Authors: Suguru NISHIJIMA, Masahira HATTORI, Naoyoshi NAGATA
Categories: Review, Japanese gut microbiome, metagenomics, polypharmacy, large-scale, lifestyle, precision medicine
Source: Proceedings of the Japan Academy. Series B, Physical and Biological Sciences
Doi: 10.2183/pjab.102.006
Authors: Suguru NISHIJIMA, Masahira HATTORI, Naoyoshi NAGATA
Metagenomics has become a powerful approach for deciphering the structure and function of the human gut microbiome, a complex microbial ecosystem in the gut. The human gut microbiome plays a crucial role in health and disease through multifaceted interactions with various factors, including age, diet, lifestyle, and medications. This review summarizes key advances in gut microbiome research over the past two decades and presents several topics from a recent large-scale, data-driven study, specifically a cohort-based initiative, the Japanese 4D microbiome project. These include a population-level characterization of the Japanese gut microbiome in a global context through comparison with 31,695 gut metagenomes from 37 countries, as well as an extensive analysis of the effects of medications. This review provides new insights into the ecology and uniqueness of the Japanese gut microbiome and highlights the importance of large-scale, well-phenotyped cohorts in advancing microbiome science.
The human body is home to diverse microorganisms, including bacteria, archaea, fungi, and viruses (including phages), which collectively form a complex and dynamic microbial community. These microbes colonize various body sites, such as the oral cavity, stomach, gut, skin, and vagina, and form unique ecosystems at each location.^1)–3)^ Among them, bacteria are the most abundant, and the total number of their cells in the human body is estimated at approximately 40 trillion, roughly equal to the number of human cells, with the majority residing in the gut.^4)^ These commensal microorganisms play an important role in maintaining host physiology, metabolism, immune function, and overall health. They are functionally and ecologically distinct from pathogens, which transiently colonize the body and often cause infectious diseases, regardless of their phylogenetic closeness. Several related terms have been introduced to describe these microbial communities. The term “microbiota”, which first appeared in 1962,^5)^ refers specifically to the community of living microorganisms, while “microbiome”, which emerged in 1988,^6)^ more broadly encompasses not only these organisms but also their genetic material (genomes and genes), transcripts, proteins, metabolites, and the surrounding ecological and environmental context. The term “metagenome”, introduced in 1998,^7)^ refers to the collection of microbial genetic elements in a given environment.
In this review, we provide an overview of human gut microbiome research to date, with a particular focus on the gut microbiome’s ecological and functional features and its association with host health and disease. Furthermore, we highlight recent large-scale, data-driven cohort studies of the gut microbiome worldwide and introduce the Japanese 4D (Disease, Drug, Diet, Daily life) microbiome cohort, which we recently established.^8)–12)^ We present the population-specific characteristics of the Japanese gut microbiome in a global context, as well as the substantial and often underappreciated influence of medications, based on this large-scale Japanese dataset. This review highlights the importance of integrating large-scale, well-phenotyped microbiome data into biomedical research and advocates for microbiome-informed strategies to advance precision medicine and public health in Japan and beyond.
