Welcome to D-Scholarship@Pitt - D-Scholarship@Pitt
[pic]
[pic]
[pic]
ABSTRACT
Despite recent advancements in healthcare that allow people living with HIV (PLWH) and healthy people living with comorbid conditions, such as obesity, diabetes, and heart disease, to live longer, new consequences arise, as people now live for longer durations of time with these diseases and comorbid conditions. Research has suggested that presence of diseases such as obesity, diabetes, and heart disease in mid-life could be predictive of cognitive decline development later on in life through several interconnected pathogenic mechanisms, each of which could potentially be exacerbated by HIV infection.
For instance, systemic inflammation caused by obesity, cardiovascular disease development, metabolic dysregulation, and HIV infection could eventually lead to neuroinflammation, development of pathogenic vascular plasticities which result from a heightened inflammatory state, and secretion of pro-inflammatory cytokines, all which ultimately culminate in cognitive decline. Eventually, this leads to a synergistic effect in PLWH, as additional cardiac complications occur in this cohort of people due to previously harsh antiretroviral therapy management, development of myocarditis, endothelial damage, and eventual heart failure. Overall, each of these processes contribute to pathogenic pathways which lead to cognitive decline, and potential development of HIV-associated neurocognitive disorder (HAND) in PLWH.
This essay aims to describe, in detail, the interplay of the aforementioned mechanisms, and to also examine if single-nucleotide polymorphisms of the cyclic AMP (cAMP) element-binding protein CREB1, which has been implicated in higher rates of cognitive decline in healthy adults, exist at significant levels in PLWH. Results show no significant interaction between alleles of CREB1 and decline status in this cohort of subjects, however it is important to continue research in this area, due to its public health implications.
This area of research is of high public health significance, because individuals living with these conditions may eventually suffer from a lower quality of life as a result of comorbid conditions. Additionally, it addresses current gaps in research by attempting to describe a causal pathway of how cognitive decline progresses in HIV-infected vs. healthy individuals, what factors (i.e. environmental, genetic) could contribute to this progression, and if/how they can be managed to ensure better quality of life.
TABLE OF CONTENTS
preface ix
1.0 Introduction 1
1.1 Cognitive Decline, Obesity, and Inflammation 2
1.2 Cognitive Decline, Metabolic Syndrome, Insulin Resistance, and Diabetes 6
1.3 Cognitive Decline, Dyslipidemia, and Cardiovascular Complications 11
1.4 HIV, Inflammation, and Immune Activation 14
1.5 HIV, ART, and Cardiovascular Complications 17
1.6 HIV and Cognitive Decline 19
1.7 Study Objectives 23
2.0 METHODS 24
2.1 Study Subjects 24
2.2 Quality Control Analysis 24
2.3 DNA Amplification 25
2.4 Quantitative PCR (qPCR) 25
2.5 Statistical Analysis 26
3.0 RESULTS 27
4.0 DISCUSSION 29
BIBLIOGRAPHY 32
List of tables
Table 1. Odds Ratio Analysis for rs2253206 SNP Call and Decline Status 27
Table 2. Odds Ratio Analysis for rs10932201 SNP Call and Decline Status 28
Table 3. Odds Ratio Analysis for rs6785 SNP Call and Decline Status 28
preface
I would like to thank my essay advisor and academic advisor, Dr. Jeremy Martinson for his guidance, mentorship, and support throughout this project. I would also like to thank my essay committee member, Dr. James Becker, for sharing his expertise during this project.
Introduction
As advances in medical care continually take place, a large portion of the population throughout the United States is living longer. Although these advances are helping the population to live longer, age-related complications are rising, leading to new concerns over the aging population. For instance, chronic conditions, such as cardiovascular disease, diabetes, obesity, and resulting comorbidities, are occurring for longer durations of time in the aging population. Presence of these diseases in mid-life has been implicated in subsequent cognitive decline later on in life 1, and rates of cognitive decline are only expected to increase in the future 2.
Inflammatory mediators related to these chronic conditions are thought to be one of the driving factors for age-related complications secondary to these comorbidities 3. These findings can be implicated in a variety of settings, including with complications arising from Human Immunodeficiency Virus (HIV). A growing body of evidence suggests that systemic inflammation, that arises from HIV infection, leads to a complex interplay of comorbidities, such as with development of cardiovascular disease and metabolic disorders 4, and may lead to the development of HAND5. Throughout this Master’s essay, I will explore the multifaceted relationships between each of these conditions in an effort to draw conclusions about the effects of inflammation and cardiovascular disease on subsequent cognitive disorder development in PLWH.
1 Cognitive Decline, Obesity, and Inflammation
The negative effects of a high prevalence of obesity in the population have been well documented over the last several decades. This disease not only has high healthcare costs associated with it, but it is also a major contributing factor to related metabolic diseases, such as cardiovascular disease (CVD), hypertension (HTN), and type 2 diabetes mellitus (T2DM). According to statistics from the Centers of Disease Control and Prevention (CDC), more than one-third of the United States adult population is considered obese 6. This statistic is highly concerning, given the negative downstream consequences that result from obesity-related comorbidities, and also given that a large proportion of the United States population consumes a “western diet,” (i.e. a diet high in fats, sugar, red meat, and refined grains) which also largely contributes to the obesity epidemic7.
The effects of obesity are chronic and cause a slow, life-long, health decline if left unmanaged. For instance, there is growing evidence that presence of obesity at midlife can lead to subsequent cognitive decline later on in life. A 2008 article which supported this evidence looked at central obesity and found that central obesity at midlife was linked to an increased risk of dementia later on in life, and that the most obese individuals in the observed cohort had a nearly three-times higher risk of dementia development, compared to the least obese individuals of the cohort 8. These findings have since been reproduced.
The observed effects of obesity develop over prolonged periods of time, which begs the question- is obesity itself a risk factor, or is something else causing these downstream health consequences? To answer this question, many researchers have studied inflammation resulting from obesity-related processes as a potential mediator in the pathway to metabolic disorders. The negative effects of inflammation on the body have been well documented in various situations. Many metabolic diseases, like CVD, HTN, T2DM, etc. are coming to light with the rise of the obesity epidemic throughout the general population. Current literature suggests that the underlying pathological factor for these issues is low-grade inflammation and resulting oxidative stress in the body, which activates the immune system and causes the downstream effect of disease development 3.
Generally speaking, neuroinflammation is thought to be a major causal factor in the etiology of various age-related diseases and is thought to occur as a pro-inflammatory state ensues during the normal aging process9–11. This occurs as microglial cells are activated in the brain and an increased level of cytokines such as TNF-α and various interleukins circulate throughout the body. Further contributing to these inflammatory issues is the progressive deterioration of the immune system through aging. As aging occurs, the immune system responds more slowly, works at a lower intensity, and its response may also occur over a prolonged period of time12–14. Overall, these processes lead to an inflammatory state which contributes to cognitive decline as normal aging occurs.
As adipose tissue accumulates inside the body during the development of obesity, the cycle of complications begins. Adipose tissue may seem like a simple accumulation of tissue resulting from a combination of genetic and environmental factors, but it is, in fact, a proinflammatory endocrine, autocrine, and paracrine organ capable of complex functions (Lau, Dhillon, Yan, Szmitko, & Verma, 2005). This tissue is able to regulate metabolic processes within the body and secretes a variety of biomarkers that affect systemic regulation. Adipose primarily consists of adipocytes (i.e. fat-storage cells) and their precursor cells, and a combination of immune cells including macrophages, fibroblasts, and leukocytes. Typically, if normal levels of these cells are maintained, there is low risk for cell ratio dysregulation and subsequent disease complications. However, in the case of obesity, excess fatty acids that circulate the bloodstream are stored as triglycerides in the adipose tissue, which eventually increases the size of the adipocytes themselves 16.
One commonly accepted pathological mechanism suggests that obesity-related issues ensue as adipocyte hypertrophy and hyperplasia occur following environmental (i.e. over-eating, stress, smoking, physical inactivity) and genetic factors that cause weight gain. When this occurs, the enlarged adipocytes experience hypoxia that then leads to downstream consequences, including adipocyte apoptosis and macrophage infiltration into the adipocytes. This mechanism leads to systemic inflammation due to pro-inflammatory metabolite production of adipokines (i.e. leptin and adiponectin, which have both been implicated in control of food energy expenditure and metabolism), and secretion of free fatty acids (FFA), tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), interleukin-1 (IL-1), and C-reactive protein (CRP), to name a few15,17. As this occurs, the lipoprotein lipase enzyme is activated by these pro-inflammatory cytokines and promotes circulation of increasing lipid levels in the blood17.
Production of these inflammatory mediators has been shown to contribute to a cascade of complications. For instance, FFA production leads to FFA circulation in the body, which can eventually lead to atherosclerotic plaque buildup and diminished pancreatic β-cell function (for further explanation, please refer to appropriate sections below) 18. Additionally, circulating FFAs can stimulate Toll-Like Receptor 4 (TLR4) and contribute to the inflammatory process by furthering the inflammatory cascade 3. As mentioned previously, during the inflammatory process resulting from obesity, adipocyte apoptosis occurs. TNF-α has been implicated as the inflammatory promoter of adipocyte apoptosis and also works to stimulate insulin resistance 19. CRP, TNF-α, and FFAs work synergistically to promote abnormal triglyceride circulation in the blood, which contributes to further cardiac and insulin resistance complications. IL-6 has a unique role as both an inflammatory and anti-inflammatory mediator and works to impair insulin sensitivity while promoting CRP production 20.
The pro-inflammatory cytokines that are activated locally in the adipose tissues eventually circulate centrally and lead to overall low-grade inflammation 3. As the previously mentioned pro-inflammatory cytokines circulate the bloodstream, they cross the blood brain barrier, and can also be produced locally in the brain as a response to the circulating cytokines, affecting various parts of the brain7. Most notably, IL-6, IL-1, and TNF-α have been shown to affect the hippocampus and cortex, since receptors for these pro-inflammatory cytokines are located throughout these brain regions. In turn, this low grade inflammation has been linked with subsequent cognitive decline, as both of these brain regions have implications in learning, memory, and cognitive processes 3,7. Furthermore, research suggests that IL-1 inhibits N-Methyl-D-Aspartate (NMDA) receptors in the brain in mouse models21. When applied to humans, this can explain hippocampal damage in the brain, as neurological signals are impaired due to NDMA receptor inhibition secondary to IL-1 influx. In turn, this damage leads to cognitive decline and deficits in learning and memory.
