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Identifying dynamic changes in biomarkers and clinical profiles is essential for understanding the progression of Alzheimer’s disease (AD). The relevant studies have primarily relied on patients with autosomal dominant AD; however, relevant studies in sporadic AD are poorly understood. Here, we analyzed longitudinal data from 665 participants (mean follow-up 4.90 ± 2.83 years). By aligning normal cognition (CN) baseline with a clinical diagnosis of mild cognitive impairment (MCI) or AD, we studied the progression of AD using a linear mixed model to estimate the clinical and biomarker changes from stable CN to MCI to AD. The results showed that the trajectory of hippocampal volume and fluorodeoxyglucose (FDG) was consistent with the clinical measures in that they did not follow a hypothetical sigmoid curve but rather showed a slow change in the initial stage and accelerated changes in the later stage from MCI conversion to AD. Dramatic hippocampal atrophy and the ADAS13 increase were, respectively, 2.5 and 1 years earlier than the MCI onset. Besides, cognitively normal people with elevated and normal amyloid showed no significant differences in clinical measures, hippocampal volume, or FDG. These results reveal that pre-MCI to pre-AD may be a better time window for future clinical trial design.

White matter tracts alterations have been reported in schizophrenia (SZ), but whether such abnormalities are associated with the effects of the disorder itself and/or genetic vulnerability remains unclear. Moreover, the specific patterns of different parts of these altered tracts have been less well studied. Thus, diffusion-weighted images were acquired from 38 healthy controls (HCs), 48 schizophrenia patients, and 33 unaffected first-degree relatives of SZs (FDRs). Diffusion properties of the 25 major tracts automatically extracted with probabilistic tractography were calculated and compared among groups. Regarding the peripheral regions of the tracts, significantly higher diffusivity values in the left superior longitudinal fasciculus (SLF) and the left anterior thalamic radiation (ATR) were observed in SZs than in HCs and unaffected FDRs. However, there were no significant differences between HCs and FDRs in these two tracts. While no main effects of group with respect to the core regions of the 25 tracts survived multiple comparisons correction, FDRs had significantly higher diffusivity values in the left medial lemniscus and lower diffusivity values in the middle cerebellar peduncle than HCs and SZs. These findings enhance the understanding of the abnormal patterns in the peripheral and core regions of the tracts in SZs and those at high genetic risk for schizophrenia. Our results suggest that alterations in the peripheral regions of the left SLF and ATR are features of established illness rather than genetic predisposition, which may serve as critical neural substrates for the psychopathology of schizophrenia.

Summary We have shown that the improvement in hippocampal-based learning in aged mice following physical exercise observed is dependent on neurogenesis in the dentate gyrus (DG) and is regulated by changes in growth hormone levels. The changes in neurocircuitry, however, which may underlie this improvement, remain unclear. Using in vivo multimodal magnetic resonance imaging to track changes in aged mice exposed to exercise, we show the improved spatial learning is due to enhanced DG connectivity, particularly the strengthening of the DG-Cornu Ammonis 3 and the DG-medial entorhinal cortex connections in the dorsal hippocampus. Moreover, we provide evidence that these changes in circuitry are dependent on neurogenesis since they were abrogated by ablation of newborn neurons following exercise. These findings identify the specific changes in hippocampal circuitry that underlie the cognitive improvements resulting from physical activity and show that they are dependent on the activation of neurogenesis in aged animals., Graphical abstract, Highlights • Exercise can enhance connectivity in the dorsal hippocampus to improve spatial learning • Circuitry changes depend on increased neurogenesis in the hippocampus of aged animals • Identification of the specific changes in circuitry underlying cognitive improvements • Enhanced connectivity occurs only after exercise of a specific duration: the sweet spot, Cognitive neuroscience, Behavioral neuroscience, Biological sciences

Background:Previous studies showed no obvious symptoms but subtle structural brain changes in a long preclinical stage of Alzheimer's disease (AD), then localized cortical and sub-cortical atrophy in MCI, and spread aggressively to nearly whole brain neurodegeneration in AD. However, the neurobiological and pathogenic substrates underlying these structural changes across AD spectrum remain largely understood.Methods: We obtained structural MRI imaging from ADNI datasets, including 83 early-stage mild cognitive impairments (EMCI), 83 late-stage mild cognitive impairments (LMCI), 83 AD, and 83 normal controls (NC), and aimed to explore structural changes across the full clinical AD spectrum and their genetic mechanism. Partial least square regressions and Spearman correlations were performed to explore how these changes associated with gene expression level obtained from Allen Human Brain Atlas. Finally, functional enrichment analyses were conducted using Metascape analysis to explore ontological pathways of the consistent genes. Results:We identified significant volume atrophy in left thalamus, left cerebellum, and bilateral middle frontal gyrus across AD spectrum. These structural changes were positively associated with gene expression levels of ABCA7, SORCS1, SORL1, PILRA, PFDN1, PLXNA4, TRIP4, and CD2AP, whereas were negatively associated with gene expression levels of CD33, PLCG2, APOE, and ECHDC3 for all three groups. Moreover, these results were verified in sub-groups of converted and stable EMCI and LMCI. Further gene enrichment analyses revealed that these positively associated genes were mainly involved in positive regulation of cellular protein localization and negative regulation of cellular component organization, whereas the negatively associated genes were mainly involved in positive regulation of iron transport. Conclusions:Overall, these results suggested that structural changes in prodromal and clinical AD might result from interaction of the same gene lists, which offered a better understanding of biological mechanisms underlying structural changes in prodromal and clinical AD.

