Sunday, July 21, 2019
Critical Analysis of Ageing Biomarkers
Critical Analysis of Ageing Biomarkers Introduction Biomarkers have been used since 1980, in aging and age related diseases. The use of biomarkers helps increase the understanding of a disease and help in diagnosis. Biomarkers can investigate a disease from early manifestations to final stages and can characterise biological age. Aging results in the deterioration of functional capacity and exposes people to diseases over time. The biomarkers should be measurable in the blood, tissues or cells and should be easily obtained from blood or urine samples. Biomarkers of exposure and biomarkers of disease are the two key types of biomarkers used in clinical settings. The effect and rate of aging is reliant upon individuals (Strimbu and Tavel, 2010). A reliable biomarker should be a predicator of life span not chronological age, should work on animals and humans and be frequently tested. There are three key types of biomarker; determine chronological age, predict life expectancy and disease predisposition. Biomarkers can enable the development of drugs to reverse or slow down the progression of a disease. Example of biomarkers of aging are cellular senescence, hormonal deregulation and oxidative stress (Sergievsky, 2004) and (Strimbu and Tavel, 2010) Biomarkers Elevated C-reactive protein (CRP) levels have been associated with increased cardiovascular disease risk. C reactive protein (CRP) biomarker is an acute phase reactant produced in the liver, following tissue injury, inflammation and infection is released into the bloodstream. An indication of cardiovascular disease risk could be the elevations in CRP levels in the blood, people with a higher or lower cardiovascular disease risk can be identified by measuring CRP levels in the blood. Elevated CRP levels cause inflammation and oxidative stress regardless of metabolic syndrome (Horiuchi and Mogi, 2011) and (Abraham et al, 2007). The data was analysed from 12 European countries and included patients over 50 years that had at least one cardiovascular risk factor with no history of cardiovascular disease. Diabetics were also analysed. Glycated haemoglobin levels were positively correlated with CRP levels and there was a negative correlation with high-density lipoprotein cholesterol levels. Women that had increased cardiovascular disease risk factor and more metabolic syndrome markers had elevated CRP levels. 30% of diabetic patients that were not receiving statin therapy had CRP levels âⰠ¥3mg/L and 50% CRP levels were âⰠ¥2mg/L, subjects with intermediate levels of cardiovascular disease risk. Mean CRP levels were âⰠ¥4.2mg/L in the overall population, levels were similar to subjects with diabetes. Subjects were over 50 years however no association was found between elevated CRP levels and age. Almost 50% subjects regardless of cardiovascular disease risk factor had CRP levels of âⰠ¥2mg/L. Increasing CRP levels were associated with metabolic syndrome markers. There was an association between raised CRP levels and greater cardiovascular risk (Halcox et al, 2014). This study looked at age related increase in compartments of visceral fat and the association with harmful changes in blood lipid profile and insulin sensitivity in non-obese women. Visceral fat has been suggested to be a predictor of variations plasma lipid levels, lipoprotein and plasma glucose-insulin concentrations. Abdominal adiposity increase helps identify age related decline in insulin sensitivity and plasma lipid levels. 178 women were categorized into four age groups, visceral and subcutaneous abdominal adipose tissue areas, body composition, blood lipid profile, glucose disposal and aerobic fitness were directly analysed. With age, there was an increase in abdominal adipose tissue. An age related proliferation was detected in total cholesterol (p The study investigated age related fluctuations in cutaneous sensation, areas of the palm and dorsal surface of the hand and nerves in the hand were observed. In eight sites of the glabrous skin and two on hairy skin on both hands cutaneous perceptual threshold was tested. 70 subjects aged between 20-88 years were used. Three tests were used von Frey thresholds, two point stimulations and Texture discrimination. The threshold for cutaneous sensation increased significantly with age (P Two point stimulation, showed increased threshold with age (P=0.046), lowest thresholds were observed in 20s (5mm) and in 60s had highest (7mm). Each area had increased loss of sensitivity with age. No significant increase was observed for threshold for texture discrimination, there was a stable surge until the 80s. From the 20s (0.27mm) up to 70s (0.44mm) an increase was observed however in the 80s (31mm) there was a decrease.No difference was seen between various sites of the hand, non-dominant/dominant and sexes. After the age of 60 males and 70 for females, there was an accelerated decline in cutaneous sensation (Bowden and McNutty, 2013). The obvious sign of aging is the decrease in muscle mass, function and increase fatigability in old age, it is suggested that there is a decline in myosin heavy chain synthesis with sacropenia. The synthesis rate decline highlights functional consequences of a weakened remodelling process. Muscle mass is regulated by muscle protein synthesis and breakdown, a lower synthesis rate compared to breakdown may result in diminished muscle mass. The loss of lean mass and decreased performance highlights metabolic changes that occur with sacorpenia. Myosin heavy chain is involved in the hydrolysis ATP to ADP, it is vital for muscle contractile functions. Myosin heavy chain synthesis rate was measured instantaneously with rates of mixed muscle and sarcoplasmic proteins. In young to middle aged people a decline in synthesis rate of mixed muscle protein (p Age related bone loss in men and women is the result of decline in hormones such as oestrogen and estradiol. It is understood that tissue growth and metabolism is regulated by insulin like growth factor (IGF) and binding proteins. The growth endorsing regulatory system IGF is growth hormone dependant and independent, it is a complex system. Six IGF