Longevity Wiki

Brain Aging

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File:Brain 090407.jpg

The brain is remarkably sensitive to the effects of aging, displaying as changes in structure and cognitive capacity, as well as increased risk for developing certain neurological disorders.[1][2] Brain health refers to the maintenance of brain functions in several aspects:

  1. Cognitive health: the ability to adequately think, learn, and remember;
  2. Motor function: the ability to control movements and balance;
  3. Emotional health: the ability to interpret and respond to emotions;
  4. Tactile function: the ability to feel and respond to sensations of touch, including pressure, pain, and temperature.[3]

Molecular and Cellular Changes

At the molecular level, brain aging, similarly to all other organ systems, is characterized by changes in gene expression, epigenetic modifications, and alterations in protein synthesis and turnover. It is also associated with the accumulation of toxic protein aggregates, such as β-amyloid and tau, which can disrupt neuronal function and contribute to the development of neurodegenerative diseases.[4][5] At the cellular level, brain aging is characterized by the accumulation of cell damage, including oxidative stress, DNA damage, and protein misfolding. This damage can lead to the dysfunction and death of brain cells, including neurons and glia. Studies have shown that dendritic arbors and spines decrease in size and/or number in cortex as a result of aging.[6][7] Aging also sets off a decline in the regenerative capacity of brain cells, such as decreased neurogenesis and oligodendrogenesis.[8][9]

System and Organismal Level Changes

At the system level, brain aging includes changes in brain connectivity and function such as alterations in neural activity, neurotransmitter function, and white matter integrity. Aging is associated with a decline in the function of essential neurotransmitter systems such as dopamine and acetylcholine, which can lead to cognitive impairment. Brain aging is associated also with changes in brain structure, such as the loss of gray matter volume and changes in white matter microstructure.[10][11][12] At the organismal level, brain aging is associated with declines in cognitive function, sensory function, and motor function. Age-related changes in the cardiovascular system, immune system, and endocrine system can also impact brain function and contribute to age-related neurodegenerative diseases.[5][13]

Hallmarks of Aging and Neurodegenerative Disorders

Hallmarks of aging, including mitophagy, cellular senescence, genomic instability, and protein aggregation, have been related to the age-associated neurodegenerative and cerebrovascular disorders.[14] Furthermore, the most frequent neurodegenerative diseases share the common attribute of protein aggregation. The aggregation of senile plaques containing amyloid-β peptide and the formation of intraneuronal tau containing neurofibrillary tangles in Alzheimer’s disease and the accumulation of misfolded α-synuclein in Parkinson’s disease are major pathogenic aspects of these diseases.[15] Protein aggregation is also a feature of amyotrophic lateral sclerosis and frontotemporal lobar dementia.[16]

Brain tissues comprise primarily postmitotic cells, including neurons and oligodendrocytes, which are sensitive to age-related alterations such as DNA damage or methylation. Indeed, Parkinson’s disease patients have been reported to consistently exhibit DNA methylation patterns associated with advanced aging.[17] Advanced aging has been also related to enhanced mitochondrial dysfunction and damage, thus promoting neurodegeneration via the production of ROS and the advancing neuroinflammation.[5]

In addition to the most common age-associated neurodegenerative diseases such as Alzheimer’s and Parkinson’s diseases and stroke, others included are age-related macular degeneration associated with blurred or distorted vision; multiple sclerosis associated with myelin damage, which disturbs the information flow within brain, and between brain and body; amyotrophic lateral sclerosis (Lou Gehrig’s disease) affecting motor neurons thus causing loss of muscle control; Huntington’s disease associated with involuntary movements, difficulty with coordination, and changes in mood and behavior; and various kinds of dementias including Lewy bodies dementia characterized by the presence of abnormal protein deposits in the brain, which causes changes in attention and alertness, visual hallucinations, and movement disorders, and vascular dementia associated with damage to the blood vessels that supply blood to the brain, which causes memory loss, difficulty with decision-making, and changes in mood and behavior.[5][11][18][19]

Brain Size

 
Average brain weight for males and females over lifespan. From the study Changes in brain weights during the span of human life.

