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Cognitive decline is a broad syndrome ranging from non-pathological/age-associated cognitive decline to pathological dementia. Mild cognitive impairment MCI) is defined as the stage of cognition that falls between normal ageing and dementia. Studies have found that early lifestyle interventions for MCI may delay its pathological progression. Hence, this review aims to determine the most efficient cognitive tools to discriminate mild cognitive decline in its early stages. After a systematic search of five online databases, a total of 52 different cognitive tools were identified. The performance of each tool was assessed by its psychometric properties, administration time and delivery method. The Montreal Cognitive Assessment (MoCA, n = 15), the Mini-Mental State Examination (MMSE, n = 14) and the Clock Drawing Test (CDT, n = 4) were most frequently cited in the literature. The preferable tools with all-round performance are the Six-item Cognitive Impairment Test (6CIT), MoCA (with the cut-offs of ≤24/22/19/15.5), MMSE (with the cut-off of ≤26) and the Hong Kong Brief Cognitive Test (HKBC). In addition, SAGE is recommended for a self-completed survey setting whilst a 4-point CDT is quick and easy to be added into other cognitive assessments. However, most tools were affected by age and education levels. Furthermore, optimal cut-off points need to be cautiously chosen while screening for MCI among different populations.

Background The Apolipoprotein E ε4 allele (i.e. ApoE4) is the strongest genetic risk factor for sporadic Alzheimer’s disease (AD). TREM2 (i.e. Triggering receptor expressed on myeloid cells 2) is a microglial transmembrane protein brain that plays a central role in microglia activation in response to AD brain pathologies. Whether higher TREM2-related microglia activity modulates the risk to develop clinical AD is an open question. Thus, the aim of the current study was to assess whether higher sTREM2 attenuates the effects of ApoE4-effects on future cognitive decline and neurodegeneration. Methods We included 708 subjects ranging from cognitively normal (CN, n  = 221) to mild cognitive impairment (MCI, n  = 414) and AD dementia ( n  = 73) from the Alzheimer’s disease Neuroimaging Initiative. We used linear regression to test the interaction between ApoE4-carriage by CSF-assessed sTREM2 levels as a predictor of longitudinally assessed cognitive decline and MRI-assessed changes in hippocampal volume changes (mean follow-up of 4 years, range of 1.7-7 years). Results Across the entire sample, we found that higher CSF sTREM2 at baseline was associated with attenuated effects of ApoE4-carriage (i.e. sTREM2 x ApoE4 interaction) on longitudinal global cognitive ( p  = 0.001, Cohen’s f 2  = 0.137) and memory decline ( p  = 0.006, Cohen’s f 2  = 0.104) as well as longitudinally assessed hippocampal atrophy ( p  = 0.046, Cohen’s f 2  = 0.089), independent of CSF markers of primary AD pathology (i.e. Aβ 1–42 , p-tau 181 ). While overall effects of sTREM2 were small, exploratory subanalyses stratified by diagnostic groups showed that beneficial effects of sTREM2 were pronounced in the MCI group. Conclusion Our results suggest that a higher CSF sTREM2 levels are associated with attenuated ApoE4-related risk for future cognitive decline and AD-typical neurodegeneration. These findings provide further evidence that TREM2 may be protective against the development of AD.

BACKGROUND We compared the ability of several plasma biomarkers versus amyloid positron emission tomography (PET) to predict rates of memory decline among cognitively unimpaired individuals. METHODS We studied 645 Mayo Clinic Study of Aging participants. Predictor variables were age, sex, education, apolipoprotein E (APOE) ε4 genotype, amyloid PET, and plasma amyloid beta (Aβ)42/40, phosphorylated tau (p‐tau)181, neurofilament light (NfL), glial fibrillary acidic protein (GFAP), and p‐tau217. The outcome was a change in a memory composite measure. RESULTS All plasma biomarkers, except NfL, were associated with mean memory decline in models with individual biomarkers. However, amyloid PET and plasma p‐tau217, along with age, were key variables independently associated with mean memory decline in models combining all predictors. Confidence intervals were narrow for estimates of population mean prediction, but person‐level prediction intervals were wide. DISCUSSION Plasma p‐tau217 and amyloid PET provide useful information about predicting rates of future cognitive decline in cognitively unimpaired individuals at the population mean level, but not at the individual person level.

