The role of gut microbiome in aging-associated diseases: where do we stand now and how technology will transform the future

ABSTRACT

The gut microbiome has emerged as a critical regulator of human aging and healthspan, with age-related dysbiosis increasingly implicated in a broad spectrum of aging-associated diseases. This review synthesizes evidence linking gut microbial alterations to infectious diseases, antimicrobial resistance, autoimmune, neurodegenerative, psychiatric, cancer, metabolic, kidney, cardiovascular, bone, and muscular diseases, highlighting shared mechanisms such as chronic inflammation, immune dysregulation, and metabolite imbalance. We further explore how enabling technologies, including functional multi-omics, synthetic biology, artificial intelligence-driven analytics, biobanking, and autologous fecal microbiota transplantation, are revolutionizing microbiome research and the design of interventions. Ethical considerations surrounding microbiome-based therapies are also addressed. To translate these scientific insights into clinical innovations, we formulate the PRIME framework: a five-phase roadmap encompassing Profiling, Reviewing, Identifying, Mapping, and Evaluating microbiome-based interventions. By integrating microbiome science, aging biology, and emerging technologies, this review provides a comprehensive blueprint for advancing precision medicine and promoting healthy aging. Furthermore, it emphasizes the importance of building future-ready capabilities to navigate the evolving landscape of age-related diseases and microbiome-driven therapeutic innovations.

1. Introduction

Aging is a natural phenomenon that almost all living organisms experience. As individuals age, there is a gradual decline in overall function and cellular health, increasing their susceptibility to a range of diseases.¹ In 2013, the first edition of the hallmarks of aging was published to improve the understanding of aging and elucidate its fundamental processes by identifying nine distinct hallmarks that collectively contribute to the manifestation of the aging phenotype.¹ Genomic instability, telomere attrition, epigenetic alterations, and a decline in proteostasis represent the basic biological factors responsible for cellular damage and aging. Compensatory biological strategies, including disrupted nutrient detection, impaired mitochondrial function, and the onset of cellular senescence, are executed as a consequence of this cellular damage. The outcome is stem cell exhaustion and changes in cellular communication, leading to an organism’s aging.¹ Ten years later, the same research group revisited and expanded on the hallmarks of aging in light of discoveries over the past decade. Three additional hallmarks of aging were added, reflecting a deeper understanding of the aging process: disabled macroautophagy, chronic inflammation, and microbiome dysbiosis.²

The gut microbiome undergoes significant alterations throughout an individual’s lifespan due to factors such as aging, dietary habits, environmental influences, and health conditions.³ Previous studies demonstrated that these changes in microbiome occur in various model organisms, including flies, fish, rodents, and humans.³ In the case of humans, the initial indications of age-related variations in microbiota were first observed through culture-based research in the 1970s.³ Subsequently, molecular techniques confirmed variations in the microbiota composition among different age groups. In general, gut microbial diversity decreases as individuals age, with shifts in the levels of Bacteroidota (formerly Bacteroidetes) and Clostridium observed in older age groups but not in younger ones.³ The health implications of these microbiota shifts are not entirely understood. However, it is consistently supported in literature that gut microbiome dysbiosis is associated with aging-related diseases.

Differences in gut microbiome between healthy and unhealthy aging have been described in different populations.^4,5 For instance, in a study of Chinese long-living individuals (≥90 years), participants were stratified into two groups: healthy long-living individuals (free of acute or chronic diseases) and unhealthy long-living individuals (with one or more conditions, including diabetes, arthritis, gastrointestinal, cardiovascular, or respiratory diseases).⁶ Shotgun metagenomic analysis of fecal specimens revealed significant differences in the microbial composition and functional capacity between the two groups. The healthy long-living cohort exhibited a higher abundance of Bacteroidota, and enrichment of functional pathways related to energy metabolism, glycan biosynthesis and metabolism, and the metabolism of cofactors and vitamins. In contrast, the unhealthy cohort showed increased abundance of Streptococcus and other potentially pathogenic taxa, alongside enrichment of pathways associated with xenobiotic biodegradation and metabolism. The unhealthy cohort also demonstrated elevated levels of starch-degrading enzymes coupled with a reduction in carbohydrate-active enzymes.⁶ These comparative findings suggest that the gut microbiome is intricately linked to health status and may play a role in promoting healthy aging.

Nevertheless, understanding whether the gut microbiome signature of healthy aging is population-specific or universally shared is a key question in gut microbiome and aging research. While previous studies have demonstrated that ethnicity and geography influence gut microbiome profile in healthy aging,^7,8 a recent multi-cohort study revealed a consistent microbial signature associated with longevity across eight independent cohorts from Japan,⁹ China,^6,10-13 and Italy.^14,15 Using shotgun metagenomic sequencing data from 1,156 fecal specimens, the study authors performed species-level functional profiling to identify microbes and metabolic pathways associated with healthy aging.¹⁰ The study authors reported that Eisenbergiella tayi, Methanobrevibacter smithii, Hungatella hathewayi, and Desulfovibrio fairfieldensis were consistently enriched in long-lived individuals across multiple cohorts compared to younger elderly and younger adults.¹⁰ Functional analyzes further revealed that E. tayi contributed to the protein N-glycosylation pathway, suggesting a key role in regulating aging in long-lived individuals. The same study also reported that M. smithii contributed to the biosynthesis of 3-dehydroquinate and chorismate, while H. hathewayi and D. fairfieldensis were found to play roles in purine nucleobase degradation (supporting purine homeostasis in the elderly) and vitamin K2 biosynthesis, respectively, suggesting a potential protective role against age-related diseases.¹⁰ These findings indicated reproducible microbial species and functions across diverse populations, providing valuable insights into the universal gut microbial signatures of long-lived individuals and expanding our understanding of host-microbiome interactions in healthy aging.¹⁰

Both microbiome and aging can impact host immunity. The link between aging and progressive deterioration of the immune system is termed immunosenescence. Immunosenescence involves changes in the frequency, distribution, maturation, and activity of innate and adaptive immune cell populations, accompanied by alterations in cytokine and chemokine profiles.^16,17 For example, older adults tend to have an accumulation of transcriptionally and functionally altered pro-inflammatory monocytes and regulatory T (T_reg) cells.^18-21 Also, older individuals were shown to have reduced naïve T and B cells, as well as impaired natural killer (NK) cell cytotoxic activity, dendritic cell (DC) phagocytosis and antigen cross-presentation, and plasma cell antibody production.^22-25 This age-associated immune remodeling leads to low-grade systemic inflammation (defined as inflammageing), as well as increased vulnerability to infections, reduced vaccination responses, cancer development, and autoimmunity.^17,26-31 Likewise, the microbiome can directly regulate innate and adaptive immunity.^17,32-35 Also, the microbiome can indirectly regulate host immunity via the secretion of outer membrane vesicles (OMVs) and the release of microbiota-derived metabolites, such as short-chain fatty acids (SCFAs) and bile acids.^36-51

SCFAs, primarily acetate, propionate, and butyrate, are recognized as key mediators linking gut microbes and host physiology.⁵² These metabolites are generated through the fermentation of dietary fiber and nourish the intestinal epithelium, thereby maintaining barrier integrity and reducing microbial translocation and chronic low-grade inflammation.^28,53 In addition, SCFAs act as systemic signaling molecules binding to the G protein-coupled receptors (GPRs) GPR41 and GPR43 on epithelial and immune cells to trigger anti-inflammatory and metabolic responses.⁵⁴ They also modulate gene expression further by inhibiting histone deacetylases (HDACs).^55,56 Together, these mechanisms maintain gut homeostasis, regulate immune function, and energy balance. With aging, however, the decline in SCFA-producing bacteria often leads to reduced SCFA availability, impaired barrier integrity, and increased systemic inflammation, which are factors that are increasingly associated with a broad spectrum of age-related conditions, including metabolic, cardiovascular, and neurodegenerative diseases.^7,57,58 Building on this evidence, recent studies have shown that aged gut microbiota can promote intestinal permeability and subsequently stimulate systemic inflammation in germ-free mouse models.^28,59,60 Although these studies illustrate the association between aging, microbiome, and host immunity, there remains an urgent need to translate these pre-clinical findings into real-life clinical interventions that can promote healthy aging.

Over the last two decades, the growth in microbiome research and market has been exponential, highlighting the promising future of this field.^61,62 There are various classes of microbiome-directed therapy, including probiotics, prebiotics, natural microbial consortia (such as fecal microbiota transplant [FMT]), and synthetic microbial consortia.^61,63 Generally, microbiome-based therapeutics aim to either alter the population composition of the microbiome or modify its functionality.⁶³ Currently, FMT is the only microbiome-based therapeutic category that has received regulatory approval, and it is approved for the treatment of recurrent Clostridioides difficile (C. difficile) infection.

This article reviews the current knowledge on the role of gut microbiome in aging-associated diseases (Figure 1). Additionally, it provides a comprehensive overview of enabling technologies for microbiome research and engineering, with a special focus on functional omics approaches, synthetic biology, artificial intelligence (AI), and microbiome and aging biobanks, as well as introducing the concept of autologous FMT (Figure 2). Furthermore, recognizing that international ethical guidelines for human microbiome research and aging research have developed independently, we formulated an integrative ethical framework that draws from both fields and is grounded in the four pillars of bioethics (Figure 3). Finally, we formulate the PRIME framework as a structured, comprehensive model poised to transform the future of gut microbiome and aging research (Figure 4).

Figure 1.

A schematic diagram showing the gut microbiome involvement in aging-associated diseases. Created in BioRender. Aldriwesh, M. (2025) https://BioRender.com/fycfapg.

Figure 2.

Autologous fecal microbiota transplantation (FMT) to promote healthy aging. We proposed the idea of autologous FMT, where an individual’s feces is collected during early adulthood, stored in a biobank, and then re-administered at a later stage of adulthood. The goal of this approach is to reverse the microbiome dysbiosis and restore microbiome homeostasis, promoting healthy aging. Created in BioRender. Aldriwesh, M. (2025) https://BioRender.com/qu0auys.

Figure 3.

An integrative ethical framework for aging and human microbiome research. We formulated an ethical framework that integrates the fields of human microbiome research and aging research. It is specifically tailored to the domains of both fields, considering the four pillars of bioethics (i.e., autonomy, non-maleficence, beneficence, and justice). Created in BioRender. Aldriwesh, M. (2025) https://BioRender.com/6albalj.

