Areas of Right Hemisphere Ischemia Associated with Impaired Comprehension of Affective Prosody in Acute Stroke

We studied 25 participants within 24 hours of acute right hemisphere ischemic stroke and 17 age and education matched hospitalized controls on tests of comprehension of affective prosody. Stroke patients were significantly more impaired than controls in identifying sarcasm versus sincerity in sentences and identifying affective prosody in sentences, monosyllables, and asyllabic utterances, and in discriminating differences in affective prosody in sentences. Impairments in prosodic comprehension were most associated with acute tissue dysfunction in right posterior frontal cortex, posterior inferior temporal cortex, and thalamus

The Mutational signature comprehensive analysis toolkit (musicatk) for the discovery, prediction, and exploration of mutational signatures

Mutational signatures are patterns of somatic alterations in the genome caused by carcinogenic exposures or aberrant cellular processes. To provide a comprehensive workflow for preprocessing, analysis, and visualization of mutational signatures, we created the Mutational Signature Comprehensive Analysis Toolkit (musicatk) package. musicatk enables users to select different schemas for counting mutation types and to easily combine count tables from different schemas. Multiple distinct methods are available to deconvolute signatures and exposures or to predict exposures in individual samples given a pre-existing set of signatures. Additional exploratory features include the ability to compare signatures to the Catalogue Of Somatic Mutations In Cancer (COSMIC) database, embed tumors in two dimensions with uniform manifold approximation and projection, cluster tumors into subgroups based on exposure frequencies, identify differentially active exposures between tumor subgroups, and plot exposure distributions across user-defined annotations such as tumor type. Overall, musicatk will enable users to gain novel insights into the patterns of mutational signatures observed in cancer cohorts. SIGNIFICANCE: The musicatk package empowers researchers to characterize mutational signatures and tumor heterogeneity with a comprehensive set of preprocessing utilities, discovery and prediction tools, and multiple functions for downstream analysis and visualization.R21 CA226188 - NCI NIH HHS; T32 GM100842 - NIGMS NIH HHShttps://cancerres.aacrjournals.org/content/81/23/5813.full-text.pd

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Blood lipids in a healthy Karachi population

Serum levels for cholesterol and triglycerides were estimated in an apparently normal healthy population of Karachi, aged between 4 and 59 years. In total, there were 632 subjects, 322 males and 310 females. Hypercholesterolemia was defined as a cholesterol level greater than 6.2 mmol l-1 (240 mg dl-1) in subjects above 20 years of age. In the age groups 20-39 and 40-59 years hypercholesterolemia was present in 26-41% of the males and 10-38% of the females. When triglyceride levels of more than 2.8 mmol l-1 (250 mg dl-1) were taken as abnormal for healthy males and females, 0-2% of the females and 10-25% of the males above 20 years of age were hypertriglyceridemic. The mean cholesterol levels in the age groups 4-9 and 10-19 years varied from 4.4 to 4.9 mmol l-1 (169.8 to 189.1 mg dl-1)

Blood‐derived mitochondrial DNA copy number is associated with Alzheimer’s Disease through the regulation of plasma lipid and amino acid metabolism

Abstract Background Blood‐derived mitochondrial DNA copy number (mtDNA‐CN) is the proxy measurement of mitochondrial function in the peripheral and central systems. Abnormal mtDNA‐CN not only indicates impaired mtDNA replication and transcription machinery but also dysregulated biological processes such as energy and lipid metabolism. However, the relationship between mtDNA‐CN and Alzheimer’s Disease (AD) and the underlying mechanisms of mitochondrial dysfunction in the pathogenesis of AD are still unclear. Method To investigate the causal relationship between mtDNA‐CN and AD, we performed two‐sample Mendelian randomization (MR) using publicly available summary statistics from GWAS for mtDNA‐CN and AD. Further, we estimated mtDNA‐CN using whole‐genome sequence data from blood samples of 1,521 ADNI participants and used a Cox proportional hazard model, adjusted for age, sex, and study phase, to assess the association between mtDNA‐CN and AD risk. The association of AD biomarkers measured in brain and plasma metabolites with mtDNA‐CN was evaluated using linear regression. We conducted causal mediation analysis to test the natural indirect effects of mtDNA‐CN change on AD risk through the significantly associated biomarkers and metabolites. Result MR analysis using a profile likelihood approach suggested a causal relationship between decreased blood‐derived mtDNA‐CN and increased risk of AD (OR = 0.71; P = 0.023). Survival analysis showed that decreased mtDNA‐CN was significantly associated with increased risk of conversion from mild cognitive impairment to AD (HR = 0.80; P = 0.0017). We also identified significant associations between mtDNA‐CN and brain glucose metabolism (β = 0.050; P = 0.047) and amyloid‐β (Aβ) (β = 0.069; P = 0.015) and CSF Aβ (β = ‐0.051; P = 0.048). Plasma Aβ was, however, not associated. Several lipid species, amino acids, biogenic amines, and inflammatory proteins in plasma were also significantly associated with mtDNA‐CN. Finally, causal mediation analyses showed that the effect of change in mtDNA‐CN on AD risk is mediated by plasma neurofilament light (β = ‐0.055; P = 0.010), glycine (β = 0.016; P = 0.044), and hexadecenoylcarnitine (β = ‐0.017; P = 0.049). Conclusion Our study indicates that mtDNA‐CN measured in blood is predictive of AD risk. Associations of mtDNA‐CN with Aβ in CSF and brain, but not plasma, suggest cross‐tissue regulation of mitochondria. Decreased mtDNA‐CN might increase AD risk through lipid and amino acid metabolism. These results also suggest potential development of mtDNA‐CN as a blood‐based biomarker