We employed an untargeted proteo‐metabolomic approach to profile circulating biomarkers in plasma samples from the I‐Lan Longitudinal Aging Study, aiming to identify biomarkers and pathways associated with physio‐cognitive decline syndrome (PCDS). In 115 propensity score‐matched PCDS case–control pairs, pathway analyses implicated dysregulation of fatty acid metabolism and inflammation in PCDS pathogenesis. Sex‐specific associations were observed, with disruptions in central carbon metabolism (elevated PKM, MDH1, and GAPDH; decreased MINPP1) and tyrosine metabolism (decreased MIF, DBH; increased thyroxine) characterizing in men. In contrast, perturbations in glutathione and phenylalanine metabolism, including increased ANPEP, GSTP1, and decreased pyroglutamic acid, were identified in women. Results suggest that dysregulated energy and redox homeostasis likely contribute to PCDS development. Notably, ANPEP, PKM, and MIF emerged as potential biomarkers, elucidating the muscle–brain crosstalk framework. Our findings provide insights into potential molecular mechanisms underlying PCDS and the muscle–brain crosstalk, marking progress toward elucidating biomarkers in the journey of healthy aging. The study identified dysregulated fatty acid metabolism and inflammation as contributors to physio‐cognitive decline syndrome (PCDS). Sex‐specific metabolic disruptions were noted, with altered central carbon and tyrosine metabolism more pronounced in men and glutathione pathway perturbations more evident in women. Several proteins, including ANPEP, PKM, and MIF, emerged as potential PCDS biomarkers, elucidating the muscle–brain crosstalk framework underlying this syndrome.

Identification of subjects at the early stages of Alzheimer's disease (AD) is fundamental for drug development and possible intervention or prevention of cognitive decline. The concept of mild cognitive impairment (MCI) evolved during the past two decades to define subjects at the transitional stage between normal aging and dementia. Evidence from cross-sectional and longitudinal studies has shown that MCI is associated with an increased risk of positive AD biomarkers and an increased annual conversion rate of 5%-17% to AD. The presence of AD biomarkers in subjects with MCI was associated with an even higher risk of progression to dementia. However, earlier clinical trials for pharmacotherapy in subjects with MCI were disappointing. To extend the spectrum of AD to an earlier stage before MCI, subjective cognitive decline (SCD) was introduced and was defined as self-reported cognitive decline before the deficits could be detected by cognitive tests. Subjects with SCD have an increased risk of underlying AD pathology. However, SCD can also develop secondary to other heterogeneous etiologies, including other neurodegenerative and psychiatric diseases, personality traits, physical conditions, and medication use. Several clinical and biomarker features were proposed to predict risk of conversion to AD in subjects with SCD. Further longitudinal studies are needed to support the validity of these high-risk features.

