Genetic variation in South Indian castes: evidence from Y-chromosome, mitochondrial, and autosomal polymorphisms

Background: Major population movements, social structure, and caste endogamy have influenced the genetic structure of Indian populations. An understanding of these influences is increasingly important as gene mapping and case-control studies are initiated in South Indian populations. Results: We report new data on 155 individuals from four Tamil caste populations of South India and perform comparative analyses with caste populations from the neighboring state of Andhra Pradesh. Genetic differentiation among Tamil castes is low (R = 0.96% for 45 autosomal short tandem repeat (STR) markers), reflecting a largely common origin. Nonetheless, caste- and continent-specific patterns are evident. For 32 lineage-defining Y-chromosome SNPs, Tamil castes show higher affinity to Europeans than to eastern Asians, and genetic distance estimates to the Europeans are ordered by caste rank. For 32 lineage-defining mitochondrial SNPs and hypervariable sequence (HVS) 1, Tamil castes have higher affinity to eastern Asians than to Europeans. For 45 autosomal STRs, upper and middle rank castes show higher affinity to Europeans than do lower rank castes from either Tamil Nadu or Andhra Pradesh. Local between-caste variation (Tamil Nadu R = 0.96%, Andhra Pradesh R = 0.77%) exceeds the estimate of variation between these geographically separated groups (R = 0.12%). Low, but statistically significant, correlations between caste rank distance and genetic distance are demonstrated for Tamil castes using Y-chromosome, mtDNA, and autosomal data. Conclusion: Genetic data from Y-chromosome, mtDNA, and autosomal STRs are in accord with historical accounts of northwest to southeast population movements in India. The influence of ancient and historical population movements and caste social structure can be detected and replicated in South Indian caste populations from two different geographic regions

Advances in multiple sclerosis research in 2009

The following review summarizes the progress in multiple sclerosis research published in the Journal of Neurology in 2009

Interaction testing and polygenic risk scoring to estimate the association of common genetic variants with treatment resistance in schizophrenia