Figure 4.

The Profile, Review, Identify, Map, and Evaluate (PRIME) framework for gut microbiome and aging research. We formulated the PRIME framework as a structured and comprehensive roadmap for investigating the gut microbiome in the context of aging, with the potential to advance the field significantly. It consists of five strategic stages: (1) association studies, (2) correlation studies, (3) causation studies, (4) translation studies, and (5) validation studies. Created in BioRender. Aldriwesh, M. (2025) https://BioRender.com/fuqxz47.

2. The role of gut microbiome in aging-associated diseases

As illustrated in Figure 1, age-related alterations in the gut microbiome are increasingly implicated in the development, progression, and outcomes of a wide range of diseases affecting nearly every organ system. This section provides a structured synthesis of evidence linking gut microbiome dysbiosis to 13 major categories of aging-associated diseases, including infectious, autoimmune, neurodegenerative, psychiatric, cancer, metabolic, cardiovascular, and sensory disorders, among others. Each subsection highlights disease-specific microbiome interactions, underlying mechanisms, and emerging translational insights, offering a comprehensive view of how microbiome science informs the future of aging and precision medicine.

2.1. Infectious diseases and antimicrobial resistance

Infectious diseases and antimicrobial resistance (AMR) pose significant challenges to global health organizations. Acquired immunodeficiency syndrome (AIDS), tuberculosis (TB), and malaria continue to represent escalating challenges in addition to the emerging and re-emerging pathogens like severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Staphylococcus aureus (S. aureus), Klebsiella pneumoniae (K. pneumoniae) and Escherichia coli (E. coli).^64,65 In 2019, more than 704 million disability-adjusted life years (DALYs) were lost globally due to 85 pathogens.⁶⁵ Additionally, bacterial infections contribute significantly to infection-related mortality, and an estimated 7.7 million out of 13.7 million infection-related deaths occurred in 2019.⁶⁶ AMR alone is responsible for relatively 1.7 million deaths worldwide, and this is expected to increase unless further actions are taken to strengthen prevention measures and public health policies.^67,68

Previous research has shown that the gut microbiome influences immune regulation and prevents the colonization of pathogenic microbes by competing for nutrients and secreting antimicrobial compounds known as bacteriocins.^69,70 The gut microbiota produces various metabolite substances that regulate the immune system, such as indole derivatives and other derivatives derived from tryptophan, as well as polyamines sourced from dietary arginine.⁷¹ These metabolites are immunomodulators that contribute to maintaining the integrity of the gut epithelium by promoting the growth of intestinal goblet cells.⁷² Additionally, tryptophan derivatives contribute to immune regulation by promoting the maturation and activation of anti-inflammatory macrophages, T_reg cells, and interleukin-22 (IL-22)-producing innate lymphoid cells 3 (ILC3).⁷³ IL-22 plays a crucial role in maintaining intestinal epithelial cell health, balancing commensal microbiota, and protecting against infections, such as Citrobacter rodentium (C. rodentium) and Salmonella typhimurium (S. typhimurium).⁷⁴

Gut microbiome dysbiosis is associated with increased susceptibility to various infectious agents, including bacterial and viral infections. For instance, the gut microbiome has been identified as a potential host factor in TB, with studies reporting significant differences in gut microbiome composition between TB patients and healthy individuals. The relative abundance of Bacteroidota (formerly Bacteroidetes), Roseburia inulinivorans (R. inulinivorans), Bifidobacterium adolescentis (B. adolescentis), and Akkermansia muciniphila (A. muciniphila) have changed significantly.^75,76 Additionally, the use of antimicrobials is a major driver of gut microbiome dysbiosis, leading to increased susceptibility to C. difficile infection.^77,78 Moreover, research indicates that the gut microbiome affects the severity of viral respiratory infections by modulating alveolar macrophage activity.⁷⁹ The gut microbiome plays a central role in the host’s immune response to SARS-CoV-2 infection,⁸⁰ human immunodeficiency virus (HIV),⁸¹ and hepatitis B,⁸² thereby helping to modulate immune responses and prevent subsequent complications.

The gut microbiome can serve as a reservoir for AMR genes,⁸³ as microbial communities in the gut can harbor resistance genes acquired from various sources. These genes can be easily exchanged between bacteria via horizontal gene transfer (HGT) through mobile genetic elements (MGEs). MGEs play a crucial role in gut microbiome dysbiosis by enabling the transfer of genes that influence bacterial fitness, AMR, and virulence, consequently influencing the ecological dynamics and functional attributes of the gut microbial community.⁸⁴

Aging is one of the most significant factors contributing to gut microbiome dysbiosis, making the older population more susceptible to infections and increasing the rate of deaths associated with AMR.³¹ In 2018, viral respiratory infections, such as influenza and viral pneumonia, were the leading causes of death in older adults, with a mortality rate of approximately 93.2 per 100,000 aged 65 or older.⁸⁵ Additionally, bacterial infections pose a significant threat to older adults due to their weak immune system, including pneumonia caused by Streptococcus pneumoniae (S. pneumoniae) and Haemophilus influenzae (H. influenzae), urinary tract infections by E. coli and Klebsiella pneumoniae (K. pneumoniae), and cellulitis by Staphylococcus aureus (S. aureus) and Streptococcus pyogenes (S. pyogenes), as well as sepsis and gastroenteritis.⁸⁶

We just mentioned that the risk of C. difficile infection increases with antimicrobial use, but it also increases with aging-related immunosenescence. In healthy individuals, the host’s normal and diverse microbiota can suppress the growth of C. difficile. However, when the host microbiota is disrupted, C. difficile can survive and thrive, leading to life-threatening diarrhea and colitis.^87,88 Until recently, the classical approach to therapy for C. difficile colitis was antimicrobial administration, which has a high failure rate. In November 2022, the U.S. Food and Drug Administration (FDA) approved the first commercial FMT product, RBX2660 (Rebyota), for the prevention of recurrent C. difficile infections (CDI) in adults. RBX2660 is prepared from donor feces and administered rectally.^89-93 In a phase 3 trial (NCT03244644 [PUNCHCD3]), RBX2660 was significantly better at preventing recurrent CDI compared with a placebo. The treatment success rate at eight weeks was 73.8%. Among those responders, the sustained clinical response rate at six months was 91.0%.⁹⁴ In April 2023, the U.S. FDA approved SER-109 (Vowst) as the first commercial oral FMT product for recurrent CDI. It contains only donor-derived spores of Bacillota (formerly Firmicutes) bacteria. The phase III trial NCT03183128 (ECOSPORIII) indicated that SER-109 could lead to a lower recurrence rate compared to placebo treatment. In the SER-109 group, 12% of patients had CDI recurrence compared to 40% in the placebo group.⁹⁵

Taken together, numerous studies have demonstrated that gut microbiome dysbiosis can directly impact infection risk in healthy individuals and that aging contributes to gut dysbiosis and an increased risk of infections. However, mechanistic studies that provide a causal relationship between aging, the gut microbiome, and infectious diseases remain limited, yet they are fundamental for translation into clinical settings.³¹

2.2. Autoimmune diseases

Autoimmune diseases are a diverse group of conditions, including more than 100 types. All autoimmune diseases are characterized by the disturbance of the immune system, which stimulates an immune response against self-antigens, leading to chronic inflammation and potentially tissue destruction.⁹⁶ The incidence of autoimmune diseases has escalated over the past decades.^97,98 Autoimmune diseases impact approximately 10% of the population, with around 64–80% of patients diagnosed being female.^98-100

Among the most common types of autoimmune diseases are autoimmune thyroiditis (including Hashimoto’s thyroiditis and Graves’ disease), psoriasis, rheumatoid arthritis (RA), polymyalgia rheumatica, inflammatory bowel disease (including Crohn’s disease and ulcerative colitis), celia disease, systemic lupus erythematosus (SLE), type 1 diabetes mellitus (T1DM), and multiple sclerosis (MS).⁹⁸ Notably, most autoimmune diseases are primarily diagnosed in middle-aged adults (Supplementary Table 1). They are rarely diagnosed in an older population, and when older adults develop autoimmune diseases, they are typically mild and may have different clinical manifestations.^101,102 Another important observation is that accelerated biological aging is associated with an increased risk of developing autoimmune diseases, which are typically diagnosed in middle-aged or younger adults, such as rheumatoid arthritis,¹⁰³ psoriasis,¹⁰⁴ T1DM,¹⁰⁵ and MS.^106,107 However, data is inconsistent regarding SLE.^108,109 Given that the association between the gut microbiome and most of these autoimmune diseases is well-established^110-112 and that the association between the gut microbiome and accelerated biological aging has also been reported,¹¹³ understanding the causal link between accelerated biological aging, gut microbiome, and autoimmune diseases is potentially a promising area of research.

Table 1.

Examples of microbiome biobanks.

Biobank name	Country	Purpose	Reference
Human Microbial Metabolome Database (MiMeDB)	USA and Canada	Connects microbial genomes to metabolites and their health implications, providing a multi-omic platform that links microbial data to the human exposome.	[375]
Human Gut Microbial Biobank (hGMB)	China	Initiative that has cultivated over 10,000 isolates from fecal specimens, representing 400 different species. It has expanded the known microbial diversity by identifying 102 novel species and proposing new genera and families.	[376]
MetaGeneBank	China	A standardized database for deep-sequenced metagenomic data, facilitating the study of microbiota and molecular functions across various diseases and countries.	[377]
Broad Institute-OpenBiome Microbiome Library (BIO-ML)	USA	Comprehensive collection featuring 7,758 gut bacterial isolates paired with genome sequences and longitudinal multi-omics data. It contributes to understanding microbial stability and dynamics within the human gut.	[378]
MicrobiomeDB	USA	A platform that integrates and analyzes microbiome data, providing tools for data mining and visualization. It enhances the ability to conduct meta-analyzes and compare results across different studies.	[379]

Among the autoimmune diseases that are more commonly diagnosed in older adults are polymyalgia rheumatica (PMR) and giant-cell arteritis (GCA). PMR is characterized by pain in the shoulder and hip girdles, resulting in significant morning stiffness, and GCA causes inflammation in blood vessels with a risk of developing partial or total blindness. Interestingly, approximately 20% of PMR patients have GCA, and approximately 50% of GCA patients have PMR.¹¹⁴ Using the integrated epidemiology unit (IEU) genome-wide association studies (GWAS) database, Zhang et al. reported that Erysipelatoclostridium and Ruminococcaceae genera are potentially protective factors for PMR. In contrast, the Butyricimonas, Eisenbergiella, and Coprobacter genera are associated with a higher risk of developing PMR.¹¹⁵ Additionally, using multiple datasets, Wu et al. identified nine taxa that were significantly associated with GCA compared to controls.¹¹⁶ In line with the gut microbiome, using temporal artery biopsies, Hoffman et al. reported that there are microbiome differences between GCA and non-GCA temporal arteries.¹¹⁷ Although all these studies suggest a link between the gut microbiome and the risk of developing autoimmune diseases in older adults, there is an urgent need to conduct pre-clinical mechanistic studies as well as extensive clinical studies that can further support these observations. For example, the role of microbiome in developing GCA in PMR patients or PMR in GCA patients is worth further investigation.

