Ageing Research Reviews最新文献

Aging is the greatest risk factor for chronic human diseases, including many eye diseases. Geroscience aims to understand the effects of the aging process on these diseases, including the genetic, molecular, and cellular mechanisms that underlie the increased risk of disease over the lifetime. Understanding of the aging eye increases general knowledge of the cellular physiology impacted by aging processes at various biological extremes. Two major diseases, age-related cataract and age-related macular degeneration (AMD) are caused by dysfunction of the lens and retina, respectively. Lens transparency and light refraction are mediated by lens fiber cells lacking nuclei and other organelles, which provides a unique opportunity to study a single aging hallmark, i.e., loss of proteostasis, within an environment of limited metabolism. In AMD, local dysfunction of the photoreceptors/retinal pigmented epithelium/Bruch’s membrane/choriocapillaris complex in the macula leads to the loss of photoreceptors and eventually loss of central vision, and is driven by nearly all the hallmarks of aging and shares features with Alzheimer’s disease, Parkinson’s disease, cardiovascular disease, and diabetes. The aging eye can function as a model for studying basic mechanisms of aging and, vice versa, well-defined hallmarks of aging can be used as tools to understand age-related eye disease.

Osteoarthritis (OA) is a chronic degenerative joint disease with multiple causative factors such as aging, mechanical injury, and obesity. Autophagy is a complex dynamic process that is involved in the degradation and modification of intracellular proteins and organelles under different pathophysiological conditions. Autophagy, as a cell survival mechanism under various stress conditions, plays a key role in regulating chondrocyte life cycle metabolism and cellular homeostasis. Non-coding RNAs (ncRNAs) are heterogeneous transcripts that do not possess protein-coding functions, but they can act as effective post-transcriptional and epigenetic regulators of gene and protein expression, thus participating in numerous fundamental biological processes. Increasing evidence suggests that ncRNAs, autophagy, and their crosstalk play crucial roles in OA pathogenesis. Therefore, we summarized the complex role of autophagy in OA chondrocytes and focused on the regulatory role of ncRNAs in OA-associated autophagy to elucidate the complex pathological mechanisms of the ncRNA-autophagy network in the development of OA, thus providing new research targets for the clinical diagnosis and treatment of OA.

Parkinson’s disease (PD) is the second most common neurodegenerative disorder, globally affecting men and women at an exponentially growing rate, with currently no cure. Disease progression starts when dopaminergic neurons begin to die. In PD, the loss of neurotransmitter, dopamine is responsible for the overall communication of neural cells throughout the body. Clinical symptoms of PD are slowness of movement, involuntary muscular contractions, speech & writing changes, lessened automatic movement, and chronic tremors in the body. PD occurs in both familial and sporadic forms and modifiable and non-modifiable risk factors and socioeconomic conditions cause PD. Early detectable diagnostics and treatments have been developed in the last several decades. However, we still do not have precise early detectable biomarkers and therapeutic agents/drugs that prevent and/or delay the disease process. Recently, artificial intelligence (AI) science and machine learning tools have been promising in identifying early detectable markers with a greater rate of accuracy compared to past forms of treatment and diagnostic processes. Artificial intelligence refers to the intelligence exhibited by machines or software, distinct from the intelligence observed in humans that is based on neural networks in a form and can be used to diagnose the longevity and disease severity of disease. The term Machine Learning or Neural Networks is a blanket term used to identify an emerging technology that is created to work in the way of a “human brain” using many intertwined neurons to achieve the same level of raw intelligence as that of a brain. These processes have been used for neurodegenerative diseases such as Parkinson’s disease and Alzheimer’s disease, to assess the severity of the patient’s condition. In the current article, we discuss the prevalence and incidence of PD, and currently available diagnostic biomarkers and therapeutic strategies. We also highlighted currently available artificial intelligence science and machine learning tools and their applications to detect disease and develop therapeutic interventions.

