Derivation of iPSC lines from two patients with familial Alzheimer's disease from India

The current prevalence of diagnosable dementia in India is 1% of people over 60 years (~3.7 million people), but is estimated to increase significantly, as ~15% world's aged population (>65 years) would be resident here by 2020 (Shah et al., 2016). While several mutations that pose a familial risk have been identified, the ethnic background may influence disease susceptibility, clinical presentation and treatment response. In this study, we report a detailed characterization of two representative HiPSC lines from a well-characterized dementia cohort from India. Availability of these lines, and associated molecular and clinical information, would be useful in the detailed exploration of the genomic contribution(s) to AD

Discovery biology of neuropsychiatric syndromes (DBNS): a center for integrating clinical medicine and basic science

Abstract Background There is emerging evidence that there are shared genetic, environmental and developmental risk factors in psychiatry, that cut across traditional diagnostic boundaries. With this background, the Discovery biology of neuropsychiatric syndromes (DBNS) proposes to recruit patients from five different syndromes (schizophrenia, bipolar disorder, obsessive compulsive disorder, Alzheimer’s dementia and substance use disorders), identify those with multiple affected relatives, and invite these families to participate in this study. The families will be assessed: 1) To compare neuro-endophenotype measures between patients, first degree relatives (FDR) and healthy controls., 2) To identify cellular phenotypes which differentiate the groups., 3) To examine the longitudinal course of neuro-endophenotype measures., 4) To identify measures which correlate with outcome, and 5) To create a unified digital database and biorepository. Methods The identification of the index participants will occur at well-established specialty clinics. The selected individuals will have a strong family history (with at least another affected FDR) of mental illness. We will also recruit healthy controls without family history of such illness. All recruited individuals (N = 4500) will undergo brief clinical assessments and a blood sample will be drawn for isolation of DNA and peripheral blood mononuclear cells (PBMCs). From among this set, a subset of 1500 individuals (300 families and 300 controls) will be assessed on several additional assessments [detailed clinical assessments, endophenotype measures (neuroimaging- structural and functional, neuropsychology, psychophysics-electroencephalography, functional near infrared spectroscopy, eye movement tracking)], with the intention of conducting repeated measurements every alternate year. PBMCs from this set will be used to generate lymphoblastoid cell lines, and a subset of these would be converted to induced pluripotent stem cell lines and also undergo whole exome sequencing. Discussion We hope to identify unique and overlapping brain endophenotypes for major psychiatric syndromes. In a proportion of subjects, we expect these neuro-endophenotypes to progress over time and to predict treatment outcome. Similarly, cellular assays could differentiate cell lines derived from such groups. The repository of biomaterials as well as digital datasets of clinical parameters, will serve as a valuable resource for the broader scientific community who wish to address research questions in the area

Sample size requirement for achieving multisite harmonization using structural brain MRI features

When data is pooled across multiple sites, the extracted features are confounded by site effects. Harmonization methods attempt to correct these site effects while preserving the biological variability within the features. However, little is known about the sample size requirement for effectively learning the harmonization parameters and their relationship with the increasing number of sites. In this study, we performed experiments to find the minimum sample size required to achieve multisite harmonization (using neuroHarmonize) using volumetric and surface features by leveraging the concept of learning curves. Our first two experiments show that site-effects are effectively removed in a univariate and multivariate manner; however, it is essential to regress the effect of covariates from the harmonized data additionally. Our following two experiments with actual and simulated data showed that the minimum sample size required for achieving harmonization grows with the increasing average Mahalanobis distances between the sites and their reference distribution. We conclude by positing a general framework to understand the site effects using the Mahalanobis distance. Further, we provide insights on the various factors in a cross-validation design to achieve optimal inter-site harmonization

Natural history of non-functioning pituitary microadenomas - results from the UK NFPA consortium.

OBJECTIVE: The optimal approach to the surveillance of non-functioning pituitary microadenomas (micro-NFPAs) is not clearly established. Our aim was to generate evidence on the natural history of micro-NFPAs to support patient care. DESIGN: Multi-centre, retrospective, cohort study involving 23 endocrine departments (UK NFPA consortium). METHODS: Clinical, imaging, and hormonal data of micro-NFPA cases between 1/1/2008 and 21/12/2021 were analysed. RESULTS: Data for 459 patients were retrieved [median age at detection 44 years [interquartile range (IQR) 31-57) - 152 males/307 females]. 419 patients had more than two MRIs [median imaging monitoring 3.5 years (IQR 1.71-6.1)]. One case developed apoplexy. Cumulative probability of micro-NFPA growth was 7.8% (95%CI 4.9%-8.1%) and 14.5% (95%CI 10.2%-18.8%) at 3 and 5 years, respectively, and of reduction 14.1% (95%CI 10.4-17.8%) and 21.3% (95%CI 16.4-26.2%) at 3 and 5 years, respectively. Median tumour enlargement was 2 mm (IQR 1-3) and 49% of micro-NFPAs that grew became macroadenomas (nearly all >5 mm at detection). Eight (1.9%) patients received surgery (only one had visual compromise with surgery required >3 years after micro-NFPA detection). Sex, age, size at baseline were not predictors of enlargement/reduction. At time of detection, 7.2%, 1.7% and 1.5% patients had secondary hypogonadism, hypothyroidism and hypoadrenalism, respectively. Two (0.6%) developed hypopituitarism during follow-up (after progression to macroadenoma). CONCLUSIONS: Probability of micro-NFPA growth is low and development of new hypopituitarism is rare. Delaying first follow-up MRI to three years and avoiding hormonal re-evaluation in absence of tumour growth or clinical manifestations is a safe approach for micro-NFPA surveillance