2.3. Neurodegenerative diseases

Neurodegenerative diseases are a group of diseases characterized by the progressive deterioration of the structural and functional integrity of the nervous system. These diseases have the potential to adversely affect motor skills, cognitive processes, and other essential physiological functions. Frequently encountered neurodegenerative diseases are Alzheimer’s disease (AD) and Parkinson’s disease (PD).¹¹⁸

AD is the most common form of dementia, marked by memory loss, cognitive decline, and personality changes. Onset can vary from the early 30 s to typical late-onset cases in the 60 s and beyond.¹¹⁹ Globally, the prevalence of AD is expected to reach 131 million by 2050. Emerging evidence suggests a strong link between gut microbiome dysbiosis and AD, highlighted by decreased levels of Bacillota (formerly Firmicutes) and increased levels of Bacteroidota (formerly Bacteroidetes).¹²⁰ Other bacterial taxa, such as Bifidobacterium, were also reduced, while Actinobacteria, Ruminococcus, and Lachnospiraceae exhibited some alterations. In AD animal models, microbial changes, including increases in Escherichia-Shigella, Desulfovibrio, Akkermansia, and Blautia, have also been observed,¹²¹ suggesting that specific microbial alterations may in some way exacerbate or mitigate AD progression. Additionally, gut microbiome dysbiosis in AD contributes to the production of bacterial amyloids and lipopolysaccharides (LPS), resulting in systemic inflammation and blood-brain barrier dysfunction. This facilitates the misfolding of amyloid-β (Aβ), a hallmark of AD, and promotes neuroinflammation.¹²² Additionally, gut microbiome composition affects microglial activation, which is critical for Aβ clearance in AD.¹²³

PD is primarily a movement disorder characterized by tremors, rigidity, and bradykinesia, but it also includes non-motor symptoms like cognitive changes and sleep disturbances. Typically, PD has an onset in mid to late adulthood, although early-onset cases before age 40 are possible. Global estimates project 9.3 million PD cases by 2030.¹²⁴ There is a significant alteration in gut microbiota in PD patients, characterized by decreased levels of Prevotellaceae and butyrate-producing bacteria, such as Roseburia and Faecalibacterium. In contrast, levels of Akkermansia and Enterobacteriaceae are elevated in PD patients,¹²⁵ indicating a possible inflammatory environment in the gut that may influence PD progression. Gut microbiota dysbiosis in PD contributes to both motor and non-motor symptoms by triggering neuroinflammation and altering neurotransmitter metabolism.¹²⁶ Additionally, microbiota-derived amyloids have been suggested to play a role in the aggregation of alpha-synuclein, a hallmark of PD pathology.¹²⁷

Recent research has explored the potential of gut microbiome-targeted therapies for neurodegenerative diseases. Probiotics have shown promise in modulating the gut microbiota and reducing inflammation in conditions such as AD and PD. For instance, in AD, probiotics such as Clostridium butyricum (C. butyricum), A. muciniphila, and Faecalibacterium prausnitzii (F. prausnitzii) have been shown to have anti-inflammatory and neuroprotective effects.¹²⁸ Similarly, in PD, Bacteroides fragilis (B. fragilis) has been shown to improve glucose metabolism and reduce peripheral inflammation.¹²³ Although the field has advanced, significant knowledge gaps remain. Most published reports consist of cross-sectional studies, which provide only a snapshot of gut microbiota composition at a single point in time. This limits our ability to establish causality or understand the dynamics of the gut-brain interaction. To address this issue, there is a pressing need for longitudinal studies that track changes in gut microbiota over time and correlate these with disease progression.

2.4. Psychiatric disorders

Psychiatric disorders such as depression, anxiety, bipolar disorder (BD) and schizophrenia can significantly impair cognitive and emotional functions, contributing to a reduced quality of life, increased healthcare costs, and physical health problems.^129-133 Although psychiatric disorders can occur across the lifespan, they become particularly relevant in aging due to increased vulnerability from biological aging and neurodegenerative processes.^134-141 In addition, the combined influence of multimorbidity, polypharmacy, and social isolation (well-established geriatric risk factors) exacerbates the clinical significance of psychiatric conditions in this population.^{132,133,142-145}

Depression affects around 264 million people and is often linked to chronic illness, social isolation, and reduced physical function.¹²⁹ Global studies have revealed gut dysbiosis in older individuals with depression, characterized by lower abundance of beneficial bacteria, such as Bifidobacterium and Lactobacillus, and higher abundance of the pro-inflammatory bacteria Enterobacteriaceae, Clostridium, and Proteobacteria. These imbalances contribute to systemic inflammation and depressive symptoms.¹⁴⁶ Studies on probiotics such as Lactobacillus and Bifidobacterium have demonstrated reductions in depressive symptoms and improved emotional processing in patients with depressive illnesses.¹⁴⁷

Anxiety disorders affect around 4–6% of the total population.¹²⁹ Gut microbiome dysbiosis in older individuals with anxiety is characterized by reduced levels of the beneficial bacteria Lactobacillus and Bifidobacterium and increased levels of the pro-inflammatory bacteria E. coli and Proteobacteria, which are associated with systemic inflammation and worsened anxiety symptoms.¹⁴⁸ Probiotic and dietary modifications, including the Mediterranean diet and prebiotic intake, have shown potential in reducing anxiety symptoms by modulating the gut microbiome and reducing inflammation.¹⁴⁹

BD affects more than 1%, with a growing recognition of late-onset BD in the older population.¹²⁹ It was reported that older BD patients have a decrease in the beneficial bacteria Bifidobacterium and Lactobacillus and an increase in the pro-inflammatory bacteria. These changes are associated with neuroinflammation and increased gut permeability.^150,151 Another global study on FMT suggested that gut microbiome-targeted therapies may help manage BD symptoms.¹⁵²

Schizophrenia affects about 21 million of the world’s population¹²⁹ and it is associated with accelerated biological aging.^141,153 Reduced microbial diversity, increased pro-inflammatory markers and immune modulation have also been observed in patients with schizophrenia.^154-157 Studies suggested that microbiota-based interventions, such as probiotics and dietary adjustments, may regulate symptoms of schizophrenia through immune modulation and modulation of neurotransmitter pathways; however, further research is needed.¹⁵⁸

In summary, while psychiatric disorders are not exclusive to older age, their prevalence, severity, and consequences are amplified in aging populations. Understanding the gut–brain–aging axis is therefore crucial to developing microbiome-based preventive and therapeutic approaches. More longitudinal, age-stratified, and interventional studies are needed to clarify causal relationships and evaluate the therapeutic potential of microbiome modulation in older adults.

2.5. Cancer

Cancer is a leading cause of death worldwide.¹⁵⁹ According to the latest global cancer statistics (GLOBOCAN 2022), there were about 20 million new cancer cases in the year 2022, with 9.7 million cancer-related deaths. In other words, during the year 2022, about 38 individuals were being diagnosed with cancer every minute. The analysis suggests that 1 in 5 individuals develop cancer in a lifetime. Unfortunately, these numbers are projected to increase, with over 35 million new cancer cases and 18.5 million cancer-related mortality in 2050. The most frequently diagnosed cancers are lung, followed by woman breast, and then colorectal cancer.¹⁶⁰ Interestingly, about 90% of cancer cases are diagnosed after 50 y of age. Hence, cancer is typically considered a disease of old age.¹⁶¹

The gut microbiome can influence cancer initiation^162-164 and prognosis.¹⁶⁵ Additionally, the diversity and composition of the gut microbiome are linked to differential therapeutic outcomes and toxicity to chemotherapy and immunotherapy in cancer patients.^165-171 While most research has focused on bacteria, emerging evidence highlights an important role for fungi (the mycobiota) in cancer as well.¹⁷² Nevertheless, earlier studies showed limited consistency regarding favorable and unfavorable microbiota. Several technical and biological confounding factors may explain this inconsistency (discussed further later in this review).^166,173,174 Additionally, the gut microbiome can travel from the gut to primary tumors and from primary tumors to metastatic sites,^163,165 further elucidating the complex relationship between cancer and the gut microbiome. The gut microbiome also exhibits substantial functional redundancy; phylogenetically unrelated taxa can perform similar roles, such as producing SCFAs, metabolizing dietary carbohydrates, modifying bile acids, or promoting cytokine secretion.¹⁷⁵ Consequently, even when microbial composition differs between individuals, key functional outputs may remain conserved.^175-177 To address these challenges, integrative analyzes suggested that focusing on the ecological topology of microbial communities, rather than individual taxa, may provide more reliable biomarkers of cancer treatment response.^173,174 For example, Derosa et al. developed TOPOSCORE, a co-abundance network–based system that identifies species-interacting groups associated with resistance or response to immunotherapy. To further increase the clinical applicability of the TOPOSCORE scoring system, it was translated into a 21-bacteria-based qPCR test, which was validated across multiple patient cohorts with different cancer types, such as non-small cell lung cancer, colorectal cancer and melanoma.¹⁷³

Furthermore, because microbiome effects on cancer are largely mediated by microbiome-derived metabolites, mechanistic links between microbial functions and cancer properties may be stronger and more clinically meaningful than those based solely on microbial presence.¹⁷⁵ Although this hypothesis has been supported by in vivo cancer models^178-182 as well as by preclinical and clinical research in other disease contexts,¹⁸³ further validation is required before clinical translation. Taken together, applying multi-omics approaches to decipher microbial community networks and assess microbial functional impacts may provide more reliable biomarkers than relying solely on microbial taxonomy.

