This scientific commentary refers to ‘Neurophysiological markers of motor compensatory mechanisms in early Parkinson’s disease’ by Passaretti et al. (https://doi.org/10.1093/brain/awae210).
{"title":"Motor compensation in Parkinson’s disease: an empirical challenge with clinical implications","authors":"Bénédicte Ballanger, Philippe Boulinguez","doi":"10.1093/brain/awae328","DOIUrl":"https://doi.org/10.1093/brain/awae328","url":null,"abstract":"This scientific commentary refers to ‘Neurophysiological markers of motor compensatory mechanisms in early Parkinson’s disease’ by Passaretti et al. (https://doi.org/10.1093/brain/awae210).","PeriodicalId":9063,"journal":{"name":"Brain","volume":null,"pages":null},"PeriodicalIF":14.5,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142444191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Asmaa Mhanna, Joel Bruss, Joseph C Griffis, Alyssa W Sullivan, Hiroto Kawasaki, Jeffrey Binder, Sara B Pillay, Matthew A Howard, Daniel Tranel, Aaron D Boes
Temporal lobe (TL) epilepsy surgery is an effective treatment option for patients with drug-resistant epilepsy. However, neurosurgery poses a risk for cognitive deficits - up to one third of patients have a decline in naming ability following TL surgery. In this study, we aimed to better understand the neural correlates associated with reduced naming performance after TL surgery, with the goal of informing surgical planning strategies to mitigate the risk of dysnomia. We retrospectively identified 85 patients who underwent temporal lobe (TL) resective surgery (49 left TL, 36 right TL) for whom naming ability was assessed before and >3 months post-surgery using the Boston Naming Test (BNT). We used multivariate lesion-symptom mapping to identify resection sites associated with naming decline, and we used lesion-network mapping to evaluate the broader functional and structural connectivity profiles of resection sites associated with naming decline. We validated our findings in an independent cohort of 59 individuals with left temporal lobectomy, along with repeating all analyses after combining the cohorts. Lesion laterality and location were important predictors of post-surgical naming performance. Naming performance significantly improved after right temporal lobectomy (P = 0.015) while a decrement in performance was observed following left temporal lobectomy (P = 0.002). Declines in naming performance were associated with surgical resection of the left anterior middle temporal gyrus (Brodmann area 21, r =0.41, P = <.001), along with a previously implicated basal temporal language area. Resection sites linked to naming decline showed a functional connectivity profile featuring a left-lateralized network closely resembling the extended semantic default mode network, and a structural connectivity profile featuring major temporo-frontal association white matter tracts coursing through the temporal stem. This extends prior work by implicating the left anterior middle temporal gyrus in naming decline and provides additional support for the role of the previously identified basal temporal language area in naming decline. Importantly, the structural and functional connectivity profiles of these regions suggest they are key nodes of a broader extended semantic network. Together these regional and network findings may help in surgical planning and discussions of prognosis.
{"title":"Lesion and lesion network localization of dysnomia after epilepsy surgery","authors":"Asmaa Mhanna, Joel Bruss, Joseph C Griffis, Alyssa W Sullivan, Hiroto Kawasaki, Jeffrey Binder, Sara B Pillay, Matthew A Howard, Daniel Tranel, Aaron D Boes","doi":"10.1093/brain/awae322","DOIUrl":"https://doi.org/10.1093/brain/awae322","url":null,"abstract":"Temporal lobe (TL) epilepsy surgery is an effective treatment option for patients with drug-resistant epilepsy. However, neurosurgery poses a risk for cognitive deficits - up to one third of patients have a decline in naming ability following TL surgery. In this study, we aimed to better understand the neural correlates associated with reduced naming performance after TL surgery, with the goal of informing surgical planning strategies to mitigate the risk of dysnomia. We retrospectively identified 85 patients who underwent temporal lobe (TL) resective surgery (49 left TL, 36 right TL) for whom naming ability was assessed before and &gt;3 months post-surgery using the Boston Naming Test (BNT). We used multivariate lesion-symptom mapping to identify resection sites associated with naming decline, and we used lesion-network mapping to evaluate the broader functional and structural connectivity profiles of resection sites associated with naming decline. We validated our findings in an independent cohort of 59 individuals with left temporal lobectomy, along with repeating all analyses after combining the cohorts. Lesion laterality and location were important predictors of post-surgical naming performance. Naming performance significantly improved after right temporal lobectomy (P = 0.015) while a decrement in performance was observed following left temporal lobectomy (P = 0.002). Declines in naming performance were associated with surgical resection of the left anterior middle temporal gyrus (Brodmann area 21, r =0.41, P = &lt;.001), along with a previously implicated basal temporal language area. Resection sites linked to naming decline showed a functional connectivity profile featuring a left-lateralized network closely resembling the extended semantic default mode network, and a structural connectivity profile featuring major temporo-frontal association white matter tracts coursing through the temporal stem. This extends prior work by implicating the left anterior middle temporal gyrus in naming decline and provides additional support for the role of the previously identified basal temporal language area in naming decline. Importantly, the structural and functional connectivity profiles of these regions suggest they are key nodes of a broader extended semantic network. Together these regional and network findings may help in surgical planning and discussions of prognosis.","PeriodicalId":9063,"journal":{"name":"Brain","volume":null,"pages":null},"PeriodicalIF":14.5,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142449592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hereditary