The morphometry of left cuneus mediating the genetic regulation on working memory

Working memory is a basic human cognitive function. However, the genetic signatures and their biological pathway remain poorly understood. In the present study, we tried to clarify this issue by exploring the potential associations and pathways among genetic variants, brain morphometry and working memory performance. We first carried out association analyses between 2‐back accuracy and 212 image‐derived phenotypes from 1141 Human Connectome Project (HCP) subjects using a linear mixed model (LMM). We found a significantly positive correlation between the left cuneus volume and 2‐back accuracy (T = 3.615, p = 3.150e−4, Cohen''s d = 0.226, corrected using family‐wise error [FWE] method). Based on the LMM‐based genome‐wide association study (GWAS) on the HCP dataset and UK Biobank 33 k GWAS summary statistics, we identified eight independent single nucleotide polymorphisms (SNPs) that were reliably associated with left cuneus volume in both UKB and HCP dataset. Within the eight SNPs, we found a negative correlation between the rs76119478 polymorphism and 2‐back accuracy accuracy (T = −2.045, p = .041, Cohen''s d = −0.129). Finally, an LMM‐based mediation analysis elucidated a significant effect of left cuneus volume in mediating rs76119478 polymorphism on the 2‐back accuracy (indirect effect = −0.007, 95% BCa CI = [−0.045, −0.003]). These results were also replicated in a subgroup of Caucasians in the HCP population. Further fine mapping demonstrated that rs76119478 maps on intergene CTD‐2315A10.2 adjacent to protein‐encoding gene DAAM1, and is significantly associated with L3HYPDH mRNA expression. Our study suggested this new variant rs76119478 may regulate the working memory through exerting influence on the left cuneus volume.     

Pre‐ and post‐conditioning with poly I:C exerts neuroprotective effect against cerebral ischemia injury in animal models: A systematic review and meta‐analysis

BackgroundToll‐like receptor (TLR) agonist polyinosinic–polycytidylic acid (poly I:C) exerts neuroprotective effects against cerebral ischemia (CI), but concrete evidence supporting its exact mechanism of action is unclear.MethodsWe evaluated the neuroprotective role of poly I:C by assessing CI indicators such as brain infarct volume (BIV), neurological deficit score (N.S.), and signaling pathway proteins. Moreover, we performed a narrative review to illustrate the mechanism of action of TLRs and their role in CI. Our search identified 164 articles and 10 met the inclusion criterion.ResultsPoly I:C reduces BIV and N.S. (p = 0.00 and p = 0.03). Interestingly, both pre‐ and post‐conditioning decrease BIV (preC p = 0.04 and postC p = 0.00) and N.S. (preC p = 0.03 and postC p = 0.00). Furthermore, poly I:C upregulates TLR3 [SMD = 0.64; CIs (0.56, 0.72); p = 0.00], downregulates nuclear factor‐κB (NF‐κB) [SMD = −1.78; CIs (−2.67, −0.88); p = 0.0)], and tumor necrosis factor alpha (TNF‐α) [SMD = −16.83; CIs (−22.63, −11.02); p = 0.00].ConclusionWe showed that poly I:C is neuroprotective and acts via the TLR3/NF‐κB/TNF‐α pathway. Our review indicated that suppressing TLR 2/4 may illicit neuroprotection against CI. Further research on simultaneous activation of TLR3 with poly I:C and suppression of TLR 2/4 might open new vistas for the development of therapeutics against CI.     