The use of microbiome-based therapeutics for cancer management is auspicious. FMT and antigen-engineered microbiota are currently under investigation in clinical settings as a potential strategy to promote immunotherapy responses and reverse immune-associated toxicities.^184-187 Additionally, Jennifer A. Wargo’s group conducted an observational study in which they profiled the gut microbiome and assessed clinicopathologic features and outcomes in a large cohort of melanoma patients treated with immune checkpoint inhibitors (ICIs). Interestingly, they reported that higher dietary fiber was associated with significantly improved progression-free survival. By conducting parallel pre-clinical studies, they found that dietary fibers can modulate the microbiome in vivo, thereby recapitulating clinical observations. They reported that mice treated with ICI and receiving a high-fiber diet had significantly higher levels of the SCFA propionate in their fecal specimen and a higher frequency of intra-tumoral CD4 + T cells and intra-tumoral interferon-γ–positive cytotoxic T cells.¹⁸⁸ Although the use of dietary fibers is relatively safe and easy to administer, predicting the outcomes of such supplementations must be investigated in a controlled approach.⁶¹ Therefore, a Phase II (NCT04645680) randomized trial comparing a high-fiber dietary intervention with a healthy control diet in melanoma patients receiving ICI is currently underway. This clinical trial is the first fully controlled feeding study among immunotherapy-treated cancer patients.¹⁸⁹

Gut microbiome dysbiosis is one of the hallmarks of aging, and polymorphic microbes are one of the hallmarks of cancer.¹⁹⁰ Aging is associated with a decrease in microbiome diversity,⁷ which is also associated with worse cancer prognosis.¹⁹¹ Moreover, research on cancer and aging has shown an overlap between microbiota associated with a better response to cancer treatment and longevity, such as the increase in Lachnospiraceae and Ruminococcaceae family members, as well as species from the Akkermansia genus.^{166-171,192,193} These findings suggest a causal link between dysbiosis, aging, and cancer.^190,194,195 However, more in-depth mechanistic studies are still lacking.

2.6. Metabolic diseases

Metabolic disorders, such as obesity and diabetes, are a significant public health concern around the world. Obesity prevalence increased significantly in the last four decades, and by 2030, it is predicted that more than half of the global adult population will be overweight or obese.¹⁹⁶ Epidemiological studies highlight that, in 2015, there were roughly 1.9 billion overweight adults and 609 million obese adults in the world. This means that around 39% of adults worldwide are overweight or obese.¹⁹⁷ All age groups are susceptible to obesity, and its patterns vary according to socioeconomic factors.^198,199 Obesity is associated with numerous health complications in age groups, including a higher risk of type 2 diabetes mellitus (T2DM), liver and cardiovascular disease, and cancer. However, older adults with obesity face additional obesity-related complications, such as functional decline, deteriorating cognitive abilities, and reduced quality of life.²⁰⁰

T2DM is another metabolic disorder as significant as obesity, and, as just mentioned, it is closely linked to it, accounting for most diabetes cases.²⁰¹ In 2019, the incidence of diabetes experienced a significant increase worldwide, with an estimated 463 million older adults living with diabetes. This number is projected to rise to 700 million by 2045.²⁰² Focusing on older adults, patients with diabetes are more likely to suffer from cardiovascular diseases, retinopathy, nephropathy, neuropathy, dementia, depression, and urinary incontinence compared to healthy individuals of the same age.²⁰³

Obesity is strongly associated with gut microbiome dysbiosis.^204,205 A high-fat diet may cause changes in the composition of the gut microbiome, characterized by decreased numbers of Bacillus bacteria and an increase in Bacillota (formerly Firmicutes) and Proteobacteria.²⁰⁶ Furthermore, obese individuals often tend to have a higher Bacillota-to-Bacteroidota ratio.²⁰⁷ Notably, microbial diversity varies across populations and is influenced by dietary habits. For instance, a study comparing gut microbiome profiles between obese and normal individuals in France and Saudi Arabia revealed significant differences between the two countries. Obese French individuals showed an increase in the Proteobacteria and Bacteroidota (formerly Bacteroidetes) phyla, while obese Saudi individuals demonstrated a significant increase in the Bacillota phylum.²⁰⁷ These population-based differences can lead to contradictory data regarding the connections between obesity and gut microbiome. Moreover, obesity can be exacerbated by the chronic inflammation induced by gut-derived metabolites, which modulate the microbiome-brain-gut axis.²⁰⁸

In diabetes mellitus, recent research has highlighted a close link between gut microbiome dysbiosis and both T1DM and T2DM.^209,210 This is due to the role of gut microbiome dysbiosis in autoimmune response, inflammation, gut permeability, and glucose metabolism dysregulations, all of which are key factors in the development and progression of diabetes. Gut microbiome dysbiosis also impacts bile acid metabolism and impairs glucose tolerance.²¹¹ It is associated with an increased risk of developing T1DM, characterized by a reduction in Bifidobacterium and Lactobacillus and an increase in Bacteroides and Clostridium. In T2DM, studies show a decrease in the SCFA-producing bacteria, such as Faecalibacterium and Roseburia, alongside increased levels of Bacillota (formerly Firmicutes).²¹²

In addition to these associations, SCFAs provide a mechanistic link between microbial composition and host metabolic health. In obesity, reduced SCFA-producing bacteria impair gut satiety hormones,²¹³ increase energy harvest,²¹⁴ and promote inflammation.⁵⁸ In contrast, adequate SCFA availability activates GPR43,⁵⁴ enhances lipid oxidation and adipose tissue browning,⁵⁶ strengthens gut barrier integrity,⁵⁷ reduces inflammation,⁵⁸ and stimulates gut–brain satiety pathways.²¹⁵ This highlights their protective role and therapeutic potential against obesity.^56,57

In T1DM, reduced levels of acetate and butyrate compromise gut barrier integrity and impair regulatory T-cell expansion, thereby promoting autoimmune destruction of pancreatic β-cells.^216,217 In T2DM, insufficient levels of acetate and propionate contribute to insulin resistance,^57,218 while low butyrate exacerbates systemic inflammation.⁵⁷ In contrast, adequate SCFA signaling improves insulin sensitivity, enhances incretin secretion, and improves glucose metabolism.²¹⁹ Overall, these disease-specific patterns highlight SCFAs as critical mediators that actively modulate immune and metabolic pathways beyond their role as microbial byproducts. In light of these mechanistic insights, therapeutic interventions such as probiotics, food-related modifications, and FMT are being explored to restore gut microbiome balance and improve SCFA availability in the management of obesity and diabetes.^220,221 Studies indicate that probiotics and FMT have a positive influence on obesity and diabetes by enhancing the production of SCFAs and regulating glucose metabolism and food intake.^208,222 Nonetheless, these studies have not yet led to approved clinical interventions.

2.7. Kidney diseases

Worldwide, kidney diseases, such as acute kidney injury (AKI) and chronic kidney disease (CKD), are leading causes of morbidity and mortality. Around 10% of the global population has CKD alone, which amounts to more than 700 million individuals, and over 1.2 million people die every year.²²³ Also, it is estimated that over 13 million people suffer from AKI each year, contributing to 1.7 million deaths worldwide.²²⁴ While CKD and AKI dominate the epidemiological landscape, other renal disorders, including glomerular diseases, polycystic kidney disease, and diabetic nephropathy, also contribute significantly to the global burden of kidney diseases.^225-227 Moreover, it is common for kidney disease to develop along with other conditions, such as diabetes, hypertension, and cardiovascular disease.^228,229

The gut microbiome and kidney function form a complex and two-way interaction known as the gut-kidney axis.²³⁰ Research has shown that gut microbiome dysbiosis can contribute to the onset and progression of kidney disease and that kidney disease itself can alter the gut microbiome, leading to gut dysbiosis.^231,232 A dysbiotic gut produces protein-bound uremic toxins (PBUTs), which enter the bloodstream and induce systemic inflammation and oxidative stress, exacerbating kidney damage.²³³ The PBUTs include indole-3-acetic acid, p-cresol sulfate, and indoxyl sulfate.²³⁴ Many bacteria from the phyla Bacillota (formerly Firmicutes) and Bacteroidota (formerly Bacteroidetes), including C. difficile, Bacteroides fragilis, and Ruminococcus gnavus, thrive under dysbiosis and accumulate these PBUTs.²³⁵ Additionally, gut dysbiosis affects the production of SCFAs, which play a critical role in intestinal integrity, reducing inflammation, and protecting renal function.²³⁶ Consequently, bacterial endotoxins, including LPS, can translocate into the bloodstream. This translocation triggers systemic inflammation, contributing to glomerulosclerosis, kidney fibrosis, and tubular damage.^237,238 The gut microbiome also plays a crucial role in the metabolism of essential nutrients, including calcium and magnesium, which are vital for kidney health.^239,240 It has been demonstrated that dysbiosis enhances intestinal oxalate absorption, alters urine pH, and disrupts calcium metabolism, ultimately leading to kidney stone formation.²⁴¹ Bacteria like Oxalobacter formigenes shows potential for reducing urinary oxalate levels and preventing calcium oxalate stones.²⁴²

As people age, kidney function naturally declines, making older adults particularly susceptible to kidney diseases.^243,244 This is due to a combination of physiological changes, comorbid conditions, and environmental factors. CKD affects 5% of individuals aged 20−39 and rises sharply to 50% in those over 70 years old.²⁴⁵ Similarly, the prevalence of AKI increases among those aged 60 and older.^245,246 Sun et al. demonstrated that changes in gut microbiota composition with age correlate with impaired kidney function, suggesting that gut dysbiosis may be a potential driver of age-related kidney dysfunction.²⁴⁷ Despite this, kidney diseases are not limited to older people, underscoring the intimate connection between age and kidney health.²⁴⁸ That said, mechanistic and observational studies with a larger sample size and long-term follow-up are required to provide deeper insights into the association between gut dysbiosis and the development of kidney disease in older populations.

