The research, led by Marina M. Watowich and colleagues, took an unusually direct approach to this question. Rather than comparing separate studies conducted in different countries with different methods, the team worked with two Indigenous groups in which individuals of shared ancestry currently span a continuum of lifestyles, from traditional subsistence practices to urban, industrialized living. The first group was the Turkana of Kenya, pastoralists in East Africa whose communities range from mobile livestock-keeping camps to settled towns. The second was the Orang Asli of Peninsular Malaysia, whose populations likewise include people practicing forest-based subsistence and others living in urban environments. Because both genetic background and lifestyle vary within these groups, the researchers could test whether the same gene behaves differently across environments within a single population, a design that minimizes the confounding that plagues cross-population comparisons.

The team focused on three domains of biology in which APOE is known to play a role: cholesterol metabolism, immune function, and reproduction. APOE encodes a protein that shuttles lipids through the bloodstream and is deeply involved in how the body handles cholesterol. It also modulates inflammatory and immune responses, and previous work has hinted that it may influence fertility. Participants were genotyped for the three major APOE isoforms, ε2, ε3, and ε4, and the researchers measured total cholesterol, LDL cholesterol, HDL cholesterol, a panel of innate immune biomarkers, and reproductive traits including reproductive lifespan and the number of children born. Crucially, they then formally tested for genotype-by-environment interactions, asking whether the effect of carrying ε4 depended on the lifestyle a person was living.

The first finding was reassuring in its consistency: the established effects of APOE on lipid biology held across all lifestyles. Having more ε4 alleles was associated with higher total cholesterol, higher LDL cholesterol, and lower HDL cholesterol, regardless of whether a person was a mobile Turkana herder, an Orang Asli villager, or an urban resident of either population. This matters because some researchers have proposed that traditional diets and high physical activity might simply erase the lipid effects of ε4. The new data do not support that strong version of the hypothesis. The allele’s influence on cholesterol appears to be a robust, intrinsic feature of its biology, one that persists even when people eat little saturated fat and walk long distances daily.

Where the environment did matter was in the immune system. The researchers found lifestyle-dependent effects of genotype on innate immune biomarkers in the Orang Asli, meaning that the relationship between carrying ε4 and levels of circulating immune markers changed depending on whether individuals lived non-industrial or industrialized lives. Intriguingly, this interaction was not observed in the Turkana, suggesting that even among non-industrial populations, the environmental modulation of APOE’s immune effects is not universal. The authors interpret this as evidence that local ecological conditions, such as pathogen exposure, diet, or other lifestyle factors that differ between the two groups and between subsistence and urban settings, can reshape how the allele expresses itself in immune biology. This kind of genotype-by-environment interaction provides a concrete mechanism by which the costs and benefits of a genetic variant can differ between the settings in which humans evolved and the settings most people inhabit today.

The reproductive findings were more nuanced and, in some ways, more sobering for advocates of the idea that ε4 is straightforwardly beneficial in traditional contexts. Across the combined samples, having more ε4 alleles was correlated with an extended reproductive lifespan, the span of years during which a person reproduces. Such an effect could, in principle, help explain how the allele persisted through natural selection despite its late-life costs: if ε4 carriers can reproduce over a longer window, the allele might pay an evolutionary dividend early enough in life to outweigh its disadvantages in old age. Previous studies in other populations, including forager-horticulturalist groups, have reported positive associations between ε4 and fertility, fueling this evolutionary argument.

However, the new study tempers that narrative considerably. The association between ε4 and extended reproductive lifespan was relatively weak, and it was not consistent across the two populations studied. Moreover, a longer reproductive lifespan did not translate into a measurable increase in reproductive output: ε4 carriers did not have more children. From an evolutionary standpoint, reproductive output is what selection ultimately acts upon, so a weak, population-inconsistent extension of reproductive lifespan that fails to produce more offspring provides only limited support for the idea that fertility benefits maintain ε4 in the human gene pool. The authors are explicit that ε4 is not universally beneficial in non-industrial contexts, a conclusion that pushes back against overly simple stories about the allele being a blessing in the wild and a curse in the city.

What the study does establish is that industrialized environments can modify the biology of APOE ε4. The immune findings in the Orang Asli demonstrate that lifestyle can change what a genotype does to the body, and the consistent lipid effects show that some consequences of the allele are more environmentally buffered than others. This layered picture fits a broader theme in modern human genetics: the effects of many variants are context-dependent, shaped by diet, activity, pathogen exposure, and other exposures that have changed radically since the advent of agriculture, cities, and industrial food systems. For APOE ε4 specifically, the implication is that the allele’s strong association with neurodegenerative and cardiometabolic disease in industrialized nations may be, in part, a mismatch phenomenon, an ancestral variant pushed into an environment that amplifies its harmful effects while stripping away whatever advantages it once offered.

The work also carries practical implications for medicine and public health. APOE genotyping is increasingly discussed as a tool for predicting Alzheimer’s risk and tailoring interventions, but this study is a reminder that risk estimates derived from industrialized cohorts may not transfer cleanly to people living different lifestyles, or to populations with different local ecologies. Understanding precisely which environmental factors modulate ε4’s effects on immunity and lipid biology, whether pathogen burden, physical activity, dietary composition, or something else entirely, could point toward interventions that recreate protective aspects of non-industrial conditions. At the same time, the inconsistency between the Turkana and Orang Asli results cautions against assuming that any single traditional lifestyle confers uniform protection.

Ultimately, the study reframes a familiar genetic villain as something more conditional. APOE ε4 is neither an unambiguous liability nor an ancestral gift; it is a variant whose consequences are negotiated between genome and environment, with cholesterol effects that persist across contexts, immune effects that bend with lifestyle in some populations but not others, and reproductive effects too weak and inconsistent to tell a clean evolutionary story. By working with the Turkana and Orang Asli across their own lifestyle transitions, the researchers have provided some of the most direct evidence yet that the biology of a single gene can diverge between industrialized and non-industrial worlds. As more populations undergo subsistence transitions, studies of this kind will be essential for understanding how the genomic legacies of our evolutionary past interact with the environments of the present, and for predicting who bears the greatest burden from variants like ε4 as the world urbanizes.