Human commensal bacteria (e.g., Escherichia coli) were first described in the late 19th century, and the scientific investigation of gut microbes using culture-based methods began in the 1950s. However, molecular phylogenetic analyses using the bacterial 16S rRNA gene later revealed that 60%–80% of gut bacterial species are difficult to culture.^13)–15)^ This finding highlighted the limitations of culture-dependent approaches in evaluating the entire structure of the human gut microbiome. This led to the widespread use of culture-independent methods, particularly 16S rRNA gene sequencing, which enabled phylogenetic profiling of microbial communities, including unculturable species.^16)–18)^ However, while 16S rRNA gene analysis provides taxonomic information about the community, it does not provide information about microbial genes and functional potential. To address this limitation, whole-genome shotgun sequencing of microbial community DNA,^19),20)^ called “metagenomics”, was applied to human gut microbiome research in the mid-2000s. These pioneering studies, which used Sanger sequencing, uncovered a variety of novel gene families and metabolic pathways, demonstrating that data-driven metagenomics is a powerful and promising approach for exploring the functional and genomic landscape of the human gut microbiome.^21),22)^
As these technological developments progressed, the International Human Microbiome Consortium (IHMC) was founded in 2008 by researchers from various countries, including Australia, Canada, China, France, Germany, Ireland, Japan, Spain, South Korea, and the United States, with the aim of sharing resources and methods to collect and integrate genomic information from the human microbiome.^23)^ Around the same time, two major projects were the Human Microbiome Project (HMP) in the United States^24),25)^ and the Metagenomics of Human Intestinal Tract (MetaHIT) project in the European Union.^26)^ Notably, the Human MetaGenome Consortium Japan (HMGJ) was launched in Japan in 2005, before the launch of the IHMC, by researchers in microbiology, genomics, bioinformatics, and immunology. The HMGJ aimed to characterize the Japanese population’s gut microbiome and develop core technologies required for microbiome studies.^22),27),28)^ These consortia laid the foundation for standardizing key workflows, including sample collection, storage, DNA extraction, library preparation, sequencing, and computational processing. The International Human Microbiome Standards (IHMS) and other studies evaluated key protocol steps, especially DNA extraction, which has the strongest impact on the obtained microbiome profile, and proposed optimized methods.^29)–32)^
Following the launch of such international initiatives, human microbiome research, particularly that on the gut microbiome, has been rapidly expanding worldwide, mainly driven by next-generation sequencing (NGS) technologies.^33),34)^ Currently, two main types of NGS technologies are widely short-read sequencing (e.g., Illumina),^35)^ which yields high-throughput data with reads of 150–300 bp, and long-read sequencing (e.g., PacBio HiFi and Oxford Nanopore),^36),37)^ which generates reads exceeding 10,000 bp. Short-read sequencing offers a throughput millions of times higher and at a significantly lower cost than traditional Sanger capillary sequencing,^38),39)^ enabling extremely rapid generation of vast amounts of microbiome data from large numbers of samples. In contrast, although long-read sequencing has lower throughput, it dramatically improves the completeness of microbial chromosomes, plasmids, and phage genomes and enhances the detection of structural variants. It also yields highly contiguous metagenome-assembled genomes (MAGs)^40),41)^ by reducing spurious assemblies and closing gaps that frequently occur in short-read assemblies, particularly in regions with highly similar sequences, such as rRNA genes and insertion sequences. These technological advances have also accelerated the sequencing of individual strain genomes. The increasing number of MAGs and isolated microbial genomes expands the taxonomic coverage of the reference genome database^42)^ and facilitates the accurate quantification of microbial abundance at the strain level.^43),44)^ Furthermore, the expanded reference genome database is a valuable resource for discovering novel and diverse microbial genes.^45)–49)^ However, many of these genes show little or no similarity to known genes, and functional characterization remains a major challenge for future research.^50)^