Brain opioid segments and striatal patterns of dopamine release induced by naloxone and morphine

Opioid receptors are expressed throughout the brain and play a major role in regulating striatal dopamine (DA) release. Clinical studies have shown that naloxone (NAL, a nonspecific opioid antagonist) in individuals with opioid use disorder and morphine (MRP, a nonspecific opioid agonist) in healthy controls, resulted in DA release in the dorsal and ventral striatum, respectively. It is not known whether the underlying patterns of striatal DA release are associated with the striatal distribution of opioid receptors. We leveraged previously published PET datasets (collected in independent cohorts) to study the brain‐wide distribution of opioid receptors and to compare striatal opioid receptor availability with striatal DA release patterns. We identified three major gray matter segments based on availability maps of DA and opioid receptors: striatum, and primary and secondary opioid segments with high and intermediate opioid receptor availability, respectively. Patterns of DA release induced by NAL and MRP were inversely associated and correlated with kappa (NAL: r(68) = −0.81, MRP: r(68) = 0.54), and mu (NAL: r(68) = −0.62, MRP: r(68) = 0.46) opioid receptor availability. Kappa opioid receptor availability accounted for a unique part of variance in NAL‐ and MRP‐DA release patterns (ΔR ² >0.14, p <.0001). In sum, distributions of opioid receptors distinguished major cortical and subcortical regions. Patterns of NAL‐ and MRP‐induced DA release had inverse associations with striatal opioid receptor availability. Our approach provides a pattern‐based characterization of drug‐induced DA targets and is relevant for modeling the role of opioid receptors in modulating striatal DA release.     

Financial decision‐making and self‐awareness for financial decision‐making is associated with white matter integrity in older adults

Financial decision‐making (FDM) and awareness of the integrity of one''s FDM abilities (or financial awareness) are both critical for preventing financial mistakes. We examined the white matter correlates of these constructs and hypothesized that the tracts connecting the temporal–frontal regions would be most strongly correlated with both FDM and financial awareness. Overall, 49 healthy older adults were included in the FDM analysis and 44 in the financial awareness analyses. The Objective Financial Competency Assessment Inventory was used to measure FDM. Financial awareness was measured by integrating metacognitive ratings into this inventory and was calculated as the degree of overconfidence or underconfidence. Diffusion tensor imaging data were processed with Tracts Constrained by Underlying Anatomy distributed as part of the FreeSurfer analytic suite, which produced average measures of fractional anisotropy and mean diffusivity in 18 white matter tracts along with the overall tract average. As expected, FDM showed the strongest negative associations with average mean diffusivity measure of the superior longitudinal fasciculus ‐temporal (SLFT; r = −.360, p = .011) and ‐parietal (r = −.351, p = .014) tracts. After adjusting for FDM, only the association between financial awareness and average mean diffusivity measure of the right SLFT (r = .310, p = .046) was significant. Overlapping white matter tracts were involved in both FDM and financial awareness. More importantly, these preliminary findings reinforce emerging literature on a unique role of right hemisphere temporal connections in supporting financial awareness.     

Intracranial and subcortical volumes in adolescents with early‐onset psychosis: A multisite mega‐analysis from the ENIGMA consortium

Early‐onset psychosis disorders are serious mental disorders arising before the age of 18 years. Here, we investigate the largest neuroimaging dataset, to date, of patients with early‐onset psychosis and healthy controls for differences in intracranial and subcortical brain volumes. The sample included 263 patients with early‐onset psychosis (mean age: 16.4 ± 1.4 years, mean illness duration: 1.5 ± 1.4 years, 39.2% female) and 359 healthy controls (mean age: 15.9 ± 1.7 years, 45.4% female) with magnetic resonance imaging data, pooled from 11 clinical cohorts. Patients were diagnosed with early‐onset schizophrenia (n = 183), affective psychosis (n = 39), or other psychotic disorders (n = 41). We used linear mixed‐effects models to investigate differences in intracranial and subcortical volumes across the patient sample, diagnostic subgroup and antipsychotic medication, relative to controls. We observed significantly lower intracranial (Cohen''s d = −0.39) and hippocampal (d = −0.25) volumes, and higher caudate (d = 0.25) and pallidum (d = 0.24) volumes in patients relative to controls. Intracranial volume was lower in both early‐onset schizophrenia (d = −0.34) and affective psychosis (d = −0.42), and early‐onset schizophrenia showed lower hippocampal (d = −0.24) and higher pallidum (d = 0.29) volumes. Patients who were currently treated with antipsychotic medication (n = 193) had significantly lower intracranial volume (d = −0.42). The findings demonstrate a similar pattern of brain alterations in early‐onset psychosis as previously reported in adult psychosis, but with notably low intracranial volume. The low intracranial volume suggests disrupted neurodevelopment in adolescent early‐onset psychosis.     