Identification of Genetic Variants and Serum Metabolites Associated with Blood‐derived Mitochondrial DNA Copy Number

Background Mitochondrial DNA Copy Number (mtDNA‐CN) can be used to estimate mitochondrial function and it varies across tissues and cell types. Blood‐derived mtDNA‐CN has been studied in aging‐related diseases including Alzheimer’s Disease (AD). However, little is known about the genetic contribution to variation of blood‐derived mtDNA‐CN and how this variation affects the level of serum metabolites. Method We developed a fast computational pipeline to accurately estimate mtDNA‐CN using whole genome sequence data from blood samples from European ancestry (EA, 2,885 AD cases and 2,777 controls), African American (AA, 1,118 AD cases and 1,725 controls), and Caribbean Hispanic (CH, 1,022 AD cases and 1,949 controls) participants of the Alzheimer’s Disease Sequencing Project (ADSP). In the combined sample and within each population group. We tested association of blood‐derived mtDNA‐CN with 17,569,705 variants (minor allele count≥20) genome‐wide using a linear mixed effect model including covariates for age, sex, sequencing center, PCR, AD status, polygenic risk score of blood cell count, and principal components of ancestry. We also tested the associations of mtDNA‐CN and levels of 175 serum metabolites in 1,521 subjects from Alzheimer’s Disease Neuroimaging Initiative. Result In the total sample, we identified genome‐wide significant (GWS) associations with variants from 24 independent loci. The top‐ranked SNP (rs1455130415 in NDUFS8, (p=3.25x10‐42) was also GWS in EAs (p=3.96x10‐28) and AAs (p=2.20x10‐27). SNP rs997412864 (p=5.13x10‐9) in GCAT was found associated with mtDNA‐CN in EAs, but not in other groups. Association of SNP rs1237233197 (p=1.40x10‐8) in NDUFS7 was specific to AAs. Measurements of two long‐chain acylcarnitine, C14:2‐OH (p=4.91x10‐7) and C18:2 (p=1.81x10‐5), were negatively associated with mtDNA‐CN after Bonferroni correction (P<2.9x10‐4). Ornithine, a non‐proteinogenic amino acid, was also negatively associated with mtDNA‐CN (p=2.32x10‐4). Conclusion We identified GWS association of blood‐derived mtDNA‐CN with a variant in a nuclear‐encoded mitochondrial gene, NDUFS8, which encodes a subunit of Complex I. In addition, mtDNA‐CN was significantly associated with two acylcarnitine metabolites and ornithine whose levels were previously reported to be decreased in blood of AD patients. These results provide more insight about the role of mitochondrial function in AD pathogenesis and suggest that blood‐derived mtDNA‐CN may be a useful biomarker for AD

