Correlating familial Alzheimer’s disease gene mutations with clinical phenotype

Alzheimer’s disease (AD) causes devastating cognitive impairment and an intense research effort is currently devoted to developing improved treatments for it. A minority of cases occur at a particularly young age and are caused by autosomal dominantly inherited genetic mutations. Although rare, familial AD provides unique opportunities to gain insights into the cascade of pathological events and how they relate to clinical manifestations. The phenotype of familial AD is highly variable and, although it shares many clinical features with sporadic AD, it also possesses important differences. Exploring the genetic and pathological basis of this phenotypic heterogeneity can illuminate aspects of the underlying disease mechanism, and is likely to inform our understanding and treatment of AD in the future

Loss of agency in apraxia

The feeling of acting voluntarily is a fundamental component of human behavior and social life and is usually accompanied by a sense of agency. However, this ability can be impaired in a number of diseases and disorders. An important example is apraxia, a disturbance traditionally defined as a disorder of voluntary skillful movements that often results from frontal-parietal brain damage. The first part of this article focuses on direct evidence of some core symptoms of apraxia, emphasizing those with connections to agency and free will. The loss of agency in apraxia is reflected in the monitoring of internally driven action, in the perception of specifically self-intended movements and in the neural intention to act. The second part presents an outline of the evidences supporting the functional and anatomical link between apraxia and agency. The available structural and functional results converge to reveal that the frontal-parietal network contributes to the sense of agency and its impairment in disorders such as apraxia. The current knowledge on the generation of motor intentions and action monitoring could potentially be applied to develop therapeutic strategies for the clinical rehabilitation of voluntary action

Testosterone imbalance may link depression and increased body weight in premenopausal women

Accumulating evidence supports a link between depression and being overweight in women. Given previously reported sex differences in fat accumulation and depression prevalence, as well as the likely role of sex hormones in both overweight and mood disorders, we hypothesised that the depression-overweight association may be mediated by sex hormones. To this end, we investigated the association of being overweight with depression, and then considered the role of sex hormones in relation to being overweight and depression in a large population-based cohort. We included a total of 3124 women, 970 premenopausal and 2154 postmenopausal from the LIFE-Adult cohort study in our analyses. We evaluated associations between being overweight (BMI >25 kg/m2), sex hormone levels, and depressive symptomatology according to Centre for Epidemiologic Studies Depression (CES-D) scores, and explored mediation of depression in a mediation model. Being overweight was significantly associated with depressive symptoms in premenopausal but not postmenopausal women. Both premenopausal and postmenopausal overweight women had higher free testosterone levels compared with normal weight women. Premenopausal women with depressive symptomatology had higher free testosterone levels compared to women without. We found a significant mediation effect of depressive symptomatology in overweight premenopausal women through free testosterone level. These findings highlight the association between being overweight and depressed, and suggest that high free testosterone levels may play a significant role in depression of overweight premenopausal women. Based on this, pharmacological approaches targeting androgen levels in overweight depressed females, in particular when standard anti-depressive treatments fail, could be of specific clinical relevance

The very long-term risk and predictors of recurrent ischaemic events after a stroke at a young age: The FUTURE study.

INTRODUCTION: Patients who suffer a stroke at a young age, remain at a substantial risk of developing recurrent vascular events and information on very long-term prognosis and its risk factors is indispensable. Our aim is to investigate this very long-term risk and associated risk factors up to 35 years after stroke. PATIENTS AND METHODS: Prospective cohort study among 656 patients with a first-ever ischaemic stroke or transient ischaemic stroke (TIA), aged 18-50, who visited our hospital (1980-2010). Outcomes assessed at follow-up (2014-2015) included TIA or ischaemic stroke and other arterial events, whichever occurred first. Kaplan-Meier analysis quantified cumulative risks. A prediction model was constructed to assess risk factors independently associated with any ischaemic event using Cox proportional hazard analyses followed by bootstrap validation procedure to avoid overestimation. RESULTS: Mean follow-up was 12.4 (SD 8.2) years (8105 person-years). Twenty-five years cumulative risk was 45.4% (95%CI: 39.4-51.5) for any ischaemic event, 30.1% (95%CI: 24.8-35.4) for cerebral ischaemia and 27.0% (95%CI: 21.1-33.0) for other arterial events. Risk factors retained in the prediction model were smoking (HR 1.35, 95%CI: 1.04-1.74), poor kidney function (HR 2.10, 95%CI: 1.32-3.35), history of peripheral arterial disease (HR 2.10, 95%CI: 1.08-3.76) and cardiac disease (HR 1.84, 95%CI: 1.06-3.18) (C-statistic 0.59 (95%CI: 0.55-0.64)). DISCUSSION AND CONCLUSION: Young stroke patients remain at a substantial risk for recurrent events; almost 1 of 2 develops a recurrent ischaemic event and 1 of 3 develops a recurrent stroke or TIA during 25 years of follow-up. Risk factors independently associated with recurrent events were poor kidney function, smoking, history of peripheral arterial disease and cardiac disease.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Frank-Erik de Leeuw received research support from the ‘‘Dutch Epilepsy Fund’’ (grant number 2010-18), ‘Dutch Heart Foundation’ (clinical established investigator grant, grant number 2014-T060) and ‘‘The Dutch Organisation for Health Research and Development’’ (VIDI innovational grant, ZonMw, grant number 016-126-351). Loes Rutten- Jacobs was supported by a British Heart Foundation Immediate Research Fellowship (FS/15/61/31626) (www. bhf.org.uk).This is the author accepted manuscript. The final version is available from SAGE Publications via https://doi.org/10.1177/239698731667344