A human baby's brain at birth averages 369 cm3 and increases, during the first year of life, to about 961 cm3, after which the growth rate declines. Brain volume peaks at the teenage years,[20] and after the age of 40 it begins declining at 5% per decade, speeding up around 70.[11] Average adult male brain weight is 1,345 grams (47.4 oz), while an adult female has an average brain weight of 1,222 grams (43.1 oz).[21] (This does not take into account neuron density nor brain-to-body mass ratio; men on average also have larger bodies than women.) Males have been found to have on average greater cerebral, cerebellar and cerebral cortical lobar volumes, except possibly left parietal.[22] The gender differences in size vary by more specific brain regions. Studies have tended to indicate that men have a relatively larger amygdala and hypothalamus, while women have a relatively larger caudate and hippocampi. When covaried for intracranial volume, height, and weight, Kelly (2007) indicates women have a higher percentage of gray matter, whereas men have a higher percentage of white matter and cerebrospinal fluid. There is high variability between individuals in these studies, however.[23]

However, Yaki (2011) found no statistically significant gender differences in the gray matter ratio for most ages (grouped by decade), except in the 3rd and 6th decades of life in the sample of 758 women and 702 men aged 20–69.[24] The average male in their third decade (ages 20–29) had a significantly higher gray matter ratio than the average female of the same age group. In contrast, among subjects in their sixth decade, the average woman had a significantly larger gray matter ratio, though no meaningful difference was found among those in their 7th decade of life.

Total cerebral and gray matter volumes peak during the ages from 10–20 years (earlier in girls than boys), whereas white matter and ventricular volumes increase. There is a general pattern in neural development of childhood peaks followed by adolescent declines (e.g. synaptic pruning). Consistent with adult findings, average cerebral volume is approximately 10% larger in boys than girls. However, such differences should not be interpreted as imparting any sort of functional advantage or disadvantage; gross structural measures may not reflect functionally relevant factors such as neuronal connectivity and receptor density, and of note is the high variability of brain size even in narrowly defined groups, for example children at the same age may have as much as a 50% differences in total brain volume.[25] Young girls have on average relative larger hippocampal volume, whereas the amygdalae are larger in boys.[23] However, multiple studies[26][26] have found a higher synaptic density in males: a 2008 study reported that men had a significantly higher average synaptic density of 12.9 × 108 per cubic millimeter, whereas in women it was 8.6 × 108 per cubic millimeter, a 33% difference. Other studies have found an average of 4 billion more neurons in the male brain,[27] corroborating this difference, as each neuron has on average 7,000 synaptic connections to other neurons.

Significant dynamic changes in brain structure take place through adulthood and aging, with substantial variation between individuals. In later decades, men show greater volume loss in whole brain volume and in the frontal lobes, and temporal lobes, whereas in women there is increased volume loss in the hippocampi and parietal lobes.[23] Men show a steeper decline in global gray matter volume, although in both sexes it varies by region with some areas exhibiting little or no age effect. Overall white matter volume does not appear to decline with age, although there is variation between brain regions.[28]

Research Statistics

 
Yearly growth of the number of documents related to brain aging in the CAS Content Collection.[29]

There is a steady, nearly exponential growth of the number of journal publications related to brain aging in the CAS Content Collection over time, remarkably intense in the last two years, a sign of the enhanced scientific interest in this area. At the same time, patenting activity is low, probably awaiting the knowledge accumulation reaching a critical level.

Further Reading

  • 2023, Aging Hallmarks and Progression and Age-Related Diseases: A Landscape View of Research Advancement [29]