It is also important to note that obesity has been implicated as a casual factor in reduced focal gray matter volume in the frontal lobes of the brain, and is also thought to impair executive function, learning and memory. Studies have shown cognitive deficits in obese individuals when compared to healthy individuals across many cognitive domains including in decision making, attention, verbal memory, and visual memory, to name a few22. Although these effects are seen gradually in the adult population through normal aging, they seem to be exacerbated in obese individuals23–25. Generally speaking, the negative downstream effects of obesity can be observed in a variety of processes, as the condition affects the body systemically. Obesity’s major effects on vasculature and potentially on cognition make it a disease of major public health concern, because consistent periods of obesity earlier on in life (i.e. midlife) have been linked with cognitive impairment later on in life22. The complex interplay of obesity, inflammation, and insulin resistance is responsible for the environment that leads to subsequent cognitive decline later on in life. Thus, the longer that these issues ensue, the higher likelihood there is for one to suffer from cognitive issues, making this trifecta of issues a highly concerning.
2 Cognitive Decline, Metabolic Syndrome, Insulin Resistance, and Diabetes
Further contributing to inflammation- and obesity-related issues is the development of metabolic syndrome (MetS), a pathologically complicated disorder which severely heightens risk of comorbidities. MetS results from the interplay between several major factors: insulin resistance, abdominal obesity, atherogenic dyslipidemia, endothelial dysfunction of the cardiovascular system, hypercoagulable state, and chronic stress. Consequently, inflammation related to MetS occurs along with these comorbid disorders, leading to chronic inflammation, vascular complications, and atherosclerotic formations 26. It is important to note that presence of MetS significantly increases likelihood of T2DM, and according to a 2017 National Health and Nutrition Examination Survey (NHANES) analysis, odds ratios showed a higher prevalence of MetS associated with elevated waist circumferences, elevated blood lipid levels, reduced high density lipoprotein (HDL) cholesterol, elevated blood pressure, and elevated fasting glucose. These findings highlight the systemic dysregulation that leads to a cascade of downstream health issues when metabolic syndrome begins to develop27.
As mentioned previously, abdominal obesity heightens the inflammatory response and has been implicated in the development of MetS. Subsequently, it is important to note that as the pro-inflammatory state ensues, the cytokines that are produced as a result of obesity-related inflammation alter the effect of the insulin response. For instance, production of TNF-α blocks the insulin signaling pathway, leading to inhibition and under-production of insulin that, in turn, causes poor glucose regulation and development of T2DM 28. Similarly, FFA production caused by adipocyte apoptosis induces insulin resistance by inhibiting insulin-mediated glucose uptake and impairing function of pancreatic β-cells. This occurs as the normal process to convert fatty acids into triglycerols is dysregulated and leads to higher levels of blood glucose and fatty acids in the blood, which can result in T2DM complications over time17,18. As IL-6 production increases, IL-6 works independently to increase CRP levels and impair insulin sensitivity 29. These increased CRP levels may contribute to insulin resistance and are also linked to future adverse cardiac events30. Overall, each of these processes leads to dyslipidemia and dysregulation of insulin and blood glucose reuptake, highlighting the interconnected nature of obesity, inflammation, insulin resistance, and T2DM.
Insulin resistance, classified by poor tolerance to glucose testing, inadequate glucose metabolism (i.e. poor clearing of glucose or higher glucose production), and/or hyperglycemia, also contributes to systemic issues through the progression of inflammation and MetS. Insulin resistance significantly contributes to the severity and development of metabolic diseases and neurodegenerative processes, as insulin sensitive tissues such as adipose, the brain, the liver, and skeletal muscle are all affected. As mentioned previously, when insulin resistance occurs, pancreatic β-cells are compromised and cause dysregulation of insulin levels systemically (i.e. eventual insulin resistance). When this dysregulation occurs, initially, pancreatic β-cells work more diligently to produce excess insulin in order to compromise for circulation of increasing blood glucose levels17. However, eventually, this results in pancreatic β-cell dysfunction due to overstimulation of these cells. In turn, this condition leads to pancreatic β-cell apoptosis, and MetS and T2DM development, as pancreatic β-cells are unable to produce normal amounts of insulin31,32. Consequently, the tissues of the aforementioned insulin-sensitive organs are unable to adequately reuptake circulating glucose. Eventually, this dysregulation of insulin pathways leads to abnormal fat uptake and distribution, and consequent vascular abnormalities17,26.
Several biochemical mechanisms are proposed to account for these issues. Typically, normally functioning insulin pathways carry out their roles as insulin is secreted by pancreatic β-cells in order to metabolize excess blood glucose. After this, insulin receptor (IR) proteins are activated and cause a cascade of biochemical reactions that then lead to glucose reuptake. When any of these aforementioned metabolic pathways are disturbed, either due to abnormal genetic or phenotypic, environmentally caused changes, insulin resistance may occur as a consequence. For instance, modifications to different serine residues have been researched as possible causal mechanisms for insulin resistance. It is postulated that proinflammatory cytokines such as TNF-α, which are secreted as a result of a larger presence of adipose, lead to hyper-phosphorylation of serine residues that may, in turn, lead to insulin resistance33–35. It is also believed that insulin resistance may be caused by under expression of insulin receptors or impaired response to the insulin ligand, due to chronic hyperglycemia, causing desensitization of these effector functions36. Furthermore, research has shown that hyperglycemia and hyperinsulinemia may also cause lower binding to insulin receptors in adipose tissues, once again reinforcing the negative feedback loop that leads to insulin resistance37. Another proposed mechanism suggested as a causal pathway to insulin resistance is through the dysregulation of the PI3K enzyme; however, existing findings on this topic remain controversial38.
With the rise of obesity and obesity-related comorbidities like MetS and T2DM, there is growing evidence for cognitive implications resulting from the interplay of inflammation and oxidative stress. Several studies have linked T2DM with cognitive decline, and have concluded that longer durations of T2DM disease processes leads to cognitive impairment later on in life 39. Additionally, a recent study looking at memory, executive function, and orientation showed a positive association between cognitive decline, increased hemoglobin A1C (HbA1c, a measure of average blood sugar level), and diabetes 40.
More specifically, as mentioned previously, the brain is one of the organs that is affected by insulin; thus, insulin resistance has been studied as a causal mechanism for issues with neuronal function. Insulin receptors are located throughout the brain and significantly contribute to certain neural pathways. In the hypothalamus, insulin acts on insulin receptors to regulate appetite, white fat mass, glucose output and production, and to respond to hypoglycemia, to name a few41. Insulin receptors are also found in areas of the brain that are important for learning and memory, such as the cerebral cortex, entorhinal cortex, and hippocampus42. It can be deduced that if there is insulin dysregulation or issues with insulin function and the aforementioned responses are also dysregulated, then insulin resistance in the brain can contribute to metabolic syndrome development43. The negative effects of insulin resistance have been observed in a recent study looking at memory functioning and deficits in people with insulin resistance versus healthy controls; this study found a negative correlation between insulin resistance and 1) scores on categorical verbal fluency tasks, 2) brain size, and 3) gray matter volume in the temporal lobes, indicating a potential degenerative influence of insulin resistance on the brain44.
For instance, as mentioned previously, TNF-α leads to hyper-phosphorylation of serine residues in the brain. This occurs as insulin receptor substrate-1 (IRS-1) is induced to phosphorylate serine residues. In turn, this phosphorylation inhibits the binding of PI3K, which typically binds through normal insulin stimulation. As a result, defective binding of PI3K results in abnormal insulin signaling within the cell45–47. Additionally, as insulin resistance occurs, insulin transport to the brain is downregulated, leading to insulin deficiency in the brain. Studies show that this process has been implicated in the causal pathway of decreased grey matter volume in the temporal lobes of the brain, indicating that this neurodegenerative process can have consequent cognitive decline implications48. For instance, even before T2DM develops, a proinflammatory state in the CNS induced by insulin resistance has been observed as a potential reason for memory impairments in older adults, through its effects on the hippocampus and hypothalamus49,50.
As can be seen, aside from insulin’s effects on metabolism, it has also been shown to regulate neurotransmitter channel activity. Thus, disruption of normal insulin mechanisms could potentially lead to dysfunctional neuron and neuronal synapse dysfunctions43. For instance, presence of insulin has been implicated as an important functional component for the glucose transporter, GLUT4, in the brain. Although this is not a major mechanism for glucose transport into the brain, it is still important to note that dysregulation of this transporter can have consequential effects in the brain as a result of insulin resistance51.
Further research evidence shows that insulin resistance may affect the hippocampus in the brain and may lead to smaller hippocampal volume, which may have consequential effects on memory and cognition52,53. These consequences occur as impaired insulin action leads to impaired NDMA receptor pathways, which insulin normally contributes to. In turn, normal neuronal synapses lose their excitatory function and a lower amount of long term potentiation occurs among the neurons in the hippocampus, likely leading to impaired learning and memory54. As discussed previously, the chronic inflammatory state induced on the brain through insulin-resistant pathways resulting from each of these processes is likely the major contributory factor leading to diabetes-associated cognitive decline.
3 Cognitive Decline, Dyslipidemia, and Cardiovascular Complications
With each of these mechanisms obstructing the normal function of insulin pathways, dyslipidemia occurs. Dyslipidemia, defined by elevated triglycerides, increased levels of low-density lipoprotein (LDL) cholesterol and decreased levels of HDL cholesterol, contributes to the inflammatory state. This process begins to occur as impaired insulin activity decreases insulin’s protective function on adipocytes and increases lipolysis in adipocytes. Consequently, FFA’s accumulate and dyslipidemia is heightened in response to a compromised insulin feedback, through which normal functioning of insulin response systems does not occur, and very low density lipoprotein (VLDL) accumulation occurs. As a result, the “bad” VLDL cholesterol is not cleared from the system appropriately, and atherosclerotic disease and endothelial dysfunction can develop, leading to subsequent cardiovascular problems 26.