2.8. Cardiovascular diseases

Cardiovascular diseases are a group of diseases that affect the heart and blood vessels, including but not limited to coronary heart disease, cerebrovascular disease, and peripheral arterial disease. Atherosclerosis is the build-up of plaque inside the arteries. When atherosclerosis develops in the inner walls of the blood vessels that supply the brain, it can lead to stroke. When atherosclerosis reduces the blood supply to the heart, it can cause myocardial infarction (also called heart attack).²⁴⁹ Cardiovascular diseases are the leading cause of death worldwide. In fact, in 2019, there were more than 523 million diagnosed cases and more than 18 cardiovascular diseases.²⁵⁰

Dysbiosis of the gut microbiome is associated with the development of cardiovascular diseases.¹⁸³ During the leaky gut condition, microbiota translocate from the gut into the systemic circulation. Then, gut microbiota-derived products, such as LPS, trigger the release of pro-inflammatory cytokines and stimulate host innate immunity.²⁵¹ This pro-inflammatory state has been linked to an increased risk of cardiovascular diseases.^252-254 Indeed, the CANTOS clinical trial reported that the inhibition of the IL-1β pathway using canakinumab reduces the risk of cardiovascular disease events, independent of lipid level lowering.²⁵⁵ Beyond gut leakiness, gut microbiota can generate biologically active metabolites that have also been linked to cardiovascular diseases, including bile acids and SCFAs. In addition, the gut microbiota metabolizes dietary choline and carnitine into trimethylamine (TMA), which is subsequently converted by hepatic flavin-containing monooxygenases (FMOs) into trimethylamine N-oxide (TMAO). Similarly, gut microbial metabolism of dietary phenylalanine generates phenylacetic acid (PAA), which is further transformed in the liver into phenylacetylglutamine (PAG). The association between these metabolites and the risk of cardiovascular disease development and prognosis was established based on direct experimental evidence generated from multiple genetic engineering studies in microbes, coupled with transplantation into germ-free mice, as well as multiple gain-of-function and loss-of-function genetic and pharmacological studies. Importantly, the findings of these mechanistic in vivo studies have been supported by large-scale clinical trials (nicely summarized in).¹⁸³ Nonetheless, several challenges remain to be addressed. For example, while a large amount of evidence suggests that microbial dysbiosis and microbial metabolites are associated with cardiovascular disease, no specific bacterial community has been identified as the driver of pathogenicity. One of the potential reasons behind such a problem is that microbiota can be influenced by diet, physical activity, smoking history, alcohol intake, obesity, co-morbidities, and medications.²⁵⁶ This, in turn, makes it challenging to determine whether specific microbial changes are driving cardiovascular diseases or, conversely, being driven by them. Additionally, a pro-inflammatory state and gut leakiness are not always associated with the development and prognosis of cardiovascular disease. Patients with colitis and inflammatory bowel diseases who have gut barrier defects do not have a higher risk for cardiovascular diseases, suggesting that a deeper understanding of this phenomenon is needed.¹⁸³ Taken together, it is well established that the gut microbiome is associated with cardiovascular diseases. However, several questions need to be answered in order to develop a successful therapeutic intervention or to develop clinically useful biomarkers.

Aging, gut microbiome, and cardiovascular diseases are likely directly connected. The incidence of cardiovascular diseases increases with age, ranging from ∼40% in 40–59-year-old individuals to 75% in adults aged 60–79 years and to 86% in older people aged >80 years.²⁵⁷ However, the fact that not all older people develop cardiovascular disease events, and many young people suffer from them, suggests that the association between aging and cardiovascular diseases is complex and multifactorial.²⁵⁸ To address this question, a recent study collected data from a large, prospective discovery cohort of 10,207 individuals aged 40 to 93 years. By performing shotgun fecal metagenomes analysis on 4,491 individuals from this discovery cohort, authors identified age- and metabolism-related gut microbiota signatures. Also, study authors were able to develop a gut microbial age (MA) metric based on 55 age-specific microbial species. They found that among unhealthy older participants aged ≥60 y, the risk for developing cardiovascular disease was exacerbated in those with high MA but diminished in those with low MA (characterized by a lower abundance of Prevotella). This risk association was independent of age, sex, educational attainment, lifestyle, diet, and medication use. These observations were further validated using four external international cohorts.²⁵⁹

2.9. Bone and muscular diseases

The most common bone and muscle disorders among older adults include osteoporosis, osteoarthritis, sarcopenia, and spinal stenosis. Each condition significantly impacts mobility, quality of life, and health outcomes for older adults.²⁶⁰

Osteoporosis is characterized by reduced bone density, making bones fragile and more prone to fractures. Osteoporosis affects over 200 million women worldwide, with significant prevalence in both genders over 50. It is prevalent in North America, Europe, and Asia, with Asia projected to account for over half of the world’s hip fractures by 2050.²⁶¹ Risk factors include aging, low calcium and vitamin D intake, and sedentary lifestyles.²⁶² The gut microbiome plays a critical role in bone metabolism, with bacterial taxa, such as Lactobacillus and Ruminococcus, emerging as key contributors. These bacteria influence osteoporosis by regulating osteoclast activity, which is responsible for bone resorption. Also, they support mitochondrial function in bone cells, which is essential for energy production and maintaining bone health.²⁶³

Osteoarthritis (OA) is a degenerative joint disease that primarily affects the hands, knees, hips, and spine. OA is one of the most common causes of disability worldwide, with a prevalence of approximately 10−15% of adults aged 60 years and older.²⁶⁴ Recent studies have linked gut microbiome dysbiosis to OA progression, with imbalances in bacterial genera, such as Bifidobacterium and Clostridium, exacerbating inflammation.²⁶⁰

Sarcopenia is the progressive loss of muscle mass and strength strongly associated with aging. Up to 50% of individuals over 80 years are affected by sarcopenia.²⁶⁵ The gut microbiota plays a significant role in sarcopenia. Dysbiosis can exacerbate the condition by disrupting key metabolic and inflammatory pathways. Specific bacteria, such as Bacteroides and Prevotella, are crucial for fiber fermentation and the production of SCFAs, which help maintain muscle mass and function. An imbalance, characterized by a reduced abundance of these beneficial bacteria and an increase in opportunistic pathogens such as Fusobacterium, contributes to chronic inflammation, which accelerates muscle degradation.²⁶⁶

Spinal stenosis refers to the narrowing of spaces within the spine, often causing nerve compression. Spinal stenosis is most common in individuals over 50 years old, affecting up to 11% of the older population.²⁶⁷ Recently, Li et al. used a Mendelian randomization approach to explore the relationship between gut bacteria and spinal stenosis. Their findings suggested that specific bacterial taxa, including Eubacterium fissicatena (E. fissicatena) and Oxalobacter, regulate the nuclear factor kappa B (NF-κB) signaling pathway, which subsequently modulates the production of pro-inflammatory cytokines, such as tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6), potentially influencing spinal health and leading to spinal stenosis.²⁶⁸

2.10. Vision loss

Vision loss is responsible for compromising quality of life in the older population. A variety of risk factors were reported for vision loss, including being 65 years or older.²⁶⁹ In a recent population-based study, researchers reported an increase in the global prevalence of vision loss, attributed to population aging from 1991 to 2019, which reached 183.37 million in 2019.²⁶⁹ The most frequent causes of vision impairment observed in later life (>60 years) are cataracts, glaucoma, age-related macular degeneration (AMD), diabetic retinopathy, and presbyopia.²⁷⁰ In 2017, the concept of the gut-retina axis was introduced by Rowan et al., emphasizing the role of the gut microbiome in the development and progression of eye diseases.²⁷¹ Since then, research in the field of gut microbiome and ocular diseases has received more attention, particularly in ophthalmology medicine.²⁷² Three primary mechanisms of the gut microbiome have been highlighted as contributing to eye diseases. The gut microbiome could modulate tear secretions in ocular surface diseases, including infectious keratitis and dry eye. Dysbiosis of the gut microbiome may compromise the integrity of the retinal barrier, contributing to retinal and macular diseases, such as AMD, diabetic retinopathy, and retinal artery occlusion. Furthermore, gut microbiome dysbiosis may induce abnormal immune system activation, which can contribute to immune-mediated eye diseases (e.g., Behçet’s disease and uveitis).²⁷³ Modulation of the gut microbiome could open new avenues for limiting the risk of vision loss and improving the quality of life in the older population.

2.11. Hearing loss

Auditory impairment hinders the acquisition of verbal communication, which can subsequently impact cognition and development, and potentially compromise social well-being. The Global Burden of Disease hearing loss collaborators reported that around 1.57 billion individuals had hearing loss in 2019. Of all individuals with hearing impairment, 62.1% were older than 50 y.²⁷⁴ The most frequent cause of hearing loss is sensorineural hearing loss (SNHL), which is also associated with dementia and AD.²⁷⁵ Furthermore, previous studies have recognized a positive correlation between SNHL and gastrointestinal tract conditions, mainly inflammatory bowel disease and celiac disease.²⁷⁶ Hence, the concept of the gut-inner ear axis has recently emerged, suggesting a potential role of the gut microbiome in the SNHL pathogenesis. However, the association studies between gut microbiome and hearing loss, especially in older adults, are still limited. In a recent Mendelian randomization study performed in 2023 to explore the causal effect of gut microbiome on SNHL, Yin and collaborators suggested a protective role of gut Lachnospiraceae (UCG001) and Intestinimonas against SNHL, while Rikenellaceae (RC9gutgroup) and Eubacterium (hallii group) were suggested to have an increased risk of SNHL.²⁷⁶ Further research is needed to elucidate the potential mechanisms of gut microbiome in the development and progress of hearing loss in older adults.

2.12. Skin diseases

Older adults are increasingly at risk for various skin diseases due to physiological changes associated with aging, including weakened immunity, prolonged exposure to environmental factors, and the effects of multiple medications.²⁷⁷ Emerging research has identified a link between gut microbiome homeostasis and skin health, along with evidence of two-way communication between the gut microbiome and skin.²⁷⁸ Previous research has also explored the relationship between gut dysbiosis and skin diseases, including atopic dermatitis, psoriasis, rosacea, and acne.²⁷⁹ Furthermore, manipulation of the gut microbiome, for example, through the use of pro- and prebiotics, has shown positive outcomes in the prevention and/or management of skin conditions, including atopic dermatitis, psoriasis, and acne.²⁸⁰ However, further research is still needed to elucidate the complex mechanism of the gut-skin axis in dermatological diseases.²⁷⁸

2.13. Reproductive system diseases

Reproductive system diseases are associated with aging. Also, in both male and female, reproductive health and hormonal regulation are intricately linked to dynamic changes in the gut microbiome.