See Also

References

  1. ↑ Ferreira LK & Busatto GF: Resting-state functional connectivity in normal brain aging. Neurosci Biobehav Rev 2013. (PMID 23333262) [PubMed] [DOI] The world is aging and, as the elderly population increases, age-related cognitive decline emerges as a major concern. Neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), allow the investigation of the neural bases of age-related cognitive changes in vivo. Typically, fMRI studies map brain activity while subjects perform cognitive tasks, but such paradigms are often difficult to implement on a wider basis. Resting-state fMRI (rs-fMRI) has emerged as an important alternative modality of fMRI data acquisition, during which no specific task is required. Due to such simplicity and the reliability of rs-fMRI data, this modality presents increased feasibility and potential for clinical application in the future. With rs-fMRI, fluctuations in regional brain activity can be detected across separate brain regions and the patterns of intercorrelation between the functioning of these regions are measured, affording quantitative indices of resting-state functional connectivity (RSFC). This review article summarizes the results of recent rs-fMRI studies that have documented a variety of aging-related RSFC changes in the human brain, discusses the neurophysiological hypotheses proposed to interpret such findings, and provides an overview of the future, highly promising perspectives in this field.
  2. ↑ Damoiseaux JS: Effects of aging on functional and structural brain connectivity. Neuroimage 2017. (PMID 28159687) [PubMed] [DOI] Over the past decade there has been an enormous rise in the application of functional and structural connectivity approaches to explore the brain's intrinsic organization in healthy and clinical populations. The notion underlying the application of these approaches to study aging is that subtle age-related disruption of the brain's regional integrity and information flow across the brain, are expressed by age-related differences in functional and structural connectivity. In this review I will discus recent advances in our understanding of how age affects our brain's intrinsic organization, and I will share my perspective on potential challenges and future directions of the field.
  3. ↑ Cognitive Health and Older Adults. https://www.nia.nih.gov/health/cognitive-health-and-older-adults (accessed Apr 26, 2023).
  4. ↑ Zia A et al.: Molecular and cellular pathways contributing to brain aging. Behav Brain Funct 2021. (PMID 34118939) [PubMed] [DOI] [Full text] Aging is the leading risk factor for several age-associated diseases such as neurodegenerative diseases. Understanding the biology of aging mechanisms is essential to the pursuit of brain health. In this regard, brain aging is defined by a gradual decrease in neurophysiological functions, impaired adaptive neuroplasticity, dysregulation of neuronal Ca2+ homeostasis, neuroinflammation, and oxidatively modified molecules and organelles. Numerous pathways lead to brain aging, including increased oxidative stress, inflammation, disturbances in energy metabolism such as deregulated autophagy, mitochondrial dysfunction, and IGF-1, mTOR, ROS, AMPK, SIRTs, and p53 as central modulators of the metabolic control, connecting aging to the pathways, which lead to neurodegenerative disorders. Also, calorie restriction (CR), physical exercise, and mental activities can extend lifespan and increase nervous system resistance to age-associated neurodegenerative diseases. The neuroprotective effect of CR involves increased protection against ROS generation, maintenance of cellular Ca2+ homeostasis, and inhibition of apoptosis. The recent evidence about the modem molecular and cellular methods in neurobiology to brain aging is exhibiting a significant potential in brain cells for adaptation to aging and resistance to neurodegenerative disorders.
  5. ↑ 5.0 5.1 5.2 5.3 Azam S et al.: The Ageing Brain: Molecular and Cellular Basis of Neurodegeneration. Front Cell Dev Biol 2021. (PMID 34485280) [PubMed] [DOI] [Full text] Ageing is an inevitable event in the lifecycle of all organisms, characterized by progressive physiological deterioration and increased vulnerability to death. Ageing has also been described as the primary risk factor of most neurodegenerative diseases, including Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and frontotemporal lobar dementia (FTD). These neurodegenerative diseases occur more prevalently in the aged populations. Few effective treatments have been identified to treat these epidemic neurological crises. Neurodegenerative diseases are associated with enormous socioeconomic and personal costs. Here, the pathogenesis of AD, PD, and other neurodegenerative diseases has been presented, including a summary of their known associations with the biological hallmarks of ageing: genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, mitochondrial dysfunction, cellular senescence, deregulated nutrient sensing, stem cell exhaustion, and altered intercellular communications. Understanding the central biological mechanisms that underlie ageing is important for identifying novel therapeutic targets for neurodegenerative diseases. Potential therapeutic strategies, including the use of NAD+ precursors, mitophagy inducers, and inhibitors of cellular senescence, has also been discussed.