Neurodegenerative disorders (NDs) such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, multiple sclerosis, and amyotrophic lateral sclerosis are severe and life-threatening conditions in which significant damage of functional neurons occurs to produce psycho-motor malfunctions. NDs are an important cause of death in the elderly population worldwide. These disorders are commonly associated with the progression of age, oxidative stress, and environmental pollutants, which are the major etiological factors. Abnormal aggregation of specific proteins such as α-synuclein, amyloid-β, huntingtin, and tau, and accumulation of the associated oligomers in neurons are the hallmark pathological features of NDs. Existing therapeutic options for NDs are only symptomatic relief and do not address root-causing factors, such as protein aggregation, oxidative stress, and neuroinflammation. Cannabidiol (CBD) is a non-psychotic natural cannabinoid obtained from Cannabis sativa that possesses multiple pharmacological actions, including antioxidant, anti-inflammatory, and neuroprotective effects in various NDs and other neurological disorders both in vitro and in vivo. CBD has gained attention as a promising drug candidate for the management of neurodegenerative disorders, such as Alzheimer’s disease and Parkinson’s disease, by inhibiting protein aggregation, free radicals, and neuroinflammation. In parallel, CBD has shown positive results in other neurological disorders, such as epilepsy, depression, schizophrenia, and anxiety, as well as adjuvant treatment with existing standard therapeutic agents. Hence, the present review focuses on exploring the possible molecular mechanisms in controlling various neurological disorders as well as the clinical applications of CBD in NDs including epilepsy, depression and anxiety. In this way, the current review will serve as a standalone reference for the researchers working in this area.

Diabetes mellitus, a metabolic condition affecting around 537 million individuals worldwide, poses significant challenges, particularly among the elderly population. The etiopathogenesis of type 2 diabetes (T2D) depends on a combination of the effects driven by advancing age, genetic background, and lifestyle habits, e.g. overnutrition. These factors influence the development of T2D differently in men and women, with an obvious sexual dimorphism possibly underlying the diverse clinical features of the disease in different sexes. More recently, environmental pollution, estimated to cause 9 million deaths every year, is emerging as a novel risk factor for the development of T2D. Indeed, exposure to atmospheric pollutants such as PM_2.5, O₃, NO₂, and Persistent Organic Pollutants (POP)s, along with their combination and bioaccumulation, is associated with the development of T2D and obesity, with a 15 % excess risk in case of exposure to very high levels of PM_2.5. Similar data are available for plasticizer molecules, e.g. bisphenol A and phthalates, emerging endocrine-disrupting chemicals. Even though causality is still debated at this stage, preclinical evidence sustains the ability of multiple pollutants to affect pancreatic function, promote insulin resistance, and alter lipid metabolism, possibly contributing to T2D onset and progression. In addition, preclinical findings suggest a possible role also for plastic itself in the development of T2D. Indeed, pioneeristic studies evidenced that micro- or nanoplastics (MNP)s, particles in the micro- or nano- range, promote cellular damage, senescence, inflammation, and metabolic disturbances, leading to insulin resistance and impaired glucose metabolism in animal and/or in vitro models. Here we synthesize recent knowledge relative to the association between air-related or plastic-derived pollutants and the incidence of T2D, discussing also the possible mechanistic links suggested by the available literature. We then anticipate the need for future studies in the field of candidate therapeutic strategies limiting pollution-induced damage in preclinical models, such as SGLT-2 inhibitors. We finally postulate that future guidelines for T2D prevention should consider pollution and sex an additional risk factors to limit the diabetes pandemic.

Alzheimer's disease (AD) and osteoporosis are two diseases that mainly affect elderly people, with increases in the occurrence of cases due to a longer life expectancy. Several epidemiological studies have shown a reciprocal association between both diseases, finding an increase in incidence of osteoporosis in patients with AD, and a higher burden of AD in osteoporotic patients. This epidemiological relationship has motivated the search for molecules, genes, signaling pathways and mechanisms that are related to both pathologies. The mechanisms found in these studies can serve to improve treatments and establish better patient care protocols.