Since the publication of the first NGS-based metagenomic study in obese and lean twins in 2009,^51)^ NGS-based metagenomics has become the global standard for the comprehensive characterization of the human gut microbiome. As of 2025, PubMed has indexed more than 55,000 publications on the human gut microbiome, including approximately 9,000 publications in 2024 alone. Clinical metagenomic studies have expanded rapidly, revealing strong associations between alterations in the gut microbiome and various chronic non-communicable diseases. These include digestive,^52)–57)^ metabolic,^51),58)–64)^ cardiovascular,^65)–67)^ oncologic,^9),68)–73)^ neurological,^74)–79)^ and other systemic conditions.^80)–84)^ These disease-associated microbiome changes, commonly referred to as “dysbiosis”, are typically characterized by significant changes in species richness (alpha-diversity), overall community structure (beta-diversity), the functional gene repertoire, as well as the abundance of specific taxa. In addition to the disease-associated alterations, many studies have identified host and environmental factors that affect the gut microbiome, including age,^85),86)^ sex,^87),88)^ BMI,^51),59)^ stool consistency,^89)–91)^ circadian rhythm,^92),93)^ dietary patterns,^94)–98)^ smoking,^99)^ alcohol consumption,^100)^ physical activity,^101)–103)^ and medications.^8),90),104)–106)^ Multi-cohort studies have also revealed that geographical location is one of the factors that largely contribute to gut microbiome variation.^85),107)–111)^ In contrast, host genetic factors play a relatively minor role in shaping gut microbiome variation compared with host and environmental factors.^112)^ Nevertheless, a few specific genetic loci, such as those related to lactase persistence (LCT) and blood group antigens (ABO/FUT2) have been associated with changes in the abundance of specific gut species.^113)–116)^
Collectively, these numerous efforts over the past 20 years underscore how recent advances in sequencing technologies have provided deeper insights into the human gut microbiome and its interactions with various host and environmental factors. The increasing recognition of microbiome–disease associations emphasizes the role of the microbiome as a key target for therapeutic and preventive interventions and as a critical component of precision and personalized medicine as well as public health.^117),118)^
The Japanese 4D (Disease, Drug, Diet, Daily Life) microbiome cohort is a large-scale, single-population cohort designed to elucidate the role of the gut microbiome in health and disease across a wide spectrum of conditions (Fig. 1).^8)–12)^ The project systematically collected fecal and salivary samples from over 9,000 well-phenotyped individuals, together with a comprehensive set of multi-omics data, including shotgun metagenomics, fecal metabolomics, host genomics, transcriptomic and epigenomic profiles, and plasma cytokine/chemokine levels. A major strength of the cohort is its high-quality clinical and lifestyle metadata, comprising over 1,500 variables per participant with minimal missing data. These metadata span diverse categories, including anthropometric traits (e.g., age, sex, body mass index [BMI], visceral fat), lifestyle factors (e.g., diet, alcohol consumption, smoking, sleep, physical activity, and oral hygiene), gastrointestinal symptoms, clinical imaging (e.g., colonoscopy, computed tomography [CT], and magnetic resonance imaging [MRI]), medical history, and detailed medication use. This level of data quality is achieved through a prospective, standardized data collection framework implemented by trained medical personnel. Physicians make disease diagnoses based on clinical findings, imaging data, and electronic health records. Medication use is verified through a double-check process involving both patient interviews and medication notebooks, enhancing the accuracy of drug usage profiling. Self-reported questionnaires on lifestyle factors are validated using the same system to minimize recall bias, missing data, and misclassification.^8),119),120)^ To minimize batch effects, all biospecimen collection, storage, processing, and sequencing workflows follow unified protocols,^121),122)^ thereby avoiding technical artifacts due to factors such as bowel preparation for colonoscopy or prolonged sample storage at room temperature and ensuring high comparability across samples and time points. The human gut microbiome exhibits substantial inter-individual variability; thus, large sample sizes are essential to achieve sufficient statistical power for detecting robust associations. The scale and depth of the 4D cohort provide a unique advantage in this context. The project has collected microbiome and clinical data linked to over 100 disease conditions and 850 medications, making it one of the most comprehensive and deeply phenotyped microbiome resources in Asia and worldwide.
Building upon this rich dataset, the subsequent sections of this review primarily focus on the Japanese 4D cohort. Specifically, we present the population-specific characteristics of the Japanese gut microbiome in a global context and highlight key host factors that shape gut microbial composition, with a particular emphasis on medication use. These findings provide insights into the ecological and functional characteristics of the Japanese gut microbiome and illustrate microbiome-host associations with potential implications for precision health strategies.
