Plasma multi-omic signatures distinguish mild cognitive impairment from pre-frailty

Aging research has long been haunted by an intuitive assumption: that when older adults grow physically weak, their minds tend to weaken too, because the two declines share a common biological root. A new study challenges that assumption at the molecular level. Researchers analyzing the blood of relatively healthy Dutch older adults found that pre-frailty and mild cognitive impairment, despite frequently appearing together in the clinic, leave completely distinct fingerprints in the blood, with not a single shared molecular marker between the two conditions.

The study, published in GeroScience, examined 50 community-dwelling older adults with an average age of 79.9 years. Twenty-nine participants were classified as physically fit, while 21 met the criteria for pre-frailty, meaning they exhibited one or two of the five Fried frailty criteria, including unintentional weight loss, exhaustion, low physical activity, slowness, and weakness. Individuals with more than two criteria, classified as fully frail, were excluded. The researchers deliberately focused on this relatively healthy population to avoid the confounding effects of advanced multimorbidity, which often masks molecular signals in studies of older, sicker cohorts.

Crucially, the two conditions overlapped partially but not completely within the same individuals, allowing the team to ask a direct question within a single well-characterized cohort: do early physical weakness and early cognitive decline circulate in the blood together, or do they travel separate paths? Participants underwent cognitive testing using the Montreal Cognitive Assessment, a 30-point screening instrument covering executive function, naming, attention, language, abstraction, delayed recall, and orientation, as well as the computerized MemTrax test, which measures recognition memory and reaction time across a series of repeated images. Mild cognitive impairment was defined as a MoCA score below 24, a threshold chosen based on recent meta-analytic evidence for optimal diagnostic balance.

The behavioral results confirmed the expected clinical link. Pre-frail participants scored 12 percent lower on the MoCA than their fit counterparts, a difference that was statistically significant at P = 0.006. Their MemTrax accuracy was also 4 percent lower (P = 0.03), while reaction time showed a nonsignificant trend toward slowing (P = 0.09). On the surface, then, physical vulnerability and cognitive vulnerability marched together, just as decades of geriatric literature would predict.

But when the researchers turned to the blood, the picture fractured. Plasma samples, collected in the fasted state, were subjected to three complementary analytical platforms. Proteomic profiling used the SomaScan 11K assay, an aptamer-based technology that quantifies roughly 11,000 proteins simultaneously and reports abundance as relative fluorescence units. Metabolomic profiling used the Nightingale Health high-throughput proton nuclear magnetic resonance platform, which measures 162 individual metabolites along with 87 metabolite ratios or particle sizes, for a total of 249 lipid and metabolic parameters. A targeted liquid chromatography–tandem mass spectrometry assay quantified 26 acylcarnitine derivatives using stable isotope–labeled internal standards.

The proteomic results were striking. The team identified 24 differentially expressed proteins associated with pre-frailty and 21 associated with mild cognitive impairment. When the two lists were compared, the overlap was zero. Among the pre-frailty markers were fatty acid-binding protein 2 (FABP2), kininogen-1 (KNG1), and myotubularin-related protein 14 (MTMR14), all significant at P < 0.01 but unchanged in the cognitive comparison. FABP2, typically associated with intestinal lipid handling and gut barrier integrity, has not previously been linked to pre-frailty and may represent a novel early marker of physical vulnerability. KNG1, a component of the coagulation cascade with pro-inflammatory potential depending on its splice variant, has been previously reported as a frailty biomarker. MTMR14, a muscle-specific inositide phosphatase, has been shown to decline with age and to accelerate skeletal muscle aging when lost, consistent with its appearance in the pre-frailty signature.

The MCI-associated proteins told a different story, rooted firmly in neurobiology. Amyloid beta precursor protein (APP) was elevated, while acetylcholinesterase (ACHE) and brain-specific angiogenesis inhibitor 1 (ADGRB1, also known as BAI1) were decreased. APP is central to amyloid processing and synaptic plasticity, and its dysregulation is a well-established feature of early Alzheimer’s disease pathology. ACHE is the enzymatic linchpin of cholinergic neurotransmission, and altered ACHE levels have been proposed as a marker of early cholinergic dysfunction in cognitive decline. ADGRB1 participates in astrocyte-mediated phagocytosis of excitatory synapses, implicating synaptic remodeling. None of these proteins moved in the pre-frailty comparison. Principal component analyses confirmed the separation: the MCI biomarker panel could not distinguish fit from pre-frail individuals, and the pre-frailty panel could not distinguish cognitively normal from impaired individuals.