optic neuropathies (HON) are a group of diseases due to genetic defects either in mitochondria or in nuclear genomes. The increasing availability of genetic testing has expanded a broader genetic and phenotypic spectrum of HON than previously recognized. To provide systematic insight into the genetic and phenotypic landscape of HON attributed to 50 nuclear genes, we conducted genetic analysis on part of 4776 index patients with clinical diagnosis of HON following our previous study on 1516 probands with Leber hereditary optic neuropathy (LHON) and mitochondrial DNA variants. Exome sequencing was performed in 473 patients diagnosed with nuclear gene-related HON (nHON) and 353 cases with unsolved LHON. Sequencing and variant interpretation in 50 causative nuclear genes indicated that the diagnostic yield of exome sequencing for nHON was 31.50% (149/473), while it was markedly lower at 1.42% (5/353) for LHON patients without primary mtDNA mutations. The top five implicated genes causing nHON in our in-house cohort, OPA1, WFS1, FDXR, ACO2, and AFG3L2, account for 82.46% of mutations. Although OPA1 was the most prevalent causative gene of nHON in both our cohort (53.25%) and literature review (37.09%), the prevalence of OPA1, WFS1, and FDXR differed significantly between our in-house cohort and the literature review (P-adjusted<0.001). Fundus changes in nHON could be stratified into three categories, the most common is optic atrophy at the examination (78.79%), the rarest is LHON-like optic atrophy (3.64%), and the intermediate is optic atrophy with concurrent retinal degeneration (17.57%), which was an independent risk factor for visual prognosis in nHON. A systematic genotype-phenotype analysis highlighted different genetic contributions for ocular, extraocular neurological, and extraocular non-neurological phenotypes. In addition, systemic variant analysis at the individual gene level suggested a revised interpretation of the pathogenicity of a WFS1 heterozygous truncation variant. This study provides a panoramic summary of both the genetic and phenotypic profiles of HON in real-world studies and literature. The category for nHON fundus phenotypes is built for future studies on molecular mechanisms underlying HON and targeted therapies. In addition to routine ophthalmic examinations, careful examination of the extraocular symptoms and meaningful genetic counseling are warranted for patients with nHON.
{"title":"Clinical and genetic landscape of optic atrophy in 826 families: insights from 50 nuclear genes","authors":"Yuxi Zheng, Panfeng Wang, Shiqiang Li, Yuxi Long, Yi Jiang, Dongwei Guo, Xiaoyun Jia, Mengchu Liu, Yiyan Zeng, Xueshan Xiao, J Fielding Hejtmancik, Qingjiong Zhang, Wenmin Sun","doi":"10.1093/brain/awae324","DOIUrl":"https://doi.org/10.1093/brain/awae324","url":null,"abstract":"Hereditary optic neuropathies (HON) are a group of diseases due to genetic defects either in mitochondria or in nuclear genomes. The increasing availability of genetic testing has expanded a broader genetic and phenotypic spectrum of HON than previously recognized. To provide systematic insight into the genetic and phenotypic landscape of HON attributed to 50 nuclear genes, we conducted genetic analysis on part of 4776 index patients with clinical diagnosis of HON following our previous study on 1516 probands with Leber hereditary optic neuropathy (LHON) and mitochondrial DNA variants. Exome sequencing was performed in 473 patients diagnosed with nuclear gene-related HON (nHON) and 353 cases with unsolved LHON. Sequencing and variant interpretation in 50 causative nuclear genes indicated that the diagnostic yield of exome sequencing for nHON was 31.50% (149/473), while it was markedly lower at 1.42% (5/353) for LHON patients without primary mtDNA mutations. The top five implicated genes causing nHON in our in-house cohort, OPA1, WFS1, FDXR, ACO2, and AFG3L2, account for 82.46% of mutations. Although OPA1 was the most prevalent causative gene of nHON in both our cohort (53.25%) and literature review (37.09%), the prevalence of OPA1, WFS1, and FDXR differed significantly between our in-house cohort and the literature review (P-adjusted&lt;0.001). Fundus changes in nHON could be stratified into three categories, the most common is optic atrophy at the examination (78.79%), the rarest is LHON-like optic atrophy (3.64%), and the intermediate is optic atrophy with concurrent retinal degeneration (17.57%), which was an independent risk factor for visual prognosis in nHON. A systematic genotype-phenotype analysis highlighted different genetic contributions for ocular, extraocular neurological, and extraocular non-neurological phenotypes. In addition, systemic variant analysis at the individual gene level suggested a revised interpretation of the pathogenicity of a WFS1 heterozygous truncation variant. This study provides a panoramic summary of both the genetic and phenotypic profiles of HON in real-world studies and literature. The category for nHON fundus phenotypes is built for future studies on molecular mechanisms underlying HON and targeted therapies. In addition to routine ophthalmic examinations, careful examination of the extraocular symptoms and meaningful genetic counseling are warranted for patients with nHON.","PeriodicalId":9063,"journal":{"name":"Brain","volume":null,"pages":null},"PeriodicalIF":14.5,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142449593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gabor G Kovacs,Yuriko Katsumata,Xian Wu,Khine Zin Aung,David W Fardo,Shelley L Forrest,,Peter T Nelson
Different subsets of Alzheimer's disease neuropathologic change (ADNC), including the intriguing set of individuals with severe/widespread Aβ plaques but no/mild tau tangles (Aβ-predominant ADNC, or AP-ADNC), may have distinct genetic and clinical features. Analyzing National Alzheimer's Coordinating Center data, we stratified 1,187 participants into AP-ADNC (n = 95), low Braak primary age related tauopathy (PART; n = 185), typical-ADNC (n = 832), and high-Braak PART (n = 75). AP-ADNC differed in some clinical features and genetic polymorphisms in the APOE, SNX1, WNT3/MAPT, and IGH genes. We conclude that AP-ADNC differs from classical ADNC with implications for in vivo studies.