To provide an overview of the diversity and structure of the Japanese gut microbiome, we constructed an integrated Japanese dataset by combining metagenomes from the Japanese 4D cohort^8),10)^ and other studies.^68),123)–125)^ This dataset comprised 5,466 gut metagenomes from individuals with diverse phenotypes, such as healthy individuals and patients with various diseases (mean age = 65.9 ± 13.2 years, 56.9% male, and mean BMI = 23.0 ± 3.5 kg/m^2^), most of which were obtained using the same enzymatic lysis-based DNA extraction method.^126)^ From this Japanese dataset, we identified 31 phyla, 44 classes, 101 orders, 220 families, 1,056 genera, and 3,551 species based on Genome Taxonomy Database (GTDB) taxonomies.^42)^ Among these, 1,071 species were detected with an average relative abundance of ≥0.05% (Fig. 2A). Most dominant taxa were classified into phyla that are recognized as major components of the human gut Bacillota, Bacillota_A, Bacillota_C (previously known as Firmicutes), Bacteroidota (formerly Bacteroidetes), Actinomycetota (formerly Actinobacteria), and Pseudomonadota (formerly Proteobacteria). At the genus level, the most abundant taxa included Blautia_A, Faecalibacterium, Phocaeicola (reclassified from Bacteroides under the GTDB taxonomy), Bacteroides, and Bifidobacterium (Fig. 2B and 2C). These genera are consistent with previous studies identifying the core members of the human gut microbiome in other countries.^2),127),128)^ We also observed considerable inter-individual variation in the microbiome profile. For a given genus, differences in relative abundance between individuals, including Gemmiger and Agthobacter, can exceed 100- to 1,000-fold (Fig. 2C), highlighting the high inter-individual variation in microbial diversity and abundance, which is consistent with earlier findings.^16),127)^
Next, we investigated the associations between these gut microbial profiles and key host factors, including age, sex, and BMI, in the Japanese dataset. Numerous genera exhibited statistically significant associations with these variables (Fig. 3). Genera positively correlated with age included Limosilactobacillus and Ligilactobacillus (both previously classified as Lactobacillus), as well as Streptococcus (Fig. 3A). These genera included taxa that predominantly colonize the oral cavity or upper gastrointestinal tract.^129),130)^ Their enrichment in older individuals supports earlier observations from previous studies.^87),131)^ Age-related species also included uncultured metagenomic species clusters without isolated representatives, such as CAG-83, GAG-170, and ER4. Additionally, we observed an increase in Klebsiella, a possible pathogen, and a decrease in Bifidobacterium in elderly individuals, as described previously.^86)^ Regarding sex differences, Phascolactobacterium_A, Prevotella, and Holdemanilla were more abundant in males, whereas Eggerthella, Phascolactobacterium, and Ruminococc**us_D were more abundant in females (Fig. 3B). The majority of these sex-associated taxa are consistent with previous studies in Japan and other countries.^87),132)^ For BMI, genera such as Acidaminococcus and Megasphaera were positively associated with higher BMI, whereas Erysipelatoclostridium was negatively associated (Fig. 3C). Overall, the association between gut bacteria and BMI was weaker than that between age and sex. Although some of these associations have been previously reported,^133),134)^ the robustness of the association across different populations remains unknown. Further studies are needed to clarify the roles of these BMI-associated taxa in host physiological and metabolic status.