Hippocampal changes are associated with increased age and cognitive decline due to mild cognitive impairment (MCI) and Alzheimer's disease (AD). These associations are often observed only in the later stages of decline. This study examined if hippocampal grading, a method measuring local morphological similarity of the hippocampus to cognitively normal controls (NCs) and AD participants, is associated with cognition in NCs, subjective cognitive decline (SCD), early (eMCI), late (lMCI), and AD. A total of 1620 Alzheimer's Disease Neuroimaging Initiative participants were examined (495 NC, 262 eMCI, 545 lMCI, and 318 AD) because they had baseline MRIs and Alzheimer's disease Assessment Scale (ADAS‐13) and Clinical Dementia Rating—Sum of Boxes (CDR‐SB) scores. In a sub‐analysis, NCs with episodic memory scores (as measured by Rey Auditory Verbal Learning Test, RAVLT) were divided into those with subjective cognitive decline (SCD+; 103) and those without (SCD−; 390). Linear regressions evaluated the influence of hippocampal grading on cognition in preclinical and prodromal AD. Lower global cognition, as measured by increased ADAS‐13, was associated with hippocampal grading: NC (p < .001), eMCI (p < .05), lMCI (p < .05), and AD (p = .01). Lower global cognition as measured increased CDR‐SB was associated with hippocampal grading in lMCI (p < .05) and AD (p < .001). Lower RAVLT performance was associated with hippocampal grading in SCD− (p < .05) and SCD+ (p < .05). These findings suggest that hippocampal grading is associated with global cognition in NC, eMCI, lMCI, and AD. Early changes in episodic memory during pre‐clinical AD are associated with changes in hippocampal grading. Hippocampal grading may be sensitive to progressive changes early in the disease course. Hippocampal grading is sensitive to global cognitive scores in normal aging, early mild cognitive impairment, late mild cognitive impairment and Alzheimer's disease. This method is also sensitive to episodic memory changes in preclinical AD (subjective cognitive decline).

Gut microbiota alteration during the aging process serves as a causative factor for aging‐related cognitive decline, which is characterized by the early hallmark, hippocampal synaptic loss. However, the impact and mechanistic role of gut microbiota in hippocampal synapse loss during aging remains unclear. Here, we observed that the fecal microbiota of naturally aged mice successfully transferred cognitive impairment and hippocampal synapse loss to young recipients. Multi‐omics analysis revealed that aged gut microbiota was characterized with obvious change in Bifidobacterium pseudolongum (B.p) and metabolite of tryptophan, indoleacetic acid (IAA) in the periphery and brain. These features were also reproduced in young recipients that were transplanted with aged gut microbiota. Fecal B.p abundance was reduced in patients with cognitive impairment compared to healthy subjects and showed a positive correlation with cognitive scores. Microbiota transplantation from patients who had fewer B.p abundances yielded worse cognitive behavior in mice than those with higher B.p abundances. Meanwhile, supplementation of B.p was capable of producing IAA and enhancing peripheral and brain IAA bioavailability, as well as improving cognitive behaviors and microglia‐mediated synapse loss in 5 × FAD transgenic mice. IAA produced from B.p was shown to prevent microglia engulfment of synapses in an aryl hydrocarbon receptor‐dependent manner. This study reveals that aged gut microbiota ‐induced cognitive decline and microglia‐mediated synapse loss that is, at least partially, due to the deficiency in B.p and its metabolite, IAA. It provides a proof‐of‐concept strategy for preventing neurodegenerative diseases by modulating gut probionts and their tryptophan metabolites. Li et al. revealed that aged gut microbiota induces cognitive decline and microglia‐mediated synapse loss. Fecal Bifidobacterium pseudolongum abundance was reduced in patients with cognitive impairment and microbiota transplantation from patients with fewer B.p abundance yielded worse cognitive behavior in mice. Supplementation with B.p improves aging‐related cognitive decline and prevents microglia engulfment of synapses via activation of IAA/AHR signaling.