Identifying a whole‐brain connectome‐based model in drug‐naïve Parkinson's disease for predicting motor impairment

Identifying a whole‐brain connectome‐based predictive model in drug‐naïve patients with Parkinson''s disease and verifying its predictions on drug‐managed patients would be useful in determining the intrinsic functional underpinnings of motor impairment and establishing general brain–behavior associations. In this study, we constructed a predictive model from the resting‐state functional data of 47 drug‐naïve patients by using a connectome‐based approach. This model was subsequently validated in 115 drug‐managed patients. The severity of motor impairment was assessed by calculating Unified Parkinson''s Disease Rating Scale Part III scores. The predictive performance of model was evaluated using the correlation coefficient (r _true) between predicted and observed scores. As a result, a connectome‐based model for predicting individual motor impairment in drug‐naïve patients was identified with significant performance (r _true = .845, p < .001, p _permu = .002). Two patterns of connection were identified according to correlations between connection strength and the severity of motor impairment. The negative motor‐impairment‐related network contained more within‐network connections in the motor, visual‐related, and default mode networks, whereas the positive motor‐impairment‐related network was constructed mostly with between‐network connections coupling the motor‐visual, motor‐limbic, and motor‐basal ganglia networks. Finally, this predictive model constructed around drug‐naïve patients was confirmed with significant predictive efficacy on drug‐managed patients (r = .209, p = .025), suggesting a generalizability in Parkinson''s disease patients under long‐term drug influence. In conclusion, this study identified a whole‐brain connectome‐based model that could predict the severity of motor impairment in Parkinson''s patients and furthers our understanding of the functional underpinnings of the disease.     

In vivo hippocampal subfield volumes in bipolar disorder—A mega‐analysis from The Enhancing Neuro Imaging Genetics through Meta‐Analysis Bipolar Disorder Working Group

The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta‐Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1‐weighted magnetic resonance imaging scans from 4,698 individuals (BD = 1,472, healthy controls [HC] = 3,226) from 23 sites worldwide were processed with FreeSurfer. We used linear mixed‐effects models and mega‐analysis to investigate differences in hippocampal subfield volumes between BD and HC, followed by analyses of clinical characteristics and medication use. BD showed significantly smaller volumes of the whole hippocampus (Cohen''s d = −0.20), cornu ammonis (CA)1 (d = −0.18), CA2/3 (d = −0.11), CA4 (d = −0.19), molecular layer (d = −0.21), granule cell layer of dentate gyrus (d = −0.21), hippocampal tail (d = −0.10), subiculum (d = −0.15), presubiculum (d = −0.18), and hippocampal amygdala transition area (d = −0.17) compared to HC. Lithium users did not show volume differences compared to HC, while non‐users did. Antipsychotics or antiepileptic use was associated with smaller volumes. In this largest study of hippocampal subfields in BD to date, we show widespread reductions in nine of 12 subfields studied. The associations were modulated by medication use and specifically the lack of differences between lithium users and HC supports a possible protective role of lithium in BD.     

The additive impact of cardio‐metabolic disorders and psychiatric illnesses on accelerated brain aging