Subject of Research: Environment-dependent effects of APOE ε4 on cholesterol, immune, and reproductive traits in Turkana and Orang Asli populations

Article Title: Divergent biological consequences of APOE isoforms across industrialized and non-industrial environments

Article References: Watowich, M. M., Petersen, R. M., Brassington, L., Arner, A. M., Rodenberg, G., Tan Boon Huat, T. B. T. A., Tam, K. L., Schellenberg, E., bin Mohd Sayed, I., John, E., Kahumbu, J. C., Muhoya, B., Gurven, M., Trumble, B. C., Njeru, S. N., Martins, D., Ayroles, J. F., Lim, Y. A. L., Venkataraman, V. V., … Lea, A. J. (2026). Divergent biological consequences of APOE isoforms across industrialized and non-industrial environments. PLOS Genetics, 22(9), e1012285. https://doi.org/10.1371/journal.pgen.1012285

Image Credits: AI Generated

DOI: 10.1371/journal.pgen.1012285

Keywords: APOE ε4, genotype-by-environment interaction, Turkana, Orang Asli, cholesterol, innate immunity, reproductive lifespan, evolutionary medicine, PLOS Genetics, lifestyle transition, Alzheimer's disease risk, human population genetics

The numbers tell a strikingly clean story. Among people with subjective cognitive decline, 28.3 percent carried at least one APOE ε4 allele. Among those with mild cognitive impairment, the figure climbed to 41.0 percent, while cognitively normal individuals carried the allele at a rate of just 22.0 percent. In statistical terms, the odds of being an ε4 carrier were significantly higher in the subjective decline group than in healthy controls, with an odds ratio of 1.28, and significantly higher still in the mild impairment group compared with the subjective decline group, at 1.48. That stepped gradient—rising steadily from normal cognition through subjective complaints to objective impairment—is exactly the pattern one would expect if subjective cognitive decline truly represents a transitional stage on the Alzheimer’s continuum rather than a clinically meaningless complaint.

To appreciate why this matters, it helps to understand how the field’s thinking has evolved. Alzheimer’s disease, which accounts for roughly 60 percent of all dementia cases worldwide, is no longer viewed as a binary diagnosis that arrives only when memory loss becomes undeniable. Instead, clinicians and researchers now describe a biological and clinical continuum: an asymptomatic stage in which amyloid and tau biomarkers are positive but cognition is intact, followed by a transitional phase in which very mild changes are perceived by the patient but remain within normal limits on formal testing, and finally mild cognitive impairment and overt dementia. The 2024 revised criteria from the Alzheimer’s Association Workgroup formalized this staging, and the transitional phase maps directly onto the syndrome of subjective cognitive decline. Interventions, most studies suggest, work best when applied early—which makes identifying who in this earliest phase is genuinely at risk a matter of urgent practical importance.

The trouble has always been definition. Before 2014, researchers used a bewildering array of overlapping labels—subjective memory impairment, subjective cognitive complaints, subjective memory concerns—often interchangeably and inconsistently. That year, Frank Jessen and colleagues provided a unified framework, defining subjective cognitive decline as a persistent, self- or informant-reported worsening of cognition, most often memory, in people whose performance on standardized tests remains normal and who show no abnormalities on neurological examination. The same group proposed a set of enrichment features, the so-called SCD-plus criteria, designed to flag cases more likely to reflect preclinical Alzheimer’s: onset at age 60 or older, symptoms beginning within the past five years, a sense of decline relative to peers, and genuine worry about the changes. Even with these tools, however, biomarker findings in this population have remained stubbornly heterogeneous, and previous reviews had produced conflicting results about whether APOE ε4 was enriched at all.

That is precisely the discrepancy the new analysis resolves. An earlier systematic review had concluded that APOE ε4 prevalence in subjective decline was essentially the same as in cognitively normal people—a finding that seemed to undercut the whole staging framework. The authors of the new meta-analysis, led by Paolo Alonge and Roberto Monastero of the University of Palermo, argue that the conflict stems largely from how studies defined the syndrome. The earlier review included studies using the older, looser classifications, whereas the new analysis applied stringent inclusion criteria aligned with the Subjective Cognitive Decline Initiative: a cognitive complaint in one or more domains, exclusion of objective impairment through formal neuropsychological testing, and exclusion of psychiatric, neurological, or systemic conditions that could muddy the picture. Under those stricter standards, the genetic gradient emerges clearly.

The methodological machinery behind the result is considerable. The team searched MEDLINE, Web of Science, and Scopus from inception to April 15, 2026, screening 474 records after duplicate removal and ultimately including 49 studies—26 cross-sectional and 23 prospective—conducted across Europe, North America, Asia, Australia, and the Middle East, with publication years ranging from 2005 to 2026. They used random-effects models with restricted maximum likelihood estimation, logit-transformed the response variable to satisfy normality assumptions, assessed heterogeneity with Cochran’s Q and the I-squared statistic, and probed publication bias with Egger’s test supplemented by Duval and Tweedie’s trim-and-fill adjustment. A leave-one-out influence analysis, using diagnostics such as Cook’s distance and DFFITS, confirmed that no single study was driving the pooled estimates. Notably, the funnel plot asymmetry pointed in the direction opposite to classical publication bias, with smaller studies tending to report lower ε4 prevalence—a known artifact of Egger’s test when applied to proportions—so the authors concluded that true publication bias was unlikely to distort the findings.

One of the most technically interesting aspects of the analysis is how the team handled correlated effect sizes. Because the odds ratios comparing mild impairment versus subjective decline and normal cognition versus subjective decline share a common reference group, they are not statistically independent. Pooling them naively would understate uncertainty. Instead, the researchers used a multivariate meta-analytic framework via the Mixmeta package, incorporating the variance–covariance matrix of the odds ratios so that within-study correlations were properly accounted for. Twenty-six studies contributed to this model. Meta-regressions added another layer, testing whether the proportion of female participants, mean age, and years of education explained the substantial between-study heterogeneity, which reached an I-squared of 90.2 percent in the subjective decline cohort.

Those meta-regressions produced findings with real biological intrigue. In the subjective decline groups, mean age showed a significant negative association with ε4 carrier prevalence, accounting for about 15 percent of the between-study variance, while education showed a significant positive association. The authors offer two plausible interpretations for the age effect: a survival bias, or the possibility that ε4 carriers convert more rapidly to more advanced stages of disease, depleting them from older subjective-decline cohorts. The education effect may reflect cognitive reserve—the idea that highly educated individuals notice and report subtle cognitive changes earlier, even while their test performance remains formally normal—or simply selection bias in who ends up in memory clinic studies. Sex distribution, by contrast, showed no significant effect. In the cognitively normal groups, both age and education correlated positively with ε4 prevalence, with education alone explaining a remarkable 91.9 percent of the between-study variance.