{"title":"Amyloid-β predominant Alzheimer's disease neuropathologic change.","authors":"Gabor G Kovacs,Yuriko Katsumata,Xian Wu,Khine Zin Aung,David W Fardo,Shelley L Forrest,,Peter T Nelson","doi":"10.1093/brain/awae325","DOIUrl":"https://doi.org/10.1093/brain/awae325","url":null,"abstract":"Different subsets of Alzheimer's disease neuropathologic change (ADNC), including the intriguing set of individuals with severe/widespread Aβ plaques but no/mild tau tangles (Aβ-predominant ADNC, or AP-ADNC), may have distinct genetic and clinical features. Analyzing National Alzheimer's Coordinating Center data, we stratified 1,187 participants into AP-ADNC (n = 95), low Braak primary age related tauopathy (PART; n = 185), typical-ADNC (n = 832), and high-Braak PART (n = 75). AP-ADNC differed in some clinical features and genetic polymorphisms in the APOE, SNX1, WNT3/MAPT, and IGH genes. We conclude that AP-ADNC differs from classical ADNC with implications for in vivo studies.","PeriodicalId":9063,"journal":{"name":"Brain","volume":null,"pages":null},"PeriodicalIF":14.5,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142447950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jan H Magielski,Sarah M Ruggiero,Julie Xian,Shridhar Parthasarathy,Peter D Galer,Shiva Ganesan,Amanda Back,Jillian L McKee,Ian McSalley,Alexander K Gonzalez,Angela Morgan,Joseph Donaher,Ingo Helbig
Speech and language disorders are known to have a substantial genetic contribution. Although frequently examined as components of other conditions, research on the genetic basis of linguistic differences as separate phenotypic subgroups has been limited so far. Here, we performed an in-depth characterization of speech and language disorders in 52 143 individuals, reconstructing clinical histories using a large-scale data-mining approach of the electronic medical records from an entire large paediatric healthcare network. The reported frequency of these disorders was the highest between 2 and 5 years old and spanned a spectrum of 26 broad speech and language diagnoses. We used natural language processing to assess the degree to which clinical diagnoses in full-text notes were reflected in ICD-10 diagnosis codes. We found that aphasia and speech apraxia could be retrieved easily through ICD-10 diagnosis codes, whereas stuttering as a speech phenotype was coded in only 12% of individuals through appropriate ICD-10 codes. We found significant comorbidity of speech and language disorders in neurodevelopmental conditions (30.31%) and, to a lesser degree, with epilepsies (6.07%) and movement disorders (2.05%). The most common genetic disorders retrievable in our analysis of electronic medical records were STXBP1 (n = 21), PTEN (n = 20) and CACNA1A (n = 18). When assessing associations of genetic diagnoses with specific linguistic phenotypes, we observed associations of STXBP1 and aphasia (P = 8.57 × 10-7, 95% confidence interval = 18.62-130.39) and MYO7A with speech and language development delay attributable to hearing loss (P = 1.24 × 10-5, 95% confidence interval = 17.46-infinity). Finally, in a sub-cohort of 726 individuals with whole-exome sequencing data, we identified an enrichment of rare variants in neuronal receptor pathways, in addition to associations of UQCRC1 and KIF17 with expressive aphasia, MROH8 and BCHE with poor speech, and USP37, SLC22A9 and UMODL1 with aphasia. In summary, our study outlines the landscape of paediatric speech and language disorders, confirming the phenotypic complexity of linguistic traits and novel genotype-phenotype associations. Subgroups of paediatric speech and language disorders differ significantly with respect to the composition of monogenic aetiologies.
{"title":"The clinical and genetic spectrum of paediatric speech and language disorders.","authors":"Jan H Magielski,Sarah M Ruggiero,Julie Xian,Shridhar Parthasarathy,Peter D Galer,Shiva Ganesan,Amanda Back,Jillian L McKee,Ian McSalley,Alexander K Gonzalez,Angela Morgan,Joseph Donaher,Ingo Helbig","doi":"10.1093/brain/awae264","DOIUrl":"https://doi.org/10.1093/brain/awae264","url":null,"abstract":"Speech and language disorders are known to have a substantial genetic contribution. Although frequently examined as components of other conditions, research on the genetic basis of linguistic differences as separate phenotypic subgroups has been limited so far. Here, we performed an in-depth characterization of speech and language disorders in 52 143 individuals, reconstructing clinical histories using a large-scale data-mining approach of the electronic medical records from an entire large paediatric healthcare network. The reported frequency of these disorders was the highest between 2 and 5 years old and spanned a spectrum of 26 broad speech and language diagnoses. We used natural language processing to assess the degree to which clinical diagnoses in full-text notes were reflected in ICD-10 diagnosis codes. We found that aphasia and speech apraxia could be retrieved easily through ICD-10 diagnosis codes, whereas stuttering as a speech phenotype was coded in only 12% of individuals through appropriate ICD-10 codes. We found significant comorbidity of speech and language disorders in neurodevelopmental conditions (30.31%) and, to a lesser degree, with epilepsies (6.07%) and movement disorders (2.05%). The most common genetic disorders retrievable in our analysis