Aging is a complex biological process involving the progressive decline of tissue function, resilience, and homeostatic regulation. While its hallmarks include genomic instability, mitochondrial dysfunction, inflammation, and altered energy metabolism (López-Otín et al., 2013; Franceschi and Campisi, 2014), increasing attention has turned to the role of the gut microbiota in modulating systemic aging mechanisms (Cryan et al., 2019; Bourrie et al., 2016; Farnworth, 2005). Fermented foods—particularly those containing diverse probiotic communities—have been proposed as dietary modulators of host-microbiota interactions (Marsh et al., 2013). Among them, milk kefir, a traditional fermented beverage produced by inoculating milk with complex microbial consortia (kefir grains), has long been regarded as a functional food with broad health potential (Marsh et al., 2013). First proposed by 1908 Medicine Nobel price E. Metchnikoff as a factor in human longevity (Metchnikoff, 1908), kefir is now being re-examined in the light of modern microbiome science (Vinderola et al., 2019).

Yet, despite its widespread use and probiotic richness, kefir remains underrepresented in targeted aging research. While several studies suggest beneficial effects on oxidative stress, immune function, metabolic regulation, and gut integrity (Kairey et al., 2022; Vinderola et al., 2019), the literature is scattered and lacks a unified framework aligned with contemporary models of aging.

In this Perspective, we apply AI-assisted evidence mapping to systematically classify the current scientific literature on kefir and aging according to four functional domains described by Colloca et al. (2020): changes in body composition, neurodegeneration, energy balance, and signaling networks for homeostasis. Rather than exhaustively cataloguing findings, our goal is to identify thematic imbalances and underexplored domains, offering a conceptual map to guide future research into kefir’s anti-aging potential. This strategy was specifically chosen to overcome the scarcity of direct studies explicitly linking kefir consumption with aging outcomes. By adopting a domain-based clustering framework, we were able to capture biologically relevant connections that may not be immediately apparent through traditional keyword-based searches, thus broadening the scope of evidence mapping and maximizing the translational relevance of the identified research gaps.

Thematic clustering of 90 studies, spanning publications from 1993 to early 2025, revealed a sensible imbalance in the literature exploring kefir’s relationship with aging. Over half of the studies were concentrated in the domain of homeostasis signaling networks, focusing predominantly on inflammation, oxidative stress, and immune modulation. These are indeed central pathways in aging biology (López-Otín et al., 2013; Franceschi and Campisi, 2014), but their overrepresentation likely reflects a mechanistic bias in the current research paradigm. While molecular mechanisms are important, the relative under representation of domains such as energy balance (11.1%) and neurodegeneration (3.3%) indicates a structural limitation in scope. Notably, domains with direct clinical implications—such as cognitive decline or metabolic flexibility—remain underexplored, despite growing evidence of kefir’s potential to influence gut–brain signaling and metabolic regulation (Cryan et al., 2019; Bourrie et al., 2016; Farnworth, 2005). Neurodegeneration was the least represented domain. This likely reflects both the difficulty in modeling cognitive aging and the underuse of neuroimaging or validated biomarkers in kefir research. Moreover, most studies in this domain were either preclinical or observational, limiting causal inference and clinical applicability.

We propose that future studies integrate longitudinal designs, assess neurocognitive endpoints, and explore inter-domain interactions—such as those between inflammation and sarcopenia, or along the gut–brain and gut–metabolism axes—which may mediate kefir’s multisystemic effects.

Moreover, efforts should be made to standardize kefir preparations, as variations between traditional and industrial formulations may confound biological outcomes (Bourrie et al., 2023).

This Perspective does not aim to provide final answers, but rather to offer a map—constructed with AI support—that reveals where the literature is concentrated and, more importantly, where it remains silent.

To better contextualize this thematic asymmetry, we summarized the domain-specific mechanistic pathways emerging from the included studies in Table 1. This overview highlights both well-characterized molecular actions—especially in the domain of homeostasis—and the relative scarcity of mechanistic insights in domains like energy regulation and neurodegeneration.

Our evidence mapping of kefir and aging literature reveals a pronounced thematic concentration on homeostasis-related signaling, to the detriment of domains like neurodegeneration and energy regulation. By applying a structured clustering model based on the aging domains proposed by Colloca et al. , we highlight the need for a broader and more clinically integrative research agenda. This includes not only exploring kefir’s molecular properties, but also assessing its translational relevance across multiple aging systems.

The approach presented here demonstrates how AI and semantic clustering can support literature synthesis and strategic research planning, offering a reproducible framework to identify gaps and reorient scientific focus in emerging health domains. The herein applied integrative pipeline, indeed, combining AI-assisted screening and semantic clustering, represents a transferable strategy that could be adapted to other functional foods or emerging research domains, maximizing discovery and guiding translational innovation. Finally, we acknowledge that the AI-assisted screening process, while efficient and reproducible, may still be susceptible to latent biases inherent in the literature, including publication bias and preferential keyword usage. These limitations reinforce the importance of expert validation and transparent classification criteria in thematic mapping studies.