Endothelial dysfunction, classified by imbalances in vasodilation and vasoconstriction of the endothelium, starts the process of atherosclerosis development15. As inflammation occurs throughout the body, the endothelium of blood vessels is compromised and leads to increased permeability of leukocytes into the vessels, increased VCAM-1 and ICAM-1 adhesion molecule expression, and increased expression of P- and E-selectins. Early research shows that these processes contribute to atherosclerotic plaque buildup, compromised plaque integrity and rupture, thrombus formation, potential occlusion of blood vessels, and eventually infarction15.
These studies have also pointed to adipokines and inflammatory cytokines produced by adipose tissue to have a major influence on the aforementioned processes, due to their contribution to the overall inflammatory state and also to cardiovascular disease risk factors15. CRP, leptin, TNF-α, serum amyloid A, and angiotensinogen are among the factors which have been explored as contributors to development of endothelial dysfunction. For instance, the inflammatory adipokine CRP, which is elevated in overweight individuals, as well as those with MetS, insulin resistance, and T2DM, has been shown to directly influence endothelial function by inducing VCAM-1, ICAM-1, selectins, and other vasoconstricting molecules55,56. Additionally, it inhibits nitric oxide (NO) production, leading to impaired angiogenesis which can lead to downstream consequences, such as small vessel disease, over time57–59. Leptin also affects the cardiovascular system by increasing platelet collection, possibility for thrombosis, and also potential cholesterol accumulation in macrophages during situations of high glucose exposure, thus highlighting the connection of cardiovascular events and diabetes57,58,60,61. TNF-α has been implicated in initiating and continuing formation of atherosclerosis by inducing VCAM-1, ICAM-1, and E-selectin expression, by encouraging apoptosis in endothelial cells, and by impairing NO availability, again leading to eventual endothelial dysfunction62–65. Serum amyloid A (SAA) has been implicated in similar situations and is also thought to contribute to greater levels of circulating apolipoprotein. This is likely results as SAA causes “good” HDL cholesterol to bind to macrophages and takes the place of apolipoprotein A1 from HDL cholesterol while diminishing free HDL cholesterol66. In turn, these processes can lead to lower levels of “good” HDL cholesterol, allowing “bad” LDL cholesterol to circulate at higher levels. Additionally, freely circulating apolipoprotein may have cognitive decline consequences as it circulates for more prolonged periods of time. Angiotensinogen also stimulates VCAM-1, ICAM-1, and MCP-1 (monocyte chemoattractant protein-1), again contributing to atherosclerotic formation much like TNF- α and CRP67. Similarly, it affects the volume of freely circulating NO in the bloodstream, leading to vascular tissue damage68. These are only a few of the inflammatory factors and their functions which persist throughout the formation of atherosclerosis and endothelial damage. As can be seen, the process is intricately complicated and has intertwined pathologies as it progresses.
Presence of the aforementioned comorbidities, combined with vascular risk factors (i.e. obesity, smoking, diabetes, hypertension, and hypercholesterolemia) have strongly been implicated as mediating factors for heart failure development, cognitive decline, and subsequent dementia development later on in life 69. In this case, the influence of inflammation on the cardiovascular system which contributes to heart failure (HF) development is once again thought to be the causal factor for cognitive decline development. Research suggests that a combination of processes occurs which leads to these two comorbidities, and that reduced cerebral blood flow (i.e. cerebral hypoperfusion) secondary to heart disease complications are the primary reasons for the ensuing cognitive impairment, as evidenced by impaired completion on attention, executive function, memory, psychomotor speed, and language tasks, later on in life 70.
The process of aging also contributes to vascular complications and leads to subsequent cognitive decline development71. Through a combination of the aforementioned processes, cerebral blood flow is obstructed and angiogenesis is decreased as a normal part of aging. Additional vascular changes, such as development of white matter hyperintensities (WMHs), also ensues59. Research suggests that WMHs occur alongside the presence of hypertension, atherosclerosis, and decreased blood vessel density72–74. These plasticities are especially concerning, because they are thought to contribute to ischemia, blood brain barrier leakage, inflammation, and neurodegeneration, all which of course have memory and behavioral implications.
4 HIV, Inflammation, and Immune Activation
Infection with HIV, leading to immune activation has been implicated as the general method of pathogenesis which leads to HIV-associated comorbidities and Acquired Immunodeficiency Syndrome (AIDS). In untreated HIV infection, systemic infection occurs as CD4+ T-cells decline and viral p24 antigen increases 75. More specifically, research suggests that CD4+ T-cell depletion occurs with CD4+ T-cells that reside in the gut, and consequently, HIV infection leads to inflammation-causing microbial translocation due to deterioration of the intestinal epithelium. It is believed that then, monocyte and T-cell activation occurs due to circulation of viral products, leading to persistent immune activation and inflammation 75. Despite the fact that T-cell activation lessens during the progression of HIV and during the course of ART, type I interferon response, monocyte activation, and inflammation and coagulation markers are still heightened in HIV+ compared with HIV- individuals75.
Inflammation defined by high production of proinflammatory cytokines and biomarkers, such as IL1-β, IL-6, TNF-α, and CRP, persists even when the infected individual is on an antiretroviral therapy (ART) regimen, and is implicated in the phenomenon known as “inflamm-aging”76. In other words, this inflammation is thought to eventually lead to cognitive decline and the development of HAND, discussed later on 75. Several studies have shown supportive evidence for this theory. For instance, the Strategies for Management of Antiretroviral Therapy (SMART) study showed that the chronic inflammatory state that HIV infection induces contributes to a greater morbidity and mortality risk in the infected cohort of people, as evidenced through higher levels of CRP, IL-6, and the protein product D-dimer which were correlated with a greater level of significance in HIV+ versus HIV- individuals. Overall, these findings suggest that there is a greater influence of inflammation on aging and age-related changes in PLWH77–81.
The complex interplay between the HIV virus and host response leads to a chronic state of inflammation in HIV+ individuals. Besides microbial translocation, several other factors including HIV replication, co-infections, and comorbidities contribute to immune activation. One theory suggests that even in virally suppressed patients, subclinical levels of viral replication occur that continuously keep the immune system heightened and trying to fight off the HIV infection.
Additionally, due to a weakened immune system, PLWH have an increased likelihood to develop a heightened response to viral or bacterial infections. Viral and bacterial co-infections may contribute to the elevated immune activation, as the immune system tries to suppress both the HIV infection and also the co-infection. Cytomegalovirus (CMV) is one of the most notable and common co-infections that can occur in PLWH and can account for 10% of the circulating memory T-cells in HIV- individuals. This percentage is even higher in PLWH. Downstream effects of this co-infection, including greater levels of atherosclerosis development and CMV-specific T-cell responses, heighten the effect of CMV infection in HIV+ individuals75. With all of these inflammatory complications occurring in HIV+ individuals, the inflammatory changes described previously persist in the HIV+ individual and lead to complicated comorbidities.
Inflammatory changes, similar to those mentioned previously, occur in the brain as well. There lacks definitive research on the exact mechanism of action of HIV on the brain, but several strong theories have been proposed as potential explanations. The most widely-accepted theory suggests that the HIV virus infects the central nervous system (CNS) through CD4+ T-cells or other monocytes which are simply circulating through this part of the body, but eventually go on to infect the cells of the CNS82,83. To further this theory, recent research has suggested that through the depletion of CD8+ T-cells in the cerebrospinal fluid, the HIV virus is able to replicate in the CNS and provide a continual source of HIV virus throughout the system84–86. Another theory suggests that the HIV infection alters vital proteins in the blood-brain barrier and in turn, causes the blood-brain barrier to experience problems, such as leakage87–89. Each of these potential mechanisms contribute inflammation and immune activation, which lead to neurological injury in the CNS.
Methods of neurological injury are also not fully understood, but several theories describe how HIV potentially leads to cognitive disorder development. For instance, shortly after initial infection, higher levels of neurofilament light chain (NFL) are detected in the cerebrospinal fluid of infected individuals90. This is highly concerning because this biomarker is indicative of neuronal damage, as evidenced through neurofilament accumulation which occurs during neuroaxonal degeneration91. Aside from occurrence of neuroinflammation, proteins such as the protein Tat, which activates transcription of HIV, have been implicated in neurological changes. It has been proposed that aside from being a crucial component in HIV transcription, Tat contributes to the development of HAND by being involved neurotoxic astrocyte activity action92. Studies suggest that eventually these processes upregulate penetration of the blood brain barrier by monocytes, again leading to a proinflammatory response93.
5 HIV, ART, and Cardiovascular Complications
Although increased life expectancy of PLWH is one of the greatest achievements of HIV research and therapy development, a variety of issues that PLWH face come along with these advances. For instance, as PLWH age, their chances of developing age- and lifestyle- related comorbidities increases, and often times, as PLWH age, they develop non-infectious comorbidities (i.e. cardiovascular disease, hypertension, T2DM, chronic kidney disease, and non-AIDS cancers, for example)4. Most notable is the bidirectional relationship between HIV-induced inflammation and comorbid diseases, namely, cardiovascular complications. This condition develops despite use of ART and occurs as the inflammatory state persists in the body as a result of both the HIV infection itself and the ART regimen. For instance, a common cardiac effect resulting from HIV infection is left ventricular (LV) dysfunction which can eventually lead to heart failure development due to abnormal LV wall thickness or dilation.
Additional cardiomyopathies, including myocarditis during late stages of HIV infection, can also occur due to cardiac function damage resulting from infection with different opportunistic infections. During development of myocarditis, cardiac myocytes are invaded by the pathogen, leading to an inflammatory response (i.e. myocarditis development) due to an induced cytokine response94. Research shows that during the development of myocarditis, the HIV virus can remain inside macrophages between myocardial cells, and may induce cytokine production which consequently damages the myocardial tissue 95. Then, the HIV virus can further damage surrounding tissues as it remains in these cells, and in turn, contributes to LV dysfunction through the induced inflammatory response96. Furthermore, this type of inflammation can negatively affect the vasculature and lead to development of atherosclerosis and eventual myocardial infarction, due to dyslipidemia defined by abnormalities in total cholesterol, LDL-C, and HDL-C, and high serum triglycerides 97.