The cross-sectional picture is complemented by a more consistent longitudinal one. The three prospective studies that directly examined APOE ε4 in subjective decline all reported an increased risk of conversion to objective cognitive impairment among carriers, and observational cohorts linked ε4 status to faster cognitive decline and greater changes in cerebrospinal fluid and plasma biomarkers—though not uniformly, with a few studies reporting no biomarker association. This matters therapeutically as well: APOE ε4 is now a reliable predictor of amyloid-related imaging abnormalities during treatment with the new anti-amyloid monoclonal antibodies, and the allele itself is being pursued as a drug target through gene editing, gene silencing, and expression regulation. Studies of APOE genotype disclosure suggest that learning one’s genetic risk influences future planning and health behaviors, with psychological effects that appear generally manageable—raising clinical and ethical questions as genetic testing edges into early cognitive assessment.

The authors are careful about limitations. Heterogeneity remained high even after meta-regression, reflecting the fact that subjective cognitive decline, like mild cognitive impairment, is an umbrella syndrome encompassing vascular, degenerative, and other etiologies rather than a single disease. Many studies were conducted in memory clinics, potentially enriching samples with higher-risk individuals, and genotype data were often reported merely as descriptive characteristics rather than primary outcomes. Regional differences in ε4 frequency—lower in Mediterranean and Asian populations than in Northern European and North American cohorts—could not be formally subgrouped. Still, the central conclusion stands: the prevalence of APOE ε4 in subjective cognitive decline falls squarely between normal cognition and mild impairment, vindicating the staging model. The path forward, the authors argue, lies in multimodal risk models that integrate genetics with fluid and imaging biomarkers, clinical variables, and other genes—a strategy that could eventually deliver personalized counseling and earlier, better-targeted intervention for the people who need it most.

Subject of Research: APOE ε4 allele prevalence in subjective cognitive decline as an intermediate stage of the Alzheimer's disease continuum

Article Title: APOE in subjective cognitive decline: a systematic review and meta-analysis

Article References: Alonge, P., Baiamonte, L., Gerardi, G., Torrente, A., Lo Mauro, E., Veronese, N., Labate, A., & Monastero, R. (2026). APOE in subjective cognitive decline: a systematic review and meta-analysis. Journal of Neurology, 273(9), Article 556. https://doi.org/10.1007/s00415-026-14077-5

Image Credits: AI Generated

DOI: 10.1007/s00415-026-14077-5

Keywords: Alzheimer's disease, APOE ε4, subjective cognitive decline, mild cognitive impairment, meta-analysis, genetic risk factor, dementia, biomarkers, neuropsychology, risk stratification, Journal of Neurology, preclinical Alzheimer's

The medial temporal lobe, encompassing the entorhinal cortex and hippocampus, is where Alzheimer’s pathology takes root. Tau tangles appear here earlier than anywhere else in the brain, and the density of these misfolded filaments tracks closely with the episodic memory failures that define the disease. Yet while the link between neocortical tau and amyloid-β is well established, the relationship within the medial temporal lobe has remained murky. Positron emission tomography, the workhorse of in vivo amyloid and tau imaging, struggles in this deep, folded region because of limited spatial resolution, off-target tracer binding, and reduced sensitivity. Autopsy tissue, by contrast, allows direct, region-specific quantification of plaques and tangles, which is precisely why the researchers turned to two of the world’s most rigorously characterized brain donation programs.

The main cohort came from the Religious Orders Study and the Rush Memory and Aging Project, longitudinal studies that have followed older Catholic clergy and Chicago-area residents for decades, with 1,587 participants donating their brains at death. The replication cohort drew from the Arizona Study of Aging and Neurodegenerative Disorders, adding 963 more donors. In the main cohort, amyloid-β load was measured as the percentage of tissue area occupied by immunostained deposits, while tau was quantified as neurofibrillary tangle density using the AT8 antibody across eight cortical regions. The Arizona cohort used semi-quantitative CERAD-style grading with thioflavin-S, Campbell-Switzer, and Gallyas staining. Crucially, both datasets allowed the team to compute separate amyloid-β and tau composites for the medial temporal lobe and for the six remaining neocortical regions, and to adjust for co-pathologies including TDP-43, Lewy bodies, and vascular lesions.

The starting point was unsurprising: in both cohorts, carrying at least one APOE-ε4 allele and being female were each associated with significantly greater medial temporal tau tangle burden, with all p-values below 0.001. APOE-ε4 carriers also showed markedly higher amyloid-β in both the neocortex and the medial temporal lobe. The effects of female sex on amyloid were weaker and less consistent, reaching significance in the main cohort only. The pivotal question was what would happen when amyloid-β entered the statistical models as a potential mediator of the tau associations.

Adjusting for global neocortical amyloid-β alone attenuated both associations but did not eliminate them. The turning point came when the researchers jointly accounted for global and regional medial temporal amyloid-β. Under that fuller specification, the association between APOE-ε4 and medial temporal tau dissolved entirely, falling to non-significance in both cohorts with p-values of at least 0.19. The female sex effect, however, remained robust, with p-values of 0.004 or lower. Models incorporating both spatial scales of amyloid pathology explained substantially more variance in medial temporal tau than global measures alone, and the results held when the team additionally adjusted for diagnostic group, clinical stage, or neocortical tau burden.

Path analysis, a form of structural equation modeling that traces how effects flow through intermediate variables, sharpened the picture. The researchers ordered the pathology variables a priori according to known neuropathological staging: diffuse neocortical plaques precede neuritic plaques, neocortical amyloid precedes medial temporal amyloid, and medial temporal amyloid precedes tangles. In both cohorts, roughly three quarters of the total APOE-ε4 effect on medial temporal tau was mediated by amyloid-β, 79.5 percent in the main cohort and 74.5 percent in the replication sample, and the residual direct effect was statistically indistinguishable from zero. For female sex, less than half of the effect was amyloid-mediated, just 44.0 percent and 14.4 percent respectively, and a significant amyloid-independent component persisted in both cohorts.