Chromatin accessibility and post-transcriptional histone modifications play important roles in gene expression regulation. However, little is known about the joint effect of multiple chromatin modifications on the gene expression level in plants, despite that the regulatory roles of individual histone marks such as H3K4me3 in gene expression have been well-documented. By using machine-learning methods, we systematically performed gene expression level prediction based on multiple chromatin modifications data in Arabidopsis and rice. We found that as few as four histone modifications were sufficient to yield good prediction performance, and H3K4me3 and H3K36me3 being the top two predictors with known functions related to transcriptional initiation and elongation, respectively. We demonstrated that the predictive powers differed between protein-coding and non-coding genes as well as between CpG-enriched and CpG-depleted genes. We also showed that the predictive model trained in one tissue or species could be applied to another tissue or species, suggesting shared underlying mechanisms. More interestingly, the gene expression levels of conserved orthologs are easier to predict than the species-specific genes. In addition, chromatin state of distal enhancers was moderately correlated to gene expression but was dispensable if given the chromatin features of the proximal regions of genes. We further extended the analysis to transcription factor (TF) binding data. Strikingly, the combinatorial effects of only a few TFs were roughly fit to gene expression levels in Arabidopsis. Overall, by using quantitative modeling, we provide a comprehensive and unbiased perspective on the epigenetic and TF-mediated regulation of gene expression in plants.

Brain atlas is an important tool in the diagnosis and treatment of neurological disorders. However, due to large variations in the organizational principles of individual brains, many challenges remain in clinical applications. Brain atlas individualization network (BAI-Net) is an algorithm that subdivides individual cerebral cortex into segregated areas using brain morphology and connectomes. The presented method integrates group priors derived from a population atlas, adjusts areal probabilities using the context of connectivity fingerprints derived from the fiber-tract embedding of tractography, and provides reliable and explainable individualized brain areas across multiple sessions and scanners. We demonstrate that BAI-Net outperforms the conventional iterative clustering approach by capturing significantly heritable topographic variations in individualized cartographies. The topographic variability of BAI-Net cartographies has shown strong associations with individual variability in brain morphology, connectivity as well as higher relationship on individual cognitive behaviors and genetics. This study provides an explainable framework for individualized brain cartography that may be useful in the precise localization of neuromodulation and treatments on individual brains.

IMPORTANCEThe dynamic changes of biomarkers and clinical profiles in sporadic Alzheimer’s disease (SAD) are poorly understood.OBJECTIVETo evaluate the impact of amyloid-β (Aβ) biomarkers on SAD by measuring the dynamic changes in biomarkers and clinical profiles in the progression of SAD.DESIGN AND SETTINGThis retrospective and longitudinal study analyzed clinical and biomarker data from 665 participants (mean follow-up 4.90 ± 2.83 years) from a subset of the AD Neuroimaging Initiative (ADNI) participants collected from August 2005 to December 2018. By aligning the timing of the changes in the various biomarkers with the stable normal cognition (CN) baseline and mild cognitive impairment (MCI) or AD onset timepoints, we combined data from the stable CN, CN conversion to MCI (CN2MCI), and MCI conversion to AD (MCI2AD) groups to identify the trajectories associated with the progression of AD.PARTICIPANTSThe participants were 294 CN, 69 CN2MCI, 300 MCI2AD, and 24 who converted from CN to MCI to AD (CN2MCI2AD) (of whom 22 were also included in the CN2MCI).EXPOSURESAmyloid-β measured by florbetapir positron emission tomography (PET) or cerebrospinal fluid assay of amyloid-β (CSF Aβ42).MAIN OUTCOMES AND MEASURESThe measures included the 13-item cognitive subscale of the AD Assessment Scale (ADAS13, as a clinical measure), hippocampal volume, and the fluorodeoxyglucose (FDG) PET standardized uptake value ratio (SUVR).RESULTSThe CN, CN2MCI, and MCI2AD subgroups’ median (interquartile range [IQR]) annual changes in ADAS13 were (0.388 [−0.278, 0.818], 1.000 [0.239, 2.330], and 3.388 [1.750, 6.169]). The annual changes in hippocampal volume for each group were (−0.005 %ICV [−0.011, −0.001], −0.006 %ICV [−0.012, −0.002], and −0.014 %ICV [−0.021, −0.009]). The annual changes in FDG PET SUVR for each group were (−0.011 [−0.030, 0.010], −0.027 [−0.056, −0.012], and −0.039 [−0.063, 0.014]). Changes in the amyloid biomarkers were inconsistent with clinical profile changes. The annual changes in CSF Aβ42 for each group were (−1.500 pg/ml [−6.000, 4.000], −2.200 [−5.667, 4.000], and −2.000 [−7.000, 2.650]) and in Aβ PET SUVR for each group were (0.004 [−0.002, 0.012], 0.004 [−0.001,0.011], and 0.005 [−0.006, 0.014]). During the stable CN and CN2MCI stages, subjects with elevated and those with normal amyloid showed no significant differences (likelihood ratio test, p < .01) in clinical measures, hippocampal volume, or FDG.CONCLUSIONS AND RELEVANCEHippocampal volume and FDG associated with clinical profiles impairment in the SAD progression. Aβ alone is not associated with clinical profiles, hippocampal volume, and FDG impairment in the preclinical stage of SAD.Key PointsQuestion: What is the role of amyloid-β in dynamic changes in biomarkers and clinical profiles in the progression of sporadic Alzheimer’s disease?Findings: The changes of the hippocampal volume and FDG that were consistent with the changes of the clinical profiles showed a non-linear change in the initial stage and an accelerated non-linear change during MCI2AD, changes in amyloid biomarkers were inconsistent with the clinical profile. Cognitively normal people with elevated or normal amyloid showed no significant differences in clinical measures, hippocampal volume, or FDG.Meaning: Amyloid-β alone may not be used as the central index for defining the preclinical stage of SAD.

