Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.

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Analysis of protein-coding genetic variation in 60,706 humans

WRITING GROUP MEMBERS Emelia J. Benjamin, MD, SCM, FAHA Michael J. Blaha, MD, MPH Stephanie E. Chiuve, ScD Mary Cushman, MD, MSc, FAHA Sandeep R. Das, MD, MPH, FAHA Rajat Deo, MD, MTR Sarah D. de Ferranti, MD, MPH James Floyd, MD, MS Myriam Fornage, PhD, FAHA Cathleen Gillespie, MS Carmen R. Isasi, MD, PhD, FAHA Monik C. Jiménez, ScD, SM Lori Chaffin Jordan, MD, PhD Suzanne E. Judd, PhD Daniel Lackland, DrPH, FAHA Judith H. Lichtman, PhD, MPH, FAHA Lynda Lisabeth, PhD, MPH, FAHA Simin Liu, MD, ScD, FAHA Chris T. Longenecker, MD Rachel H. Mackey, PhD, MPH, FAHA Kunihiro Matsushita, MD, PhD, FAHA Dariush Mozaffarian, MD, DrPH, FAHA Michael E. Mussolino, PhD, FAHA Khurram Nasir, MD, MPH, FAHA Robert W. Neumar, MD, PhD, FAHA Latha Palaniappan, MD, MS, FAHA Dilip K. Pandey, MBBS, MS, PhD, FAHA Ravi R. Thiagarajan, MD, MPH Mathew J. Reeves, PhD Matthew Ritchey, PT, DPT, OCS, MPH Carlos J. Rodriguez, MD, MPH, FAHA Gregory A. Roth, MD, MPH Wayne D. Rosamond, PhD, FAHA Comilla Sasson, MD, PhD, FAHA Amytis Towfighi, MD Connie W. Tsao, MD, MPH Melanie B. Turner, MPH Salim S. Virani, MD, PhD, FAHA Jenifer H. Voeks, PhD Joshua Z. Willey, MD, MS John T. Wilkins, MD Jason HY. Wu, MSc, PhD, FAHA Heather M. Alger, PhD Sally S. Wong, PhD, RD, CDN, FAHA Paul Muntner, PhD, MHSc On behalf of the American Heart Association Statistics Committee and Stroke Statistics Subcommittee Heart Disease and Stroke Statistics—2017 Update

Heart Disease and Stroke Statistics—2017 Update: A Report From the American Heart Association

Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain, providing biological plausibility for the findings. Many findings have the potential to provide entirely new insights into aetiology, but associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that have important roles in immunity, providing support for the speculated link between the immune system and schizophrenia.

/pdf/biological-insights-from-108-schizophrenia-associated-3rfvth8dm9.pdf

Biological insights from 108 schizophrenia-associated genetic loci

For most human complex diseases and traits, SNPs identified by genome-wide association studies (GWAS) explain only a small fraction of the heritability. Here we report a user-friendly software tool called genome-wide complex trait analysis (GCTA), which was developed based on a method we recently developed to address the “missing heritability” problem. GCTA estimates the variance explained by all the SNPs on a chromosome or on the whole genome for a complex trait rather than testing the association of any particular SNP to the trait. We introduce GCTA's five main functions: data management, estimation of the genetic relationships from SNPs, mixed linear model analysis of variance explained by the SNPs, estimation of the linkage disequilibrium structure, and GWAS simulation. We focus on the function of estimating the variance explained by all the SNPs on the X chromosome and testing the hypotheses of dosage compensation. The GCTA software is a versatile tool to estimate and partition complex trait variation with large GWAS data sets.

https://www.cell.com/ajhg/pdf/S0002-9297(10)00598-7.pdf

GCTA: a tool for genome-wide complex trait analysis.

The effects of the COVID-19 pandemic on the psychosocial well-being of people with disabilities.