In females, menopause (a hallmark of reproductive aging) is associated with reduced microbial diversity, loss of beneficial taxa such as Lactobacillus and Bifidobacterium, and enrichment of pro-inflammatory species, which contribute to higher risks of cardiometabolic, bone, and cognitive disorders.^281-286 The gut microbiome plays a crucial role in modulating a female’s hormonal health, particularly through its interaction with sex hormones, such as estrogen and progesterone. This relationship is bidirectional: sex hormones influence the composition of the microbiome, while specific gut microbes, particularly those comprising the estrobolome modulate systemic estrogen levels through enzymatic activity. These microbes produce β-glucuronidase, which deconjugates estrogens in the gut, allowing their reabsorption and influencing circulating hormone levels.²⁸⁷ Hormonal fluctuations during menopause can alter both the composition and activity of the microbiome, particularly in areas such as the oral, gut, vaginal tract, and skin.²⁸⁸ For example, the drop in estrogen levels during menopause is linked to disruptions in the gut microbiota, including decreased diversity and microbial imbalance, which may trigger inflammation and elevate the risk of conditions like heart disease and cognitive decline.²⁸⁸ Moreover, aged females exhibit a decrease in beneficial microbes, such as Bifidobacterium, and an increase in pathogenic taxa, which correlates with diseases like T2DM and atherosclerosis. These changes suggest a strong influence of hormonal aging on microbiome-related disease risk.²⁸⁹

In addition, emerging evidence indicates that the gut microbiome plays a critical role in male reproductive function. Gut dysbiosis has been associated with impaired semen parameters, including oligozoospermia, asthenozoospermia, and teratozoospermia, as well as alterations in seminal plasma composition.^290-297 For example, Cao et al reported lower abundances of Bifidobacterium, Blautia, and Collinsella, and higher Bacteroides in men with severe oligospermia.²⁹⁸ Several studies have explored potential mechanisms by which gut dysbiosis impairs male reproductive function, including disrupted hormonal regulation, systemic inflammation, and oxidative stress.^{290,292,299-306} Importantly, recent studies suggest that gut dysbiosis may underlie the age-related decline in semen quality and male infertility.^306-308 Collectively, these findings suggest that reproductive aging and microbiome alterations are interdependent processes that shape disease susceptibility over a male’s lifetime.

Several animal and human studies suggest that probiotic supplementation can restore microbial balance and improve reproductive outcomes. For example, experimental work has shown that live Lacticaseibacillus and Limosilactobacillus strains significantly increased sperm motility and vitality (~30–40%) and enhanced mitochondrial function.³⁰⁹ In rodent models, probiotic mixtures reversed spermatogenesis damage induced by environmental toxins such as bisphenol A, improving gut barrier integrity and SCFA production.³¹⁰ More importantly, in human trials, multi-strain probiotics improved sperm concentration, motility, and morphology, likely through antioxidant and anti-inflammatory mechanisms.³¹¹ Similarly, probiotics supplementation can increase term pregnancies in females with infertility of unknown origin and improve female reproductive functions.^312,313

Taken together, while these findings highlight promising roles of the gut-microbiome axis in reproductive health, current evidence has notable limitations. Human studies are restricted to relatively small cohorts and heterogeneous probiotic strains, doses, and durations, limiting comparability. Many mechanistic insights arise from animal or ex vivo models, which may not fully translate to humans. In addition, genetic approaches such as Mendelian randomization rely on 16S rRNA-based GWAS data, which lack species-level resolution. Larger, well-designed clinical trials and high-resolution multi-omics approaches are required to establish causality and guide the development of targeted microbiome-based interventions for infertility and other reproductive system diseases.

3. Enabling technologies for microbiome research and engineering

Despite the large number of published studies on microbiome-based therapeutics, it has been challenging to translate most of the pre-clinical findings into beneficial medical interventions. Indeed, there has been little consistency between studies regarding the microbiome community specifically identified as the driver of pathogenicity. Potential reasons include technical confounding factors, such as fecal specimen collection methods, DNA extraction protocols, bioinformatics pipelines, and definitions of treatment outcomes. Additionally, several biological confounding factors exist, including geographical differences in patient populations, host comorbidities, and medications.^61,63,183 Furthermore, the reports of microbiome-based therapeutic effects are conflicting, which is likely due to differences in intervention doses and treatment durations.

Most routinely employed sequencing techniques, particularly amplicon-based approaches such as 16S rRNA gene sequencing, often lack the resolution necessary to distinguish microbial taxa at the species or strain level. Consequently, these methods provide only a limited, low-resolution view of microbiome communities and functional activity within a given specimen. They do not provide a clear understanding of the microbe-microbe and microbe-host interactions. As a result, despite numerous proof-of-concept pre-clinical studies, several clinical trials failed to demonstrate efficacy or were terminated due to a lack of efficacy.^61,63,183 That being said, the implementation of advanced multi-omics approaches combined with AI platforms is predicted to overcome most of the current hurdles and advance the field of microbiome research.⁶¹

3.1. Functional omics approaches to investigating microbiome

The gut microbiome, with its intricate web of microbial life, has emerged as a revolutionary and disruptive force in science and innovation. Its role as a “second genome” influences various aspects of human health, including metabolism, immune regulation, and disease susceptibility.³¹⁴ To fully harness its transformative power, we must comprehend its complex composition and multifaceted functions.^63,183,315 This section explores cutting-edge technologies that shed light on the microbiome’s mysteries and reveal its profound impact on human well-being and the future of biotechnology.

As we delve into the quest to uncover microbial potential, the revolutionary approach of culturomics takes center stage. Culturomics is a cutting-edge culturing method that surpasses traditional techniques, employing multiple culture conditions, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS), and 16S ribosomal ribonucleic acid (16S rRNA) sequencing to identify bacterial species.³¹⁶ This groundbreaking holistic approach marks a significant advancement in the field of clinical microbiology, overcoming the challenges of culturing previously uncultured microorganisms.³¹⁶ The advent of sophisticated identification methods, e.g., MALDI-TOF MS, and the integration of molecular tools have paved the way for the emergence of microbial culturomics.

The second aspect delves deeply into genetic materials—the genome sequencing potential inherent within the microbiome’s DNA. Metagenomics approaches serve as our guiding compass, enabling us to examine the taxonomic composition of microbial communities and investigate the functions of individual genes.³¹⁷ In the quest for comprehensive taxonomic characterization, metagenomics presents a comparison between 16S rRNA and shotgun sequencing data. Through shotgun metagenomics, we obtain short-read sequences, offering a broad view of microbial diversity and potential functional pathways. Furthermore, long-read sequencing technologies, such as those from PacBio and Oxford Nanopore, provide detailed insights into complex genomic structures, enabling us to unravel the entire genetic landscape of the microbiome.³¹⁷ This comprehensive genomic analysis provides invaluable knowledge, advancing our understanding of the microbiome’s role in shaping human health. Delving deeper into the microbiome's secrets, functional metagenomics emerges as a powerful approach for microbiome profiling. Metatranscriptomics captures active gene expressions, providing real-time insights into the microbiome’s functional capacity.³¹⁸ Complementing this, metaproteomics unveils the microbial ballet of protein expression, illuminating essential processes.³¹⁸ Meanwhile, metametabolomics reveals microbial metabolites, shedding light on their roles in shaping the microbiome’s functions and interactions.³¹⁹ This multi-omics strategy presents a comprehensive picture of the microbiome’s functionality, paving the way for transformative applications in geriatric medicine.

3.2. Synthetic biology and genetic tools for microbial reprogramming

Synthetic biology presents new opportunities for exploring microbes as innovation in microbial technology continues to advance. By combining principles of engineering and biology, this field offers precise techniques for reprogramming microbes for diagnostic and therapeutic applications.^320-322 These techniques, such as genetic circuits, biosensors, memory systems, and kill switches, enable researchers to manipulate the behavior of microorganisms with precision.^323-325 Therefore, we can gain a better understanding of the dynamics of microbiomes and develop innovative applications in areas such as geriatric medicine.³²⁶

Genetic logic circuits represent a key innovation in synthetic biology, providing practical methods to control gene expression in microbes. In simple terms, these circuits use mechanisms such as AND, OR, and NOT gates, allowing microbes to respond to complex environmental signals with high precision.³²⁷ For instance, engineered microbes can release therapeutic compounds only if specific disease biomarkers are present, ensuring targeted treatment with minimal side effects. This high specificity makes precision medicine more effective.³²⁶ Additionally, biosensors and quorum sensing are becoming increasingly important in the field of synthetic biology. These advancements can enhance microbes’ ability to detect and respond to their environment in real time.³²⁸ Microbial communities utilize biosensors to detect environmental signals, including toxins and disease markers. Likewise, quorum-sensing mechanisms help microbial communities facilitate the formation of biofilms, among other activities.³²⁹

Through synthetic biology, microbes can be engineered to become active agents that stabilize microbiomes and deliver targeted therapeutic outcomes to individuals. Furthermore, synthetic biology enables microbes to track their interactions with environmental stimuli using memory systems, such as Clustered, regularly interspaced short palindromic repeats (CRISPR)-based DNA recording.³³⁰ This allows microbes to monitor their exposures to pollutants, pathogens, or other stimuli, providing valuable insights into microbiome dynamics over time. For microbial engineering, especially as therapeutic agents, it is crucial to ensure the safety of modified microbes, which can be achieved through genetic “kill switches” that prevent unintended consequences.³²⁵ These genetic mechanisms safeguard the modified microbes, enabling them to achieve their intended functions and self-destruct under controlled conditions.³³¹ For example, modified strains of E. coli and Lactobacillus are being used as anti-tumor agents.^332-334 These strains are designed to target and colonize tumor sites while carrying genetic kill switches that can be deactivated only when triggered, guaranteeing a safe and controlled intervention. Adapting microbial hosts, commonly known as chassis, for synthetic biology is key to these beneficial innovations for humans. Advances in molecular editing tools, such as CRISPR/CRISPR-associated protein (Cas) and other gene-editing techniques, have enabled researchers to modify microbial genomes, leading to increased microbial genome stability and efficiency.³³⁵ Recently, CRISPR/Cas9 has been extensively used for site-directed mutagenesis and gene deletion or insertion across a wide range of bacteria.³³⁶ For instance, it has been employed to edit genes in microbiome-related bacteria, such as Clostridium sporogenes (C. sporogenes), advancing our understanding of host-microbiome relationships.³³⁷

Microbial engineering is further advanced by in situ genetic manipulation, which enables researchers to edit microbial communities in their natural habitats. Mobile genetic elements, such as phages,³³⁸ phage-inducible chromosomal islands,³³⁹ plasmids,³⁴⁰ and transposons,³⁴¹ can be utilized as carriers to transfer DNA into microbiota in situ. The advantage of using these elements lies in their ability to introduce targeted genetic changes without disrupting the ecological context. All in all, by utilizing these technologies, we can manipulate and harness the microbiome in unprecedented ways, from preventing disease to advancing personalized medicine. By harnessing the power of microbial science and deepening our knowledge of the microbes around us, we are paving the way for a healthier and more sustainable future.