Severe mental illnesses (SMI) including major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia spectrum disorder (SSD) elevate accelerated brain aging risks. Cardio‐metabolic disorders (CMD) are common comorbidities in SMI and negatively impact brain health. We validated a linear quantile regression index (QRI) approach against the machine learning “BrainAge” index in an independent SSD cohort (N = 206). We tested the direct and additive effects of SMI and CMD effects on accelerated brain aging in the N = 1,618 (604 M/1,014 F, average age = 63.53 ± 7.38) subjects with SMI and N = 11,849 (5,719 M/6,130 F; 64.42 ± 7.38) controls from the UK Biobank. Subjects were subdivided based on diagnostic status: SMI+/CMD+ (N = 665), SMI+/CMD− (N = 964), SMI−/CMD+ (N = 3,765), SMI−/CMD− (N = 8,083). SMI (F = 40.47, p = 2.06 × 10⁻¹⁰) and CMD (F = 24.69, p = 6.82 × 10⁻⁷) significantly, independently impacted whole‐brain QRI in SMI+. SSD had the largest effect (Cohen’s d = 1.42) then BD (d = 0.55), and MDD (d = 0.15). Hypertension had a significant effect on SMI+ (d = 0.19) and SMI− (d = 0.14). SMI effects were direct, independent of MD, and remained significant after correcting for effects of antipsychotic medications. Whole‐brain QRI was significantly (p < 10⁻¹⁶) associated with the volume of white matter hyperintensities (WMH). However, WMH did not show significant association with SMI and was driven by CMD, chiefly hypertension (p < 10⁻¹⁶). We used a simple and robust index, QRI, the demonstrate additive effect of SMI and CMD on accelerated brain aging. We showed a greater effect of psychiatric illnesses on QRI compared to cardio‐metabolic illness. Our findings suggest that subjects with SMI should be among the targets for interventions to protect against age‐related cognitive decline.     

Abnormal brain functional network dynamics in obsessive–compulsive disorder patients and their unaffected first‐degree relatives

We utilized dynamic functional network connectivity (dFNC) analysis to compare participants with obsessive–compulsive disorder (OCD) with their unaffected first‐degree relative (UFDR) and healthy controls (HC). Resting state fMRI was performed on 46 OCD, 24 UFDR, and 49 HCs, along with clinical assessments. dFNC analyses revealed two distinct connectivity states: a less frequent, integrated state characterized by the predominance of between‐network connections (State I), and a more frequent, segregated state with strong within‐network connections (State II). OCD patients spent more time in State II and less time in State I than HC, as measured by fractional windows and mean dwell time. Time in each state for the UFDR were intermediate between OCD patients and HC. Within the OCD group, fractional windows of time spent in State I was positively correlated with OCD symptoms (as measured by the obsessive compulsive inventory‐revised [OCI‐R], r = .343, p<.05, FDR correction) and time in State II was negatively correlated with symptoms (r = −.343, p<.05, FDR correction). Within each state we also examined connectivity within and between established intrinsic connectivity networks, and found that UFDR were similar to the OCD group in State I, but more similar to the HC groups in State II. The similarities between OCD and UFDR groups in temporal properties and State I connectivity indicate that these features may reflect the endophenotype for OCD. These results indicate that the temporal dynamics of functional connectivity could be a useful biomarker to identify those at risk.     

The regional effect of serum hormone levels on cerebral blood flow in healthy nonpregnant women

Sex hormones estrogen (EST) and progesterone (PROG) have received increased attention for their important physiological action outside of reproduction. While studies have shown that EST and PROG have significant impacts on brain function, their impact on the cerebrovascular system in humans remains largely unknown. To address this, we used a multi‐modal magnetic resonance imaging (MRI) approach to investigate the link between serum hormones in the follicular phase and luteal phase of the menstrual cycle (MC) with measures of cerebrovascular function (cerebral blood flow [CBF]) and structure (intracranial artery diameter). Fourteen naturally cycling women were recruited and assessed at two‐time points of their MC. CBF was derived from pseudo‐continuous arterial spin labeling while diameters of the internal carotid and basilar artery was assessed using time of flight magnetic resonance angiography, blood samples were performed after the MRI. Results show that PROG and EST had opposing and spatially distinct effects on CBF: PROG correlated negatively with CBF in anterior brain regions (r = −.86, p < .01), while EST correlations were positive, yet weak and most prominent in posterior areas (r = .78, p < .01). No significant correlations between either hormone or intracranial artery diameter were observed. These results show that EST and PROG have opposing and regionally distinct effects on CBF and that this relationship is likely not due to interactions with large intracranial arteries. Considering that CBF in healthy women appears tightly linked to their current hormonal state, future studies should consider assessing MC‐related hormone fluctuations in the design of functional MRI studies in this population.     