  6. ↑ Duan H et al.: Age-related dendritic and spine changes in corticocortically projecting neurons in macaque monkeys. Cereb Cortex 2003. (PMID 12902394) [PubMed] [DOI] Alterations in neuronal morphology occur in primate cerebral cortex during normal aging, vary depending on the neuronal type, region and cortical layer, and have been related to memory and cognitive impairment. We analyzed how such changes affect a specific subpopulation of cortical neurons forming long corticocortical projections from the superior temporal cortex to prefrontal area 46. These neurons were identified by retrograde transport in young and old macaque monkeys. Dendritic arbors of retrogradely labeled neurons were visualized in brain slices by intracellular injection of Lucifer Yellow, and reconstructed three-dimensionally using computer-assisted morphometry. Total dendritic length, numbers of segments, numbers of spines, and spine density were analyzed in layer III pyramidal neurons forming the projection considered. Sholl analysis was used to determine potential age-related changes in dendritic complexity. We observed statistically significant age-related decreases in spine numbers and density on both apical and basal dendritic arbors in these projection neurons. On apical dendrites, changes in spine numbers occurred mainly on the proximal dendrites but spine density decreased uniformly among the different branch orders. On basal dendrites, spine numbers and density decreased preferentially on distal branches. Regressive dendritic changes were observed only in one particular portion of the apical dendrites, with the general dendritic morphology and extent otherwise unaffected by aging. In view of the fact that there is no neuronal loss in neocortex and hippocampus in old macaque monkeys, it is possible that the memory and cognitive decline known to occur in these animals is related to rather subtle changes in the morphological and molecular integrity of neurons subserving identifiable neocortical association circuits that play a critical role in cognition.
  7. ↑ Dickstein DL et al.: Dendritic spine changes associated with normal aging. Neuroscience 2013. (PMID 23069756) [PubMed] [DOI] [Full text] Given the rapid rate of population aging and the increased incidence of cognitive decline and neurodegenerative diseases with advanced age, it is important to ascertain the determinants that result in cognitive impairment. It is also important to note that much of the aged population exhibit 'successful' cognitive aging, in which cognitive impairment is minimal. One main goal of normal aging studies is to distinguish the neural changes that occur in unsuccessful (functionally impaired) subjects from those of successful (functionally unimpaired) subjects. In this review, we present some of the structural adaptations that neurons and spines undergo throughout normal aging and discuss their likely contributions to electrophysiological properties and cognition. Structural changes of neurons and dendritic spines during aging, and the functional consequences of such changes, remain poorly understood. Elucidating the structural and functional synaptic age-related changes that lead to cognitive impairment may lead to the development of drug treatments that can restore or protect neural circuits and mediate cognition and successful aging.
  8. ↑ Sikora E et al.: Cellular Senescence in Brain Aging. Front Aging Neurosci 2021. (PMID 33732142) [PubMed] [DOI] [Full text] Aging of the brain can manifest itself as a memory and cognitive decline, which has been shown to frequently coincide with changes in the structural plasticity of dendritic spines. Decreased number and maturity of spines in aged animals and humans, together with changes in synaptic transmission, may reflect aberrant neuronal plasticity directly associated with impaired brain functions. In extreme, a neurodegenerative disease, which completely devastates the basic functions of the brain, may develop. While cellular senescence in peripheral tissues has recently been linked to aging and a number of aging-related disorders, its involvement in brain aging is just beginning to be explored. However, accumulated evidence suggests that cell senescence may play a role in the aging of the brain, as it has been documented in other organs. Senescent cells stop dividing and shift their activity to strengthen the secretory function, which leads to the acquisition of the so called senescence-associated secretory phenotype (SASP). Senescent cells have also other characteristics, such as altered morphology and proteostasis, decreased propensity to undergo apoptosis, autophagy impairment, accumulation of lipid droplets, increased activity of senescence-associated-β-galactosidase (SA-β-gal), and epigenetic alterations, including DNA methylation, chromatin remodeling, and histone post-translational modifications that, in consequence, result in altered gene expression. Proliferation-competent glial cells can undergo senescence both in vitro and in vivo, and they likely participate in neuroinflammation, which is characteristic for the aging brain. However, apart from proliferation-competent glial cells, the brain consists of post-mitotic neurons. Interestingly, it has emerged recently, that non-proliferating neuronal cells present in the brain or cultivated in vitro can also have some hallmarks, including SASP, typical for senescent cells that ceased to divide. It has been documented that so called senolytics, which by definition, eliminate senescent cells, can improve cognitive ability in mice models. In this review, we ask questions about the role of senescent brain cells in brain plasticity and cognitive functions impairments and how senolytics can improve them. We will discuss whether neuronal plasticity, defined as morphological and functional changes at the level of neurons and dendritic spines, can be the hallmark of neuronal senescence susceptible to the effects of senolytics.
  9. ↑ Tripathi A: New cellular and molecular approaches to ageing brain. Ann Neurosci 2012. (PMID 25205996) [PubMed] [DOI] [Full text] The last decade has witnessed a mammoth progress in the area of brain ageing. Recent gene profiling and brain imaging techniques have made it possible to explore the dark areas of ageing neurons in a new molecular perspective. Many conserved pathways and cellular and molecular mechanisms particularly nuclear mitochondrial molecular interactions are known now. Disruptions in mitochondrial function and reduction in cellular antioxidative and immunoproteins contribute to generation of reactive oxygen species (ROS) which leads to deteriorated adult neurogenesis, reduced white matter and compromised neural plasticity. The overall deteriorated structure and function of neurons is manifested in form of cognitive decline and prolonged neurodegenerative disorders. Dietary restrictions (DR), physical and mental activities however have been shown to counter these ailments. However more precise molecular dynamics at protein levels is still debatable which is the future task for neuroscientists.