To contextualize the population-specific features of the Japanese gut microbiome on a global scale, we extended our analysis to a total of 31,695 gut metagenomes from 37 countries worldwide, including the Japanese dataset (n = 5,466) and metagenomes from other countries (n = 26,229), which were compiled in a previous study.^91)^ Principal component analysis revealed a clear clustering of samples into two major one consisting primarily of individuals from high-income countries (i.e., industrialized or Westernized countries) and another composed of individuals from lower-income countries (i.e., non-industrialized or non-Westernized countries) (Fig. 4A). This clustering reflects previously reported global patterns in gut microbiome composition.^85),135)–137)^ The gut microbiomes from high-income populations were predominantly composed of Bacteroides and Phocaeicola, whereas those from lower-income regions were dominated by Prevotella (Fig. 4B). While the precise drivers of these differences remain under debate, dietary patterns and lifestyle factors are widely believed to play significant roles.^138)–140)^ The Japanese gut microbiomes were clearly positioned within the cluster of high-income countries, aligning with findings from prior research.^107),141)^ Comparative analysis between Japan and other countries identified genera significantly enriched in the Japanese microbiome (Fig. 4C, false discovery rate [FDR] < 0.05), including Ruminococcus_B, Faecalimonas, Streptococcus, Erysipelatoclostridium, and Bifidobacterium. In contrast, ER4, CAG-245, and RUG115 genera, which have not yet been isolated or cultured and are more prevalent in low-income countries, were significantly depleted (FDR < 0.05).
The significant enrichment of Bifidobacterium is one of the hallmark characteristics of the Japanese gut microbiome.^107),141)^ However, the underlying mechanisms driving this enrichment are not fully understood. Recent genome-wide association studies linking host genetic variants with gut microbial profiles have identified single-nucleotide polymorphisms (SNPs) in the LCT gene, which encodes the enzyme lactase, as being strongly associated with the abundance of Bifidobacterium in the gut.^113),114),142)^ It has been proposed that individuals with reduced or absent lactase activity in adulthood, a condition known as lactose intolerance, have undigested lactose reaching the gut, where it serves as a substrate that promotes the growth of Bifidobacterium. Given that lactose intolerance is prevalent among East Asians,^143)^ including the Japanese, we hypothesized that the elevated levels of Bifidobacterium in the Japanese gut may reflect an interaction between this genetic trait and dietary habits.^144)^ To explore this hypothesis, we examined country-level milk consumption data from the FAOSTAT database^145)^ and evaluated its relationship with the average relative abundance of Bifidobacterium across countries. The analysis showed that countries with a high prevalence of lactase persistence (e.g., Europe, North America, and South/Central Asia) typically consumed more milk than those where lactose nonpersistence is more common (e.g., Africa, East Asia, and South America). While no significant correlation was observed between milk consumption and Bifidobacterium abundance in countries with prevalent lactase persistence (Pearson correlation = −0.018, p = 0.94), a strong positive correlation was found in countries with high lactose intolerance (Pearson correlation = 0.69, p = 0.0023) (Fig. 5). Japan had the second-highest milk intake among East Asian countries after Mongolia, and the relative abundance of Bifidobacterium was similar to that of Mongolia. However, some African countries, such as Mozambique, Ghana, the Central African Republic, and Cameroon, had low milk intake and the lowest levels of Bifidobacterium abundances. Historically, milk consumption increased after World War II through school nutrition programs and food aid initiatives in Japan.^146)^ Since then, dairy intake has risen alongside income growth, making Japan one of the largest dairy consumers in East Asia today.^147)^ These findings suggest that the interaction between the genetic background of the Japanese population and increased milk consumption contributes to the enrichment of Bifidobacterium in the gut of modern Japanese individuals. Elevated Bifidobacterium levels have been associated with improved lactose-intolerance symptoms,^148)^ which may partly explain why approximately 80% of genetically lactose-intolerant Japanese individuals remain asymptomatic.^149)^ The high abundance of Bifidobacterium may be attributed to their genomes encoding a larger repertoire of carbohydrate-metabolizing enzymes, such as glycosidases, that can hydrolyze undigested dietary carbohydrates reaching the colon, compared with other gut species, such as Bacteroides.^150)^ However, the precise mechanisms underlying their striking proliferation in response to lactose remain unclear.