Importance About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts. Objective To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples. Design, Setting, and Participants Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n=10 501) and individuals with non-TRS (n=20 325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]). Main Outcomes and Measures GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition. Results The study included a total of 85 490 participants (48 635 [56.9%] male) in its GWAS stage and 1380 participants (859 [62.2%] male) in its PRS validation stage. Treatment resistance in schizophrenia emerged as a polygenic trait with detectable heritability (1% to 4%), and several traits related to intelligence and cognition were found to be genetically correlated with it (genetic correlation, 0.41-0.69). PRS analysis in the CardiffCOGS prevalence sample showed a positive association between TRS and a history of taking clozapine (r² = 2.03%; P = .001), which was replicated in the STRATA-G incidence sample (r² = 1.09%; P = .04). Conclusions and Relevance In this GWAS, common genetic variants were differentially associated with TRS, and these associations may have been obscured through the amalgamation of large GWAS samples in previous studies of broadly defined schizophrenia. Findings of this study suggest the validity of meta-analytic approaches for studies on patient outcomes, including treatment resistance.Funding/Support: This work was supported by Medical Research Council Centre grant MR/ L010305/1, Medical Research Council Program grant MR/P005748/1, and Medical Research Council Project grants MR/L011794/1 and MC_PC_17212 to Cardiff University and by the National Centre for Mental Health, funded by the Welsh Government through Health and Care Research Wales. This work acknowledges the support of the Supercomputing Wales project, which is partially funded by the European Regional Development Fund via the Welsh Government. Dr Pardiñas was supported by an Academy of Medical Sciences Springboard Award (SBF005\1083). Dr Andreassen was supported by the Research Council of Norway (grants 283798, 262656, 248980, 273291, 248828, 248778, and 223273); KG Jebsen Stiftelsen, South-East Norway Health Authority, and the European Union’s Horizon 2020 Research and Innovation Programme (grant 847776). Dr Ajnakina was supported by an National Institute for Health Research postdoctoral fellowship (PDF-2018-11-ST2-020). Dr Joyce was supported by the University College London Hospitals/UCL University College London Biomedical Research Centre. Dr Kowalec received funding from the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie grant agreement (793530) from the government of Canada Banting postdoctoral fellowship programme and the University of Manitoba. Dr Sullivan was supported by the Swedish Research Council (Vetenskapsrådet, D0886501), the European Union’s Horizon 2020 programme (COSYN, 610307) and the US National Institute of Mental Health (U01 MH109528 and R01 MH077139). The Psychiatric Genomics Consortium was partly supported by the National Institute Of Mental Health (grants R01MH124873). The Sweden Schizophrenia Study was supported by the National Institute Of Mental Health (grant R01MH077139). The STRATA consortium was supported by a Stratified Medicine Programme grant to Dr MacCabe from the Medical Research Council (grant MR/L011794/1), which funded the research and supported Drs Pardiñas, Smart, Kassoumeri, Murray, Walters, and MacCabe. Dr Smart was supported by a Collaboration for Leadership in Applied Health Research and Care South London at King’s College Hospital National Health Service Foundation Trust. The AESOP (US) cohort was funded by the UK Medical Research Council (grant G0500817). The Belfast (UK) cohort was funded by the Research and Development Office of Northern Ireland. The Bologna (Italy) cohort was funded by the European Community’s Seventh Framework program (HEALTH-F2-2010–241909, project EU-GEI). The Genetics and Psychosis project (London, UK) cohort was funded by the UK National Institute of Health Research Specialist Biomedical Research Centre for Mental Health, South London and the Maudsley National Health Service Mental Health Foundation Trust (SLAM) and the Institute of Psychiatry, Psychology, and Neuroscience at King’s College London; Psychiatry Research Trust; Maudsley Charity Research Fund; and the European Community’s Seventh Framework program (HEALTH-F2-2009-241909, project EU-GEI). The Lausanne (Switzerland) cohort was funded by the Swiss National Science Foundation (grants 320030_135736/1, 320030-120686, 324730-144064, 320030-173211, and 171804); the National Center of Competence in Research Synaptic Bases of Mental Diseases from the Swiss National Science Foundation (grant 51AU40_125759); and Fondation Alamaya. The Oslo (Norway) cohort was funded by the Research Council of Norway (grant 223273/F50, under the Centers of Excellence funding scheme, 300309, 283798) and the South-Eastern Norway Regional Health Authority (grants 2006233, 2006258, 2011085, 2014102, 2015088, and 2017-112). The Paris (France) cohort was funded by European Community’s Seventh Framework program (HEALTH-F2-2010–241909, project EU-GEI). The Prague (Czech Republic) cohort was funded by the Ministry of Health of the Czech Republic (grant NU20-04-00393). The Santander (Spain) cohort was funded by the following grants to Dr Crespo-Facorro: Instituto de Salud Carlos III (grants FIS00/3095, PI020499, PI050427, and PI060507), Plan Nacional de Drogas Research (grant 2005-Orden sco/3246/2004), SENY Fundatio Research (grant 2005-0308007), Fundacion Marques de Valdecilla (grant A/02/07, API07/011) and Ministry of Economy and Competitiveness and the European Fund for Regional Development (grants SAF2016-76046-R and SAF2013-46292-R). The West London (UK) cohort was funded by The Wellcome Trust (grants 042025, 052247, and 064607)

Energy extraction from the biologic battery in the inner ear

Endocochlear potential (EP) is a battery-like electrochemical gradient found in and actively maintained by the inner ear [superscript 1, 2]. Here we demonstrate that the mammalian EP can be used as a power source for electronic devices. We achieved this by designing an anatomically sized, ultra-low quiescent-power energy harvester chip integrated with a wireless sensor capable of monitoring the EP itself. Although other forms of in vivo energy harvesting have been described in lower organisms [superscript 3, 4, 5], and thermoelectric [superscript 6], piezoelectric [superscript 7] and biofuel [superscript 8, 9] devices are promising for mammalian applications, there have been few, if any, in vivo demonstrations in the vicinity of the ear, eye and brain. In this work, the chip extracted a minimum of 1.12 nW from the EP of a guinea pig for up to 5 h, enabling a 2.4 GHz radio to transmit measurement of the EP every 40–360 s. With future optimization of electrode design, we envision using the biologic battery in the inner ear to power chemical and molecular sensors, or drug-delivery actuators for diagnosis and therapy of hearing loss and other disorders.Focus Center Research Program. Focus Center for Circuit & System Solutions. Semiconductor Research Corporation. Interconnect Focus CenterNational Institutes of Health (U.S.) (Grant K08 DC010419)National Institutes of Health (U.S.) (Grant T32 DC00038)Bertarelli Foundatio

Reply to: New Meta- and Mega-analyses of Magnetic Resonance Imaging Findings in Schizophrenia: Do They Really Increase Our Knowledge About the Nature of the Disease Process?