Sensitivity analyses reinforced the dissociation. Among donors with no significant amyloid-β pathology on the CERAD scale, 499 in the main cohort and 211 in the replication set, APOE-ε4 showed no association with medial temporal tau at all. Female sex, meanwhile, remained significantly linked to higher tau in the main cohort and showed a strong trend in the replication sample. When the team repeated the analyses separately for the entorhinal cortex and hippocampus, and when they tested for APOE-ε4 by sex interactions, the same pattern emerged: after accounting for amyloid-β, women carried more medial temporal tau regardless of genotype.

The authors propose plausible, if unproven, mechanisms for the sex-specific vulnerability. Endocrine transitions, particularly the loss of estrogen around menopause, have been linked to tau burden in prior imaging studies, and sex differences in neuroimmune biology, including microglial activation, have been tied to both amyloid and tau pathologies. The persistence of the sex effect in amyloid-free brains and after adjustment for disease-stage proxies suggests that female-associated tau accumulation in the medial temporal lobe is at least partly an amyloid-independent process, potentially accelerating progression and amplifying tau-mediated cognitive decline. The study’s design, being cross-sectional autopsy data, cannot establish causality or temporal ordering, and the cohorts lack racial, ethnic, and socioeconomic diversity, limitations the authors acknowledge candidly.

For the APOE-ε4 story, the findings carry a more encouraging message. If the gene variant amplifies tau largely through its strong effects on amyloid-β accumulation and distribution, then the new generation of anti-amyloid therapies might, in principle, blunt the downstream tau consequences that matter most for cognition, particularly in early disease stages when localized amyloid and tau deposits fall below PET detection thresholds. The study also highlights a methodological blind spot: most in vivo studies quantify amyloid with a global neocortical composite, potentially obscuring the local amyloid-tau interplay within the medial temporal lobe that the autopsy data reveal. Whether plaque removal alters tau trajectories in a genotype-dependent manner will require longitudinal and interventional evidence that this design cannot provide.

The practical upshot is a call for precision in trial design. Post hoc analyses of some anti-amyloid trials have hinted at sex differences in treatment outcomes, though such exploratory subgroup findings were never powered for definitive interaction testing. The new results argue that sex and APOE genotype should be built into prespecified analytic plans for therapies targeting amyloid, tau, or APOE biology, rather than treated as afterthoughts. They also frame a pressing open question for the field: identifying the biological basis of women’s heightened medial temporal tau vulnerability could clarify why Alzheimer’s prevalence and progression differ by sex and open therapeutic avenues that current amyloid-centric strategies leave untouched. Until then, the autopsy bench has delivered a clear verdict, APOE-ε4 works through amyloid, and female sex, at least in part, works around it.

Subject of Research: Amyloid-β-mediated versus amyloid-independent pathways linking APOE-ε4 and female sex to medial temporal tau pathology in Alzheimer's disease

Article Title: Global and regional amyloid-β in explaining APOE-ε4 and sex associations with medial temporal tau: a neuropathology study

Article References: Salvadó, G., Groot, C., Wisse, L. E., Vogel, J. W., Beach, T. G., Serrano, G. E., Reiman, E. M., Schneider, J. A., Bennett, D. A., Ossenkoppele, R., & Hansson, O. (2026). Global and regional amyloid-β in explaining APOE-ε4 and sex associations with medial temporal tau: a neuropathology study. Acta Neuropathologica, 152(1), Article 49. https://doi.org/10.1007/s00401-026-03095-2

Image Credits: AI Generated

DOI: 10.1007/s00401-026-03095-2

Keywords: Alzheimer's disease, APOE-ε4, tau tangles, amyloid-β, medial temporal lobe, neuropathology, sex differences, hippocampus, entorhinal cortex, brain donation, dementia risk, clinical trials

Hereditary spastic paraplegias, or HSPs, are a genetically diverse group of neurological disorders in which degeneration of the central nervous system’s corticospinal tracts produces progressive stiffness and weakness of the lower limbs. Clinicians distinguish pure forms, in which pyramidal signs dominate the picture, from complicated forms accompanied by additional neurological or systemic features such as cognitive impairment, thinning of the corpus callosum, epilepsy, peripheral neuropathy, or skeletal anomalies. More than 87 distinct genetic loci have been linked to the disease, and 73 causative genes have been cloned to date. Despite this heterogeneity, mutations in SPG4/SPAST, which encodes the spastin protein, remain the single most frequent cause of the autosomal dominant forms, accounting for a substantial share of all diagnosed families worldwide.

Spastin belongs to the AAA family of ATPases, enzymes that harness the energy of ATP hydrolysis to remodel cellular structures. Its best-characterized roles involve membrane trafficking and the regulation of microtubule reorganization, processes critical to the long axons of motor neurons. More than 300 different pathogenic variants in the gene have been described, and symptoms typically emerge between the second and fourth decades of life, though onset can range from early childhood to beyond age 70. Recognizing the gene’s dominance and the variability of its presentation, an international team set out to map the SPG4/SPAST mutation profile across three continents and to correlate specific variants with the clinical features they produce.

Between 2001 and 2025, the researchers recruited 726 patients diagnosed with HSP, including 628 familial and 98 sporadic cases, drawn from Italy, Brazil, and Japan. The cohort comprised 313 probands from families with pure or complicated disease, and clinical assessments were performed by movement disorder specialists using standardized instruments including the Spastic Paraplegia Rating Scale. Genetic analysis combined Sanger sequencing of all 17 coding exons of SPG4/SPAST with whole-exome or whole-genome sequencing in selected patients and multiplex ligation-dependent probe amplification to detect large genomic rearrangements that shorter-read methods can miss. Healthy control groups from all three countries provided comparison data.

The genetic results were revealing. Overall, 60.9 percent of patients carried no pathogenic SPAST variant, underscoring the extensive genetic heterogeneity of HSP. Among the rest, sequencing identified 52 different heterozygous mutations in 263 autosomal dominant and 21 sporadic cases. Missense mutations were the largest class at 39.2 percent, followed by splice-site mutations, small deletions, nonsense mutations, insertions, and large rearrangements detected by MLPA, which accounted for 15.7 percent. Four novel variants were identified, absent from population databases and from nearly 400 controls, and all co-segregated with disease in their families. Notably, patients carrying missense mutations experienced an earlier median onset, at 36 years, compared with 42 years for carriers of other mutational classes.