Identification of rare coding variants associated with Alzheimer’s disease

Abstract Background Previous whole exome sequencing (WES) studies of Alzheimer’s disease (AD) have identified genome‐wide significant associations with rare variants in several novel genes and highlighted the need for investigations in larger samples. We combined WES and whole genome sequencing (WGS) data assembled by the Alzheimer Disease Sequencing Project (ADSP) to increase the power for detecting associations of AD with rare variants in gene coding regions. Method We developed an efficient computational pipeline to perform both pre‐merging and post‐merging genotype, variant and sample‐level quality control (QC) on WGS data containing 16,905 individuals and WES data for 20,504 individuals. The resultant sample included participants from European (EA, 11,279 AD cases, 8,924 controls), African American (AA, 2,757 AD cases, 4,336 controls), and Caribbean Hispanic (CH 1,438 AD cases, 3,256 controls) ancestries. We employed GENESIS to test association of AD with 250,465 bi‐allelic QC’d variants using a logistic model including covariates for age, sex, exome capture kit, read length, and ancestry principal components (PCs). Result In the total sample, variants from APOE and other known AD genes including SORL1 (P = 5.30×10‐7), NECTIN2 (P = 6.94×10‐7), and TREM2 R47H (P = 2.34×10‐13) crossed or neared the study‐wide significance (SWS) threshold of P = 2.00×10‐7 (0.05/250,465). SWS or borderline significant associations were also found with variants in several novel loci including TKTL2 (P = 2.35×10‐8), D2HGDH , (P = 1.09×10‐7) , CECR1 (P = 4.02×10‐7), PDHA2 (P = 2.76×10‐7), GOLGA1 (P = 1.72×10‐7), CYLD (P = 1.84×10‐7), and RP11‐243M5.4 (P = 1.37×10‐7). PSEN1 missense mutation G206A (rs63750082) previously associated with early onset AD in the CH group, was significantly associated with late onset AD in the same population (P = 1.58×10‐13). SWS association of AD with APOE was observed in all groups. Significant associations were also observed with variants in SERPINB8 (P = 3.77×10‐9) and FAM171A (P = 7.20×10‐7) in EAs and TLR4 (P = 4.58×10‐7) in CH. Associations with several top‐ranked variants were replicated in the Alzheimer’s Disease Genetics Consortium GWAS dataset that were imputed using the TOPMed reference panel and ADSP 5K WGS dataset. Conclusion We demonstrated that merging WGS and WES datasets can increase power to detect associations with rare coding variants in genes including ones previously implicated in AD ( CYLD and TLR4) and early‐onset stroke ( CECR1 )

Global burden of 87 risk factors in 204 countries and territories, 1990–2019 : a systematic analysis for the Global Burden of Disease Study 2019

Background: Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease. Methods: GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk–outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk–outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk–outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden. Findings: The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. In 2019, the leading Level 2 risk factor globally for attributable deaths was high systolic blood pressure, which accounted for 10·8 million (95% uncertainty interval [UI] 9·51–12·1) deaths (19·2% [16·9–21·3] of all deaths in 2019), followed by tobacco (smoked, second-hand, and chewing), which accounted for 8·71 million (8·12–9·31) deaths (15·4% [14·6–16·2] of all deaths in 2019). The leading Level 2 risk factor for attributable DALYs globally in 2019 was child and maternal malnutrition, which largely affects health in the youngest age groups and accounted for 295 million (253–350) DALYs (11·6% [10·3–13·1] of all global DALYs that year). The risk factor burden varied considerably in 2019 between age groups and locations. Among children aged 0–9 years, the three leading detailed risk factors for attributable DALYs were all related to malnutrition. Iron deficiency was the leading risk factor for those aged 10–24 years, alcohol use for those aged 25–49 years, and high systolic blood pressure for those aged 50–74 years and 75 years and older. Interpretation: Overall, the record for reducing exposure to harmful risks over the past three decades is poor. Success with reducing smoking and lead exposure through regulatory policy might point the way for a stronger role for public policy on other risks in addition to continued efforts to provide information on risk factor harm to the general public. Funding: Bill & Melinda Gates Foundation.Peer reviewe

Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease. Methods: GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk–outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk–outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk–outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden. Findings: The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. In 2019, the leading Level 2 risk factor globally for attributable deaths was high systolic blood pressure, which accounted for 10·8 million (95% uncertainty interval [UI] 9·51–12·1) deaths (19·2% [16·9–21·3] of all deaths in 2019), followed by tobacco (smoked, second-hand, and chewing), which accounted for 8·71 million (8·12–9·31) deaths (15·4% [14·6–16·2] of all deaths in 2019). The leading Level 2 risk factor for attributable DALYs globally in 2019 was child and maternal malnutrition, which largely affects health in the youngest age groups and accounted for 295 million (253–350) DALYs (11·6% [10·3–13·1] of all global DALYs that year). The risk factor burden varied considerably in 2019 between age groups and locations. Among children aged 0–9 years, the three leading detailed risk factors for attributable DALYs were all related to malnutrition. Iron deficiency was the leading risk factor for those aged 10–24 years, alcohol use for those aged 25–49 years, and high systolic blood pressure for those aged 50–74 years and 75 years and older. Interpretation: Overall, the record for reducing exposure to harmful risks over the past three decades is poor. Success with reducing smoking and lead exposure through regulatory policy might point the way for a stronger role for public policy on other risks in addition to continued efforts to provide information on risk factor harm to the general public. Funding: Bill & Melinda Gates Foundation