  10. ↑ Mattson MP & Arumugam TV: Hallmarks of Brain Aging: Adaptive and Pathological Modification by Metabolic States. Cell Metab 2018. (PMID 29874566) [PubMed] [DOI] [Full text] During aging, the cellular milieu of the brain exhibits tell-tale signs of compromised bioenergetics, impaired adaptive neuroplasticity and resilience, aberrant neuronal network activity, dysregulation of neuronal Ca2+ homeostasis, the accrual of oxidatively modified molecules and organelles, and inflammation. These alterations render the aging brain vulnerable to Alzheimer's and Parkinson's diseases and stroke. Emerging findings are revealing mechanisms by which sedentary overindulgent lifestyles accelerate brain aging, whereas lifestyles that include intermittent bioenergetic challenges (exercise, fasting, and intellectual challenges) foster healthy brain aging. Here we provide an overview of the cellular and molecular biology of brain aging, how those processes interface with disease-specific neurodegenerative pathways, and how metabolic states influence brain health.
  11. ↑ 11.0 11.1 11.2 Peters R: Ageing and the brain. Postgrad Med J 2006. (PMID 16461469) [PubMed] [DOI] [Full text] Ageing causes changes to the brain size, vasculature, and cognition. The brain shrinks with increasing age and there are changes at all levels from molecules to morphology. Incidence of stroke, white matter lesions, and dementia also rise with age, as does level of memory impairment and there are changes in levels of neurotransmitters and hormones. Protective factors that reduce cardiovascular risk, namely regular exercise, a healthy diet, and low to moderate alcohol intake, seem to aid the ageing brain as does increased cognitive effort in the form of education or occupational attainment. A healthy life both physically and mentally may be the best defence against the changes of an ageing brain. Additional measures to prevent cardiovascular disease may also be important.
  12. ↑ Sowell ER et al.: Mapping cortical change across the human life span. Nat Neurosci 2003. (PMID 12548289) [PubMed] [DOI] We used magnetic resonance imaging and cortical matching algorithms to map gray matter density (GMD) in 176 normal individuals ranging in age from 7 to 87 years. We found a significant, nonlinear decline in GMD with age, which was most rapid between 7 and about 60 years, over dorsal frontal and parietal association cortices on both the lateral and interhemispheric surfaces. Age effects were inverted in the left posterior temporal region, where GMD gain continued up to age 30 and then rapidly declined. The trajectory of maturational and aging effects varied considerably over the cortex. Visual, auditory and limbic cortices, which are known to myelinate early, showed a more linear pattern of aging than the frontal and parietal neocortices, which continue myelination into adulthood. Our findings also indicate that the posterior temporal cortices, primarily in the left hemisphere, which typically support language functions, have a more protracted course of maturation than any other cortical region.
  13. ↑ Blinkouskaya Y et al.: Brain aging mechanisms with mechanical manifestations. Mech Ageing Dev 2021. (PMID 34600936) [PubMed] [DOI] [Full text] Brain aging is a complex process that affects everything from the subcellular to the organ level, begins early in life, and accelerates with age. Morphologically, brain aging is primarily characterized by brain volume loss, cortical thinning, white matter degradation, loss of gyrification, and ventricular enlargement. Pathophysiologically, brain aging is associated with neuron cell shrinking, dendritic degeneration, demyelination, small vessel disease, metabolic slowing, microglial activation, and the formation of white matter lesions. In recent years, the mechanics community has demonstrated increasing interest in modeling the brain's (bio)mechanical behavior and uses constitutive modeling to predict shape changes of anatomically accurate finite element brain models in health and disease. Here, we pursue two objectives. First, we review existing imaging-based data on white and gray matter atrophy rates and organ-level aging patterns. This data is required to calibrate and validate constitutive brain models. Second, we review the most critical cell- and tissue-level aging mechanisms that drive white and gray matter changes. We focuse on aging mechanisms that ultimately manifest as organ-level shape changes based on the idea that the integration of imaging and mechanical modeling may help identify the tipping point when normal aging ends and pathological neurodegeneration begins.
  14. ↑ Hou Y et al.: Ageing as a risk factor for neurodegenerative disease. Nat Rev Neurol 2019. (PMID 31501588) [PubMed] [DOI] Ageing is the primary risk factor for most neurodegenerative diseases, including Alzheimer disease (AD) and Parkinson disease (PD). One in ten individuals aged ≥65 years has AD and its prevalence continues to increase with increasing age. Few or no effective treatments are available for ageing-related neurodegenerative diseases, which tend to progress in an irreversible manner and are associated with large socioeconomic and personal costs. This Review discusses the pathogenesis of AD, PD and other neurodegenerative diseases, and describes their associations with the nine biological hallmarks of ageing: genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, mitochondrial dysfunction, cellular senescence, deregulated nutrient sensing, stem cell exhaustion and altered intercellular communication. The central biological mechanisms of ageing and their potential as targets of novel therapies for neurodegenerative diseases are also discussed, with potential therapies including NAD+ precursors, mitophagy inducers and inhibitors of cellular senescence.