Loss of long‐term benefit from VIM‐DBS in essential tremor: A secondary analysis of repeated measurements

AimsDeep brain stimulation (DBS) in the ventral intermediate nucleus (Vim‐DBS) is the preferred surgical therapy for essential tremor (ET). Tolerance and disease progression are considered to be the two main reasons underlying the loss of long‐term efficacy of Vim‐DBS. This study aimed to explore whether Vim‐DBS shows long‐term loss of efficacy and to evaluate the reasons for this diminished efficacy from different aspects.MethodsIn a repeated‐measures meta‐analysis of 533 patients from 18 studies, Vim‐DBS efficacy was evaluated at ≤6 months, 7–12 months, 1–3 years, and ≥4 years. The primary outcomes were the score changes in different components of the Fahn‐Tolosa‐Marin Tremor Rating Scale (TRS; total score, motor score, hand‐function score, and activities of daily living [ADL] score). Secondary outcomes were the long‐term predictive factors.ResultsThe TRS total, motor, and ADL scores showed significant deterioration with disease progression (p = 0.002, p = 0.047, and p < 0.001, respectively), while the TRS total (p < 0.001), hand‐function (p = 0.036), and ADL (p = 0.004) scores indicated a significant long‐term reduction in DBS efficacy, although the motor subscore indicated no loss of efficacy. Hand‐function (p < 0.001) and ADL (p = 0.028) scores indicated DBS tolerance, while the TRS total and motor scores did not. Stimulation frequency and preoperative score were predictive factors for long‐term results.ConclusionThis study provides level 3a evidence that long‐term Vim‐DBS is effective in controlling motor symptoms without waning benefits. The efficacy reduction for hand function was caused by DBS tolerance, while that for ADL was caused by DBS tolerance and disease progression. More attention should be given to actual functional recovery rather than changes in motor scores in patients with ET.     

Pre‐supplementary motor network connectivity and clinical outcome of magnetic stimulation in obsessive–compulsive disorder

A large proportion of patients with obsessive–compulsive disorder (OCD) respond unsatisfactorily to pharmacological and psychological treatments. An alternative novel treatment for these patients is repetitive transcranial magnetic stimulation (rTMS). This study aimed to investigate the underlying neural mechanism of rTMS treatment in OCD patients. A total of 37 patients with OCD were randomized to receive real or sham 1‐Hz rTMS (14 days, 30 min/day) over the right pre‐supplementary motor area (preSMA). Resting‐state functional magnetic resonance imaging data were collected before and after rTMS treatment. The individualized target was defined by a personalized functional connectivity map of the subthalamic nucleus. After treatment, patients in the real group showed a better improvement in the Yale–Brown Obsessive Compulsive Scale than the sham group (F _1,35 = 6.0, p = .019). To show the neural mechanism involved, we identified an “ideal target connectivity” before treatment. Leave‐one‐out cross‐validation indicated that this connectivity pattern can significantly predict patients'' symptom improvements (r = .60, p = .009). After real treatment, the average connectivity strength of the target network significantly decreased in the real but not in the sham group. This network‐level change was cross‐validated in three independent datasets. Altogether, these findings suggest that personalized magnetic stimulation on preSMA may alleviate obsessive–compulsive symptoms by decreasing the connectivity strength of the target network.     