3.3. Artificial intelligence in microbiome and aging research

Artificial Intelligence (AI), including machine learning (ML) and deep learning (DL), has emerged as a robust set of tools in the study of aging and gut microbiome.^342-344 These technologies enable researchers to integrate and analyze complex, high-dimensional datasets, thereby significantly advancing our understanding of the gut microbiome profiles and their influence on biological aging,^345-347 aging-related diseases,^348,349 and the development of therapeutic interventions.^350,351 One of the initial advancements in this field was the development of microbiome-based aging clocks, which utilize ML models to estimate biological age from gut microbial compositions.^352,353 Examples of such models include the Ensemble Multi-View Aging Clock,³⁵⁴ the Metatranscriptomic Aging Clock,³⁵³ and the Microbiome-Metabolome XGBoost Model.³⁴³ All these models have demonstrated high predictive accuracy and have identified a range of age-associated microbial taxa, commonly including genera such as Bacteroides, Prevotella, and Akkermansia.^343,355 Despite this, factors such as population demographics and analytical methods can influence the specific biomarkers identified.^352,355

In addition to aging prediction, microbiome-based AI models have also been used to evaluate physical frailty in older individuals, which is widely recognized as a key marker of functional decline.^356,357 In these individuals, the predicted age of the microbiome often exceeds their chronological age; this phenomenon is strongly correlated with clinical frailty scores.³⁵⁴ Representative models include Random Forest, Elastic Net regression, and XGBoost, which employ ensemble approaches to uncover non-linear microbial patterns and detect alterations such as the reduction in SCFA-producing bacteria.³⁵⁴

AI-driven approaches have also been explored for risk stratification of aging-related diseases. Models built with algorithms such as Random Forest, Support Vector Machines (SVMs), and gradient boosting algorithms (e.g., XGBoost) have distinguished Parkinson’s disease, Alzheimer’s disease, and cardiometabolic conditions from healthy aging with moderate accuracy (AUCs typically 0.65–0.75).^349,358,359 More recently, deep learning architectures, including long short-term memory (LSTM) networks and convolutional models, have been applied to Parkinson’s disease datasets with promising but cohort-specific results.³⁶⁰

Multi-omics integration has further improved predictive performance and provided mechanistic insights, such as lipid/energy metabolism alteration in Parkinson’s disease and reduced abundance of Akkermansia muciniphila in Alzheimer’s disease.^361,362 However, these applications face challenges, including limited generalizability due to geographic and dietary variability, as well as small sample sizes.^363-365 Although these tools hold significant promise for screening frailty, early disease detection, and risk stratification, their clinical translation require larger datasets, multi-cohort validation, and improved interpretation.^364,366

Beyond diseases prediction, AI also facilitates the integration of multi-omics data, including metagenomics, metabolomics, and host transcriptomics, to elucidate the mechanistic connections between microbial metabolism and host aging pathways.^367,368 Using AI, researchers can gain deeper insights into host-microbe dynamics by uncovering complex patterns and interactions that traditional methods may overlook.³⁶⁹ Such insights are contributing to the development of new AI-guided interventions, including personalized probiotics and nutrition strategies designed to modulate the microbiome and promote healthy aging.³⁷⁰ Together, AI, the gut microbiome, and aging represent a dynamic research frontier with increasing translational potential.

3.4. Biobanks in gut microbiome and aging research

Biobanks are organized collections of human biological specimens, including fecal specimen, paired with detailed demographic and clinical data and stored under rigorous ethical and operational standards for research purposes.³⁷¹ These repositories adhere to international guidelines to ensure the quality, safety, and integrity of their practices, with robust frameworks addressing ethical, legal, and social considerations, including donor privacy and specimen use.³⁷¹ As a milestone in the research and development ecosystem, biobanks provide a strategic infrastructure for advancing precision and personalized medicine and enabling transformative clinical breakthroughs by offering access to high-quality biological specimens and a comprehensive clinical dataset.

Well-established microbiome biobanks have emerged as pivotal resources for advancing research on the complex interactions between host health and microbial ecosystems in health and disease (Table 1). Moreover, aging-centered biobanks, such as the Human Aging Genomic Resources, which encompasses databases including GenAge, AnAge, DrugAge, GenDR, CellAge, and LongevityMap, have significantly contributed to the field by cataloging genes, species, drugs, and genetic variants related to aging and longevity.³⁷² The Finnish Biobank Collaboration also highlights the importance of integrating diverse biobank datasets, with contributions from the Arctic Biobank, the Borealis Biobank, and the Finnish Institute for Health and Welfare Biobank, focusing on metabolic risk, frailty, and healthy aging across nearly 1.4 million individuals.³⁷³ An additional example is the Aging Research Biobank, established by the National Institute on Aging in the USA, which aims to understand the nature of aging and the aging process, as well as common age-associated diseases, to extend the healthspan of individuals.³⁷⁴

The integration of gut microbiome profile data into aging biobanks remains overlooked, but microbiome aging biobanks have immense potential to support groundbreaking discoveries. They would provide sustainable platforms for exploring the complex relationships between the gut microbiome and aging processes, including the role of microbial communities and associated metabolites in modulating risks associated with non-communicable diseases, which are common among aging populations.³⁸⁰ Moreover, biobanks may facilitate the identification of microbial metabolites and bioactive compounds that influence the key physiological processes underpinning aging.³⁸⁰

3.5. Autologous fecal microbiota transplantation to promote healthy aging

As we discussed earlier, the concept of heterologous FMT has been increasingly investigated to support the restoration of microbial community composition and function, and it is currently approved for the treatment of recurrent C. difficile infection.^381,382 However, the application of heterologous FMT might have potentially adverse consequences.^381,382 First, FMT requires meticulous screening of the donor’s gut microbiome to ensure the absence of potential intestinal pathogens and ensure procedural safety. A few years ago, the U.S. FDA reported several cases of severe adverse events likely due to the transmission of pathogenic organisms in FMT clinical trials. As a result, the U.S. FDA and the European Directorate for the Quality of Medicines and Health Care (EDQM) have released updated guidelines for the development of live biotherapeutic products.^383,384 Also, the donor’s intrinsic and extrinsic factors may influence the success rate of FMT in a patient. Beyond donor selection, the recipients’ genetics, diet, and lifestyle also possess an additional level of complexity. These factors can play a crucial role in the initial response and long-term maintenance of FMT.⁶¹

Therefore, the concept of autologous FMT has recently emerged, in which an individual’s feces is collected during a healthy state, biobanked, and reintroduced later when that individual develops specific symptoms.³⁸² Previous studies have examined the effectiveness of autologous FMT in inflammatory bowel disease,³⁸⁵ hematopoietic stem cell transplantation,³⁸⁶ and obesity.³⁸⁷ The preliminary results indicated that autologous FMT could be utilized as a therapeutic approach to restore the healthy function of the gut microbiome.^385–387

In the context of aging, research has demonstrated that heterologous FMT from young or long-lived donors can restore gut microbiome homeostasis, decrease gut permeability and systemic inflammation, increase SCFAs and SCFAs-producing bacteria, and enhance cognitive functions in aged recipients.³⁸² However, data on autologous FMT for promoting healthy aging are scarce in the literature. In autologous FMT, an individual’s feces is collected during early adulthood, stored in a biobank, and then re-administered at a later stage of adulthood, representing a protective and therapeutic approach that may hold promise as an anti-aging intervention (Figure 2). Further longitudinal studies are needed to determine the optimal timing of feces collection and whether a single collection is sufficient or if pooling multiple fecal specimens during early adulthood is more effective. Dietary considerations during the period of fecal specimen collection may play a significant role in maintaining gut microbiome homeostasis, as a plant-based diet has been shown to promote the growth of beneficial bacteria and their associated metabolites.³⁸⁸ Technical considerations related to fecal specimen storage and preservation are also crucial for maintaining the integrity of microbial communities and preventing contamination. This area of research is in its infancy but holds potential promise for healthy aging.

3.6. Ethics in microbiome and aging research

International ethical guidelines governing research involving human subjects were designed to ensure ethical conduct, protect participants’ rights, and uphold scientific integrity. Key guidelines include (I) the World Medical Association Declaration of Helsinki (ethical principles for medical research involving human participants)³⁸⁹; (II) the U.S. Department of Health and Human Services Belmont Report (ethical principles and guidelines for the protection of human subjects of research)³⁹⁰; (III) the Council for International Organizations of Medical Sciences in collaboration with the World Health Organization³⁹¹; (IV) the Universal Declaration on Bioethics and Human Rights³⁹²; and (V) the Good Clinical Practice Guidelines (the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use).³⁹³ In light of these international guidelines, ethical considerations in human microbiome studies^394-397 and aging research^398,399 have been developed independently, with robust ethical guidelines established in each domain. However, a significant gap remains in addressing the unique ethical considerations at the intersection of human microbiome research and aging. Therefore, we have synthesized an ethical framework from both fields (i.e., the human microbiome and aging) considering the four pillars of bioethics (i.e., autonomy, non-maleficence, beneficence, and justice).⁴⁰⁰ Figure 3 depicts the ethical framework tailored to the specific domains of human microbiome and aging research.

3.6.1. Autonomy

Informed consent is a central ethical requirement in human microbiome studies, as it ensures that participants are fully aware of the study’s aims, methods, and potential risks. In aging research, consent is particularly significant because cognitive decline may affect the ability to provide informed consent.³⁹⁵ Obtaining this consent is essential because study participants must be able to understand the implications of microbiome research, as it may include unforeseen health insights or privacy concerns. Ethical research practices must prioritize the dignity and rights of older adults, ensuring that they benefit from research without being subjected to undue risks.³⁹⁸

3.6.2. Non-maleficence

Because the human microbiome is intricately linked to personal identity, which raises concerns about privacy and the potential misuse of sensitive data. Consequently, ethical standards must address how human microbiome data are stored, accessed, and used to ensure that individuals’ rights are protected.³⁹⁵ Data-sharing practices must strike a balance between scientific advancement and participants’ privacy to protect personal data while facilitating meaningful research collaboration.