Another well-known feature of the Japanese gut microbiome is the enrichment of genes encoding polysaccharide-degrading enzymes that target specific polysaccharides (e.g., porphyran and agar) in marine red algae such as seaweed and wakame.^107),151),152)^ These genes appear to have been acquired by human gut-associated Bacteroides species via horizontal gene transfer from marine bacteria.^151)^ Interestingly, although these genes are highly prevalent in the gut microbiome of the Japanese population, they are markedly less common in Western populations.^107),152)^ This represents a clear example of adaptive evolution in gut microbiome function, likely shaped by host dietary habits and frequent contact between the gut and environmental microbial species. To expand upon these previous findings and assess the global distribution of these transferred genes, we reanalyzed metagenomic data for two key β-porphyranase and β-agarase, which hydrolyze porphyran and agar, respectively. Consistent with prior studies,^107)^ these genes were detected in nearly 90% of Japanese individuals (Fig. 6). Furthermore, our analysis revealed that these genes were frequently detected in individuals from other East Asian and Pacific countries, including South Korea, China, Thailand, Fiji, and Mongolia (detection 6.3%–95.5%, Fig. 6), with Korean samples showing a prevalence comparable to that of Japanese samples. In contrast, the genes were rarely detected in samples from Europe, Central Asia, North America, and South America (detection 0%–16.7%) and were entirely absent in samples from Africa (Fig. 6). This geographic difference suggests that seaweed consumption promotes the retention of these genes in gut microbiomes and that frequent horizontal gene transfer, similar to that of antibiotic resistance genes,^153)^ plays a significant role in shaping regional microbiome function. These findings underscore the impact of dietary culture and environmental exposure on the functional landscape of human-associated microbial communities.
A variety of internal and external factors contribute—either directly or indirectly—to inter-individual variation in the gut microbiome. To better understand the host factors that shape gut microbiome composition, we assessed their relative contributions to microbiome variability within the Japanese 4D cohort (n = 4,198).^8)^ This was enabled by the availability of standardized, comprehensive metadata, including detailed records of disease history, diet, lifestyle, and medication use, allowing for a multifactorial analysis of microbiome-associated variables within a unified framework.
Our analysis revealed that medication use had the strongest impact among all categories examined (Fig. 7A). Notably, its impact exceeded that of disease status and was approximately three times greater than that of intrinsic host factors such as age, sex, and BMI. Dietary habits and lifestyle factors, such as alcohol consumption and smoking, showed intermediate effects, while physical activity and sedentary behavior showed the weakest associations. These findings were consistent across the taxonomic (genus and species) and functional (gene) levels. Importantly, this analysis was based on detailed records of 759 distinct medications, substantially exceeding the scope of previous studies,^90),154)^ and provides robust evidence for the substantial role of medications in shaping gut microbial communities. Although the number of drugs investigated was smaller, our finding that medications showed the strongest associations aligned with observations from other large-scale European cohorts, including the Flemish Gut Flora Project (n = 1,106)^90)^ and MetaCardis (n = 2,173)^105)^ (Fig. 7A). In contrast, the effect of medication was modest in the Dutch Microbiome Project (n = 8,208),^155)^ possibly due to the limited range of drug types collected in that study (Fig. 7A).