Immunotherapy choice and maintenance for generalized myasthenia gravis in China

AimsTo compare long‐term efficacy and safety of immunotherapeutic strategies as maintenance to prevent disease relapses of generalized myasthenia gravis (MG) in real‐world settings.MethodsThis is a retrospective cohort study on generalized MG conducted in seven major neurological centers across China. Eligible participants were patients with generalized MG who were under minimal manifestation status or better. Main outcome measures were probability of patients free of relapses and causes of drug discontinuation.ResultsAmong 1064 patients enrolled, the median (interquartile range) age was 50.3 (37.0‐62.5) years and 641 (60.2%) were women. Disease relapse was significantly lower for rituximab (6.1%) compared with all the other monotherapies (hazard ratio [HR] = 0.18, 95% confidence interval [CI] 0.06 to 0.56, P = .0030). As combination therapies, tacrolimus in combination with corticosteroids reduced risk of disease relapses compared with azathioprine with corticosteroids (HR = 0.45, 95% CI 0.25 to 0.81, P = .0077) or mycophenolate mofetil with corticosteroids (HR = 0.32, 95% CI 0.15 to 0.67, P = .0020). Otherwise, lower‐dose corticosteroids or azathioprine as monotherapy significantly increased risk of disease relapses (HR = 2.78, 95% CI 1.94 to 3.99, P < .0001; HR = 2.14, 95% CI 1.42 to 3.23, P = .0003, respectively). The proportion of discontinuation was lowest in patients with rituximab (20.4%) as monotherapy and tacrolimus with corticosteroids (23.6%). Overall, combination treatment of immunosuppressants with corticosteroids had a lower rate of discontinuation compared with corresponding monotherapy (HR = 0.51, 95% CI 0.36 to 0.71, P < .0001).ConclusionsRituximab as monotherapy and tacrolimus with corticosteroids displayed better clinical efficacy as well as drug maintenance to prevent disease relapses in patients with generalized MG.     

Increasing nodal vulnerability and nodal efficiency implied recovery time prolonging in patients with supplementary motor area syndrome

Supplementary motor area (SMA) syndrome is a surgery‐related complication that commonly occurs after removing SMA glioma, and needs weeks to recover. However, susceptible factors of patients suffering from SMA syndrome remain unknown. Graphic theory was applied to reveal topological properties of sensorimotor network (SMN) by processing resting‐state functional magnetic resonance images in 66 patients with SMA gliomas. Patients were classified into SMA and non‐SMA groups based on whether they suffered from SMA syndrome. We collected recovery time and used causal mediation analysis to find association between topological properties and recovery time. Compared with the non‐SMA group, higher vulnerability (left: p = .0018; right: p = .0033) and lower fault tolerance (left: p = .0022; right: p = .0248) of the whole SMN were found in the SMA group. Moreover, higher nodal properties of lesional‐hemispheric cingulate cortex (nodal efficiency: left, p = .0389; right, p = .0169; nodal vulnerability: left, p = .0185; right, p = .0085) and upper limb region of primary motor cortex (PMC; nodal efficiency: left, p = .0132; right, p = .0001; nodal vulnerability: left, p = .0091; right, p = .0209) were found in the SMA group. Nodal efficiency and nodal vulnerability of cingulate cortex and upper limb region of PMC were important predictors for SMA syndrome occurring and recovery time prolonging. Neurosurgeons should carefully deal with upper limb region of PMC and cingulate cortex, and protect them if these two region were unnecessary to damage during SMA glioma resection.     

Selective cutoff reporting in studies of the accuracy of the Patient Health Questionnaire‐9 and Edinburgh Postnatal Depression Scale: Comparison of results based on published cutoffs versus all cutoffs using individual participant data meta‐analysis

ObjectivesSelectively reported results from only well‐performing cutoffs in diagnostic accuracy studies may bias estimates in meta‐analyses. We investigated cutoff reporting patterns for the Patient Health Questionnaire‐9 (PHQ‐9; standard cutoff 10) and Edinburgh Postnatal Depression Scale (EPDS; no standard cutoff, commonly used 10–13) and compared accuracy estimates based on published cutoffs versus all cutoffs.MethodsWe conducted bivariate random effects meta‐analyses using individual participant data to compare accuracy from published versus all cutoffs.ResultsFor the PHQ‐9 (30 studies, N = 11,773), published results underestimated sensitivity for cutoffs below 10 (median difference: −0.06) and overestimated for cutoffs above 10 (median difference: 0.07). EPDS (19 studies, N = 3637) sensitivity estimates from published results were similar for cutoffs below 10 (median difference: 0.00) but higher for cutoffs above 13 (median difference: 0.14). Specificity estimates from published and all cutoffs were similar for both tools. The mean cutoff of all reported cutoffs in PHQ‐9 studies with optimal cutoff below 10 was 8.8 compared to 11.8 for those with optimal cutoffs above 10. Mean for EPDS studies with optimal cutoffs below 10 was 9.9 compared to 11.8 for those with optimal cutoffs greater than 10.ConclusionSelective cutoff reporting was more pronounced for the PHQ‐9 than EPDS.     