With growing advancements in antiretroviral medications for treatment of HIV, PLWH are able to live longer lives. However, concerns about issues related to HIV medications arise, because as HIV-infection causes hypertriglyceridemia and decreased HDL levels, ART also contributes to metabolic changes, dyslipidemia, and insulin resistance 97. Consequently, there is an increase in concern for MetS and T2DM development, both of which further exacerbate the inflammatory state and reinforce the damaging cycle of comorbidities.
To add to these effects, PLWH also suffer from a collection of further non-specific cardiovascular comorbidities, referred to as anti-retroviral-associated-lipodystrophy (LD) syndrome, as a result of prolonged exposure to ART98. Through this condition, PLWH may have abnormal fat distribution with lipoatrophy in certain parts of the body where fat is normally stored, lipoaccumulation between the abdomen and neck, and/or visceral obesity. When this occurs, the inflammatory state is heightened further, due to the adipose accumulation’s contribution to secretion of inflammatory cytokines and insulin resistance, both of which are implicated in the causal pathways of cognitive decline, as mentioned previously99,100.
During the early days of ART, ART consisted of a multiple-pill-a-day drug cocktail, and individuals on ART were observed to have the aforementioned abnormal fat distribution patterns as a result of these heavy drug regimens that potentially contributed to metabolic issues101. Further side effects included hypertriglyceridemia, abnormal levels of LDL and HDL, and insulin resistance102–104. For instance, protease inhibitors, which were historically an integral part of the early drug regimens, have now been implicated in MetS development, and now have known side effects including dyslipidemia, insulin resistance, LD syndrome, cardiovascular disease, and cerebrovascular disease development105–109. These issues arise as protease inhibitors cause free cholesterol and free lipids to accumulate while blocking normal mechanisms of lipogenesis. In addition, protease inhibitors contribute to metabolic syndrome by preventing glucose uptake in adipocytes and by causing accumulation of abnormally folded proteins110–113.
Nucleoside analogue reverse transcriptase inhibitors (NRTIs) contribute to these issues on a smaller scale as well, as they alter ATP production through inhibition of enzyme activity which leads to adipocyte death. As mentioned previously, adipocyte apoptosis is frequently followed by a variety of inflammatory changes, all which contribute to low-grade inflammation in the body114–118. Presence of the aforementioned comorbid side effects plays into the cycle of cognitive decline as the body is put into an inflammatory state, and atherosclerosis and endothelial damage occur.
6 HIV and Cognitive Decline
Over the past few decades, HIV pathogenesis has been well studied, and the devastating effects of HIV and its subsequent progression to AIDS have come to light. With these advances in research, many comorbidities for PLWH have been identified. One of these comorbidities, HAND, has been implicated as a disease model for people who suffer from cognitive impairment and suffer from co-infection with HIV. As mentioned previously, HIV affects the central and peripheral nervous systems to varying degrees, resulting in neurotoxicity and increased inflammatory state5. Recent studies have even shown that HIV infection begins affecting the central nervous system within as little as eight days after the initial infection, highlighting the severity and swiftness of the virus’s ability for neuroinvasion119. HAND has been proposed as a condition that people infected with HIV have suffered from since the discovery of the disease. ART has strived to reduce and change symptoms of HAND, including “behavioral changes; difficulties with decision making, problem solving, concentration, learning, language, and memory; loss of coordination; weakness; and tremors,” but the condition still plagues PLWH120. According to statistical estimates, 50% of the HIV+ population eventually develops some form of cognitive impairment120.
Recent therapeutic efforts have successfully reduced its more severe effects, but less taxing versions still affect PLWH. Varying degrees of neurotoxicity and levels of HAND have been identified through the progression of HIV disease. HIV-associated dementia (HAD), the most severe form of HAND, presents with dementia like symptoms and if left unregulated, causes severe cognitive and functional atrophy resulting in death after a short period of time121. Mild neurocognitive disease (MND) and asymptomatic neurocognitive impairment (ANI) are currently the more worrisome versions of HAND, due to difficulty in diagnosis and treatment. These two levels of HAND are less severe, but more prevalent in the United States population, due to an increase in aging among the HIV+ population. Symptoms of these two disorders include cognitive impairment with possible functional impairment120.
Despite heavy use of ART, HAND will remain a persistent condition as long as HIV remains in the body, due to the chronic inflammatory state that HIV infection causes in individuals. Changes in brain composition resulting from HIV infection and ART lead to this neuroinflammation that reinforces the HAND causing cycle. Neurotoxicity and inflammation occur in PLWH as the immune response is activated and both infected and non-infected macrophages and microglia, chemokines, cytokines, and other inflammatory markers are initiated5. Blood screening in HIV patients can give further indicative information of the infection and its inflammation status. This is seen through high levels in blood elements such as IL-6, CRP, D-dimer, and Cystatin C97.
In turn, this heightened state of inflammation makes it harder for the body to control the infection and allows infected cells to infect nearby healthy cells more easily as the immune system is suppressed. ART therapy aims to reduce some of this inflammation, but not all is reduced, and in individuals suffering from HAND, “abnormalities in white and gray matter, which supports the role of neuroinflammation as a cause of HAND” can be seen120. As the aging HIV+ population continues to live through these medical advances, it is postulated that the number of people living with HAND will increase and give rise to further aging-related comorbidities such as “renal failure, osteoporosis, cancer, cardiovascular disease, and further cognitive decline (due to) age related brain vulnerability”122.
Comorbidities of HAND need to be addressed to ensure that HIV+ people can continue to live normal lives in later ages and to make sure that they adhere to their ART drug regimens in order to decrease possible complications related to this. First, it is important to point out that HIV is thought to be a possible accelerator of aging through the effects it has on the immune system. In turn, quicker aging has shown to impair cognition by the previously discussed inflammatory response and disruption of neurological pathways 5. This inflammation not only causes physical changes to the brain, but also affects the “cognitive reserve” of the patients. In other words, levels of neuronal connections are either increased or decreased in the brain5. This change in neuroplasticity gives rise to a variety of neurologic and psychiatric problems that are seen in people living with HIV.
Further neurological complications resulting from HIV infection can occur during the late stages of neurological infection. Although rare for people who are on ART treatment, vacuolar myelopathy still causes neurological complications in HIV patients. This debilitating complication damages the nerves of the spinal cord and consequently affects coordination, sensory input and integration, causes incontinence, and generalized weakness & stiffness123. Overall, the varying degrees of the most common neurological complications occur as the HIV infection progresses. ART can be used to slow down the progression of these complications, but as the HIV+ population ages, perhaps years of inflammation and chronic issues related to HIV will give rise to such conditions in more latent forms. For this reason, it is important to be aware of the potential harms that HIV infection has on the nervous system and its effects on the central nervous system.
This long list of risk factors and causes of distress contribute to comorbidities in PLWH in several ways. For instance, contributing stressors can lead to worsening outcomes due to weakening immunologic function in HIV+ patients by contributing to chronic stress. In this instance, we see that there is a psychosocial connection to physical health. Stress and effects on the body are interrelated and systemic.
Stress affects the body overall, and with chronic exposure, stress can contribute to accelerated aging and fatigue. Consequently, stress becomes a mediator between neurologic and psychosocial issues in patients with HIV. Prolonged exposure to the aforementioned stressors can cause many psychologic issues, such as anxiety and depression, which equally feed into the cycle of neurologic and psychosocial disorders in PLWH.
As can be seen, the cyclic effect of HIV infection complicates treatment, because there is not one single pathway that causes consequences in HIV infection. Reciprocal complications and comorbidities act together and influence each other, as is evident in the relationship between HAND and psychosocial/mental issues. Limitations exist in this research, because it is difficult to discern which has a more profound effect, HAND or psychosocial issues, and which of the two issues is more directly contributory to complications with HIV.
7 Study Objectives
The aim of this study is to determine if a relationship exists between cognitive decline and markers of cardiovascular disease and inflammation in men of the MACS cohort.
Specifically, this study aims to do the following:
1. To observe the prevalence of gene SNPs, which have been related to cognitive function, in a sample population from the MACS cohort. Three SNPs from the cyclic AMP (cAMP) element-binding protein CREB1 are studied to see if presence of certain alleles in each of the SNPs appear at a higher rate in the cognitive decline vs no cognitive decline group of the study sample. Each of the three genotypic SNPs of CREB1, rs10932201, rs2253206, and rs6785, have previously been shown to have a significant effect on memory and executive function in healthy adults.124
2. To determine what type of relationship exists between cognitive decline progressors and markers of cardiovascular disease, using support from the preceding introductory literature review.
METHODS
1 Study Subjects
The analyses conducted for purposes of this study used a sample cohort of 101 subjects from the Pitt Men’s Study (PMS), a well-defined prospective, longitudinally studied cohort of men who have sex with men (MSM). The PMS is part of the larger Multicenter AIDS Cohort Study (MACS). Study criteria have required participants to undergo extensive physical and psychological testing at each follow-up appointment, and large-scale clinical data has been generated on each of these subjects. These 101 subjects were selected due to their prior involvement in a cardiovascular risk sub-study. Most subjects’ cognitive decline and HIV status were documented for the purposes of this study. After subsequent testing, the study population was reduced to 96 individuals, in order for laboratory testing to take place.
2 Quality Control Analysis
Prior to conducting DNA amplification, spot checks on the sample cohort of 101 subjects were completed to confirm that enough of the subjects’ DNA existed. NanoDrop nucleic acid quantification was done to assess the quantity and quality of DNA in the existing sample of subjects. Traditional polymerase chain reactions (PCR) were conducted using DNA and standard MasterMix. After this, samples were run on a 2% agarose gel and compared to the size marker Φx174HaeIII. A final sample size of 96 subjects with viable DNA were chosen for analysis.
