was assessed by echocardiography. Pathological changes in mouse myocardial tissue were identified using hematoxylin and eosin and Masson’s trichrome staining. Cell viability was assessed using the Cell Counting Kit-8. The protein expressions of CSE, p-PI3K, PI3K, p-PKB, PKB, p-mTOR, mTOR, and autophagy-related markers (Beclin-1, P62, and LC3) were detected using Western blotting. We found that NaHS and L-Cys treatment attenuated myocardial disarray, fibrosis, and left ventricular dysfunction in UCM mice. These abnormalities were further aggravated by PPG supplementation. Enhanced autophagy and decreased phosphorylation of PI3K, PKB, and mTOR protein expression by UCM were altered by NaHS and L-Cys treatment. In vitro, uremic serum increased overactive autophagy and decreased the phosphorylation levels of PI3K, PKB, and mTOR in cardiomyocytes, which was substantially exacerbated by endogenous H2S deficiency and attenuated by pre-treatment with 100 µm NaHS. However, the protective effects of NaHS were completely inhibited by LY294002. These findings support a protective effect of H2S exerted against UCM by reducing overactive autophagy through activation of the PI3K/PKB/mTOR pathway.</p

Table_3_Common gene signatures and molecular mechanisms of diabetic nephropathy and metabolic syndrome.XLS

BackgroundDiabetic nephropathy (DN) is the leading cause of end-stage renal disease. Multiple metabolic toxicities, redox stress, and endothelial dysfunction contribute to the development of diabetic glomerulosclerosis and DN. Metabolic syndrome (MetS) is a pathological state in which the body’s ability to process carbohydrates, fats, and proteins is compromised because of metabolic disorders, resulting in redox stress and renal remodeling. However, a causal relationship between MetS and DN has not been proven. This study aimed to provide valuable information for the clinical diagnosis and treatment of MetS with DN.MethodsHere, transcriptome data of DN and MetS patients were obtained from the Gene Expression Omnibus database, and seven potential biomarkers were screened using bioinformatics analysis. In addition, the relationship between these marker genes and metabolism and immune infiltration was explored. Among the identified marker genes, the relationship between PLEKHA1 and the cellular process, oxidative phosphorylation (OXPHOS), in DN was further investigated through single-cell analysis.ResultsWe found that PLEKHA1 may represent an important biomarker that perhaps initiates DN by activating B cells, proximal tubular cells, distal tubular cells, macrophages, and endothelial cells, thereby inducing OXPHOS in renal monocytes.ConclusionOverall, our findings can aid in further investigation of the effects of drug treatment on single cells of patients with diabetes to validate PLEKHA1 as a therapeutic target and to inform the development of targeted therapies.</p

Image_1_Common gene signatures and molecular mechanisms of diabetic nephropathy and metabolic syndrome.TIF

BackgroundDiabetic nephropathy (DN) is the leading cause of end-stage renal disease. Multiple metabolic toxicities, redox stress, and endothelial dysfunction contribute to the development of diabetic glomerulosclerosis and DN. Metabolic syndrome (MetS) is a pathological state in which the body’s ability to process carbohydrates, fats, and proteins is compromised because of metabolic disorders, resulting in redox stress and renal remodeling. However, a causal relationship between MetS and DN has not been proven. This study aimed to provide valuable information for the clinical diagnosis and treatment of MetS with DN.MethodsHere, transcriptome data of DN and MetS patients were obtained from the Gene Expression Omnibus database, and seven potential biomarkers were screened using bioinformatics analysis. In addition, the relationship between these marker genes and metabolism and immune infiltration was explored. Among the identified marker genes, the relationship between PLEKHA1 and the cellular process, oxidative phosphorylation (OXPHOS), in DN was further investigated through single-cell analysis.ResultsWe found that PLEKHA1 may represent an important biomarker that perhaps initiates DN by activating B cells, proximal tubular cells, distal tubular cells, macrophages, and endothelial cells, thereby inducing OXPHOS in renal monocytes.ConclusionOverall, our findings can aid in further investigation of the effects of drug treatment on single cells of patients with diabetes to validate PLEKHA1 as a therapeutic target and to inform the development of targeted therapies.</p