of electronic medical records were STXBP1 (n = 21), PTEN (n = 20) and CACNA1A (n = 18). When assessing associations of genetic diagnoses with specific linguistic phenotypes, we observed associations of STXBP1 and aphasia (P = 8.57 × 10-7, 95% confidence interval = 18.62-130.39) and MYO7A with speech and language development delay attributable to hearing loss (P = 1.24 × 10-5, 95% confidence interval = 17.46-infinity). Finally, in a sub-cohort of 726 individuals with whole-exome sequencing data, we identified an enrichment of rare variants in neuronal receptor pathways, in addition to associations of UQCRC1 and KIF17 with expressive aphasia, MROH8 and BCHE with poor speech, and USP37, SLC22A9 and UMODL1 with aphasia. In summary, our study outlines the landscape of paediatric speech and language disorders, confirming the phenotypic complexity of linguistic traits and novel genotype-phenotype associations. Subgroups of paediatric speech and language disorders differ significantly with respect to the composition of monogenic aetiologies.","PeriodicalId":9063,"journal":{"name":"Brain","volume":null,"pages":null},"PeriodicalIF":14.5,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yuta Katsumi, Inola A Howe, Ryan Eckbo, Bonnie Wong, Megan Quimby, Daisy Hochberg, Scott M McGinnis, Deepti Putcha, David A Wolk, Alexandra Touroutoglou, Bradford C Dickerson
Identifying individuals with early-stage Alzheimer’s disease (AD) at greater risk of steeper clinical decline would enable better-informed medical, support, and life planning decisions. Despite accumulating evidence on the clinical prognostic value of tau positron emission tomography (PET) in typical late-onset amnestic AD, its utility in predicting clinical decline in individuals with atypical forms of AD remains unclear. Across heterogeneous clinical phenotypes, patients with atypical AD consistently exhibit abnormal tau accumulation in the posterior nodes of the default mode network of the cerebral cortex. This evidence suggests that tau burden in this functional network could be a common imaging biomarker for prognostication across the syndromic spectrum of AD. Here, we examined the relationship between baseline tau PET signal and the rate of subsequent clinical decline in a sample of 48 A+/T+/N+ patients with mild cognitive impairment or mild dementia due to AD with atypical clinical phenotypes: Posterior Cortical Atrophy (n = 16), logopenic variant Primary Progressive Aphasia (n = 15), and amnestic syndrome with multi-domain impairment and young age of onset < 65 years (n = 17). All patients underwent magnetic resonance imaging (MRI), tau PET, and amyloid PET scans at baseline. Each patient’s longitudinal clinical decline was assessed by calculating the annualized change in the Clinical Dementia Rating Sum-of-Boxes (CDR-SB) scores from baseline to follow-up (mean time interval = 14.55 ± 3.97 months). Atypical early AD patients showed an increase in CDR-SB by 1.18 ± 1.25 points per year: t(47) = 6.56, p < .001, Cohen’s d = 0.95. Across clinical phenotypes, baseline tau in the default mode network was the strongest predictor of clinical decline (R2 = .30), outperforming a simpler model with baseline clinical impairment and demographic variables (R2 = .10), tau in other functional networks (R2 = .11-.26), and the magnitude of cortical atrophy (R2 = .20) and amyloid burden (R2 = .09) in the default mode network. Overall, these findings point to the contribution of default mode network tau to predicting the magnitude of clinical decline in atypical early AD patients one year later. This simple measure could aid the development of a personalized prognostic, monitoring, and treatment plan, which would help clinicians not only predict the natural evolution of the disease but also estimate the effect of disease-modifying therapies on slowing subsequent clinical decline given the patient’s tau burden while still early in the disease course.
早期阿尔茨海默病（AD）患者的临床衰退风险较高，如果能识别出这些患者，就能做出更明智的医疗、支持和生活规划决策。尽管有越来越多的证据表明，tau 正电子发射断层扫描（PET）对典型的晚发性失忆性阿尔茨海默病具有临床预后价值，但它在预测非典型阿尔茨海默病患者临床衰退方面的作用仍不明确。在各种不同的临床表型中，非典型AD患者在大脑皮层默认模式网络的后部节点始终表现出异常的tau堆积。这些证据表明，这一功能网络中的 tau 负荷可能是一种常见的影像生物标志物，可用于 AD 综合征谱系的预后判断。在这里，我们研究了48例A+/T+/N+轻度认知障碍或轻度痴呆患者的基线tau PET信号与随后临床衰退速度之间的关系：后皮质萎缩症（16 例）、对数开放变异型原发性进行性失语症（15 例）和伴有多领域损害和年轻发病年龄 < 65 岁的失忆综合征（17 例）。所有患者都在基线时接受了磁共振成像（MRI）、tau PET和淀粉样蛋白PET扫描。通过计算从基线到随访期间（平均时间间隔 = 14.55 ± 3.97 个月）临床痴呆评分总和（CDR-SB）分数的年化变化，评估每位患者的纵向临床衰退情况。非典型早期AD患者的CDR-SB每年增加1.18 ± 1.25分：t(47) = 6.56, p < .001, Cohen's d = 0.95。在所有临床表型中，默认模式网络中的基线tau是临床衰退的最强预测因子（R2 = .30），优于包含基线临床损害和人口统计学变量（R2 = .10）、其他功能网络中的tau（R2 = .11-.26）以及默认模式网络中皮质萎缩（R2 = .20）和淀粉样蛋白负荷（R2 = .09）的简单模型。总之，这些发现表明默认模式网络tau有助于预测非典型早期AD患者一年后临床衰退的程度。这种简单的测量方法有助于制定个性化的预后、监测和治疗计划，不仅能帮助临床医生预测疾病的自然演变，还能根据患者在病程早期的 tau 负担，估计疾病调整疗法对减缓后续临床衰退的效果。