3 DNA Amplification
After conducting the quality control analysis, whole genome amplification was carried out using Illustra’s Ready-To-Go™ GenomiPhi™ V3 DNA Amplification Kit. This method of amplification employs isothermal multiple strand displacement in which the template DNA strands are denatured in a sample buffer, the denatured sample is added to GenomiPhi V3 freeze-dried cake, the mixture is incubated at 30°C, and the sample is heat inactivated. The purpose of whole genome amplification was to ensure that enough DNA was present for subsequent single nucleotide polymorphism (SNP) analysis.
4 Quantitative PCR (qPCR)
As mentioned previously, SNPs from the CREB1 gene, implicated in cognitive decline, were selected for analysis in this cohort. qPCR was completed for each SNP (rs2253206, rs6785, rs10932201) using a TaqMan assay. This assay is used for genotyping through PCR primer pairs and two TaqMan probes which have FAM and VIC dye labels. The specific alleles of the targeted gene are identified through the use of these fluorescent dyes, as the TaqMan probes adhere specifically to the complementary sequence of the allele it is targeting. PCR amplification is employed in this amplification in order to yield enough product for the dye to adhere to and create the subsequent fluorescent signal.
5 Statistical Analysis
Odds ratios for the SNPs rs10932201, rs2253206, and rs6785 were calculated to see
if there is an association between each of the alleles of the aforementioned SNPs and the cognitive decline status of the individuals in the study population. Results were used to approximate the potential risk of developing cognitive decline with specific alleles of SNPs. Major and minor alleles were determined using data analysis submitted to the National Center for Biotechnology Information’s dbSNP library. 125–127
RESULTS
A total of 88 study subjects produced conclusive SNP call results for both rs2253206 and rs10932201, and a total of 85 study subjects produced conclusive SNP call results for rs6785. Several subjects from the initial study population were not included in this analysis due to incomplete data on decline status or inability for SNP call determination by the software that was used. Overall, the study population contained a larger number of individuals who were positive for cognitive decline. Odds ratios were calculated for each of the SNPs to determine if the minor allele in each SNP had a significant dominant or recessive effect. Results are as follows.
Table 1. Odds Ratio Analysis for rs2253206 SNP Call and Decline Status
|rs2253206 |Decline Status | |
|SNP Call | | |
| |Positive |Normal |Total |
|A/A |11 |11 |22 |
|A/G |23 |19 |42 |
|G/G |17 |7 |24 |
|Total |51 |37 |88 |
|P-Value for Recessive Minor Allele: 0.1383 |
|Odds Ratio for Recessive Minor Allele: 0.47 (95% CI 0.17-1.28) |
|P-Value for Dominant Minor Allele: 0.3844 |
|Odds Ratio for Dominant Minor Allele: 0.65 (95% CI 0.25-1.72) |
The major allele reference for rs2253206 is the A allele and the minor allele is the G allele. P-value results compared to a 95% confidence interval indicate no significant interaction between the minor allele, G, and decline status.
Table 2. Odds Ratio Analysis for rs10932201 SNP Call and Decline Status
|rs10932201 |Decline Status | |
|SNP Call | | |
| |Positive |Normal |Total |
|A/A |7 |3 |10 |
|A/G |27 |21 |48 |
|G/G |17 |13 |30 |
|Total |51 |37 |88 |
|P-Value for Recessive Minor Allele: 0.4174 |
|Odds Ratio for Recessive Minor Allele: 0.55 (95% CI 0.13-2.31) |
|P-Value for Dominant Minor Allele: 0.8603 |
|Odds Ratio for Dominant Minor Allele: 0.92 (95% CI 0.38-2.25) |
The major allele reference for rs10932201 is the G allele and the minor allele is the A allele. P-value results compared to a 95% confidence interval indicate no significant interaction between the minor allele, A, and decline status.
Table 3. Odds Ratio Analysis for rs6785 SNP Call and Decline Status
|rs6785 |Decline Status | |
|SNP Call | | |
| |Positive |Normal |Total |
|A/A |0.5 |0.5 |1 |
|A/G |23 |14 |37 |
|G/G |25 |22 |47 |
|Total |48.5 |36.5 |85 |
|P-Value for Recessive Minor Allele: 0.8863 |
|Odds Ratio for Recessive Minor Allele: 1.33 (95% CI 0.03-68.82) |
|P-Value for Dominant Minor Allele: 0.4238 |
|Odds Ratio for Dominant Minor Allele: 0.70 (95% CI 0.29-1.67) |
The major allele reference for rs6785 is the G allele and the minor allele is the A allele. P-value results compared to a 95% confidence interval indicate no significant interaction between the minor allele, A, and decline status.
DISCUSSION
Based on a prior review of existing literature, it is highly likely that there are many genes which contribute to different pathways leading to cognitive decline. Previous studies have cited the three CREB1 SNPs as having a significant effect on semantic and/or episodic memory, indicating that the presence of these SNPs could potentially predispose an individual to accelerated aging and abnormal cognitive decline124. The analysis of these three SNPs in the cohort of MACS subjects used here shows no significant effect of these SNPs, as evidenced by individually calculated p-values. When compared to a 95% confidence interval, the p-value for each of the SNPs was greater than .05 for analyses looking at the minor allele as both dominant and recessive. Because of this, it is unclear which allele acts in a dominant manner and which allele acts in a recessive manner for each individual SNP.
There are several limitations which exist in this study and which could be affecting the results. For instance, the number of subjects on which data was collected was fairly small (85-88 subjects). Because of this, the analysis likely lacks statistical power and could potentially contain Type-II error. In order to ensure adequate statistical power, a larger sample size is needed for future studies. Furthermore, this study may contain selection bias, as it is looking at a very specific cohort of patients who were previously selected for a cardiovascular sub-study. In turn, the study sample does not have a mix of subjects who are representative of the naturally occurring rates of HIV status and cognitive decline status in the general population. Additionally, only three gene SNPs were studied, potentially omitting SNPs in other coding regions which could have a greater effect on memory and cognitive decline. In future studies, a more comprehensive population breakdown needs to be determined, because as mentioned previously, there is a larger number of people positive for cognitive decline in this cohort. Doing so should provide results that are more indicative of the general population.
Because of these limitations, further research is needed to determine the applicability of these results. Future analyses should increase sample size and, in turn, statistical power, while simultaneously broadening the demographics of the study population. In turn, this should provide a more accurate description and a more broadly applicable result set in terms of this data. Furthermore, additional gene SNPs which are implicated in cognitive decline should be studied in order to determine if there are other SNPs with a more significant influence on cognitive decline, and to also determine how HIV might affect cognitive decline progression when these SNPs are present. Having this knowledge could lead to alternative personalized medicine treatment plans which are more individualized based on the host genetics of an HIV+ individual. Additionally, understanding what non-genetic factors (i.e. environmental, and modifiable factors like obesity) contribute to cognitive decline development in an HIV+ vs. HIV- population is important for future research directions and treatment development. This knowledge could lead to new recommendations for lifestyle modifications.
As mentioned previously, with advances in healthcare, those living with HIV, are able to live longer lives. Although these advances diminish mortality rates of a disease that was once impossible to manage, a new set of public health problems come to light. As can be seen through the magnitude of inflammatory changes, combined with development of cardiovascular problems, cognitive decline is set to happen in this population and may be occurring at a faster rate due to the aforementioned changes. This is highly concerning, as healthcare resources and workforce issues may arise. For instance, more healthcare resources will be put into the aging population, and eventually, the individuals suffering from cognitive decline will have to use even more resources with activities of daily living and functioning. For this reason, it is important to continue studying the possible genetic mechanisms and gene SNPs which contribute to accelerated cognitive decline and aging, in order to be able to detect potential cognitive decline progressors early on, and allow for adequate planning.
BIBLIOGRAPHY
1. U.S. Department of Health and Human Services C for DC and P (CDC). Aggregated 2015 Subjective Cognitive Decline. . Published 2015. Accessed July 11, 2018.
2. Alzheimer’s Association. 2016 ALZHEIMER’S DISEASE FACTS AND FIGURES. . Accessed June 11, 2018.
3. Solas M, Milagro FI, Ramírez MJ, Martínez JA. Inflammation and gut-brain axis link obesity to cognitive dysfunction: plausible pharmacological interventions. Curr Opin Pharmacol. 2017. doi:10.1016/j.coph.2017.10.005
4. Guaraldi G, Zona S, Brothers TD, et al. Aging with HIV vs. HIV seroconversion at older age:A diverse population with distinct comorbidity profiles. PLoS One. 2015. doi:10.1371/journal.pone.0118531
5. Tedaldi EM, Minniti NL, Fischer T. HIV-Associated Neurocognitive Disorders: The Relationship of HIV Infection with Physical and Social Comorbidities. Biomed Res Int. 2015:1-13. doi:10.1155/2015/641913
6. U.S. Department of Health and Human Services C for DC and P (CDC). Adult Obesity Facts. . Published 2017. Accessed June 11, 2018.