Deep transfer learning of structural magnetic resonance imaging fused with blood parameters improves brain age prediction

Machine learning has been applied to neuroimaging data for estimating brain age and capturing early cognitive impairment in neurodegenerative diseases. Blood parameters like neurofilament light chain are associated with aging. In order to improve brain age predictive accuracy, we constructed a model based on both brain structural magnetic resonance imaging (sMRI) and blood parameters. Healthy subjects (n = 93; 37 males; aged 50–85 years) were recruited. A deep learning network was firstly pretrained on a large set of MRI scans (n = 1,481; 659 males; aged 50–85 years) downloaded from multiple open‐source datasets, to provide weights on our recruited dataset. Evaluating the network on the recruited dataset resulted in mean absolute error (MAE) of 4.91 years and a high correlation (r = .67, p <.001) against chronological age. The sMRI data were then combined with five blood biochemical indicators including GLU, TG, TC, ApoA1 and ApoB, and 9 dementia‐associated biomarkers including ApoE genotype, HCY, NFL, TREM2, Aβ40, Aβ42, T‐tau, TIMP1, and VLDLR to construct a bilinear fusion model, which achieved a more accurate prediction of brain age (MAE, 3.96 years; r = .76, p <.001). Notably, the fusion model achieved better improvement in the group of older subjects (70–85 years). Extracted attention maps of the network showed that amygdala, pallidum, and olfactory were effective for age estimation. Mediation analysis further showed that brain structural features and blood parameters provided independent and significant impact. The constructed age prediction model may have promising potential in evaluation of brain health based on MRI and blood parameters.     

Different sensorimotor mechanism in fast and slow progression amyotrophic lateral sclerosis

The huge heterogeneity of the disease progression rate may cause inconsistent findings between local activity and functional connectivity of the primary sensorimotor area (PSMA) in amyotrophic lateral sclerosis (ALS). For illustration of this hypothesis, resting‐state fMRI (RS‐fMRI) data were collected and analyzed on 38 “definite” or “probable” ALS patients (19 fast and 19 slow, cut off median = 0.41) and 37 matched healthy controls. Amplitude of low frequency fluctuations (ALFFs) and functional connectivity strength (FCS) were analyzed within the PSMA. There was a decreased ALFF (p _FDR <.05) and FCS (p = .022) in all ALS patients. The two metrics shared about 50% of variance (R = .7) and both showed significant positive correlation with ALS Functional Rating Scale‐Revised (ALSFRS‐R) in the fast (p values <.034) but not in the slow progression groups. Interestingly, when regressing out the ALFF, the PSMA network FCS, especially the inter‐hemisphere FCS, showed negative correlation with the ALSFRS‐R score in the slow (R = −.54, p = .026) but not the fast progression group. In summary, the current results suggest that RS‐fMRI local activity and network functional connectivity accounts for the severity differently in the slow and fast progression ALS patients.     

Abnormal dynamic functional connectivity after sleep deprivation from temporal variability perspective

Sleep deprivation (SD) is very common in modern society and regarded as a potential causal mechanism of several clinical disorders. Previous neuroimaging studies have explored the neural mechanisms of SD using magnetic resonance imaging (MRI) from static (comparing two MRI sessions [one after SD and one after resting wakefulness]) and dynamic (using repeated MRI during one night of SD) perspectives. Recent SD researches have focused on the dynamic functional brain organization during the resting‐state scan. Our present study adopted a novel metric (temporal variability), which has been successfully applied to many clinical diseases, to examine the dynamic functional connectivity after SD in 55 normal young subjects. We found that sleep‐deprived subjects showed increased regional‐level temporal variability in large‐scale brain regions, and decreased regional‐level temporal variability in several thalamus subregions. After SD, participants exhibited enhanced intra‐network temporal variability in the default mode network (DMN) and increased inter‐network temporal variability in numerous subnetwork pairs. Furthermore, we found that the inter‐network temporal variability between visual network and DMN was negative related with the slowest 10% respond speed (β = −.42, p = 5.57 × 10⁻⁴) of the psychomotor vigilance test after SD following the stepwise regression analysis. In conclusion, our findings suggested that sleep‐deprived subjects showed abnormal dynamic brain functional configuration, which provides new insights into the neural underpinnings of SD and contributes to our understanding of the pathophysiology of clinical disorders.     