Introduction Multimorbidity, defined as the co-occurrence of two or more long-term medical conditions, is an increasing public health concern worldwide causing enormous burden to individuals, healthcare systems and societies. The most effective way of decreasing the burden caused by multimorbidity is to find tools for its successful prevention but gaps in research evidence limit capacities to develop prevention strategies. The aim of the MOLTO study (Multimorbidity - identifying the most burdensome patterns, risk factors and potentials to reduce future burden) is to provide novel evidence required for cost-effective prevention of multimorbidity by defining the multimorbidity patterns causing the greatest burden at the population level, by examining their risk and protective factors and by estimating the potentials to reduce the future burden. Methods and analysis The MOLTO study is based on the data from the Finnish population-based cross-sectional (FINRISK 2002–2012, FinHealth 2017 the Migrant Health and Well-being Study 2010–2012) and longitudinal (Health 2000/2011) health examination surveys with individual-level link to administrative health registers, allowing register-based follow-up for the study participants. Both cross-sectional and longitudinal study designs will be used. Multimorbidity patterns will be defined using latent class analysis. The burden caused by multimorbidity as well as risk and protective factors for multimorbidity will be analysed by survival analysis methods such as Cox proportional hazards and Poisson regression models. Ethics and dissemination The survey data have been collected following the legislation at the time of the survey. The ethics committee of the Hospital District of Helsinki and Uusimaa has approved the data collection and register linkages for each survey. The results will be published as peer-reviewed scientific publications.

/pdf/study-protocol-for-an-epidemiological-study-multimorbidity-16k6g1bo.pdf

Study protocol for an epidemiological study ‘Multimorbidity − identifying the most burdensome patterns, risk factors and potentials to reduce future burden (MOLTO)’ based on the Finnish health examination surveys and the ongoing register-based follow-up

Background CT is often used for fracture evaluation following knee trauma and to diagnose ACL injuries would also be valuable. Purpose To investigate the diagnostic accuracy of dual energy CT (DECT) for detection of ACL tears in acute and subacute knee injuries. Material and Methods Patients with suspected ACL injury were imaged with DECT and MRI. Clinically blinded DECT images were independently read twice by two radiologists. ACL was classified as normal or abnormal. Arthroscopy served as reference method. Sensitivity and positive predictive value (PPV) were calculated, and diagnostic performance between DECT and MRI was assessed. Results 48 patients (26 M, 22 F, mean age 23 years, range 15–37 years) were imaged with a mean of 25 days following trauma. Of these, 21 patients underwent arthroscopy with a mean of 195 days after trauma. Arthroscopy revealed 19 ACL tears and 2 ACLs with no tear. The combined sensitivity was 76.3% (95% CI 66.8–85.9) and 86.8 (95% CI 71.9–95.6) for DECT and MRI, respectively. There was no statistically significant difference between these two methods (p = .223). The positive predictive value (PPV) was 93.5 (95% CI 84.3–98.2) and 91.7 (95% CI 77.5–98.3) for DECT and MRI, respectively. Conclusion DECT has lower sensitivity to detect an ACL rupture than MRI, but the difference is not statistically significant. The PPV is high in both methods.

/pdf/sensitivity-of-dect-in-acl-tears-a-prospective-study-with-1ibbt2m5.pdf

Sensitivity of DECT in ACL tears. A prospective study with arthroscopy as reference method

Both self-report and diagnostic interview for anxiety disorder reveal suicidal ideation in a population-based study

Projections of the development of mobility limitations of older adults are needed for evidence-based policy making. The aim of this study was to generate projections of mobility limitations among older people in the United States, England, and Finland.We applied multiple imputation modelling with bootstrapping to generate projections of stair climbing and walking limitations until 2026. A physical activity intervention producing a beneficial effect on self-reported activities of daily living measures was identified in a comprehensive literature search and incorporated in the scenarios used in the projections. We utilised the harmonised longitudinal survey data from the Ageing Trajectories of Health - Longitudinal Opportunities and Synergies (ATHLOS) project (N = 24,982).Based on the scenarios from 2012 to 2026, the prevalence of walking limitations will decrease from 9.4 to 6.4%. A physical activity intervention would decrease the prevalence of stair climbing limitations compared with no intervention from 28.9 to 18.9% between 2012 and 2026.A physical activity intervention implemented on older population seems to have a positive effect on maintaining mobility in the future. Our method provides an interesting option for generating projections by incorporating intervention-based scenarios. 

/pdf/using-multiple-imputation-and-intervention-based-scenarios-3s25ayjd.pdf

Seppo Koskinen

Papers

The effects of the COVID-19 pandemic on the psychosocial well-being of people with disabilities.

Study protocol for an epidemiological study ‘Multimorbidity − identifying the most burdensome patterns, risk factors and potentials to reduce future burden (MOLTO)’ based on the Finnish health examination surveys and the ongoing register-based follow-up

Sensitivity of DECT in ACL tears. A prospective study with arthroscopy as reference method

Both self-report and diagnostic interview for anxiety disorder reveal suicidal ideation in a population-based study

Using multiple imputation and intervention-based scenarios to project the mobility of older adults