7. Freeman LR, Haley-Zitlin V, Rosenberger DS, Granholm A-C. Damaging effects of a high-fat diet to the brain and cognition: a review of proposed mechanisms. Nutr Neurosci. 2014;17(6):241-251. doi:10.1179/1476830513Y.0000000092
8. Whitmer RA, Gustafson DR, Barrett-Connor E, Haan MN, Gunderson EP, Yaffe K. Central obesity and increased risk of dementia more than three decades later. Neurology. 2008;71(14):1057-1064. doi:10.1212/01.WNL.0000306313.89165.EF
9. Mattson MP, Chan SL, Duan W. Modification of Brain Aging and Neurodegenerative Disorders by Genes, Diet, and Behavior. Physiol Rev. 2002. doi:10.1152/physrev.00004.2002
10. Streit W. Microglia and Alzheimer’s disease pathogenesis. J Neurosci Res. 2004;77(1):1-8.
11. Tuppo EE, Arias HR. The role of inflammation in Alzheimer’s disease. Int J Biochem Cell Biol. 2005. doi:10.1016/j.biocel.2004.07.009
12. Giunta S. Exploring the complex relations between inflammation and aging (inflamm-aging): Anti-inflamm-aging remodelling of inflamm- aging, from robustness to frailty. Inflamm Res. 2008:558-563. doi:10.1007/s00011-008-7243-2
13. Giunta B, Fernandez F, Nikolic W V., et al. Inflammaging as a prodrome to Alzheimer’s disease. J Neuroinflammation. 2008. doi:10.1186/1742-2094-5-51
14. Desai A, Grolleau-Julius A, Yung R. Leukocyte function in the aging immune system. J Leukoc Biol. 2010;87:1001-1009.
15. Lau DCW, Dhillon B, Yan H, Szmitko PE, Verma S. Adipokines: molecular links between obesity and atheroslcerosis. Am J Physiol Hear Circ Physiol. 2005;288:2031-2041. doi:10.1152/
16. Luo L, Liu M. Adipose tissue in control of metabolism. J Endocrinol. 2016. doi:10.1530/JOE-16-0211
17. Verdile G, Keane KN, Cruzat VF, et al. Inflammation and Oxidative Stress: The Molecular Connectivity between Insulin Resistance, Obesity, and Alzheimer’s Disease. Mediators Inflamm. 2015;2015:105828. doi:10.1155/2015/105828
18. Boden G, Lebed B, Schatz M, Homko C, Lemieux S. Effects of acute changes of plasma free fatty acids on intramyocellular fat content and insulin resistance in healthy subjects. Diabetes. 2001;50(7):1612-1617. doi:10.2337/DIABETES.50.7.1612
19. Xydakis AM, Case CC, Jones PH, et al. Adiponectin, Inflammation, and the Expression of the Metabolic Syndrome in Obese Individuals: The Impact of Rapid Weight Loss through Caloric Restriction. doi:10.1210/jc.2003-031826
20. Stenl K, Wernstedt I, Llman TF, Wallenius V, Wallenius K, Jansson J-O. Interleukin-6 Levels in the Central Nervous System Are Negatively Correlated with Fat Mass in Overweight/Obese Subjects. doi:10.1210/jc.2002-021733
21. Murray CA, Lynch MA. Evidence That Increased Hippocampal Expression of the Cytokine Interleukin-1 Is a Common Trigger for Age-and Stress-Induced Impairments in Long-Term Potentiation.; 1998. doi:
22. Dahl AK, Hassing LB. Obesity and cognitive aging. Epidemiol Rev. 2013;35:22-32. doi:10.1093/epirev/mxs002
23. Pannacciulli N, Del Parigi A, Chen K, Le DSNT, Reiman EM, Tataranni PA. Brain abnormalities in human obesity: A voxel-based morphometric study. Neuroimage. 2006;31:1419-1425. doi:10.1016/j.neuroimage.2006.01.047
24. Elias MF, Elias PK, Sullivan LM, Wolf PA, D’Agostino RB. Obesity, diabetes and cognitive deficit: The Framingham Heart Study. Neurobiol Aging. 2005;26(1):11-16. doi:10.1016/J.NEUROBIOLAGING.2005.08.019
25. Waldstein SR, Katzel LI. Interactive relations of central versus total obesity and blood pressure to cognitive function. Int J Obes. 2006;30:201-207. doi:10.1038/sj.ijo.0803114
26. Kaur J. A Comprehensive Review on Metabolic Syndrome. 2014. doi:10.1155/2014/943162
27. Moore JX, Chaudhary N, Akinyemiju T. Metabolic Syndrome Prevalence by Race/Ethnicity and Sex in the United States, National Health and Nutrition Examination Survey, 1988–2012. Prev Chronic Dis. 2017;14:160287. doi:10.5888/pcd14.160287
28. Hotamisligil GS. Inflammation and metabolic disorders. Nature. 2006;444(7121):860-867. doi:10.1038/nature05485
29. Diamant M, Lamb HJ, van de Ree MA, et al. The Association between Abdominal Visceral Fat and Carotid Stiffness Is Mediated by Circulating Inflammatory Markers in Uncomplicated Type 2 Diabetes. J Clin Endocrinol Metab. 2005;90(3):1495-1501. doi:10.1210/jc.2004-1579
30. Deepa R, Velmurugan K, Arvind K, et al. Serum levels of interleukin 6, C-reactive protein, vascular cell adhesion molecule 1, and monocyte chemotactic protein 1 in relation to insulin resistance and glucose intolerance—the Chennai Urban Rural Epidemiology Study (CURES). Metabolism. 2006;55(9):1232-1238. doi:10.1016/j.metabol.2006.05.008
31. Gill H, Mugo M, Whaley-Connell A, Stump C, Sowers JR. The Key Role of Insulin Resistance in the Cardiometabolic Syndrome. Am J Med Sci. 2005;330(6):290-294. doi:10.1097/00000441-200512000-00006
32. Petersen KF, Shulman GI. Etiology of insulin resistance. Am J Med. 2006. doi:10.1016/j.amjmed.2006.01.009
33. Araki E, Lipes M, Patti M-E, et al. Alternative pathway of insulin signalling in mice with targeted disruption of the IRS-1 gene. Nature. 1994;372:186-190.
34. Hotamisligil GS, Peraldi P, Budavari A, Ellis R, White MF, Spiegelman BM. IRS-1-mediated inhibition of insulin receptor tyrosine kinase activity in TNF-alpha- and obesity-induced insulin resistance. Science. 1996;271(5249):665-668. doi:10.1126/SCIENCE.271.5249.665
35. Stuart CA, Howell MEA, Cartwright BM, et al. Insulin resistance and muscle insulin receptor substrate-1 serine hyperphosphorylation. Physiol Rep. 2014;2(12). doi:10.14814/phy2.12236
36. Garvey WT, Olefsky JM, Marshall S. Insulin induces progressive insulin resistance in cultured rat adipocytes. Sequential effects at receptor and multiple postreceptor sites. Diabetes. 1986;35(3):258-267. doi:10.2337/DIAB.35.3.258
37. Burén J, Liu H-X, Lauritz J, Eriksson JW. High Glucose and Insulin in Combination Cause Insulin Receptor Substrate-1 and-2 Depletion and Protein Kinase B Desensitisation in Primary Cultured Rat Adipocytes: Possible Implications for Insulin Resistance in Type 2 Diabetes. Vol 148.; 2003. . Accessed July 16, 2018.
38. Barbour LA, Shao J, Qiao L, et al. Human Placental Growth Hormone Increases Expression of the P85 Regulatory Unit of Phosphatidylinositol 3-Kinase and Triggers Severe Insulin Resistance in Skeletal Muscle. Endocrinology. 2004;145(3):1144-1150. doi:10.1210/en.2003-1297
39. Okereke OI, Kang JH, Cook NR, et al. Type 2 Diabetes Mellitus and Cognitive Decline in Two Large Cohorts of Community-Dwelling Older Adults. J Am Geriatr Soc. 2008;56(6):1028-1036. doi:10.1111/j.1532-5415.2008.01686.x
40. Zheng F, Yan L, Yang Z, Zhong B, Xie W. HbA1c, diabetes and cognitive decline: the English Longitudinal Study of Ageing. Diabetologia. 2018. doi:10.1007/s00125-017-4541-7
41. Wynne K, Stanley S, McGowan B, Bloom S. Appetite control. J Endocrinol. 2005;184(2):291-318. doi:10.1677/joe.1.05866
42. Marks JL, King MG, Baskin DG. Localization of insulin and type 1 IGF receptors in rat brain by in vitro autoradiography and in situ hybridization. Adv Exp Med Biol. 1991;293:459-470. . Accessed July 16, 2018.
43. Kleinridders A, Ferris HA, Cai W, Kahn CR. Insulin action in brain regulates systemic metabolism and brain function. In: Diabetes. ; 2014. doi:10.2337/db14-0568
44. Lind L, Fors N, Hall J, Marttala K, Stenborg A. A Comparison of Three Different Methods to Evaluate Endothelium-Dependent Vasodilation in the Elderly: The Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) Study. Arterioscler Thromb Vasc Biol. 2005;25(11):2368-2375. doi:10.1161/01.ATV.0000184769.22061.da
45. Hirosumi J, Tuncman G, Chang L, et al. A central role for JNK in obesity and insulin resistance. Nature. 2002;420(6913):333-336. doi:10.1038/nature01137
46. Nakamura T, Furuhashi M, Li P, et al. Double-Stranded RNA-Dependent Protein Kinase Links Pathogen Sensing with Stress and Metabolic Homeostasis. Cell. 2010;140(3):338-348. doi:10.1016/j.cell.2010.01.001
47. Sun XJ, Rothenberg P, Kahn CR, et al. Structure of the insulin receptor substrate IRS-1 defines a unique signal transduction protein. Nature. 1991;352(6330):73-77. doi:10.1038/352073a0
48. Benedict C, Brooks SJ, Kullberg J, et al. Impaired Insulin Sensitivity as Indexed by the HOMA Score Is Associated With Deficits in Verbal Fluency and Temporal Lobe Gray Matter Volume in the Elderly. Diabetes Care. 2012;35(3):488-494. doi:10.2337/dc11-2075
49. Bruehl H, Sweat V, Hassenstab J, Polyakov V, Convit A. Cognitive impairment in nondiabetic middle-aged and older adults is associated with insulin resistance. J Clin Exp Neuropsychol. 2010;32(5):487-493. doi:10.1080/13803390903224928
50. Craft S. Insulin resistance syndrome and Alzheimer’s disease: Age- and obesity-related effects on memory, amyloid, and inflammation. Neurobiol Aging. 2005;26(1):65-69. doi:10.1016/j.neurobiolaging.2005.08.021
51. McEwen BS, Reagan LP. Glucose transporter expression in the central nervous system: relationship to synaptic function. Eur J Pharmacol. 2004;490(1-3):13-24. doi:10.1016/j.ejphar.2004.02.041
52. Benedict C, Hallschmid M, Schultes B, Born J, Kern W. Intranasal Insulin to Improve Memory Function in Humans. Neuroendocrinology. 2007;86(2):136-142. doi:10.1159/000106378
53. Freiherr J, Hallschmid M, Frey WH, et al. Intranasal Insulin as a Treatment for Alzheimer’s Disease: A Review of Basic Research and Clinical Evidence. CNS Drugs. 2013;27(7):505-514. doi:10.1007/s40263-013-0076-8
54. Van Der Heide LP, Kamal A, Artola A, Gispen WH, Ramakers GMJ. Insulin modulates hippocampal activity-dependent synaptic plasticity in a N-methyl-d-aspartate receptor and phosphatidyl-inositol-3-kinase-dependent manner. J Neurochem. 2005;94(4):1158-1166. doi:10.1111/j.1471-4159.2005.03269.x
55. Pasceri V, Willerson JT, Yeh ET. Direct proinflammatory effect of C-reactive protein on human endothelial cells. Circulation. 2000;102(18):2165-2168. . Accessed July 25, 2018.