  15. ↑ Bourdenx M et al.: Protein aggregation and neurodegeneration in prototypical neurodegenerative diseases: Examples of amyloidopathies, tauopathies and synucleinopathies. Prog Neurobiol 2017. (PMID 26209472) [PubMed] [DOI] Alzheimer's and Parkinson's diseases are the most prevalent neurodegenerative diseases that generate important health-related direct and indirect socio-economic costs. They are characterized by severe neuronal losses in several disease-specific brain regions associated with deposits of aggregated proteins. In Alzheimer's disease, β-amyloid peptide-containing plaques and intraneuronal neurofibrillary tangles composed of hyperphosphorylated microtubule-associated protein tau are the two main neuropathological lesions, while Parkinson's disease is defined by the presence of Lewy Bodies that are intraneuronal proteinaceous cytoplasmic inclusions. α-Synuclein has been identified as a major protein component of Lewy Bodies and heavily implicated in the pathogenesis of Parkinson's disease. In the past few years, evidence has emerged to explain how these aggregate-prone proteins can undergo spontaneous self-aggregation, propagate from cell to cell, and mediate neurotoxicity. Current research now indicates that oligomeric forms are probably the toxic species. This article discusses recent progress in the understanding of the pathogenesis of these diseases, with a focus on the underlying mechanisms of protein aggregation, and emphasizes the pathophysiological molecular mechanisms leading to cellular toxicity. Finally, we present the putative direct link between β-amyloid peptide and tau in causing toxicity in Alzheimer's disease as well as α-synuclein in Parkinson's disease, along with some of the most promising therapeutic strategies currently in development for those incurable neurodegenerative disorders.
  16. ↑ Ransohoff RM: How neuroinflammation contributes to neurodegeneration. Science 2016. (PMID 27540165) [PubMed] [DOI] Neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and frontotemporal lobar dementia are among the most pressing problems of developed societies with aging populations. Neurons carry out essential functions such as signal transmission and network integration in the central nervous system and are the main targets of neurodegenerative disease. In this Review, I address how the neuron's environment also contributes to neurodegeneration. Maintaining an optimal milieu for neuronal function rests with supportive cells termed glia and the blood-brain barrier. Accumulating evidence suggests that neurodegeneration occurs in part because the environment is affected during disease in a cascade of processes collectively termed neuroinflammation. These observations indicate that therapies targeting glial cells might provide benefit for those afflicted by neurodegenerative disorders.
  17. ↑ Horvath S & Ritz BR: Increased epigenetic age and granulocyte counts in the blood of Parkinson's disease patients. Aging (Albany NY) 2015. (PMID 26655927) [PubMed] [DOI] [Full text] It has been a long standing hypothesis that blood tissue of PD Parkinson's disease (PD) patients may exhibit signs of accelerated aging. Here we use DNA methylation based biomarkers of aging ("epigenetic clock") to assess the aging rate of blood in two ethnically distinct case-control data sets. Using n=508 Caucasian and n=84 Hispanic blood samples, we assess a) the intrinsic epigenetic age acceleration of blood (IEAA), which is independent of blood cell counts, and b) the extrinsic epigenetic age acceleration rate of blood (EEAA) which is associated with age dependent changes in blood cell counts. Blood of PD subjects exhibits increased age acceleration according to both IEAA (p=0.019) and EEAA (p=6.1 x 10(-3)). We find striking differences in imputed blood cell counts between PD cases and controls. Compared to control subjects, PD subjects contains more granulocytes (p=1.0 x 10(-9) in Caucasians, p=0.00066 in Hispanics) but fewer T helper cells (p=1.4 x 10(-6) in Caucasians, p=0.0024 in Hispanics) and fewer B cells (p=1.6 x 10(-5) in Caucasians, p=4.5 x 10(-5) in Hispanics). Overall, this study shows that the epigenetic age of the immune system is significantly increased in PD patients and that granulocytes play a significant role.
  18. ↑ Thal DR et al.: Neurodegeneration in normal brain aging and disease. Sci Aging Knowledge Environ 2004. (PMID 15190177) [PubMed] [DOI] Normal "healthy" aging is defined as aging without disease. Many aged people do not exhibit symptoms of disease and lead normal lives, but nonetheless display pathological changes that are characteristic of Alzheimer's disease (AD), Parkinson's disease (PD), dementia with Lewy bodies (DLB), and/or cerebrovascular disease (CVD). These changes are restricted to distinct brain regions and might represent preclinical stages of these disorders. This Perspective discusses arguments in favor of and against the hypothesis that pathological changes related to AD, PD, DLB, and CVD in the brains of nondemented elderly people represent early stages of these diseases rather than healthy aging. We conclude that early pathological disease-related changes do indeed constitute the beginning of AD, PD, DLB, and CVD rather than normal concomitants of aging, even in the absence of any clinical symptoms. Aging is, therefore, a major risk factor for these diseases but does not necessarily lead to age-related diseases.
  19. ↑ Neurological Disorders - a Common Problem of Aging. https://reliantmedicalgroup.org/blog/2014/08/05/neurological-disorders-common-problem-aging/ (accessed Apr 26, 2023).
  20. ↑ Giedd JN et al.: Brain development during childhood and adolescence: a longitudinal MRI study. Nat Neurosci 1999. (PMID 10491603) [PubMed] [DOI]
  21. ↑ "Reader in Gender archaeology" , ISBN: 9780415173605