Two of the novel variants carried particular weight. A missense change designated c.1382T>G, producing a p.Leu461Arg substitution within the protein’s AAA domain, was found in 18 unrelated patients from seven Italian families who all shared a common haplotype, pointing to a founder effect. Meanwhile, a small deletion of exon 13 appeared in ten unrelated patients from one Brazilian and two Japanese pedigrees, though haplotype analysis suggested these represented independent mutational events. Multivariate regression confirmed that SPG4 mutation status was independently predicted by later age at onset, a predominantly pure phenotype, lower disability stage, and a familial inheritance pattern, consistent with the gene’s established profile.

The most dramatic discovery emerged from the complicated cases. Among 72 SPG4 patients with complicated disease, foot deformities and cognitive deficits were the leading complications. Remarkably, all 18 affected individuals from the seven Italian families carrying the novel p.Leu461Arg variant had developed features compatible with early-onset dementia, and the same association held in the Brazilian and Japanese families carrying the exon 13 deletion. In every family member diagnosed with early-onset dementia, cerebrospinal fluid analysis showed a decreased Aβ42/Aβ40 ratio, consistent with cerebral amyloid plaque accumulation, while p-tau181 levels remained normal or low, indicating an absence of significant tau pathology or neurofibrillary tangle formation.

Autopsy studies on four patients cemented the pathological picture. Brain examination of a 64-year-old Italian patient carrying the novel variant revealed severe atrophy of the frontal, temporal, and parietal lobes, the hippocampus, amygdala, and entorhinal cortex, alongside a spinal cord thinner than normal with degeneration of the corticospinal tracts. Microscopically, the cortex was laden with senile plaques with congophilic cores and neuritic pathology, yet cotton wool plaques, neurofibrillary tangles, and Lewy bodies were entirely absent, and no abnormal α-synuclein or TDP-43 aggregates were detected. The case was classified as plaque-only dementia, scoring A3-B0-C3 on the National Institute on Aging–Alzheimer’s Association ABC system, with frequent neuritic plaque density by CERAD criteria. Comparable findings were confirmed in the other autopsied patients from Brazil and Japan.

Neuroimaging reinforced the clinical observations. Brain MRI in SPG4 patients with cognitive issues showed cerebral atrophy, particularly of the temporal lobes, while patients with intellectual disability displayed a thin corpus callosum without cerebellar involvement or white matter abnormalities. Amyloid PET imaging with 18F-flutemetamol in patients with early-onset dementia revealed cortical tracer binding consistent with substantial β-amyloid deposition, with Centiloid scores exceeding 50, even in individuals lacking overt neuropathological confirmation. Intriguingly, all autopsy-confirmed cases were homozygous for the APOE ε4 allele, a genotype known to foster a biological environment permissive to amyloid-rich, plaque-dominated dementia, and among all cognitively impaired patients, two-thirds were ε4 homozygotes.

The authors propose that these SPG4 variants may define a new disease manifestation: a form of hereditary spastic paraplegia complicated by an atypical, plaque-only pathological subtype of dementia. Because whole-exome and whole-genome sequencing excluded mutations in other dementia-related genes, including those classically associated with Alzheimer’s disease, the mutated spastin protein itself appears to be the likely culprit, though the precise mechanism linking microtubule dysfunction to amyloid accumulation remains unknown. The study also found that 21 percent of ostensibly sporadic cases carried SPG4 mutations, a rate higher than in small families with two affected members, suggesting that the boundary between familial and sporadic HSP is blurrier than previously assumed, with de novo mutations, incomplete penetrance, and misclassified family histories all contributing. The researchers caution that larger haplotype studies and archival research are needed to confirm the founder hypothesis, but the work opens a compelling new frontier in understanding how a single gene can shape both motor degeneration and dementia vulnerability.

Subject of Research: SPG4/SPAST mutations and their association with hereditary spastic paraplegia and plaque-only dementia

Article Title: SPG4 and Dementia: Expanding the Clinical Spectrum

Article References: SPG4 and Dementia: Expanding the Clinical Spectrum. (n.d.). https://doi.org/10.1002/acn3.70371

Image Credits: AI Generated

DOI: 10.1002/acn3.70371

Keywords: hereditary spastic paraplegia, SPG4, SPAST, spastin, dementia, amyloid plaques, plaque-only dementia, APOE ε4, genetics, neurodegeneration, amyloid PET, founder effect

Sarcopenic obesity is a condition in which excess adiposity coexists with reduced muscle mass and reduced muscle function. It matters because the two components feed each other in a vicious loop. Obesity accelerates muscle loss through chronic low-grade inflammation, insulin resistance and oxidative stress, while declining muscle mass lowers resting energy expenditure and encourages further fat accumulation. Shared drivers—aging itself, physical inactivity and chronic disease—perpetuate the cycle. Estimates of how common the condition is have varied wildly across studies precisely because researchers kept defining it differently: some used low strength plus a high body mass index, others low muscle mass plus high waist circumference, and still others required both muscle deficits alongside excess fat. A recent meta-analysis put the global prevalence at roughly 11 percent among adults aged 60 and older, rising to about 23 percent past age 75, but those numbers are hard to compare when the yardsticks differ.

The Taiwan study drew on the Taiwan Initiatives for Geriatric Epidemiological Research, recruiting 446 eligible participants from a senior health check-up programme at National Taiwan University Hospital between 2015 and 2017. After excluding people with prevalent dementia, neurological conditions, missing data or a body mass index below 18.5 kilograms per square metre, the final analytic sample comprised 366 older adults with a median age of 75, about 55 percent of them women. Each participant underwent a baseline assessment and a repeat evaluation two years later. Muscle mass was estimated with bioelectrical impedance analysis and normalized by body weight, with the lowest sex-specific quartile classified as low. Handgrip strength was measured with a dynamometer using Asian Working Group for Sarcopenia cutoffs of less than 28 kilograms for men and less than 18 kilograms for women. Obesity was defined as a body mass index of at least 27, a threshold specific to Taiwanese adults rather than the conventional cutoff of 30.

Cognition was assessed with a battery of neuropsychological tests at both visits. Global cognition was measured with the Taiwanese version of the Montreal Cognitive Assessment, while domain-specific measures included immediate and delayed logical memory recall, attention via the Trail Making Test A and digit span tasks, executive function via the Trail Making Test B, and semantic verbal fluency. The researchers then used generalized linear mixed models—statistical frameworks that handle repeated measurements within the same person—to estimate how phenotype status related to cognitive performance, adjusting for age, sex, education, the APOE ε4 allele, depressive symptoms, smoking, alcohol use, hypertension, diabetes, dyslipidemia, heart disease, physical activity, and blood levels of the inflammatory markers C-reactive protein and interleukin-6.