To further investigate the effects of medication, we performed stratified analyses based on Anatomical Therapeutic Chemical level 1 classifications. Gastrointestinal drugs, antidiabetic agents, and systemic anti-infectives showed the strongest associations with microbiome variation (Fig. 7B). Gastrointestinal and antidiabetic drugs had even stronger associations with microbiome composition than antibiotics, including broad-spectrum agents, which are traditionally considered the most disruptive to the gut microbiome.^156)–158)^ This unexpected result may partly reflect differences in the duration of treatment. While antibiotics are typically prescribed for the short-term use (1–2 weeks),^159)^ gastrointestinal drugs such as proton pump inhibitors (PPIs) and laxatives, as well as antidiabetic agents, are often taken chronically over extended periods. Such long-term exposures may induce persistent alterations not only in the gut microbiome but also in gut physiology, such as pH, bile acids, digestive enzyme activity, and nutrient availability, which, in turn, reshape the microbial ecosystem.^160),161)^
As described above, PPIs and antidiabetic drugs showed stronger associations with microbiome composition than other medications in the Japanese 4D cohort. PPI use was associated with a significant increase in α-diversity, as measured by Shannon diversity (Fig. 8A), with the enrichment of facultative anaerobes, including oral taxa colonizing the gut, such as Streptococcus and Lactobacillus. The expansion of such oral taxa in the gut (e.g., Streptococcus, Lactobacillus, Actinomyces, Veillonella, and Rothia) aligns with the findings of independent studies in the Netherlands and the TwinsUK cohort.^162),163)^ The relative abundance of multidrug-resistant opportunistic pathogens, including Klebsiella pneumoniae, Enterococcus faecium, and Streptococcus pneumoniae, was also significantly elevated in PPI users in the Japanese 4D cohort.^8)^ These bacteria are major causes of severe nosocomial infections and are classified by the WHO as “priority pathogens” due to their antibiotic resistance and high mortality risk.^164)^ This finding suggests that use of PPI may promote intestinal colonization by multidrug-resistant organisms, with potential clinical implications, particularly in immunocompromised or hospitalized patients. In addition, PPI use was associated with a reduction in short-chain fatty acid (SCFA)-producing bacteria, including Blautia.^8)^ Similar trends were observed in the TwinsUK cohort, including the depletion of Faecalibacterium and Coprococcus.^163)^ This reduction may be driven by the direct pharmacological effects of PPIs, as supported by in vitro findings.^165)^ In contrast, the increase in oral bacteria was not replicated in vitro,^165)^ suggesting an indirect effect of PPI-mediated acid suppression on the gut microbiome. The loss of gastric acid as a natural antimicrobial barrier facilitates the translocation and colonization of oral microbes in the gut.^160)^ In support of this hypothesis, an increased abundance of oral taxa, such as Streptococcus and Veillonella, has also been reported in patients with a history of gastrectomy.^166)^ Importantly, these changes were not observed in H2-receptor antagonist users, which have a weaker acid-suppressive effect than PPIs.^167)^ A longitudinal analysis in the Japanese 4D cohort further demonstrated that the levels of Streptococcus and Lactobacillus increased during PPI use and returned to baseline levels after cessation, indicating that these shifts are reversible and causally related to drug exposure. Despite their widespread global use, PPIs are frequently prescribed inappropriately and for extended periods.^168)^ Indeed, one study reported that 92.5% of PPI users exceeded the recommended treatment duration,^169)^ and the rate of inappropriate prescriptions increased from 13.9% in 2012 to 28% in 2017.^170)^ Such overuse not only contributes to socioeconomic burdens but is also associated with various organ complications, including kidney injury, small intestinal bacterial overgrowth, spontaneous bacterial peritonitis, and intestinal infections.^171)^ Given the potential role of PPI-induced microbiome alterations in enhancing disease susceptibility, a careful re-evaluation of clinical indications and optimization of treatment duration may warrant urgent consideration.
Among the antidiabetic drugs, α-glucosidase inhibitors (α-GIs) had the most pronounced impact on the gut microbiome.^8)^ Unlike PPIs, α-GI use was associated with reduced α-diversity and decreased abundance of several SCFA-producing genera, such as Ruminococcus, Clostridium, Anaerostipes, and Roseburia, as well as an increased abundance of Bifidobacterium and Lactobacillus (Fig. 8B), consistent with findings from α-GI intervention studies in China.^172),173)^ Mechanistically, α-GIs inhibit the saccharolytic activity that converts dietary polysaccharides into smaller sugars, improving glycemic control and resulting in increased undigested carbohydrates reaching the colon, where they are efficiently utilized by Bifidobacterium species as an energy source.^174)^ Similarly, Lactobacillus ferments glucose to lactate via homofermentation in the gut.^175)^ The enhanced fermentation is accompanied by enhanced gas production (CO2 and H2),^176),177)^ which may be responsible for common early side effects of α-GIs such as abdominal bloating and flatulence. Moreover, α–GI-induced microbial shifts may be linked to therapeutic outcomes, such as glycemic improvement,^172)^ suggesting that gut microbiome composition could serve as a potential biomarker for treatment outcomes. These findings illustrate the bidirectional interaction between drugs and the gut microbiome through host physiology, influencing both therapeutic efficacy and adverse effects.