3.6.3. Beneficence

The significant public health implications associated with human microbiome research necessitate the development of ethical guidelines for biobanking and the use of human microbiome data in public health initiatives. The commercialization of microbiome data and its implications for public health must be carefully managed to prevent exploitation.

3.6.4. Justice

The inclusion of vulnerable populations in human microbiome and aging research presents ethical, practical, and scientific challenges. Common examples of vulnerable cohorts include those consisting of older individuals, persons with disabilities, socioeconomically disadvantaged groups, or communities that experience restricted access to healthcare or educational resources. These cohorts may offer distinctive perspectives on the microbiome’s influence on the aging process; however, they simultaneously create a need for increased safeguards to guarantee ethical involvement and the equitable distribution of benefits. The commercialization of human microbiome research, particularly in the context of aging, presents significant ethical challenges that are focused primarily on equitable benefit distribution, informed consent, privacy considerations, and the potential for exploitation of vulnerable populations. The application of microbiome research findings to marketable products, including probiotics or anti-aging interventions, requires that any benefits be justly allocated, especially when the products are developed from participant contributions or indigenous microbiome specimens. All participants should be adequately informed about the research process and the potential commercial outcomes, thereby ensuring that their informed consent extends to the use of their biological data for profit-oriented objectives.

3.7. The PRIME framework for microbiome and aging research

To answer the question posed in the title of this article, “how technology will transform the future,” we formulate the PRIME framework—a structured and comprehensive roadmap to guide future research on the microbiome and aging. It consists of five strategic stages: (1) association studies (i.e., Profiling the gut microbiome in an age-associated disease using an integrated multi-omics approach), (2) correlation studies (i.e., Reviewing multi-omics data to generate mechanistic hypotheses regarding the microbiome involvement in a specific age-associated disease), (3) causation studies (i.e., Identifying specific gut microbiota or microbiota-associated products directly implicated in that disease), (4) translation studies (i.e., Mapping experimental findings into clinically applicable biomarkers, diagnostics or therapeutic interventions), and (5) validation studies (i.e., Evaluating the discovered biomarker(s), diagnostic or therapeutic interventions in clinical settings to ensure efficacy and safety) (Figure 4). Although a similar workflow exists,³²⁷ the PRIME framework offers a more systematic, structured, detailed, and current approach. It incorporates recent advances in multi-omics methodologies and outlines a wide range of potential clinical interventions. Therefore, we believe that implementing the strategies outlined in the PRIME framework will support continued advancement in the field and contribute to efforts promoting healthy aging.

4. Precision nutrition in modulating the gut microbiome to promote healthy aging

Recent studies have demonstrated that the gut microbiome composition and function can predict an individual’s response to dietary interventions, enabling the development of tailored strategies that integrate both diet and microbiome to optimize health outcomes.^401-403 Precision nutrition is increasingly employing multi-omics approaches, combined with dietary tracking, to link diet, gut microbiome, and metabolic health.^404,405 By mapping the effects of specific dietary patterns on microbial composition and metabolite profiles, researchers can design personalized diets that preserve beneficial microbes, limit inflammation, and improve metabolic outcomes.^370,406-409 Despite these advances, implementing precision nutrition remains challenging due to the complexity of integrating diverse datasets. Translating these strategies into public health or clinical practice requires a deeper understanding of the mechanisms driving interindividual variability.⁴¹⁰

Precision nutrition has also gained attention as a promising approach to support healthy aging by enhancing metabolic health and overall quality of life in older adults.^407,408 Recent advances highlight the potential of diet-derived bioactive compounds to modulate biological aging by shaping gut microbiome composition and function.⁴⁰⁷ Controlled interventions demonstrated that tailored dietary strategies can improve metabolic outcomes and overall well-being, supporting the feasibility of microbiome-informed precision nutrition approaches in aging populations.⁴¹¹ Early studies suggested that the Mediterranean diet may further support healthy aging,⁴¹² and interventions promoting SCFAs production have been shown to enhance gut barrier integrity and reduce age-associated disorders.^413,414 Collectively, these findings underscore a bidirectional relationship between diet, gut microbiome, and aging, highlighting precision nutrition as a promising approach to promote longevity and reduce the risk of age-associated diseases.

5. Environmental stressors in space: impact on gut microbiome and aging

Spaceflight has a profound impact on the human gut microbiome, primarily due to environmental stressors such as microgravity, cosmic radiation, and restricted diets. These factors induce shifts in microbial composition, including reduced populations of beneficial butyrate-producing bacteria, which play a key role in maintaining gut barrier integrity and modulating immune responses.⁴¹⁵ Astronauts experience reduced microbial diversity and increased intestinal permeability, both of which are linked to systemic inflammation and metabolic dysfunction.⁴¹⁶ These physiological changes may impair angiogenesis and contribute to conditions like spaceflight-associated neuro-ocular syndrome (SANS), as poor gut health influences vascular processes and ocular health.⁴¹⁵ Furthermore, immune suppression observed in space travelers is often associated with gut dysbiosis, which may increase susceptibility to infections and chronic diseases.^416,417 On the other hand, evidence from long-duration missions shows that spaceflight affects cellular aging markers, such as telomere length. Notably, telomeres have been observed to lengthen during spaceflight and then shorten rapidly upon return to Earth, with an increase in critically short telomeres. These dynamic shifts may reflect a stress-induced genomic response.⁴¹⁸ To counteract these effects, microbiome-targeted interventions are under investigation. Prebiotics, probiotics, and synbiotics have shown potential in simulated microgravity and space analog models, where supplementation improved gut barrier integrity, reduced pathogen overgrowth, and supported immune resilience.^419,420 These studies highlight the potential of microbiome modulation as a countermeasure to protect astronaut health during long-duration space missions. Although aging has been associated with changes in the microbiome and space travel is known to accelerate aging-related processes, the causal relationships among aging, spaceflight, and the microbiome remain to be fully elucidated.

6. Conclusions

The gut microbiome is associated with aging and the development of age-related diseases. Globally, considerable effort has been made to characterize microbiome composition and dynamics in these contexts to identify effective intervention strategies that promote healthy aging and restore microbial homeostasis. However, translating pre-clinical findings into clinical interventions has been challenging due to both biological complexity and technical limitations. To date, the only FDA-approved microbiome-based therapeutic is FMT for recurrent C. difficile infection. Despite these challenges, recent advances in multi-omics technologies, the expansion of aging and microbiome biobanks, and the integration of AI are poised to accelerate progress. The formulated PRIME framework will enable the translation of scientific insights into clinical innovations. By integrating microbiome science, aging biology, and emerging technologies, this review provides a comprehensive blueprint for advancing precision medicine and promoting healthy aging while also enhancing future capabilities to respond to the evolving landscape of age-related diseases and therapeutic innovations.

Supplementary Material

Supplementary material

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Supplementary Table 1

Funding Statement

This research was funded by grant HF-KSA 005 (NRC23R-467-08) from Hevolution Foundation to King Abdullah International Medical Research Center (KAIMRC), King Saud bin Abdulaziz University for Health Sciences (KSAU-HS), Ministry of National Guard Health Affairs (MNGHA), Riyadh, Saudi Arabia.

Supplemental material

Supplemental data for this article can be accessed at https://doi.org/10.1080/19490976.2025.2607076.

Disclosure of potential conflicts of interest

The authors report there are no competing interests to declare.

Author contributions

CRediT: Marwh G. Aldriwesh: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Visualization, Writing – original draft, Writing – review and editing; Raniah S. Alotibi, Nasser Alqurainy, Shatha Alrabiah: Data curation, Investigation, Methodology, Visualization, Writing – original draft, Writing – review and editing; Assad M. Arafah, Majed F. Alghoribi: Investigation, Methodology, Writing – original draft, Writing – review and editing; Reham Ajina: Conceptualization, Data curation, Investigation, Methodology, Supervision, Visualization, Writing – original draft, Writing – review and editing.

Data availability statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Abbreviations

Aβ

Amyloid-beta

AD

Alzheimer’s disease

AI

Artificial intelligence

AIDS

Acquired immunodeficiency syndrome

AKI

Acute kidney injury

AMR

Antimicrobial resistance

AMD

Age-related macular degeneration

BD

Bipolar disorder

BMI

Body mass index

CDI

Clostridium difficile infection

CKD

Chronic kidney disease

CRISPR-Cas

Clustered, regularly interspaced short palindromic repeats-associated protein

DALYs

Disability-adjusted life years

DC

Dendritic cell

DL

Deep learning

EDQM

European Directorate for the Quality of Medicines and Health Care

FDA

Food and Drug Administration

FMT

Fecal microbiota transplant

GCA

Giant-cell arteritis

GLOBOCAN

Global cancer

GLP-1

Glucagon-like peptide-1

GPRs

G protein-coupled receptors

GWAS

Genome-wide association studies

HGT

Horizontal gene transfer

HIV

Human immunodeficiency virus

HDACs

Histone deacetylases

ICI

Immune checkpoint inhibitor

IEU

Integrated epidemiology unit

IgE

Immunoglobulin E

ILC3

Innate lymphoid cells 3

IL-6

Interleukin-6

IL-22

Interleukin-22

MA

Microbial age

MALDI-TOF MS

Matrix-assisted laser desorption ionization-time of flight mass spectrometry

MGE

Mobile genetic element

ML

Machine learning

MS

Multiple sclerosis

NF-κB

Nuclear factor kappa B

NK

Natural killer cell

OA

Osteoarthritis

OMV

Outer membrane vesicle

PAG

Phenylacetylglutamine

PBUT

Protein-bound uremic toxin

PD

Parkinson’s disease

PMR

Polymyalgia rheumatica

RA

Rheumatoid arthritis

SANA

Spaceflight-associated neuro-ocular syndrome

SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2

SCFA

Short-chain fatty acid

SLE

Systemic lupus erythematosus

SNHL

Sensorineural hearing loss

SVM

Support Vector Machine

TB

Tuberculosis

TMAO

Trimethylamine N-oxide

TNF-α

Tumor necrosis factor-alpha

T_reg cells

Regulatory T cells

T1DM

Type 1 diabetes mellitus

T2DM

Type 2 diabetes mellitus

16S rRNA

16S ribosomal ribonucleic acid