The results were striking. Of the 366 participants, 303 had neither sarcopenia nor obesity, 20 had sarcopenia alone, 27 had obesity alone, and 16—about 4 percent—met the full consensus criteria for sarcopenic obesity. That small group stood out. Compared with people who had neither condition, those with sarcopenic obesity scored nearly one point lower on the Montreal Cognitive Assessment (a beta coefficient of −0.96), and showed significantly poorer immediate free recall and attention on the Trail Making Test A. Obesity alone, by contrast, was linked only to poorer executive function on the Trail Making Test B, and sarcopenia alone showed no robust association with global cognition. When the researchers modeled baseline status and its interaction with follow-up time, baseline sarcopenic obesity predicted poorer executive function over time, suggesting the phenotype marks not just a snapshot of lower performance but a trajectory of decline.

The team also examined a related, simpler phenotype called dynapenic obesity—the combination of low muscle strength and obesity without any requirement for measured muscle loss. Because grip strength is far easier to assess than muscle mass in clinics and community settings, dynapenic obesity has long been proposed as a pragmatic screening tool, though it has often been conflated with sarcopenic obesity in the literature. In this cohort, the two phenotypes overlapped completely: all 16 participants with dynapenic obesity also met the criteria for sarcopenic obesity. Dynapenic obesity was associated with even slightly larger deficits—about −1.15 points on the Montreal Cognitive Assessment—along with poorer memory and attention, and a significant interaction with time for executive function. The authors are careful to stress that this overlap means the two phenotypes cannot be treated as independent entities here; the findings speak to a shared, strength-based signal of muscle–adiposity imbalance rather than proof that grip strength outperforms muscle mass measurement.

Robustness was tested aggressively. When obesity was redefined using Asian-specific waist circumference cutoffs (90 centimetres for men, 80 for women), sarcopenic obesity remained associated with poorer global cognition and attention. When obesity was defined by the highest sex-specific quartile of fat mass index, the association with global cognition and memory persisted. Alternative thresholds for low muscle mass—the lowest tertile and quintile—produced the same conclusions, and re-including seven participants excluded solely for being underweight left the results essentially unchanged. Exploratory stratified analyses hinted at who may be most vulnerable: associations with poorer global cognition appeared among women, among people without the APOE ε4 allele, and among those in the highest tertile of interleukin-6 or C-reactive protein, even though the participants’ inflammatory marker levels generally fell below clinical thresholds for overt inflammation. These subgroup findings, the authors caution, were not adjusted for multiple comparisons and must be treated as hypothesis-generating.

Why might a muscle–fat imbalance reach the brain? The mechanisms are likely multifactorial. Age-related muscle decline and physical inactivity promote adiposity, insulin resistance and systemic low-grade inflammation, which in turn can impair muscle metabolism, damage the vasculature and drive neuroinflammation. The observation that cognitive deficits clustered in participants with relatively higher interleukin-6 or C-reactive protein is compatible with such inflammatory pathways, and the pattern of stronger associations among people without diabetes suggests metabolic context matters. There may also be sex-specific biology at work, including differences in inflammatory profiles and sex hormones that influence skeletal muscle aging. But the study is observational, and reverse causality cannot be excluded: early cognitive impairment may itself reduce physical activity and alter body composition long before dementia is diagnosable.

The practical takeaway may prove to be the study’s most consequential contribution. A grip dynamometer and a bathroom scale are cheap, fast and universally available. If the combination of weak grip and elevated body mass index flags older adults at risk of early cognitive impairment, it offers a first-step, community-based screening strategy that could direct people toward fuller evaluations of body composition and cognition before irreversible decline sets in. The authors emphasize that the clinical utility of this approach requires validation in larger cohorts with more balanced distributions of muscle mass and strength, longer follow-up, and objective measures of physical activity. Still, in a world where both obesity and population aging are accelerating simultaneously, the message is hard to ignore: what matters for the aging brain may not be fat or muscle alone, but the dangerous arithmetic of losing one while gaining the other.

Subject of Research: Associations of consensus-defined sarcopenic obesity and dynapenic obesity with early cognitive impairment in older adults

Article Title: Consensus‐Defined Sarcopenic Obesity and a Related Dynapenic Obesity Phenotype in Relation to Early Cognitive Impairment

Article References: Wang, M.-C., Peng, T.-C., Chiou, J.-M., Chen, Y.-C., & Chen, J.-H. (2026). Consensus‐Defined Sarcopenic Obesity and a Related Dynapenic Obesity Phenotype in Relation to Early Cognitive Impairment. Journal of Cachexia, Sarcopenia and Muscle, 17(5), Article e70395. https://doi.org/10.1002/jcsm.70395

Image Credits: AI Generated

DOI: 10.1002/jcsm.70395

Keywords: sarcopenic obesity, dynapenic obesity, cognitive impairment, aging, muscle mass, handgrip strength, obesity, ESPEN-EASO consensus, inflammation, APOE ε4, cohort study, geriatric health

The study drew on the Island Study Linking Aging and Neurodegenerative Disease (ISLAND), a ten-year community-based initiative in Tasmania, Australia, that combines dementia education with large-scale data collection. From more than 1,300 potentially eligible participants, the researchers assembled a cross-sectional sample of 339 cognitively unimpaired adults with an average age of about 66 years, roughly 71 percent of them women. Of these, 238 reported no noticeable cognitive changes and served as asymptomatic controls, while 101 met criteria for subjective cognitive decline (SCD)—a self-perceived, persistent worsening of memory or mental function despite normal performance on cognitive tests. SCD matters because older adults with it progress to dementia at roughly twice the annual rate of those without it, and neuroimaging studies suggest it shares pathological features with mild cognitive impairment and Alzheimer’s dementia.

The participants completed the Tasmanian Test, a browser-based, self-administered battery of motor, cognitive, and speech tasks that they performed at home without supervision. For the speech component, they recorded four maximally paced DDK tasks in fixed order: rapid repetition of the monosyllables “pa,” “ta,” and “ka,” followed by the trisyllable sequence “pataka.” Each test lasted ten seconds, with up to two reattempts allowed. From the resulting audio recordings, the team extracted a rich set of features quantifying repetitions, speaking time, pauses, voice onset time—the interval between the release of a plosive consonant and the onset of vocal fold vibration—and variability measures. Crucially, they also computed derived “motor cost” measures by subtracting performance on one stimulus from another, capturing differences in articulatory control between bilabial, alveolar, and velar consonants, and between simple and complex sequences.