In recent years, the impact of medications and drug–drug interactions on the human gut microbiome has received increasing attention. Polypharmacy, commonly defined as the concurrent use of five or more medications, is highly prevalent among older adults, with 10%–15% of individuals aged ≥75 years being prescribed 10 or more medications.^178)^ Polypharmacy has been associated with increased risks of mortality, falls, frailty, and cognitive decline.^179)^ Clinical challenges associated with polypharmacy include poor medication adherence, heightened risk of drug–drug interactions, and increased incidence of adverse drug events.^180)^
Analyses in the Japanese 4D cohort (n = 4,198) revealed that polypharmacy induces significant alterations in the gut microbiome composition and function (Fig. 8C). Shannon diversity significantly decreased with increasing number of medications taken.^8)^ Furthermore, individuals taking more medications also exhibited marked shifts in microbial composition, characterized by the enrichment of genera such as Streptococcus and Lactobacillus, which are typical of the upper gastrointestinal tract. This shift may reflect drug-induced alterations in luminal pH and oxygen levels, which favor the expansion of acid-tolerant and facultative anaerobes. Furthermore, polypharmacy was positively associated with opportunistic pathogens, such as Klebsiella (Fig. 8C). We also observed a reduced abundance of beneficial SCFA-producing taxa, including Roseburaia, Dorea, Faecalibacterium, Alistipes, Coprococcus, Eubacterium, Clostridium, and Anaerostipes.^8)^ The decline in SCFA producers may reduce metabolic and spatial competition, creating ecological niches that facilitate the expansion of opportunistic pathobionts.^156)–158)^ Similar alterations were observed in an independent cohort study in Sweden (n = 2,223),^181)^ such as enrichment of Rothia and Lactobacillus, opportunistic pathogens (e.g., Escherichia and Enterococcus), and depletion of SCFA producers (e.g., Eubacterium, Alistipes, and Faecalibacterium) (Fig. 8C). This finding supports the robustness and generalizability of polypharmacy-associated dysbiosis. These findings suggest that polypharmacy contributes to the disruption of gut microbial homeostasis and may increase susceptibility to infection or inflammation, particularly in older adults and individuals with comorbidities. Given that approximately 60% of adults aged ≥65 years are prescribed at least one potentially inappropriate medication,^182)^ optimizing pharmacotherapy—including the deprescribing of unnecessary medications—may be essential not only for mitigating adverse drug events but also for preserving gut microbiome integrity.
In this review, we summarized two decades of microbiome research and introduced the Japanese 4D cohort, a recent large-scale initiative in Japan, which integrates highly standardized metagenomic datasets with detailed dietary, disease, medication, and lifestyle metadata. Leveraging this rich resource, we identified robust associations between gut microbiome profiles and host factors, such as age, sex, and BMI, and uncovered population-specific microbial taxa and genes shaped by the cultural and genetic backgrounds unique to Japan. Importantly, among the host variables examined, medication use—particularly proton pump inhibitors, antidiabetic agents, and polypharmacy—emerged as a dominant factor influencing gut microbiome structure and function, often with clinically relevant effects. These findings highlight the critical importance of incorporating detailed, standardized drug information into microbiome research to avoid confounding and to better interpret host-microbe associations. This review also highlights the value of large, well-phenotyped cohorts—ideally comprising thousands of individuals—for generating statistically robust insights while accounting for host and environmental heterogeneity. Finally, building harmonized, longitudinal, and globally collaborative microbiome datasets will be key to advancing microbiome-informed strategies for precision medicine and public health, both in Japan and worldwide.