The metabolomics data reinforced the same conclusion. Mild cognitive impairment was associated with ten significantly altered metabolites, including an elevated ratio of apolipoprotein B to apolipoprotein A1, increased VLDL cholesterol, and elevated cholesteryl esters in VLDL particles. Together, these changes point toward a shift in lipoprotein metabolism toward a more pro-atherogenic profile, driven by apolipoprotein B–containing and triglyceride-rich particles. This pattern aligns with growing evidence linking dyslipidemia to cognitive decline and neurodegenerative risk. Pre-frailty, in contrast, was associated with only one altered metabolite: the ratio of phospholipids to total lipids in very small VLDL particles, which was decreased. Notably, VLDL particle size itself showed no association with pre-frailty (P = 0.75), suggesting that subtle changes in lipoprotein composition or remodeling, rather than overt particle size differences, characterize early physical vulnerability. There was no overlap between the metabolic signatures of the two conditions.

The acylcarnitine analysis added one more piece to the puzzle. Of the 26 carnitine derivatives measured, only C18:0 acylcarnitine differed significantly between fit and pre-frail participants (P < 0.05), and it was decreased, not elevated, in the pre-frail group. This finding was unexpected, because impaired mitochondrial fatty acid oxidation typically drives circulating acylcarnitine levels upward, reflecting incomplete fat breakdown. The authors note that a similar decrease in C18:0 has been reported in patients with myalgic encephalomyelitis/chronic fatigue syndrome, though the mechanism remains unclear. Intriguingly, no acylcarnitine differences emerged between the MCI and cognitively normal groups, suggesting that mitochondrial lipid metabolism may be more closely tied to early physical decline than to early cognitive impairment in this population. The researchers speculate this could relate to the dominant fuels each tissue uses: glucose for the brain, fatty acids for skeletal muscle.

Taken together, the results deliver a clear and somewhat counterintuitive message. The clinical co-occurrence of frailty and cognitive impairment, which is well documented and associated with heightened risks of disability, falls, hospitalization, and mortality, does not appear to arise from shared systemic molecular mechanisms, at least in the early stages captured by this study. Instead, the two conditions seem to proceed along parallel but biologically distinct pathways, one rooted in muscle, vascular, and inflammatory biology, the other in amyloid processing, cholinergic signaling, and lipoprotein metabolism.

The study has limitations that the authors are careful to acknowledge. The cross-sectional design cannot establish whether the observed molecular differences precede or result from either condition. The modest sample size of 50 may have limited power to detect subtle shared signals that do exist but remained below the threshold of detection. Plasma, while accessible and clinically relevant, may not fully capture tissue-specific biology, particularly brain-derived alterations relevant to cognition or muscle-specific processes relevant to frailty. The findings are also hypothesis-generating rather than definitive, given the exploratory nature of the analysis and the large number of proteins tested, and validation in independent cohorts will be essential.

Still, the study’s core contribution lies precisely in what it failed to find. By analyzing frailty and cognition within the same well-characterized, relatively homogeneous cohort, avoiding cross-cohort comparisons and excluding major comorbidities, the researchers produced a clean test of the shared-mechanism hypothesis, and the test came back negative. The identified biomarkers themselves are not all new; many have been reported before in separate contexts, which the authors cite as internal validation of their analytical approach. What is new is the demonstration that, within the same people, the two signatures do not intersect.

If the finding holds up in larger, longitudinal studies, the implications for aging medicine could be significant. Rather than searching for a unified therapy that addresses both physical frailty and cognitive decline as manifestations of a single aging process, clinicians and drug developers may need to pursue disease-specific treatments, targeting muscle and metabolic pathways for frailty and neurobiological and lipid pathways for cognitive impairment. In a field where cognitive frailty is often treated as one syndrome, this study suggests it may be more accurate to think of two distinct diseases that simply tend to arrive together.