Why should rapid syllable repetition be sensitive to Alzheimer’s disease at all? The neurobiological rationale rests on the brain circuits that govern sub-second timing and sequential motor control. Functional MRI studies show that paced syllable repetition engages the putamen and cerebellum in a rate-dependent manner, and that rapid syllable-sequence production recruits the cerebellum in proportion to articulatory complexity. Cerebellar-basal ganglia circuits are central to internal timing and error correction, and Alzheimer’s-related alterations in cerebellar connectivity have been documented. Unlike connected speech tasks such as picture description, which confound motor control with language and memory demands, DDK tasks isolate the pure motor dimension of speech production—making them a potentially cleaner window onto preclinical brain changes.

The researchers tested whether these motor speech measures were associated with three established Alzheimer’s risk indicators: subjective cognitive decline, carriage of the apolipoprotein E ε4 allele, and plasma concentrations of phosphorylated tau 181 (p-tau181). Each carries weight. APOE ε4 is the strongest genetic risk factor for late-onset Alzheimer’s, conferring roughly three- to fourfold increased risk with one allele and eight- to fifteenfold with two. Plasma p-tau181 rises during preclinical disease, performs comparably to tau PET for classifying amyloid positivity in people with SCD, and predicts progression to Alzheimer’s dementia in cognitively unimpaired individuals. Blood samples had been collected at in-person clinics across Tasmania in 2021, with p-tau181 measured using an ultrasensitive single-molecule array platform and APOE genotype determined by PCR.

The statistical approach was deliberately cautious. Bivariate, nonparametric analyses with Benjamini-Hochberg correction for multiple comparisons found that no associations with SCD or APOE ε4 survived adjustment—only one measure, a “pa”-“ta” cost of repetition duration variability, remained significantly linked to plasma p-tau181. The team then turned to LASSO-penalized regression, a machine learning technique that shrinks coefficients to prevent overfitting in high-dimensional data. To stabilize estimates against the randomness of cross-validation fold assignment, they used a percentile-LASSO procedure, running each tenfold cross-validation process one hundred times and fitting the final model at the 95th percentile of the regularization parameter. Logistic models predicted SCD and APOE ε4 status, while a linear model predicted natural log-transformed p-tau181, with age, sex, education, anxiety, and depression available as covariates.

The results were intriguingly patterned. In the main analysis of 315 participants with complete data, motor speech measures predicted SCD with an area under the curve of 0.700, APOE ε4 carriage with an AUC of 0.715, and log-transformed p-tau181 with a mean absolute error of 0.323. For SCD, the simple models selected only depression as a predictor, but the more complex “maximal” models—which allowed interaction terms—consistently outperformed them and selected several motor speech features, always in interaction with depression. For APOE ε4, the simple models prevailed, with voice onset time features and variability measures prominent among the selected predictors, alongside age. For p-tau181, age was the only non-speech covariate chosen, and one derived measure in particular—voice onset time variability cost for “ka”-“pataka”—appeared in the superior model of every analysis, sometimes standing alone and sometimes interacting with age, education, and depression.

Depression emerged as a recurring complication. Because depression can affect subjective cognition, speech, and motor function alike, the researchers ran sensitivity analyses excluding participants with Hospital Anxiety and Depression Scale scores of eight or above, and separately incorporating hearing loss and expanded samples of participants with incomplete biomarker data. These analyses revealed potentially mitigating effects of depression and hints of bias from the limited availability of blood biomarker data. In the expanded sample, APOE ε4 prediction fell to barely better than chance in the full group, yet improved markedly in the low-depression subset, where more motor speech predictors were selected. The authors interpret this as evidence that depression may modify or obscure genuine relationships between motor speech control and Alzheimer’s risk factors, and that even subclinical depression may need explicit adjustment in future studies.

The study has clear limitations that the authors acknowledge candidly. It was cross-sectional and exploratory, so temporal direction cannot be established and longitudinal follow-up will be essential. The sample was predominantly White, highly educated women of Northern European ancestry, limiting generalizability, and participants were health-motivated volunteers in a dementia risk reduction program. Exclusion of cognitive impairment relied on self-reported diagnoses, and blood biomarker data were available only for those who attended clinics, introducing potential selection bias that the expanded-sample analyses could only partially address. The authors also note that the differencing process used to compute motor costs may reduce intra-individual variability, complicating interpretation of those derived measures.

Even with those caveats, the findings broaden the Alzheimer’s motor phenotype—which already includes slower gait, reduced stride length linked to p-tau181, and faster motor decline in APOE ε4 carriers—into the domain of speech motor control. If replicated with counter-balanced task order and longitudinal designs, motor speech measures could become scalable, non-invasive behavioral indicators that complement gait analysis and blood biomarkers in population screening. The vision is compelling: a browser-based test that anyone can take at home, extracting subtle signatures of articulatory timing and consistency that reflect the earliest biological whispers of Alzheimer’s disease. For now, the study stands as careful, early-stage evidence that the voice may know something about the brain that standard cognitive tests do not yet reveal.

Subject of Research: Associations between motor speech performance in rapid syllable repetition tasks and Alzheimer's disease risk markers in cognitively unimpaired older adults

Article Title: Motor speech markers of Alzheimer’s risk

Article References: Motor speech markers of Alzheimer’s risk. (n.d.). https://doi.org/10.1007/s11357-026-02560-w

Image Credits: AI Generated

DOI: 10.1007/s11357-026-02560-w

Keywords: Alzheimer's disease, motor speech, diadochokinesis, subjective cognitive decline, APOE ε4, p-tau181, blood biomarkers, digital biomarkers, dementia screening, GeroScience, speech analysis, preclinical detection

Mild cognitive impairment, often abbreviated as MCI, is one of the most diagnostically frustrating states in medicine. It describes a genuine decline in memory or thinking that goes beyond normal aging, yet it sits on a fault line: some people with MCI stabilize or even revert to normal cognition, while others progress to full dementia, most commonly Alzheimer’s disease. Previous meta-analyses of dozens of cohort studies have shown that annual conversion rates vary enormously between clinical settings, and a large fraction of people diagnosed with MCI never develop dementia at all. This heterogeneity is precisely why clinicians have long sought reliable tools to separate the two trajectories, and why misclassification carries such high stakes, either exposing stable patients to unnecessary treatment or delaying care for those truly at risk.