56. Verma S, Li S-H, Badiwala M V, et al. Endothelin antagonism and interleukin-6 inhibition attenuate the proatherogenic effects of C-reactive protein. Circulation. 2002;105(16):1890-1896. . Accessed August 14, 2018.
57. Cooke JP, Oka RK. Does leptin cause vascular disease? Circulation. 2002;106(15):1904-1905. . Accessed July 25, 2018.
58. Konstantinides S, Schäfer K, Koschnick S, Loskutoff DJ. Leptin-dependent platelet aggregation and arterial thrombosis suggests a mechanism for atherothrombotic disease in obesity. J Clin Invest. 2001;108(10):1533-1540. doi:10.1172/JCI13143
59. Verma S, Wang C-H, Li S-H, et al. A self-fulfilling prophecy: C-reactive protein attenuates nitric oxide production and inhibits angiogenesis. Circulation. 2002;106(8):913-919. . Accessed July 25, 2018.
60. Loffreda S, Yang SQ, Lin HZ, et al. Leptin regulates proinflammatory immune responses. FASEB J. 1998;12(1):57-65. . Accessed July 25, 2018.
61. O’Rourke L, Gronning LM, Yeaman SJ, Shepherd PR. Glucose-dependent regulation of cholesterol ester metabolism in macrophages by insulin and leptin. J Biol Chem. 2002;277(45):42557-42562. doi:10.1074/jbc.M202151200
62. Bhagat K, Vallance P. Inflammatory cytokines impair endothelium-dependent dilatation in human veins in vivo. Circulation. 1997;96(9):3042-3047. . Accessed July 26, 2018.
63. Choy JC, Granville DJ, Hunt DW, McManus BM. Endothelial cell apoptosis: biochemical characteristics and potential implications for atherosclerosis. J Mol Cell Cardiol. 2001;33(9):1673-1690. doi:10.1006/jmcc.2001.1419
64. Hermann C, Assmus B, Urbich C, Zeiher AM, Dimmeler S. Insulin-mediated stimulation of protein kinase Akt: A potent survival signaling cascade for endothelial cells. Arterioscler Thromb Vasc Biol. 2000;20(2):402-409. . Accessed July 26, 2018.
65. Wang P, Ba ZF, Chaudry IH. Administration of tumor necrosis factor-alpha in vivo depresses endothelium-dependent relaxation. Am J Physiol. 1994;266(6 Pt 2):H2535-41. doi:10.1152/ajpheart.1994.266.6.H2535
66. Lin Y, Rajala MW, Berger JP, Moller DE, Barzilai N, Scherer PE. Hyperglycemia-induced production of acute phase reactants in adipose tissue. J Biol Chem. 2001;276(45):42077-42083. doi:10.1074/jbc.M107101200
67. Tham DM, Martin-McNulty B, Wang Y, et al. Angiotensin II is associated with activation of NF-kappaB-mediated genes and downregulation of PPARs. Physiol Genomics. 2002;11(1):21-30. doi:10.1152/physiolgenomics.00062.2002
68. Verma S, Anderson TJ. Fundamentals of endothelial function for the clinical cardiologist. Circulation. 2002;105(5):546-549. . Accessed July 27, 2018.
69. Gottesman RF, Albert MS, Alonso A, et al. Associations Between Midlife Vascular Risk Factors and 25-Year Incident Dementia in the Atherosclerosis Risk in Communities (ARIC) Cohort. JAMA Neurol. 2017;74(10):1246. doi:10.1001/jamaneurol.2017.1658
70. Alosco ML, Spitznagel MB, Gunstad J. Obesity as a risk factor for poor neurocognitive outcomes in older adults with heart failure. Heart Fail Rev. 2014;19(3):403-411. doi:10.1007/s10741-013-9399-2
71. Steppan CM, Bailey ST, Bhat S, et al. The hormone resistin links obesity to diabetes. Nature. 2001;409(6818):307-312. doi:10.1038/35053000
72. Verma S, Wang C-H, Weisel RD, et al. Hyperglycemia potentiates the proatherogenic effects of C-reactive protein: reversal with rosiglitazone. J Mol Cell Cardiol. 2003;35(4):417-419. . Accessed July 27, 2018.
73. Visser M, Bouter LM, McQuillan GM, Wener MH, Harris TB. Elevated C-reactive protein levels in overweight and obese adults. JAMA. 1999;282(22):2131-2135. . Accessed July 27, 2018.
74. Wajchenberg BL. Subcutaneous and Visceral Adipose Tissue: Their Relation to the Metabolic Syndrome. Endocr Rev. 2000;21(6):697-738. doi:10.1210/edrv.21.6.0415
75. Hunt PW. HIV and inflammation: Mechanisms and consequences. Curr HIV/AIDS Rep. 2012. doi:10.1007/s11904-012-0118-8
76. Franceschi C, Bonafè M, Valensin S, et al. Inflamm-aging. An evolutionary perspective on immunosenescence. Ann N Y Acad Sci. 2000;908:244-254. . Accessed July 31, 2018.
77. Kuller LH, Tracy R, Belloso W, et al. Inflammatory and Coagulation Biomarkers and Mortality in Patients with HIV Infection. Deeks S, ed. PLoS Med. 2008;5(10):e203. doi:10.1371/journal.pmed.0050203
78. Wikby A, Nilsson B-O, Forsey R, et al. The immune risk phenotype is associated with IL-6 in the terminal decline stage: Findings from the Swedish NONA immune longitudinal study of very late life functioning. Mech Ageing Dev. 2006;127(8):695-704. doi:10.1016/j.mad.2006.04.003
79. Reuben DB, Cheh AI, Harris TB, et al. Peripheral blood markers of inflammation predict mortality and functional decline in high-functioning community-dwelling older persons. J Am Geriatr Soc. 2002;50(4):638-644. . Accessed July 31, 2018.
80. Volpato S, Guralnik JM, Ferrucci L, et al. Cardiovascular disease, interleukin-6, and risk of mortality in older women: the women’s health and aging study. Circulation. 2001;103(7):947-953. . Accessed July 31, 2018.
81. Harris TB, Ferrucci L, Tracy RP, et al. Associations of elevated interleukin-6 and C-reactive protein levels with mortality in the elderly. Am J Med. 1999;106(5):506-512. . Accessed July 31, 2018.
82. Liu Y, Tang XP, McArthur JC, Scott J, Gartner S. Analysis of human immunodeficiency virus type 1 gp160 sequences from a patient with HIV dementia: evidence for monocyte trafficking into brain. J Neurovirol. 2000;6 Suppl 1:S70-81. . Accessed August 14, 2018.
83. Spudich S, Gonzalez-Scarano F. HIV-1-Related Central Nervous System Disease: Current Issues in Pathogenesis, Diagnosis, and Treatment. Cold Spring Harb Perspect Med. 2012;2(6):a007120-a007120. doi:10.1101/cshperspect.a007120
84. Schnell G, Price RW, Swanstrom R, Spudich S. Compartmentalization and clonal amplification of HIV-1 variants in the cerebrospinal fluid during primary infection. J Virol. 2010;84(5):2395-2407. doi:10.1128/JVI.01863-09
85. Marcondes MCG, Morsey B, Emanuel K, Lamberty BG, Flynn CT, Fox HS. CD8+ T cells maintain suppression of simian immunodeficiency virus in the central nervous system. J Infect Dis. 2015;211(1):40-44. doi:10.1093/infdis/jiu401
86. Schmitz JE, Simon MA, Kuroda MJ, et al. A nonhuman primate model for the selective elimination of CD8+ lymphocytes using a mouse-human chimeric monoclonal antibody. Am J Pathol. 1999;154(6):1923-1932. doi:10.1016/S0002-9440(10)65450-8
87. Xu R, Feng X, Xie X, Zhang J, Wu D, Xu L. HIV-1 Tat protein increases the permeability of brain endothelial cells by both inhibiting occludin expression and cleaving occludin via matrix metalloproteinase-9. Brain Res. 2012;1436:13-19. doi:10.1016/j.brainres.2011.11.052
88. András IE, Pu H, Deli MA, Nath A, Hennig B, Toborek M. HIV-1 Tat protein alters tight junction protein expression and distribution in cultured brain endothelial cells. J Neurosci Res. 2003;74(2):255-265. doi:10.1002/jnr.10762
89. Awan FM, Anjum S, Obaid A, Ali A, Paracha RZ, Janjua HA. In-silico analysis of claudin-5 reveals novel putative sites for post-translational modifications: Insights into potential molecular determinants of blood-brain barrier breach during HIV-1 infiltration. Infect Genet Evol. 2014;27:355-365. doi:10.1016/j.meegid.2014.07.022
90. Peluso MJ, Meyerhoff DJ, Price RW, et al. Cerebrospinal fluid and neuroimaging biomarker abnormalities suggest early neurological injury in a subset of individuals during primary HIV infection. J Infect Dis. 2013;207(11):1703-1712. doi:10.1093/infdis/jit088
91. Lu C-H, Macdonald-Wallis C, Gray E, et al. Neurofilament light chain: A prognostic biomarker in amyotrophic lateral sclerosis. Neurology. 2015;84(22):2247-2257. doi:10.1212/WNL.0000000000001642
92. Tewari M, Monika , Varghse RK, Menon M, Seth P. Astrocytes mediate HIV-1 Tat-induced neuronal damage via ligand-gated ion channel P2X7R. J Neurochem. 2015;132(4):464-476. doi:10.1111/jnc.12953
93. Bethel-Brown C, Yao H, Hu G, Buch S. Platelet-derived growth factor (PDGF)-BB-mediated induction of monocyte chemoattractant protein 1 in human astrocytes: implications for HIV-associated neuroinflammation. J Neuroinflammation. 2012;9(1):262. doi:10.1186/1742-2094-9-262
94. Magnani JW, Dec GW. Myocarditis: Current Trends in Diagnosis and Treatment. Circulation. 2006;113(6):876-890. doi:10.1161/CIRCULATIONAHA.105.584532
95. Lipshultz SE, Mas CM, Henkel JM, Franco VI, Fisher SD, Miller TL. HAART to Heart: Highly active antiretroviral therapy and the risk of cardiovascular disease in HIV-infected or exposed children and adults. Expert Rev Anti Infect Ther. 2012. doi:10.1586/eri.12.53
96. Duan M, Yao H, Hu G, Chen X, Lund AK, Buch S. HIV Tat induces expression of ICAM-1 in HUVECs: implications for miR-221/-222 in HIV-associated cardiomyopathy. Mukhopadhyay P, ed. PLoS One. 2013;8(3):e60170. doi:10.1371/journal.pone.0060170
97. Feeney ER, Mallon PWG. HIV and HAART-Associated Dyslipidemia. Open Cardiovasc Med J. 2011;5:49-63.
98. Moyle G, Moutschen M, Martínez E, et al. Epidemiology, assessment, and management of excess abdominal fat in persons with HIV infection. AIDS Rev. 12(1):3-14. . Accessed August 14, 2018.