{"title":"Default mode network tau predicts future clinical decline in atypical early Alzheimer’s disease","authors":"Yuta Katsumi, Inola A Howe, Ryan Eckbo, Bonnie Wong, Megan Quimby, Daisy Hochberg, Scott M McGinnis, Deepti Putcha, David A Wolk, Alexandra Touroutoglou, Bradford C Dickerson","doi":"10.1093/brain/awae327","DOIUrl":"https://doi.org/10.1093/brain/awae327","url":null,"abstract":"Identifying individuals with early-stage Alzheimer’s disease (AD) at greater risk of steeper clinical decline would enable better-informed medical, support, and life planning decisions. Despite accumulating evidence on the clinical prognostic value of tau positron emission tomography (PET) in typical late-onset amnestic AD, its utility in predicting clinical decline in individuals with atypical forms of AD remains unclear. Across heterogeneous clinical phenotypes, patients with atypical AD consistently exhibit abnormal tau accumulation in the posterior nodes of the default mode network of the cerebral cortex. This evidence suggests that tau burden in this functional network could be a common imaging biomarker for prognostication across the syndromic spectrum of AD. Here, we examined the relationship between baseline tau PET signal and the rate of subsequent clinical decline in a sample of 48 A+/T+/N+ patients with mild cognitive impairment or mild dementia due to AD with atypical clinical phenotypes: Posterior Cortical Atrophy (n = 16), logopenic variant Primary Progressive Aphasia (n = 15), and amnestic syndrome with multi-domain impairment and young age of onset &lt; 65 years (n = 17). All patients underwent magnetic resonance imaging (MRI), tau PET, and amyloid PET scans at baseline. Each patient’s longitudinal clinical decline was assessed by calculating the annualized change in the Clinical Dementia Rating Sum-of-Boxes (CDR-SB) scores from baseline to follow-up (mean time interval = 14.55 ± 3.97 months). Atypical early AD patients showed an increase in CDR-SB by 1.18 ± 1.25 points per year: t(47) = 6.56, p &lt; .001, Cohen’s d = 0.95. Across clinical phenotypes, baseline tau in the default mode network was the strongest predictor of clinical decline (R2 = .30), outperforming a simpler model with baseline clinical impairment and demographic variables (R2 = .10), tau in other functional networks (R2 = .11-.26), and the magnitude of cortical atrophy (R2 = .20) and amyloid burden (R2 = .09) in the default mode network. Overall, these findings point to the contribution of default mode network tau to predicting the magnitude of clinical decline in atypical early AD patients one year later. This simple measure could aid the development of a personalized prognostic, monitoring, and treatment plan, which would help clinicians not only predict the natural evolution of the disease but also estimate the effect of disease-modifying therapies on slowing subsequent clinical decline given the patient’s tau burden while still early in the disease course.","PeriodicalId":9063,"journal":{"name":"Brain","volume":null,"pages":null},"PeriodicalIF":14.5,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142444193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Eleanor G Seaby, Annie Godwin, Géraldine Meyer-Dilhet, Valentine Clerc, Xavier Grand, Tia Fletcher, Laloe Monteiro, Martijn Kerkhofs, Valerio Carelli, Flavia Palombo, Marco Seri, Giulia Olivucci, Mina Grippa, Claudia Ciaccio, Stefano D’Arrigo, Maria Iascone, Marion Bermudez, Jan Fischer, Nataliya Di Donato, Sophie Goesswein, Marco L Leung, Daniel C Koboldt, Cortlandt Myers, Gudny Anna Arnadottir, Kari Stefansson, Patrick Sulem, Ethan M Goldberg, Ange-Line Bruel, Frederic Tran Mau Them, Marjolaine Willems, Hans Tomas Bjornsson, Hakon Bjorn Hognason, Eirny Tholl Thorolfsdottir, Emanuele Agolini, Antonio Novelli, Giuseppe Zampino, Roberta Onesimo, Katherine Lachlan, Diana Baralle, Heidi L Rehm, Anne O’Donnell-Luria, Julien Courchet, Matt Guille, Cyril F Bourgeois, Sarah Ennis
DDX17 is an RNA helicase shown to be involved in critical processes during the early phases of neuronal differentiation. Globally, we compiled a case-series of 11 patients with neurodevelopmental phenotypes harbouring de novo monoallelic variants in DDX17. All 11 patients in our case series had a neurodevelopmental phenotype, whereby intellectual disability, delayed speech and language, and motor delay predominated. We performed in utero cortical electroporation in the brain of developing mice, assessing axon complexity and outgrowth of electroporated neurons, comparing wild-type and Ddx17 knockdown. We then undertook ex vivo cortical electroporation on neuronal progenitors to quantitatively assess axonal development at a single cell resolution. Mosaic ddx17 crispants and heterozygous knockouts in Xenopus tropicalis were generated for assessment of morphology, behavioural assays, and neuronal outgrowth measurements. We further undertook transcriptomic analysis of neuroblastoma SH-SY5Y cells, to identify differentially expressed genes in DDX17-KD cells compared to controls. Knockdown of Ddx17 in electroporated mouse neurons in vivo showed delayed neuronal migration as well as decreased cortical axon complexity. Mouse primary cortical neurons revealed reduced axon outgrowth upon knockdown of Ddx17 in vitro. The axon outgrowth phenotype was replicated in crispant ddx17 tadpoles and in heterozygotes. Heterozygous tadpoles had clear neurodevelopmental defects and showed an impaired neurobehavioral phenotype. Transcriptomic analysis identified a statistically significant number of differentially expressed genes involved in neurodevelopmental processes in DDX17-KD cells compared to control cells. We have identified potential neurodevelopment disease-causing variants in a gene not previously associated with genetic disease, DDX17. We provide evidence for the role of the gene in neurodevelopment in both mammalian and non-mammalian species and in controlling the expression of key neurodevelopment genes.