Circadian rhythms are biological rhythms that originate from the “master circadian clock,” called the suprachiasmatic nucleus (SCN). SCN orchestrates the circadian rhythms using light as a chief zeitgeber, enabling humans to synchronize their daily physio-behavioral activities with the Earth’s light-dark cycle. However, chronic/ irregular photic disturbances from the retina via the retinohypothalamic tract (RHT) can disrupt the amplitude and the expression of clock genes, such as the period circadian clock 2, causing circadian rhythm disruption (CRd) and associated neuropathologies. The present review discusses neuromodulation across the RHT originating from retinal photic inputs and modulation offered by endocannabinoids as a function of mitigation of the CRd and associated neuro-dysfunction. Literature indicates that cannabinoid agonists alleviate the SCN’s ability to get entrained to light by modulating the activity of its chief neurotransmitter, i.e., γ-aminobutyric acid, thus preventing light-induced disruption of activity rhythms in laboratory animals. In the retina, endocannabinoid signaling modulates the overall gain of the retinal ganglion cells by regulating the membrane currents (Ca²⁺, K⁺, and Cl^- channels) and glutamatergic neurotransmission of photoreceptors and bipolar cells. Additionally, endocannabinoids signalling also regulate the high-voltage-activated Ca²⁺ channels to mitigate the retinal ganglion cells and intrinsically photosensitive retinal ganglion cells-mediated glutamate release in the SCN, thus regulating the RHT-mediated light stimulation of SCN neurons to prevent excitotoxicity. As per the literature, cannabinoid receptors 1 and 2 are becoming newer targets in drug discovery paradigms, and the involvement of endocannabinoids in light-induced CRd through the RHT may possibly mitigate severe neuropathologies.

Parkinson's disease (PD), recognized as the second most prevalent neurodegenerative disease in the aging population, presents a significant challenge due to the current lack of effective treatment methods to mitigate its progression. Many pathogenesis of PD are related to lysosomal dysfunction. Moreover, extensive genetic studies have shown a significant correlation between the lysosomal membrane protein TMEM175 and the risk of developing PD. Building on this discovery, TMEM175 has been identified as a novel potassium ion channel. Intriguingly, further investigations have found that potassium ion channels gradually close and transform into hydrion "excretion" channels in the microenvironment of lysosomes. This finding was further substantiated by studies on TMEM175 knockout mice, which exhibited pronounced motor dysfunction in pole climbing and suspension tests, alongside a notable reduction in dopamine neurons within the substantia nigra compacta. Despite these advancements, the current research landscape is not without its controversies. In light of this, the present review endeavors to methodically examine and consolidate a vast array of recent literature on TMEM175. This comprehensive analysis spans from the foundational research on the structure and function of TMEM175 to expansive population genetics studies and mechanism research utilizing cellular and animal models.A thorough understanding of the structure and function of TMEM175, coupled with insights into the intricate mechanisms underpinning lysosomal dysfunction in PD dopaminergic neurons, is imperative. Such knowledge is crucial for pinpointing precise intervention targets, thereby paving the way for novel therapeutic strategies that could potentially alter the neurodegenerative trajectory of PD.

Cellular senescence is a cell fate driven by different types of stress, where damaged cells exit from the cell cycle and, in many cases, develop an inflammatory senescence-associated secretory phenotype (SASP). Senescence has often been linked to driving aging and the onset of multiple diseases conferred by the harmful SASP, which disrupts tissue homeostasis and impairs the regular function of many tissues. This phenomenon was first observed in vitro when fibroblasts halted replication after approximately 50 population doublings. In addition to replication-induced senescence, factors such as DNA damage and oncogene activation can induce cellular senescence both in culture and in vivo. Despite their contribution to aging and disease, identifying senescent cells in vivo has been challenging due to their heterogeneity. Although senescent cells can express the cell cycle inhibitors p16^Ink4a and/or p21^Cip1 and exhibit SA-ß-gal activity and evidence of a DNA damage response, there is no universal biomarker for these cells, regardless of inducer or cell type. Recent studies have analyzed the transcriptomic characteristics of these cells, leading to the identification of signature gene sets like CellAge, SeneQuest, and SenMayo. Advancements in single-cell and spatial RNA sequencing now allow for analyzing senescent cell heterogeneity within the same tissue and the development of machine learning algorithms, e.g., SenPred, SenSig, and SenCID, to discover cellular senescence using RNA sequencing data. Such insights not only deepen our understanding of the genetic pathways driving cellular senescence, but also promote the development of its quantifiable biomarkers. This review summarizes the current knowledge of transcriptomic signatures of cellular senescence and their potential as in vivo biomarkers.