99. Greenfield JR, Samaras K, Jenkins AB, et al. Obesity is an important determinant of baseline serum C-reactive protein concentration in monozygotic twins, independent of genetic influences. Circulation. 2004;109(24):3022-3028. doi:10.1161/01.CIR.0000130640.77501.79
100. Grunfeld C, Rimland D, Gibert CL, et al. Association of upper trunk and visceral adipose tissue volume with insulin resistance in control and HIV-infected subjects in the FRAM study. J Acquir Immune Defic Syndr. 2007;46(3):283-290. . Accessed July 29, 2018.
101. Safrin S, Grunfeld C. Fat distribution and metabolic changes in patients with HIV infection. AIDS. 1999;13(18):2493-2505. . Accessed July 29, 2018.
102. Paula AA, Falcão MC, Pacheco AG. Metabolic syndrome in HIV-infected individuals: underlying mechanisms and epidemiological aspects. AIDS Res Ther. 2013;10(1):32. doi:10.1186/1742-6405-10-32
103. Janiszewski PM, Ross R, Despres J-P, et al. Hypertriglyceridemia and waist circumference predict cardiovascular risk among HIV patients: a cross-sectional study. Maartens G, ed. PLoS One. 2011;6(9):e25032. doi:10.1371/journal.pone.0025032
104. Guaraldi G, Zona S, Alexopoulos N, et al. Coronary Aging in HIV‐Infected Patients. Clin Infect Dis. 2009;49(11):1756-1762. doi:10.1086/648080
105. Jericó C, Knobel H, Montero M, et al. Metabolic syndrome among HIV-infected patients: prevalence, characteristics, and related factors. Diabetes Care. 2005;28(1):132-137. . Accessed August 1, 2018.
106. Samaras K, Wand H, Law M, Emery S, Cooper D, Carr A. Prevalence of metabolic syndrome in HIV-infected patients receiving highly active antiretroviral therapy using International Diabetes Foundation and Adult Treatment Panel III criteria: associations with insulin resistance, disturbed body fat compartmentalization, elevated C-reactive protein, and [corrected] hypoadiponectinemia. Diabetes Care. 2007;30(1):113-119. doi:10.2337/dc06-1075
107. Jacobson DL, Tang AM, Spiegelman D, et al. Incidence of metabolic syndrome in a cohort of HIV-infected adults and prevalence relative to the US population (National Health and Nutrition Examination Survey). J Acquir Immune Defic Syndr. 2006;43(4):458-466. doi:10.1097/01.qai.0000243093.34652.41
108. Paton NI, Kityo C, Hoppe A, et al. Assessment of Second-Line Antiretroviral Regimens for HIV Therapy in Africa. N Engl J Med. 2014;371(3):234-247. doi:10.1056/NEJMoa1311274
109. Wang Y, Lv Z, Chu Y. HIV protease inhibitors: a review of molecular selectivity and toxicity. HIV/AIDS - Res Palliat Care. 2015;7:95. doi:10.2147/HIV.S79956
110. Zhou H, Gurley EC, Jarujaron S, et al. HIV protease inhibitors activate the unfolded protein response and disrupt lipid metabolism in primary hepatocytes. Am J Physiol Gastrointest Liver Physiol. 2006;291(6):G1071-80. doi:10.1152/ajpgi.00182.2006
111. Murata H, Hruz PW, Mueckler M. The Mechanism of Insulin Resistance Caused by HIV Protease Inhibitor Therapy. J Biol Chem. 2000;275(27):20251-20254. doi:10.1074/jbc.C000228200
112. Murata H, Hruz PW, Mueckler M. Indinavir inhibits the glucose transporter isoform Glut4 at physiologic concentrations. AIDS. 2002;16(6):859-863. . Accessed August 1, 2018.
113. Gills JJ, Lopiccolo J, Tsurutani J, et al. Nelfinavir, A lead HIV protease inhibitor, is a broad-spectrum, anticancer agent that induces endoplasmic reticulum stress, autophagy, and apoptosis in vitro and in vivo. Clin Cancer Res. 2007;13(17):5183-5194. doi:10.1158/1078-R-07-0161
114. Carr A, Cooper DA. Adverse effects of antiretroviral therapy. Lancet. 2000;356(9239):1423-1430. doi:10.1016/S0140-6736(00)02854-3
115. Nasi M, Pinti M, Chiesa E, et al. Decreased mitochondrial DNA content in subcutaneous fat from HIV-infected women taking antiretroviral therapy as measured at delivery. Antivir Ther. 2011;16(3):365-372. doi:10.3851/IMP1764
116. Galluzzi L, Pinti M, Troiano L, et al. Changes in mitochondrial RNA production in cells treated with nucleoside analogues. Antivir Ther. 2005;10(1):191-195. . Accessed August 1, 2018.
117. Galluzzi L, Pinti M, Guaraldi G, et al. Altered mitochondrial RNA production in adipocytes from HIV-infected individuals with lipodystrophy. Antivir Ther. 2005;10 Suppl 2:M91-9. . Accessed August 14, 2018.
118. Shiramizu B, Shikuma KM, Kamemoto L, et al. Placenta and cord blood mitochondrial DNA toxicity in HIV-infected women receiving nucleoside reverse transcriptase inhibitors during pregnancy. J Acquir Immune Defic Syndr. 2003;32(4):370-374. . Accessed August 1, 2018.
119. Valcour V, Chalermchai T, Sailasuta N, et al. Central Nervous System Viral Invasion and Inflammation During Acute HIV Infection. J Infect Dis. 2012;206(2):275-282. doi:10.1093/infdis/jis326
120. U.S. Department of Health and Human Services, Health Resources and Services Administration HB. Medication-Assisted Addiction Treatment. HRSA CARE Action. 2011:1-10. . Accessed December 1, 2016.
121. Clifford DB, Ances BM. HIV-associated neurocognitive disorder. Lancet Infect Dis. 2013;13(11):976-986. doi:10.1016/S1473-3099(13)70269-X
122. Gannon P, Khan MZ, Kolson DL. Current understanding of HIV-associated neurocognitive disorders pathogenesis. Curr Opin Neurol. 2011;24(3):275-283. doi:10.1097/WCO.0b013e32834695fb
123. Neurological Complications of HIV | Johns Hopkins Medicine Health Library. . Accessed December 1, 2016.
124. Wolf C, An Y, Tanaka T, et al. Cross-Sectional and Longitudinal Effects of CREB1 Genotypes on Individual Differences in Memory and Executive Function: Findings from the BLSA. Front Aging Neurosci. 2017;9:142. doi:10.3389/fnagi.2017.00142
125. U.S. National Library of Medicine NC for BI. Reference SNP (refSNP) Cluster Report: rs10932201. . Accessed August 9, 2018.
126. U.S. National Library of Medicine NC for BI. Reference SNP (refSNP) Cluster Report: rs2253206. . Accessed August 9, 2018.
127. U.S. National Library of Medicine NC for BI. Reference SNP (refSNP) Cluster Report: rs6785. . Accessed August 9, 2018.
-----------------------
UNDERSTANDING THE PROGRESSION OF HIV-ASSOCIATED NEUROCOGNITIVE DISORDER (HAND) THROUGH CARDIOVASCULAR DISEASE AND MARKERS OF INFLAMMATION
by
Vessela Miladinova
BS, Psychology, University of Pittsburgh, 2016
Submitted to the Graduate Faculty of
Infectious Diseases and Microbiology
the Graduate School of Public Health in partial fulfillment
of the requirements for the degree of
Master of Public Health
University of Pittsburgh
2018
UNIVERSITY OF PITTSBURGH
Graduate School of Public Health
This essay was submitted
by
Vessela Miladinova
on
August 24, 2018
and approved by
Essay Advisor:
Jeremy Martinson, DPhil _________________________________
Assistant Professor
Infectious Diseases and Microbiology, Human Genetics
Graduate School of Public Health
University of Pittsburgh
Committee Member:
James Becker, PhD _________________________________
Professor
Psychiatry, Psychology, and Neurology
School of Medicine
University of Pittsburgh
Copyright © by Vessela Miladinova
2018
UNDERSTANDING THE PROGRESSION OF HIV-ASSOCIATED NEUROCOGNITIVE DISORDER (HAND) THROUGH CARDIOVASCULAR DISEASE AND MARKERS OF INFLAMMATION
Vessela Miladinova, MPH
University of Pittsburgh, 2018
................
................
In order to avoid copyright disputes, this page is only a partial summary.
To fulfill the demand for quickly locating and searching documents.
It is intelligent file search solution for home and business.
Related download
Related searches
- welcome to 2nd grade printable
- welcome to relias training course
- welcome to people s bank online
- welcome to city of new haven ct
- welcome to njmcdirect
- welcome to the team letter
- welcome to school songs preschool
- welcome to this place song
- welcome to this place
- welcome to gmail email
- open house welcome to parents
- welcome to patient portal