{"title":"Monoallelic de novo variants in DDX17 cause a neurodevelopmental disorder","authors":"Eleanor G Seaby, Annie Godwin, Géraldine Meyer-Dilhet, Valentine Clerc, Xavier Grand, Tia Fletcher, Laloe Monteiro, Martijn Kerkhofs, Valerio Carelli, Flavia Palombo, Marco Seri, Giulia Olivucci, Mina Grippa, Claudia Ciaccio, Stefano D’Arrigo, Maria Iascone, Marion Bermudez, Jan Fischer, Nataliya Di Donato, Sophie Goesswein, Marco L Leung, Daniel C Koboldt, Cortlandt Myers, Gudny Anna Arnadottir, Kari Stefansson, Patrick Sulem, Ethan M Goldberg, Ange-Line Bruel, Frederic Tran Mau Them, Marjolaine Willems, Hans Tomas Bjornsson, Hakon Bjorn Hognason, Eirny Tholl Thorolfsdottir, Emanuele Agolini, Antonio Novelli, Giuseppe Zampino, Roberta Onesimo, Katherine Lachlan, Diana Baralle, Heidi L Rehm, Anne O’Donnell-Luria, Julien Courchet, Matt Guille, Cyril F Bourgeois, Sarah Ennis","doi":"10.1093/brain/awae320","DOIUrl":"https://doi.org/10.1093/brain/awae320","url":null,"abstract":"DDX17 is an RNA helicase shown to be involved in critical processes during the early phases of neuronal differentiation. Globally, we compiled a case-series of 11 patients with neurodevelopmental phenotypes harbouring de novo monoallelic variants in DDX17. All 11 patients in our case series had a neurodevelopmental phenotype, whereby intellectual disability, delayed speech and language, and motor delay predominated. We performed in utero cortical electroporation in the brain of developing mice, assessing axon complexity and outgrowth of electroporated neurons, comparing wild-type and Ddx17 knockdown. We then undertook ex vivo cortical electroporation on neuronal progenitors to quantitatively assess axonal development at a single cell resolution. Mosaic ddx17 crispants and heterozygous knockouts in Xenopus tropicalis were generated for assessment of morphology, behavioural assays, and neuronal outgrowth measurements. We further undertook transcriptomic analysis of neuroblastoma SH-SY5Y cells, to identify differentially expressed genes in DDX17-KD cells compared to controls. Knockdown of Ddx17 in electroporated mouse neurons in vivo showed delayed neuronal migration as well as decreased cortical axon complexity. Mouse primary cortical neurons revealed reduced axon outgrowth upon knockdown of Ddx17 in vitro. The axon outgrowth phenotype was replicated in crispant ddx17 tadpoles and in heterozygotes. Heterozygous tadpoles had clear neurodevelopmental defects and showed an impaired neurobehavioral phenotype. Transcriptomic analysis identified a statistically significant number of differentially expressed genes involved in neurodevelopmental processes in DDX17-KD cells compared to control cells. We have identified potential neurodevelopment disease-causing variants in a gene not previously associated with genetic disease, DDX17. We provide evidence for the role of the gene in neurodevelopment in both mammalian and non-mammalian species and in controlling the expression of key neurodevelopment genes.","PeriodicalId":9063,"journal":{"name":"Brain","volume":null,"pages":null},"PeriodicalIF":14.5,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142440210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mads G Stemmerik,Giorgio Tasca,Nils Erik Gilhus,Laurent Servais,Alex Vicino,Lorenzo Maggi,Valeria Sansone,John Vissing
Muscle diseases cover a diverse group of disorders that in most cases are hereditary. The rarity of the individual muscle diseases provides a challenge for researchers when wanting to establish natural history of the conditions and when trying to develop diagnostic tools, therapies, and outcome measures to evaluate disease progression. With emerging molecular therapies in many genetic muscle diseases, as well as biological therapies for the immune-mediated ones, biological biomarkers play an important role in both drug development and evaluation. In this review, we focus on the role of biological biomarkers in muscle diseases and discuss their utility as surrogate endpoints in therapeutic trials. We categorise these as either 1) disease unspecific markers, 2) markers of specific pathways that may be used for more than one disease or 3) disease-specific markers. We also propose that evaluation of specific therapeutic interventions benefits from biological markers that match the intervention.