Background Subjective cognitive decline (SCD) has been proposed as a pre-MCI at-risk condition of Alzheimer’s disease (AD). Current research is focusing on a refined assessment of specific SCD features associated with increased risk for AD, as proposed in the SCD-plus criteria. We developed a structured interview (SCD-I) for the assessment of these features and tested their relationship with AD biomarkers. Methods We analyzed data of 205 cognitively normal participants of the DELCODE study (mean age = 68.9 years; 52% female) with available CSF AD biomarkers (Aß-42, p-Tau181, Aß-42/Tau ratio, total Tau). For each of five cognitive domains (including memory, language, attention, planning, others), a study physician asked participants about the following SCD-plus features: the presence of subjective decline, associated worries, onset of SCD, feeling of worse performance than others of the same age group, and informant confirmation. We compared AD biomarkers of subjects endorsing each of these questions with those who did not, controlling for age. SCD was also quantified by two summary scores: the number of fulfilled SCD-plus features, and the number of domains with experienced decline. Covariate-adjusted linear regression analyses were used to test whether these SCD scores predicted abnormality in AD biomarkers. Results Lower Aß-42 levels were associated with a reported decline in memory and language abilities, and with the following SCD-plus features: onset of subjective decline within 5 years , confirmation of cognitive decline by an informant , and decline-related worries . Furthermore, both quantitative SCD scores were associated with lower Aß42 and lower Aß42/Tau ratio, but not with total Tau or p-Tau181. Conclusions Findings support the usefulness of a criterion-based interview approach to assess and quantify SCD in the context of AD and validate the current SCD-plus features as predictors of AD pathology. While some features seem to be more closely associated with AD biomarkers than others, aggregated scores over several SCD-plus features or SCD domains may be the best predictors of AD pathology.

INTRODUCTION The neuroanatomical changes driving both cognitive and mobility impairments, an emerging preclinical dementia syndrome, are not fully understood. We examined gray‐matter volumes (GMVs) and structural covariance networks (SCNs) abnormalities in community‐based older people preceding the conversion to physio‐cognitive decline syndrome (PCDS). METHODS Voxel‐wise brain GMV and established SCNs were compared between PCDS and non‐PCDS converters. RESULTS The study included 343 individuals (60.2 ± 6.9 years, 49.6% men) with intact cognitive and mobility functions. Over an average 5.6‐year follow‐up, 116 transitioned to PCDS. Identified regions with abnormal GMVs in PCDS converters were over cerebellum and caudate, which served as seeds for SCNs establishment. Significant differences in cerebellum‐based (to right frontal pole and left middle frontal gyrus) and caudate‐based SCNs (to right caudate putamen, right planum temporale, left precentral gyrus, right postcentral gyrus, and left parietal operculum) between converters and nonconverters were observed. DISCUSSION This study reveals early neuroanatomic changes, emphasizing the cerebellum's role, in dual cognitive and mobility impairments. Highlights Neuroanatomic precursors of dual cognitive and mobility impairments are identified. Cerebellar GMV reductions and increased right caudate GMV precede the onset of PCDS. Altered cerebellum‐ and caudate‐based SCNs drive PCDS transformation. This research establishes a foundation for understanding PCDS as a specific dementia syndrome.

Subjective cognitive decline (SCD)—self‐perceived cognitive worsening without objective deficits—has emerged as a clinically meaningful, potential early manifestation of Alzheimer's disease (AD). Positioned at the intersection of normal aging, neuropsychiatric symptoms, and preclinical neurodegeneration, SCD offers a unique window for early detection and intervention. However, detection heterogeneity, variable prognostic trajectories, and limited equity in assessment hinder its full clinical utility. This position paper synthesizes current evidence on SCD's diagnostic complexity, neurobiological underpinnings, and modifiable influences. We highlight the need for harmonized assessment frameworks, scalable digital tools, inclusive research, and ethically grounded biomarker disclosure practices. Importantly, we advocate for personalized, (non‐)pharmacological interventions targeting this early phase. By refining the conceptualization and operationalization of SCD, we can better identify individuals at heightened AD risk and deliver timely, equitable, and meaningful prevention strategies. SCD represents a pivotal inflection point in the dementia continuum—and a call to shift toward proactive brain health. Highlights Subjective cognitive decline (SCD) may signal early‐stage Alzheimer's despite normal test performance. Diagnostic heterogeneity limits current clinical and research utility. Biomarkers and digital tools could enhance risk stratification in SCD. Mental health and social context shape symptom reporting and outcomes. SCD offers a window for tailored (non‐drug) preventive interventions.