  22. ↑ Carne RP et al.: Cerebral cortex: an MRI-based study of volume and variance with age and sex. J Clin Neurosci 2006. (PMID 16410199) [PubMed] [DOI] The aim of the present study was to examine quantitative differences in lobar cerebral cortical volumes in a healthy adult population. Quantitative volumetric MRI of whole brain, cerebral and cerebellar volumes was performed in a cross-sectional analysis of 97 normal volunteers, with segmented frontal, temporal, parietal and occipital cortical volumes measured in a subgroup of 60 subjects, 30 male and 30 female, matched for age and sex. The right cerebral hemisphere was larger than the left across the study group with a small (<1%) but significant difference in symmetry (P<0.001). No difference was found between volumes of right and left cerebellar hemispheres. Rightward cerebral cortical asymmetry (right larger than left) was found to be significant across all lobes except parietal. Males had greater cerebral, cerebellar and cerebral cortical lobar volumes than females. Larger male cerebral cortical volumes were seen in all lobes except for left parietal. Females had greater left parietal to left cerebral hemisphere and smaller left temporal to left cerebral hemisphere ratios. There was a mild reduction in cerebral volumes with age, more marked in males. This study confirms and augments past work indicating underlying structural asymmetries in the human brain, and provides further evidence that brain structures in humans are differentially sensitive to the effects of both age and sex.
  23. ↑ 23.0 23.1 23.2 Cosgrove KP et al.: Evolving knowledge of sex differences in brain structure, function, and chemistry. Biol Psychiatry 2007. (PMID 17544382) [PubMed] [DOI] [Full text] Clinical and epidemiologic evidence demonstrates sex differences in the prevalence and course of various psychiatric disorders. Understanding sex-specific brain differences in healthy individuals is a critical first step toward understanding sex-specific expression of psychiatric disorders. Here, we evaluate evidence on sex differences in brain structure, chemistry, and function using imaging methodologies, including functional magnetic resonance imaging (fMRI), positron emission tomography (PET), single photon emission computed tomography (SPECT), and structural magnetic resonance imaging (MRI) in mentally healthy individuals. MEDLINE searches of English-language literature (1980-November 2006) using the terms sex, gender, PET, SPECT, MRI, fMRI, morphometry, neurochemistry, and neurotransmission were performed to extract relevant sources. The literature suggests that while there are many similarities in brain structure, function, and neurotransmission in healthy men and women, there are important differences that distinguish the male from the female brain. Overall, brain volume is greater in men than women; yet, when controlling for total volume, women have a higher percentage of gray matter and men a higher percentage of white matter. Regional volume differences are less consistent. Global cerebral blood flow is higher in women than in men. Sex-specific differences in dopaminergic, serotonergic, and gamma-aminobutyric acid (GABA)ergic markers indicate that male and female brains are neurochemically distinct. Insight into the etiology of sex differences in the normal living human brain provides an important foundation to delineate the pathophysiological mechanisms underlying sex differences in neuropsychiatric disorders and to guide the development of sex-specific treatments for these devastating brain disorders.
  24. ↑ Taki Y et al.: Correlations among brain gray matter volumes, age, gender, and hemisphere in healthy individuals. PLoS One 2011. (PMID 21818377) [PubMed] [DOI] [Full text] To determine the relationship between age and gray matter structure and how interactions between gender and hemisphere impact this relationship, we examined correlations between global or regional gray matter volume and age, including interactions of gender and hemisphere, using a general linear model with voxel-based and region-of-interest analyses. Brain magnetic resonance images were collected from 1460 healthy individuals aged 20-69 years; the images were linearly normalized and segmented and restored to native space for analysis of global gray matter volume. Linearly normalized images were then non-linearly normalized and smoothed for analysis of regional gray matter volume. Analysis of global gray matter volume revealed a significant negative correlation between gray matter ratio (gray matter volume divided by intracranial volume) and age in both genders, and a significant interaction effect of age × gender on the gray matter ratio. In analyzing regional gray matter volume, the gray matter volume of all regions showed significant main effects of age, and most regions, with the exception of several including the inferior parietal lobule, showed a significant age × gender interaction. Additionally, the inferior temporal gyrus showed a significant age × gender × hemisphere interaction. No regional volumes showed significant age × hemisphere interactions. Our study may contribute to clarifying the mechanism(s) of normal brain aging in each brain region.
  25. ↑ Giedd JN: The teen brain: insights from neuroimaging. J Adolesc Health 2008. (PMID 18346658) [PubMed] [DOI] Few parents of a teenager are surprised to hear that the brain of a 16-year-old is different from the brain of an 8-year-old. Yet to pin down these differences in a rigorous scientific way has been elusive. Magnetic resonance imaging, with the capacity to provide exquisitely accurate quantifications of brain anatomy and physiology without the use of ionizing radiation, has launched a new era of adolescent neuroscience. Longitudinal studies of subjects from ages 3-30 years demonstrate a general pattern of childhood peaks of gray matter followed by adolescent declines, functional and structural increases in connectivity and integrative processing, and a changing balance between limbic/subcortical and frontal lobe functions, extending well into young adulthood. Although overinterpretation and premature application of neuroimaging findings for diagnostic purposes remains a risk, converging data from multiple imaging modalities is beginning to elucidate the implications of these brain changes on cognition, emotion, and behavior.