{"title":"Biological biomarkers in muscle diseases relevant for follow-up and evaluation of treatment.","authors":"Mads G Stemmerik,Giorgio Tasca,Nils Erik Gilhus,Laurent Servais,Alex Vicino,Lorenzo Maggi,Valeria Sansone,John Vissing","doi":"10.1093/brain/awae323","DOIUrl":"https://doi.org/10.1093/brain/awae323","url":null,"abstract":"Muscle diseases cover a diverse group of disorders that in most cases are hereditary. The rarity of the individual muscle diseases provides a challenge for researchers when wanting to establish natural history of the conditions and when trying to develop diagnostic tools, therapies, and outcome measures to evaluate disease progression. With emerging molecular therapies in many genetic muscle diseases, as well as biological therapies for the immune-mediated ones, biological biomarkers play an important role in both drug development and evaluation. In this review, we focus on the role of biological biomarkers in muscle diseases and discuss their utility as surrogate endpoints in therapeutic trials. We categorise these as either 1) disease unspecific markers, 2) markers of specific pathways that may be used for more than one disease or 3) disease-specific markers. We also propose that evaluation of specific therapeutic interventions benefits from biological markers that match the intervention.","PeriodicalId":9063,"journal":{"name":"Brain","volume":null,"pages":null},"PeriodicalIF":14.5,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142436180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Astrid M Alsema,Sophie Puvogel,Laura Kracht,Marree J Webster,Cynthia Shannon Weickert,Bart J L Eggen,Iris E C Sommer
Dysfunctional GABAergic and dopaminergic neurons are thought to exist in the ventral midbrain of patients with schizophrenia, yet transcriptional changes underpinning these abnormalities have not yet been localized to specific neuronal subsets. In the ventral midbrain, control over dopaminergic activity is maintained by both excitatory (glutamate) and inhibitory (GABA) input neurons. To further elucidate neuron pathology at the single-cell level, we characterized the transcriptional diversity of distinct NEUN+ populations in the human ventral midbrain and then tested for schizophrenia-associated changes in neuronal subset proportions and gene activity changes within neuronal subsets. Combining single nucleus RNA-sequencing with fluorescence-activated sorting of NEUN+ nuclei, we analysed 31,669 nuclei. Initially, we detected 18 transcriptionally distinct neuronal populations in the human ventral midbrain, including 2 "mixed" populations. The presence of neuronal populations in the midbrain was orthogonally validated with immunohistochemical stainings. "Mixed" populations contained nuclei expressing transcripts for vesicular glutamate transporter 2 (SLC17A6) and Glutamate Decarboxylase 2 (GAD2), but these transcripts were not typically co-expressed by the same nucleus. Upon more fine-grained subclustering of the 2 "mixed" populations, 16 additional subpopulations were identified that were transcriptionally classified as excitatory or inhibitory. In the midbrains of individuals with schizophrenia, we observed potential differences in the proportions of two (sub)populations of excitatory neurons, two subpopulations of inhibitory neurons, one "mixed" subpopulation, and one subpopulation of TH-expressing neurons. This may suggest that transcriptional changes associated with schizophrenia broadly affect excitatory, inhibitory, and dopamine neurons. We detected 99 genes differentially expressed in schizophrenia compared to controls within neuronal subpopulations identified from the 2 "mixed" populations, with the majority (67) of changes within small GABAergic neuronal subpopulations. Overall, single-nucleus transcriptomic analyses profiled a high diversity of GABAergic neurons in the human ventral midbrain, identified putative shifts in the proportion of neuronal subpopulations, and suggested dysfunction of specific GABAergic subpopulations in schizophrenia, providing directions for future research.
{"title":"Schizophrenia-associated changes in neuronal subpopulations in the human midbrain.","authors":"Astrid M Alsema,Sophie Puvogel,Laura Kracht,Marree J Webster,Cynthia Shannon Weickert,Bart J L Eggen,Iris E C Sommer","doi":"10.1093/brain/awae321","DOIUrl":"https://doi.org/10.1093/brain/awae321","url":null,"abstract":"Dysfunctional GABAergic and dopaminergic neurons are thought to exist in the ventral midbrain of patients with schizophrenia, yet transcriptional changes underpinning these abnormalities have not yet been localized to specific neuronal subsets. In the ventral midbrain, control over dopaminergic activity is maintained by both excitatory (glutamate) and inhibitory (GABA) input neurons. To further elucidate neuron pathology at the single-cell level, we characterized the transcriptional diversity of distinct NEUN+ populations in the human ventral midbrain and then tested for schizophrenia-associated changes in neuronal subset proportions and gene activity changes within neuronal subsets. Combining single nucleus RNA-sequencing with fluorescence-activated sorting of NEUN+ nuclei, we analysed 31,669 nuclei. Initially, we detected 18 transcriptionally distinct neuronal populations in the human ventral midbrain, including 2 \"mixed\" populations. The presence of neuronal populations in the midbrain was orthogonally validated with immunohistochemical stainings. \"Mixed\" populations contained nuclei expressing transcripts for vesicular glutamate transporter 2 (SLC17A6) and Glutamate Decarboxylase 2 (GAD2), but these transcripts were not typically co-expressed by the same nucleus. Upon more fine-grained subclustering of the 2 \"mixed\" populations, 16 additional subpopulations were identified that were transcriptionally classified as excitatory or inhibitory. In the midbrains of individuals with schizophrenia, we observed potential differences in the proportions of two (sub)populations of excitatory neurons, two subpopulations of inhibitory neurons, one \"mixed\" subpopulation, and one subpopulation of TH-expressing neurons. This may suggest that transcriptional changes associated with schizophrenia broadly affect excitatory, inhibitory, and dopamine neurons. We detected 99 genes differentially expressed in schizophrenia compared to controls within neuronal subpopulations identified from the 2 \"mixed\" populations, with the majority (67) of changes within small GABAergic neuronal subpopulations. Overall, single-nucleus transcriptomic analyses profiled a high diversity of GABAergic neurons in the human ventral midbrain, identified putative shifts in the proportion of neuronal subpopulations, and suggested dysfunction of specific GABAergic subpopulations in schizophrenia, providing directions for future research.","PeriodicalId":9063,"journal":{"name":"Brain","volume":null,"pages":null},"PeriodicalIF":14.5,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142436218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Marvin Petersen, Mirthe Coenen, Charles DeCarli, Alberto De Luca, Ewoud van der Lelij, Frederik Barkhof, Thomas Benke, Christopher P L H Chen, Peter Dal-Bianco, Anna Dewenter, Marco Duering, Christian Enzinger, Michael Ewers, Lieza G Exalto, Evan M Fletcher, Nicolai Franzmeier, Saima Hilal, Edith Hofer, Huiberdina L Koek, Andrea B Maier, Pauline M Maillard, Cheryl R McCreary, Janne M Papma, Yolande A L Pijnenburg, Reinhold Schmidt, Eric E Smith, Rebecca M E Steketee, Esther van den Berg, Wiesje M van der Flier, Vikram Venkatraghavan, Narayanaswamy Venketasubramanian, Meike W Vernooij, Frank J Wolters, Xin Xu, Andreas Horn, Kaustubh R Patil, Simon B Eickhoff, Götz Thomalla, J Matthijs Biesbroek, Geert Jan Biessels, Bastian Cheng