A multimodal neuroimaging classifier for alcohol dependence

With progress in magnetic resonance imaging technology and a broader dissemination of state-of-the-art imaging facilities, the acquisition of multiple neuroimaging modalities is becoming increasingly feasible. One particular hope associated with multimodal neuroimaging is the development of reliable data-driven diagnostic classifiers for psychiatric disorders, yet previous studies have often failed to find a benefit of combining multiple modalities. As a psychiatric disorder with established neurobiological effects at several levels of description, alcohol dependence is particularly well-suited for multimodal classification. To this aim, we developed a multimodal classification scheme and applied it to a rich neuroimaging battery (structural, functional task-based and functional resting-state data) collected in a matched sample of alcohol-dependent patients (N = 119) and controls (N = 97). We found that our classification scheme yielded 79.3% diagnostic accuracy, which outperformed the strongest individual modality - grey-matter density - by 2.7%. We found that this moderate benefit of multimodal classification depended on a number of critical design choices: a procedure to select optimal modality-specific classifiers, a fine-grained ensemble prediction based on cross-modal weight matrices and continuous classifier decision values. We conclude that the combination of multiple neuroimaging modalities is able to moderately improve the accuracy of machine-learning-based diagnostic classification in alcohol dependence

A multimodal neuroimaging classifier for alcohol dependence

With progress in magnetic resonance imaging technology and a broader dissemination of state-of-the-art imaging facilities, the acquisition of multiple neuroimaging modalities is becoming increasingly feasible. One particular hope associated with multimodal neuroimaging is the development of reliable data-driven diagnostic classifiers for psychiatric disorders, yet previous studies have often failed to find a benefit of combining multiple modalities. As a psychiatric disorder with established neurobiological effects at several levels of description, alcohol dependence is particularly well-suited for multimodal classification. To this aim, we developed a multimodal classification scheme and applied it to a rich neuroimaging battery (structural, functional task-based and functional resting-state data) collected in a matched sample of alcohol-dependent patients (N = 119) and controls (N = 97). We found that our classification scheme yielded 79.3% diagnostic accuracy, which outperformed the strongest individual modality - grey-matter density - by 2.7%. We found that this moderate benefit of multimodal classification depended on a number of critical design choices: a procedure to select optimal modality-specific classifiers, a fine-grained ensemble prediction based on cross-modal weight matrices and continuous classifier decision values. We conclude that the combination of multiple neuroimaging modalities is able to moderately improve the accuracy of machine-learning-based diagnostic classification in alcohol dependence

Identification of sex hormone-binding globulin in the human hypothalamus

Gonadal steroids are known to influence hypothalamic functions through both genomic and non-genomic pathways. Sex hormone-binding globulin ( SHBG) may act by a non-genomic mechanism independent of classical steroid receptors. Here we describe the immunocytochemical mapping of SHBG-containing neurons and nerve fibers in the human hypothalamus and infundibulum. Mass spectrometry and Western blot analysis were also used to characterize the biochemical characteristics of SHBG in the hypothalamus and cerebrospinal fluid (CSF) of humans. SHBG-immunoreactive neurons were observed in the supraoptic nucleus, the suprachiasmatic nucleus, the bed nucleus of the stria terminalis, paraventricular nucleus, arcuate nucleus, the perifornical region and the medial preoptic area in human brains. There were SHBG-immunoreactive axons in the median eminence and the infundibulum. A partial colocalization with oxytocin could be observed in the posterior pituitary lobe in consecutive semithin sections. We also found strong immunoreactivity for SHBG in epithelial cells of the choroid plexus and in a portion of the ependymal cells lining the third ventricle. Mass spectrometry showed that affinity-purified SHBG from the hypothalamus and choroid plexus is structurally similar to the SHBG identified in the CSF. The multiple localizations of SHBG suggest neurohypophyseal and neuroendocrine functions. The biochemical data suggest that CSF SHBG is of brain rather than blood origin. Copyright (c) 2005 S. Karger AG, Base