Brain serotonin transporter is associated with cognitive‐affective biases in healthy individuals

Cognitive affective biases describe the tendency to process negative information or positive information over the other. These biases can be modulated by changing extracellular serotonin (5‐HT) levels in the brain, for example, by pharmacologically blocking and downregulating the 5‐HT transporter (5‐HTT), which remediates negative affective bias. This suggests that higher levels of 5‐HTT are linked to a priority of negative information over positive, but this link remains to be tested in vivo in healthy individuals. We, therefore, evaluated the association between 5‐HTT levels, as measured with [¹¹C]DASB positron emission tomography (PET), and affective biases, hypothesising that higher 5‐HTT levels are associated with a more negative bias. We included 98 healthy individuals with measures of [¹¹C]DASB binding potential (BP_ND) and affective biases using The Emotional Faces Identification Task by subtracting the per cent hit rate for happy from that of sad faces (EFIT_AB). We evaluated the association between [¹¹C]DASB BP_ND and EFIT_AB in a linear latent variable model, with the latent variable (5‐HTT_LV) modelled from [¹¹C]DASB BP_ND in the fronto‐striatal and fronto‐limbic networks implicated in affective cognition. We observed an inverse association between 5‐HTT_LV and EFIT_AB (β = −8% EFIT_AB per unit 5‐HTT_LV, CI = −14% to −3%, p = .002). These findings show that higher 5‐HTT levels are linked to a more negative bias in healthy individuals. High 5‐HTT supposedly leads to high clearance of 5‐HT, and thus, a negative bias could result from low extracellular 5‐HT. Future studies must reveal if a similar inverse association exists in individuals with affective disorders.     

Cortical N‐acetylaspartate concentrations are impacted in chronic stroke but do not relate to motor impairment: A magnetic resonance spectroscopy study

Magnetic resonance spectroscopy (MRS) measures cerebral metabolite concentrations, which can inform our understanding of the neurobiological processes associated with stroke recovery. Here, we investigated whether metabolite concentrations in primary motor and somatosensory cortices (sensorimotor cortex) are impacted by stroke and relate to upper‐extremity motor impairment in 45 individuals with chronic stroke. Cerebral metabolite estimates were adjusted for cerebrospinal fluid and brain tissue composition in the MRS voxel. Upper‐extremity motor impairment was indexed with the Fugl‐Meyer (FM) scale. N‐acetylaspartate (NAA) concentration was reduced bilaterally in stroke participants with right hemisphere lesions (n = 23), relative to right‐handed healthy older adults (n = 15; p = .006). Within the entire stroke sample (n = 45) NAA and glutamate/glutamine (GLX) were lower in the ipsilesional sensorimotor cortex, relative to the contralesional cortex (NAA: p < .001; GLX: p = .003). Lower ipsilesional NAA was related to greater extent of corticospinal tract (CST) injury, quantified by a weighted CST lesion load (p = .006). Cortical NAA and GLX concentrations did not relate to the severity of chronic upper‐extremity impairment (p > .05), including after a sensitivity analysis imputing missing metabolite data for individuals with large cortical lesions (n = 5). Our results suggest that NAA, a marker of neuronal integrity, is sensitive to stroke‐related cortical damage and may provide mechanistic insights into cellular processes of cortical adaptation to stroke. However, cortical MRS metabolites may have limited clinical utility as prospective biomarkers of upper‐extremity outcomes in chronic stroke.