  26. ↑ 26.0 26.1 Rabinowicz T et al.: Structure of the cerebral cortex in men and women. J Neuropathol Exp Neurol 2002. (PMID 11829343) [PubMed] [DOI] Expanding previous studies of human cerebral cortical sexual dimorphism showing higher neuronal densities in males, we investigated whether gender differences also exist in the extent of neuropil, size of neuronal somata, and volumes of astrocytes. This histo-morphometric study includes select autopsy brains of 6 males and 5 females, 12 to 24 yr old. In each brain, 86 defined loci were analyzed for cortical thickness, neuronal and astrocytic (8 loci) density (stereological counts), and neuronal and astrocytic (8 loci) soma size, enabling calculations of neuropil and astrocytic volumes. The female group showed significantly larger neuropil volumes than males, whereas neuronal soma size and astrocytic volumes did not differ. The expanded data confirmed higher neuronal densities in males than in females without a gender difference in cortical thickness. These findings indicate that fundamental gender differences exist in the structure of the human cerebral cortex, with more numerous, smaller neuronal units in men and fewer, larger ones in women; they may underlie gender-specific abilities and susceptibilities to disease affecting the neocortex. Laterality differences between the sexes were restricted to neuronal soma size showing significantly larger values in the female group in the left hemisphere. This gender difference may support female's right-handedness, language advantage, and tendency for bilateral activation patterns.
  27. ↑ Pakkenberg B & Gundersen HJ: Neocortical neuron number in humans: effect of sex and age. J Comp Neurol 1997. (PMID 9215725) [PubMed] Modern stereological methods provide precise and reliable estimates of the number of neurons in specific regions of the brain. We decided to estimate the total number of neocortical neurons in the normal human brain and to analyze it with respect to the major macro- and microscopical structural components, to study the internal relationships of these components, and to quantitate the influence of important physiological variables on brain structure. The 94 brains reported represent a consecutive collection of brains from the general Danish population. The average numbers of neocortical neurons were 19 billion in female brains and 23 billion in male brains, a 16% difference. In our study, which covered the age range from 20 years to 90 years, approximately 10% of all neocortical neurons are lost over the life span in both sexes. Sex and age were the main determinants of the total number of neurons in the human neocortex, whereas body size, per se, had no influence on neuron number. Some of the data presented have been analyzed by using new mathematical designs. An equation predicting the total neocortical neuron number in any individual in which sex and age are known is provided.
  28. ↑ Good CD et al.: A voxel-based morphometric study of ageing in 465 normal adult human brains. Neuroimage 2001. (PMID 11525331) [PubMed] [DOI] Voxel-based-morphometry (VBM) is a whole-brain, unbiased technique for characterizing regional cerebral volume and tissue concentration differences in structural magnetic resonance images. We describe an optimized method of VBM to examine the effects of age on grey and white matter and CSF in 465 normal adults. Global grey matter volume decreased linearly with age, with a significantly steeper decline in males. Local areas of accelerated loss were observed bilaterally in the insula, superior parietal gyri, central sulci, and cingulate sulci. Areas exhibiting little or no age effect (relative preservation) were noted in the amygdala, hippocampi, and entorhinal cortex. Global white matter did not decline with age, but local areas of relative accelerated loss and preservation were seen. There was no interaction of age with sex for regionally specific effects. These results corroborate previous reports and indicate that VBM is a useful technique for studying structural brain correlates of ageing through life in humans.
  29. ↑ 29.0 29.1 Tenchov R et al.: Aging Hallmarks and Progression and Age-Related Diseases: A Landscape View of Research Advancement. ACS Chem Neurosci 2023. (PMID 38095562) [PubMed] [DOI] Aging is a dynamic, time-dependent process that is characterized by a gradual accumulation of cell damage. Continual functional decline in the intrinsic ability of living organisms to accurately regulate homeostasis leads to increased susceptibility and vulnerability to diseases. Many efforts have been put forth to understand and prevent the effects of aging. Thus, the major cellular and molecular hallmarks of aging have been identified, and their relationships to age-related diseases and malfunctions have been explored. Here, we use data from the CAS Content Collection to analyze the publication landscape of recent aging-related research. We review the advances in knowledge and delineate trends in research advancements on aging factors and attributes across time and geography. We also review the current concepts related to the major aging hallmarks on the molecular, cellular, and organismic level, age-associated diseases, with attention to brain aging and brain health, as well as the major biochemical processes associated with aging. Major age-related diseases have been outlined, and their correlations with the major aging features and attributes are explored. We hope this review will be helpful for apprehending the current knowledge in the field of aging mechanisms and progression, in an effort to further solve the remaining challenges and fulfill its potential.
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