White matter hyperintensities of presumed vascular origin (WMH) are associated with cognitive impairment and are a key imaging marker in evaluating brain health. However, WMH volume alone does not fully account for the extent of cognitive deficits and the mechanisms linking WMH to these deficits remain unclear. Lesion network mapping (LNM) enables to infer if brain networks are connected to lesions and could be a promising technique for enhancing our understanding of the role of WMH in cognitive disorders. Our study employed LNM to test the following hypotheses: (1) LNM-informed markers surpass WMH volumes in predicting cognitive performance, and (2) WMH contributing to cognitive impairment map to specific brain networks. We analyzed cross-sectional data of 3,485 patients from 10 memory clinic cohorts within the Meta VCI Map Consortium, using harmonized test results in 4 cognitive domains and WMH segmentations. WMH segmentations were registered to a standard space and mapped onto existing normative structural and functional brain connectome data. We employed LNM to quantify WMH connectivity to 480 atlas-based gray and white matter regions of interest (ROI), resulting in ROI-level structural and functional LNM scores. We compared the capacity of total and regional WMH volumes and LNM scores in predicting cognitive function using ridge regression models in a nested cross-validation. LNM scores predicted performance in three cognitive domains (attention/executive function, information processing speed, and verbal memory) significantly better than WMH volumes. LNM scores did not improve prediction for language functions. ROI-level analysis revealed that higher LNM scores, representing greater connectivity to WMH, in gray and white matter regions of the dorsal and ventral attention networks were associated with lower cognitive performance. Measures of WMH-related brain network connectivity significantly improve the prediction of current cognitive performance in memory clinic patients compared to WMH volume as a traditional imaging marker of cerebrovascular disease. This highlights the crucial role of network integrity, particularly in attention-related brain regions, improving our understanding of vascular contributions to cognitive impairment. Moving forward, refining WMH information with connectivity data could contribute to patient-tailored therapeutic interventions and facilitate the identification of subgroups at risk of cognitive disorders.
{"title":"Enhancing cognitive performance prediction by white matter hyperintensity connectivity assessment","authors":"Marvin Petersen, Mirthe Coenen, Charles DeCarli, Alberto De Luca, Ewoud van der Lelij, Frederik Barkhof, Thomas Benke, Christopher P L H Chen, Peter Dal-Bianco, Anna Dewenter, Marco Duering, Christian Enzinger, Michael Ewers, Lieza G Exalto, Evan M Fletcher, Nicolai Franzmeier, Saima Hilal, Edith Hofer, Huiberdina L Koek, Andrea B Maier, Pauline M Maillard, Cheryl R McCreary, Janne M Papma, Yolande A L Pijnenburg, Reinhold Schmidt, Eric E Smith, Rebecca M E Steketee, Esther van den Berg, Wiesje M van der Flier, Vikram Venkatraghavan, Narayanaswamy Venketasubramanian, Meike W Vernooij, Frank J Wolters, Xin Xu, Andreas Horn, Kaustubh R Patil, Simon B Eickhoff, Götz Thomalla, J Matthijs Biesbroek, Geert Jan Biessels, Bastian Cheng","doi":"10.1093/brain/awae315","DOIUrl":"https://doi.org/10.1093/brain/awae315","url":null,"abstract":"White matter hyperintensities of presumed vascular origin (WMH) are associated with cognitive impairment and are a key imaging marker in evaluating brain health. However, WMH volume alone does not fully account for the extent of cognitive deficits and the mechanisms linking WMH to these deficits remain unclear. Lesion network mapping (LNM) enables to infer if brain networks are connected to lesions and could be a promising technique for enhancing our understanding of the role of WMH in cognitive disorders. Our study employed LNM to test the following hypotheses: (1) LNM-informed markers surpass WMH volumes in predicting cognitive performance, and (2) WMH contributing to cognitive impairment map to specific brain networks. We analyzed cross-sectional data of 3,485 patients from 10 memory clinic cohorts within the Meta VCI Map Consortium, using harmonized test results in 4 cognitive domains and WMH segmentations. WMH segmentations were registered to a standard space and mapped onto existing normative structural and functional brain connectome data. We employed LNM to quantify WMH connectivity to 480 atlas-based gray and white matter regions of interest (ROI), resulting in ROI-level structural and functional LNM scores. We compared the capacity of total and regional WMH volumes and LNM scores in predicting cognitive function using ridge regression models in a nested cross-validation. LNM scores predicted performance in three cognitive domains (attention/executive function, information processing speed, and verbal memory) significantly better than WMH volumes. LNM scores did not improve prediction for language functions. ROI-level analysis revealed that higher LNM scores, representing greater connectivity to WMH, in gray and white matter regions of the dorsal and ventral attention networks were associated with lower cognitive performance. Measures of WMH-related brain network connectivity significantly improve the prediction of current cognitive performance in memory clinic patients compared to WMH volume as a traditional imaging marker of cerebrovascular disease. This highlights the crucial role of network integrity, particularly in attention-related brain regions, improving our understanding of vascular contributions to cognitive impairment. Moving forward, refining WMH information with connectivity data could contribute to patient-tailored therapeutic interventions and facilitate the identification of subgroups at risk of cognitive disorders.","PeriodicalId":9063,"journal":{"name":"Brain","volume":null,"pages":null},"PeriodicalIF":14.5,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142431269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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