Are there any Biomarkers of Aging? Biomarkers of the Brain

Vincent van Ginneken*

DOI: 10.26717/BJSTR.2017.01.000151

Received: June 12, 2017   Published: June 27, 2017

To view the Full Article   Peer-reviewed Article PDF

Abstract

Biomarkers of aging would give the true “biological age”, which may be different from the chronological age. Population perspectives regarding to aging, age-related diseases and life-expectancy of populations are extremely useful for e.g. governments and/or politicians. The problem with finding biomarkers of aging is that there are several theories of aging related to research areas like: oxidative stress, mitochondrial damage, telomeres shortage and cellular senescence, apoptosis and genetic predisposition. Although maximum lifespan would be a means of validating biomarkers of aging, it would not be a practical means for long-lived species such as humans because longitudinal studies would take far too much time. Ideally, biomarkers of aging should assay the biological process of aging and not a predisposition to disease.

Despite the fact that few biomarkers are found for aging some examples are given from Systems Biology: metabolomics, proteomics, genomics and lipidomics. While as somatic index Sarcopenia or “Nutritional Frailty” (≈nutritional stress), has been well documented for potential biomarkers of aging human brain research is underestimated. One target that has been looked at in this manuscript are biomarkers of brain aging. So far, brain function and age have proved too complex to produce reliable biomarkers. Here we present as a start material from the Netherlands Brain Bank, from a small cohort of elderly patients (>65 years) (all NIDDM diabetes patients) frequency distributions of the ultimate scope of the lifespan in neural tissue and some histopathological post mortem determined biomarkers such as Healthy (39.4%), mild- Alzheimer (32.8%), Dementia (13.5%) , Multiple Sclerosis (4.2%) several Dualistic Mix-forms (3.9%), Vascular Dementia (3.5%) and Parkinson (2.7%). Brain disease pattern were split up related to age and gender. Mix varieties and Vasculair Dementia are more common in the male brain while in the female brain mild-Alzheimer disease is more common. All the scores for brain somatic index (Control and diseased) are skewed to the left which is indicative for brain shrinkage of this elderly (>65+ years old) population. Brain diseases are not interrelated with Body Mass Index (BMI) in the elderly with type 2 diabetes so obesity is not the major cause for their morbidity

Keywords: Biomarkers of aging; Elderly; Reductionism; Systems biology; Metabolomics; Proteomics; Genomics; Lipidomics; Somatic; Sarcopenia; Brain; Type 2 Diabetes; Mild-Alzheimer; Dementia; Multiple Sclerosis; Dualistic Mix-Forms; Vascular Dementia And Parkinson; Morbidity; Body Mass Index (Bmi)

Abbreviations:MLS: Maximum Life Span; ROS: Reactive Oxygen Species; HD: Huntington’s Diseases; HMDB: Human Metabolome Database; NHGRI: National Human Genome Research; GC-MS: Gas chromatography mass spectrometry; LC-MS: liquid chromatography mass spectrometry; MD-LCMS: multidimensional liquid chromatography mass spectrometry; NMR: Nuclear magnetic resonance; PTM: Post-translational modification; CR: Caloric Restriction; SPM30: senescence marker protein-30; SAA-1: Serum Amyloid protein A-1; NGS: Next Generation Sequencing ; BBB: Blood-Brain-Barrier ; VBM: Voxel-based-morphometry

Introduction | Personalized Medical Treatment and Biomarkers of Aging | Brain Biomarkers of Aging| Perspectives| Acknowledgement | References | Figures | Tables |