Background: The parahippocampal gyrus (PHG) is an important region of the limbic system that plays an important role in episodic memory. Elucidation of the PHG connectivity pattern will aid in the understanding of memory deficits in neurodegenerative diseases. Objective: To investigate if disease severity associated altered PHG connectivity in Alzheimer’s disease (AD) exists. Methods: We evaluated resting-state functional magnetic resonance imaging data from 18 patients with amnestic mild cognitive impairment (MCI), 35 patients with AD, and 21 controls. The PHG connectivity pattern was examined by calculating Pearson’s correlation coefficients between the bilateral PHG and whole brain. Group comparisons were performed after controlling for the effects of age and gender. The functional connectivity strength in each identified region was correlated with the MMSE score to evaluate the relationship between connectivity and cognitive ability. Results: Several brain regions of the default mode network showed reduced PHG connectivity in the AD patients, and PHG connectivity was associated with disease severity in the MCI and AD subjects. More importantly, correlation analyses showed that there were positive correlations between the connectivity strengths of the left PHG-PCC/Pcu and left PHG-left MTG and the Mini-Mental State Examination, indicating that with disease progression from MCI to severe AD, damage to the functional connectivity of the PHG becomes increasingly severe. Conclusions: These results indicate that disease severity is associated with altered PHG connectivity, contributing to knowledge about the reduction in cognitive ability and impaired brain activity that occur in AD/MCI. These early changes in the functional connectivity of the PHG might provide some potential clues for identification of imaging markers for the early detection of MCI and AD.

Traditional anatomical studies of the parahippocampal region (PHR) defined the lateral portion into two subregions, the perirhinal (PRC) and parahippocampal (PHC) cortices. Based on this organization, several models suggested that the PRC and the PHC play different roles in memory through connections with different memory-related brain networks. To identify the key components of the human PHR, we used a well accepted connection-based parcellation method on two independent datasets. Our parcellation divided the PRC and PHC into three subregions, specifically, the rostral PRC, caudal PRC (PRCc), and PHC. The connectivity profile for each subregion showed that the rostral PRC was connected to the anterior temporal (AT) system and the PHC was connected to the posterior medial (PM) system. The transition area (PRCc) integrated the AT-PM systems. These results suggest that the lateral PHR not only contains functionally segregated subregions, but also contains a functionally integrated subregion.SIGNIFICANCE STATEMENTWe redefined the cartography of the human parahippocampal region (PHR) and identified a transition subarea based on distinct anatomical and functional connectivity profiles. This well defined anatomical organization of the PHR is necessary for expanding our understanding and studying the functional relevance of its subregions in recognition memory. We found that the transition subregion [caudal perirhinal cortex (PRCc)] is a functionally integrated subregion that integrates the anterior temporal (AT)–posterior medial (PM) systems. In addition, we found that the core components of the AT and PM systems connect with the PHR in the rostral PRC and parahippocampal cortex (PHC), respectively, rather than connecting with the traditional, larger, and thus less concise PRC and PHC areas. This may lead to new insights into the human memory system and related neurodegenerative diseases.

Purpose: Several recent studies have identified structural changes in the cerebral cortex that occur with extensive motor training. However, limited studies have been conducted to explore the structural changes of subcortical structures, which are thought to play important roles in motor functioning. This study aims to localize the shape differences of the subcortical structures between the diving players and the nonathlete group. Methods: Twelve professional players with top-level diving skills and 12 age- and education-matched healthy controls without any training experience were scanned with a 3-T magnetic resonance imaging. Data were processed using FSL-FIRST, a model-based segmentation and registration tool. Results: Compared with the nonathlete group, we found significant regional inflation in the bilateral thalamus and the left globus pallidus in diving players. Conclusion: Although we cannot rule out the effect of predispositions, the regional inflation of the thalamus and globus pallidus might reflect the experience-dependent plasticity because of extensive diving training.