binding proteins included in the IGF system as well as IGF-I and IGF-II. Osteoblastic diversity and bone development is improved by IGF-I and IGF-II which are abundant growth factors in bone tissue. These factors upsurge the production of type1 collagen fibres and apposition rates of bone matrix, degradation of bone collagen is reduced. The effects of IGF-I and IGF-II maybe potentiated or repressed by IGFBPs although they are anabolic. Metabolic activity and clearance of IGF-I and IGF-II is regulated by IGFBPs, IGF independent action that can inhibit or stimulate cellular function by four IGFBPs. Osteoblasts are able to synthesize all six IGFBPs. The role of serum levels of IGF-I and IGF-II, and IGFBP-1, 2 and 3 on bone mineral density was examined on various skeletal sites, in an age stratified random sample of 344 males and females. IGF-I and IGFBP-3 levels declined with increasing age in males and females, IGFBP-2 levels increased with age. Associations between IGFBP-2 and lateral spine BMD were not observed however with age adjustment IGFBPs with BMD were significant for males and females. The most significant independent predictor of bone mineral density was IGFBP-2 amongst all the ones studies in males and females (Amin et al, 2004) Alterations in brain tissue and grey matter can help in diagnosis and treatment of Alzheimer disease, multiple sclerosis, schizophrenia etc. Aging has a profound effect on the brain. Grey and white matter contrast functionally and anatomically as well as having different patterns in brain development. MRI imaging is an effective way of investigating brain morphometric in vivo enabling the production of accurate and reliable information. Investigations have looked at age specific effects on various brain regions findings from the analysis have revealed brain tissue loss with age may vary between the various brain regions and hemispheres. 55 healthy volunteers aged between 20 and 86 were separated into two groups (20-49 and 50-86). Current or existing neuropsychiatric illness and substance abuse was excluded by a neurologist in an interview. Evaluations were done using MRI imaging and 50 separate brain volume images were under review. Results revealed reduction in grey matter with increasing age in males and females, deterioration begins at 20 years of age. Increasing age results in significant loss grey matter (4.9%). Increase in white matter is observed however accelerated decline in instigated around age of 40. A significant difference was observed between the two age groups (p=0.38), older people had significantly lower grey and white matter in the intracranial space as compared to younger ones (p Discussion Elevations of the biomarkers were helpful indicators in the development of disease and understanding age related changes in the body. Elevated CRP levels were observed in majority of patients regardless of cardiovascular risk. However, CRP is a non-specific inflammatory marker and elevations could be due to other biological processes. Amplified CRP levels is not the foremost casual factor for cardiovascular disease the levels (Halcox et al, 2014). Abdominal fat accumulation were seen to be an independent factor of age related change in plasma lipid levels and insulin sensitivity. Results revealed that abdominal visceral fat increased with age. The findings were consistent because age had an effect on insulin sensitivity (DeNino et al, 2001). Cutaneous sensation deteriorates with age, differences are also observed between sexes and hands. The extent of deterioration may have been undervalued this could have affected the results. There was difficulty in the assessment of skin hydration and the role of skin mechanics was inadequate. The associations between fine motor control and cutaneous sensation could be an area to study (Bowden and McNutty, 2013). There was an age related decline in myosin heavy chain synthesis but average synthesis rates were measured. Muscle mass decline was associated with incapacity for the skeletal muscle to remodel. Insulin resistance could have a role in declined myosin heavy chain synthesis due to its chronic effect. Differences between males and females were established. Data was normalized to whole body protein turnover to fat free mass because normalizations to body composition were fraught. Future research should investigate whether age related decline in synthesis rate could be retreated by use of replacement hormones (Balagopal et al, 1997). Age related bone loss was evident in males and females; the predictor for bone density was IGFBP-2. The results were not generalizable to the cognitively impaired. Correlations were observed between serum levels of IGF-1 and tissue levels within bone but there was limited understanding of the action at a local level. Future research should be directed towards investigating the complex role of the IGF system influence on bone metabolism (Amin et al, 2004). The exclusion of subjects with neurological conditions made comparisons difficult between young and old. An estimation of brain tissue loss can be done in healthy living subjects. The findings from the study were consistent with longitudinal studies (Robert et al, 2002). References Anti aging team . (2014). Biomarkers of aging . Available: http://www.anti-aging-guide.com/62biomakers.php. Last accessed 28th Feb 2015. Gertrude H. Sergievsky. (2004). Biomarkers: Potential Uses and Limitations. Taub Institute for Research on Alzheimerââ¬â¢s Disease and the Aging Brain,. 1 (2), 182-188. Jacob Abraham, Catherine Y. Campbell, Aamir Cheema, Ty J. Gluckman, Roger S. Blumenthal, Peter Danyi,. (2007). C-Reactive Protein in Cardiovascular Risk Assessment:. The Journal of Cardiometabolic Syndrome. 2 (2), 119-123. Jocelyn L. Bowden Penelope A. McNulty. (2012). Age-related changes in cutaneous sensation in the healthy. American Aging Association. 35 (2), 1077-1089. Julian PJ Halcox1,2*, Carine Roy3, Florence Tubach3,4, Josà © R Banegas5,6, Jean Dallongeville7, Guy De Backer8,. (2014). C-reactive protein levels in patients at. BMC Cardiovascular Disorders. 14 (25), 1-9. Kyle Strimbu and Jorge A. Tavel. (2010). What are Biomarkers?. 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