The research team, led by Bipul Simkhada of Florida International University together with colleagues at the University of Miami, the University of Florida, and Clemson University, tackled the problem with a multimodal machine-learning framework. They assembled 2008 samples drawn from 828 unique individuals with MCI in the Alzheimer’s Disease Neuroimaging Initiative, one of the largest and most thoroughly characterized longitudinal dementia datasets in existence. Each sample combined three distinct families of information: cognitive and functional assessments gathered during clinical visits, demographic and genetic variables including APOE genotype, and structural features extracted from magnetic resonance imaging of the brain. Based on what actually happened over a two-year follow-up window, subjects were labeled as either stable MCI, comprising 1306 samples, or progressive MCI, comprising 702 samples that converted to dementia.

Methodological rigor was central to the design. Rather than relying on a single train-test split, which can inflate performance estimates, the researchers used nested cross-validation, a scheme in which model selection and performance evaluation are separated at every step. They also addressed the inherent class imbalance between stable and progressive samples using the synthetic minority over-sampling technique, known as SMOTE, and paid careful attention to feature scaling, calibration of predicted probabilities, and the selection of clinically meaningful decision thresholds. These details matter because a prediction tool that reports probabilities poorly calibrated against real-world outcomes can mislead physicians even when its raw accuracy appears impressive. The team’s final model was a calibrated version of XGBoost, a gradient-boosted decision tree algorithm widely used in biomedical prediction for its ability to capture nonlinear interactions between variables without requiring enormous computing resources.

The results were striking. During nested cross-validation, the multimodal XGBoost model achieved a balanced accuracy of 81.28 percent, with a standard deviation of 2.56 percent, meaning that it correctly identified both converters and non-converters at nearly equal rates despite the unequal group sizes. On an independent held-out test set that the model had never seen during training, balanced accuracy reached 81.99 percent, with a bootstrap mean of 81.97 percent and a 95 percent confidence interval spanning 78.22 to 85.51 percent. Crucially, the multimodal combination outperformed any single data type used alone. Cognitive tests, demographic risk factors, and brain imaging each carried predictive signal, but their fusion proved strictly superior, underscoring a complementary relationship between the observable decline in day-to-day function and the silent anatomical erosion happening inside the brain.

What elevates the study beyond a simple accuracy benchmark is its insistence on explainability. Black-box predictions have historically been a barrier to clinical adoption, so the researchers interrogated their model using SHAP, or SHapley Additive exPlanations, a technique derived from cooperative game theory that assigns each input feature a precise contribution to every individual prediction, alongside permutation feature importance, which measures how much performance degrades when a given variable is shuffled. The analyses converged on a coherent and clinically intuitive picture. The strongest predictors included functional impairment measures, specifically the Functional Activities Questionnaire and the Clinical Dementia Rating Sum of Boxes, which capture whether a person is struggling with finances, medications, shopping, and other instrumental tasks of daily living.

Cognitive performance scores followed closely, particularly the 11-item and 13-item versions of the Alzheimer’s Disease Assessment Scale cognitive subscale and the Mental State Examination, familiar bedside instruments that quantify memory, orientation, language, and attention. Alongside these behavioral markers, the model leaned heavily on biological signals: the APOE ε4 allele, the best-established genetic risk factor for sporadic Alzheimer’s disease, and a constellation of structural brain abnormalities. The imaging features that mattered most mapped onto regions long implicated in the disease, including the hippocampus, the memory-forming structure that atrophies earliest, the lateral ventricles that expand as surrounding tissue shrinks, the parietal and temporal lobes where cortical thinning tracks disease spread, and the amygdala, a deep structure involved in emotion and memory circuits.

The convergence of these strands is perhaps the study’s most important conceptual message. Neither cognitive test scores nor genetic risk nor imaging atrophy alone tells the whole story, but when a patient shows functional decline on questionnaires, poor performance on structured cognitive batteries, carries an ε4 allele, and exhibits measurable shrinkage in exactly the brain regions vulnerable to Alzheimer’s pathology, the probability of near-term conversion rises sharply. The researchers describe this alignment of cognitive-functional impairment and region-specific neurodegeneration as the strongest indicator of impending dementia, a finding that reinforces the biological intuition that clinical symptoms and structural damage advance together during the transition period.

The practical implications are considerable. Because all of the input data can be collected during a single clinical visit, without longitudinal repeated scans or experimental fluid biomarkers, the framework could in principle be deployed in memory clinics using instruments that clinicians already administer. An accurate two-year risk estimate would allow physicians to triage patients, directing high-risk individuals toward early anti-amyloid therapy, closer monitoring, and participation in clinical trials, while sparing lower-risk patients unnecessary interventions and anxiety. It would also sharpen the design of prevention studies, which currently spend enormous resources enrolling participants who never progress. The team has made its analysis code publicly available on GitHub, and the underlying data come from the openly accessible ADNI database, allowing other groups to validate and extend the approach.

Challenges remain before such models enter routine practice. ADNI participants are volunteers who tend to be well educated and predominantly of European ancestry, and recent systematic reviews have flagged limited generalizability and high risk of bias across many published MCI prediction models, so independent validation in diverse, real-world populations will be essential. Still, the combination of robust validation methodology, calibrated probabilities, explainable outputs, and accuracy above 80 percent using only routine clinical data marks a meaningful advance. As the population ages and the number of people living with mild cognitive impairment climbs into the tens of millions worldwide, tools that can distinguish, at the first appointment, who will decline and who will not, may fundamentally reshape how medicine confronts the earliest and most treatable stage of dementia.

Subject of Research: Multimodal machine-learning prediction of two-year conversion from mild cognitive impairment to dementia

Article Title: Multimodal prediction of MCI-to-dementia conversion over a two-year window

Article References: Simkhada, B., Liang, T. Y., Cui, X., Adeyosoye, M., Simkhada, B., Cabrerizo, M., Cid, R. C., Burke, S. L., Barreto, A., Rishe, N., Loewenstein, D. A., & Adjouadi, M. (2026). Multimodal prediction of MCI-to-dementia conversion over a two-year window. GeroScience. https://doi.org/10.1007/s11357-026-02551-x

Image Credits: AI Generated

DOI: 10.1007/s11357-026-02551-x

Keywords: mild cognitive impairment, Alzheimer's disease, dementia, machine learning, XGBoost, explainable AI, SHAP, structural MRI, APOE ε4, hippocampal atrophy, ADNI, GeroScience