This work was supported by National Institute of Biomedical Imaging and Bioengineering Grant No. U54EB020403 (to the ENIGMA consortium)

Genome-wide Association Studies in Ancestrally Diverse Populations: Opportunities, Methods, Pitfalls, and Recommendations

Genome-wide association studies (GWASs) have focused primarily on populations of European descent, but it is essential that diverse populations become better represented. Increasing diversity among study participants will advance our understanding of genetic architecture in all populations and ensure that genetic research is broadly applicable. To facilitate and promote research in multi-ancestry and admixed cohorts, we outline key methodological considerations and highlight opportunities, challenges, solutions, and areas in need of development. Despite the perception that analyzing genetic data from diverse populations is difficult, it is scientifically and ethically imperative, and there is an expanding analytical toolbox to do it well

AN OVERVIEW OF THE INTEGRATED CRATE INTERROGATION SYSTEM (ICIS) FOR USE AT THE SAVANNAH RIVER SITE

ABSTRACT The Integrated Crate Interrogation System (ICIS) was developed for use at the Savannah River Site to assay transuranic waste in large containers. The system comprises a Box Segmented Gamma Scanner (BSGS) providing high resolution gamma spectroscopy, and a Box Neutron Assay System (BNAS) providing passive neutron counting capability. The multi-modality approach is taken where the assay results from the gamma and neutron systems are combined to complement each other in satisfying Waste Isolation Pilot Plant (WIPP) criteria. This paper gives an overview of the system that has been built, factory calibrated, and delivered to the site. The BSGS is similar to a standard Canberra Segmented Gamma Box Counter, but with the addition of a transmission option for ascertaining density and rudimentary fill-height information. This supplements the Multi-Curve approach based on efficiency in energy and density. The BSGS has a moving trolley which travels on rails through a passive emission counting station using large BEGe detectors, and a transmission counting station using NaI detectors in conjunction with high-and low-beam transmission stages. The assay result provides information on the Pu, Am and/or U isotopic ratios using standard isotopic analysis codes, quantitative measurement of Pu and U for low and medium density matrices, and direct measurement of other gamma emitters in the waste that are not identified in the isotopic measurement. It also provides basic positional information to improve the accuracy of both the gamma and the neutron measurement

Multiple sclerosis management during the COVID-19 pandemic

Altres ajuts: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. The development of standardized data collection as part of routine clinical care through Multiple Sclerosis Partners Advancing Technology and Health Solutions (MS PATHS) was developed and implemented at CC, JH, and CEMCAT in partnership with Biogen. Biogen did not have involvement in study design, data analysis or interpretation, or manuscript preparation.People with multiple sclerosis (MS) may be at higher risk for complications from the 2019 coronavirus (COVID-19) pandemic due to use of immunomodulatory disease modifying therapies (DMTs) and greater need for medical services. To evaluate risk factors for COVID-19 susceptibility and describe the pandemic's impact on healthcare delivery. Surveys sent to MS patients at Cleveland Clinic, Johns Hopkins, and Vall d'Hebron-Centre d'Esclerosi Múltiple de Catalunya in April and May 2020 collected information about comorbidities, DMTs, exposures, COVID-19 testing/outcomes, health behaviors, and disruptions to MS care. There were 3028/10,816 responders. Suspected or confirmed COVID-19 cases were more likely to have a known COVID-19 contact (odds ratio (OR): 4.38; 95% confidence interval (CI): 1.04, 18.54). In multivariable-adjusted models, people who were younger, had to work on site, had a lower education level, and resided in socioeconomically disadvantaged areas were less likely to follow social distancing guidelines. 4.4% reported changes to therapy plans, primarily delays in infusions, and 15.5% a disruption to rehabilitative services. Younger people with lower socioeconomic status required to work on site may be at higher exposure risk and are potential targets for educational intervention and work restrictions to limit exposure. Providers should be mindful of potential infusion delays and MS care disruption

A Predictive Model for Corticosteroid Response in Individual Patients with MS Relapses

<div><p>Objectives</p><p>To derive a simple predictive model to guide the use of corticosteroids in patients with relapsing remitting MS suffering an acute relapse.</p><p>Materials and Methods</p><p>We analysed individual patient randomised controlled trial data (n=98) using a binary logistic regression model based on age, gender, baseline disability scores [physician-observed: expanded disability status scale (EDSS) and patient reported: multiple sclerosis impact scale 29 (MSIS-29)], and the time intervals between symptom onset or referral and treatment.</p><p>Results</p><p>Based on two a priori selected cut-off points (improvement in EDSS ≥ 0.5 and ≥ 1.0), we found that variables which predicted better response to corticosteroids after 6 weeks were younger age and lower MSIS-29 physical score at the time of relapse (model fit 71.2% - 73.1%).</p><p>Conclusions</p><p>This pilot study suggests two clinical variables which may predict the majority of the response to corticosteroid treatment in patients undergoing an MS relapse. The study is limited in being able to clearly distinguish factors associated with treatment response or spontaneous recovery and needs to be replicated in a larger prospective study.</p></div