Retinal imaging for the assessment of stroke risk: a systematic review.

BACKGROUND: Stroke is a leading cause of morbidity and mortality. Retinal imaging allows non-invasive assessment of the microvasculature. Consequently, retinal imaging is a technology which is garnering increasing attention as a means of assessing cardiovascular health and stroke risk. METHODS: A biomedical literature search was performed to identify prospective studies that assess the role of retinal imaging derived biomarkers as indicators of stroke risk. RESULTS: Twenty-four studies were included in this systematic review. The available evidence suggests that wider retinal venules, lower fractal dimension, increased arteriolar tortuosity, presence of retinopathy, and presence of retinal emboli are associated with increased likelihood of stroke. There is weaker evidence to suggest that narrower arterioles and the presence of individual retinopathy traits such as microaneurysms and arteriovenous nicking indicate increased stroke risk. Our review identified three models utilizing artificial intelligence algorithms for the analysis of retinal images to predict stroke. Two of these focused on fundus photographs, whilst one also utilized optical coherence tomography (OCT) technology images. The constructed models performed similarly to conventional risk scores but did not significantly exceed their performance. Only two studies identified in this review used OCT imaging, despite the higher dimensionality of this data. CONCLUSION: Whilst there is strong evidence that retinal imaging features can be used to indicate stroke risk, there is currently no predictive model which significantly outperforms conventional risk scores. To develop clinically useful tools, future research should focus on utilization of deep learning algorithms, validation in external cohorts, and analysis of OCT images.

Rare and common genetic determinants of mitochondrial function determine severity but not risk of amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease involving selective vulnerability of energy-intensive motor neurons (MNs). It has been unclear whether mitochondrial function is an upstream driver or a downstream modifier of neurotoxicity. We separated upstream genetic determinants of mitochondrial function, including genetic variation within the mitochondrial genome or autosomes; from downstream changeable factors including mitochondrial DNA copy number (mtCN). Across three cohorts including 6,437 ALS patients, we discovered that a set of mitochondrial haplotypes, chosen because they are linked to measurements of mitochondrial function, are a determinant of ALS survival following disease onset, but do not modify ALS risk. One particular haplotype appeared to be neuroprotective and was significantly over-represented in two cohorts of long-surviving ALS patients. Causal inference for mitochondrial function was achievable using mitochondrial haplotypes, but not autosomal SNPs in traditional Mendelian randomization (MR). Furthermore, rare loss-of-function genetic variants within, and reduced MN expression of, ACADM and DNA2 lead to ∼50 % shorter ALS survival; both proteins are implicated in mitochondrial function. Both mtCN and cellular vulnerability are linked to DNA2 function in ALS patient-derived neurons. Finally, MtCN responds dynamically to the onset of ALS independently of mitochondrial haplotype, and is correlated with disease severity. We conclude that, based on the genetic measures we have employed, mitochondrial function is a therapeutic target for amelioration of disease severity but not prevention of ALS.

Causal factors in primary open angle glaucoma: a phenome-wide Mendelian randomisation study.

Primary open angle glaucoma (POAG) is a chronic, adult-onset optic neuropathy associated with characteristic optic disc and/or visual field changes. With a view to identifying modifiable risk factors for this common neurodegenerative condition, we performed a 'phenome-wide' univariable Mendelian randomisation (MR) study that involved analysing the relationship between 9661 traits and POAG. Utilised analytical approaches included weighted mode based estimation, the weighted median method, the MR Egger method and the inverse variance weighted (IVW) approach. Eleven traits related to POAG risk were identified including: serum levels of the angiopoietin-1 receptor (OR [odds ratio] = 1.11, IVW p = 2.34E-06) and the cadherin 5 protein (OR = 1.06, IVW p = 1.31E-06); intraocular pressure (OR = 2.46-3.79, IVW p = 8.94E-44-3.00E-27); diabetes (OR = 5.17, beta = 1.64, IVW p = 9.68E-04); and waist circumference (OR = 0.79, IVW p = 1.66E-05). Future research focussing on the effects of adiposity, cadherin 5 and angiopoietin-1 receptor on POAG development and progression is expected to provide key insights that might inform the provision of lifestyle modification advice and/or the development of novel therapies.

Phenome-wide Mendelian randomisation analysis identifies causal factors for age-related macular degeneration.

Background: Age-related macular degeneration (AMD) is a leading cause of blindness in the industrialised world and is projected to affect >280 million people worldwide by 2040. Aiming to identify causal factors and potential therapeutic targets for this common condition, we designed and undertook a phenome-wide Mendelian randomisation (MR) study. Methods: We evaluated the effect of 4591 exposure traits on early AMD using univariable MR. Statistically significant results were explored further using: validation in an advanced AMD cohort; MR Bayesian model averaging (MR-BMA); and multivariable MR. Results: Overall, 44 traits were found to be putatively causal for early AMD in univariable analysis. Serum proteins that were found to have significant relationships with AMD included S100-A5 (odds ratio [OR] = 1.07, p-value = 6.80E-06), cathepsin F (OR = 1.10, p-value = 7.16E-05), and serine palmitoyltransferase 2 (OR = 0.86, p-value = 1.00E-03). Univariable MR analysis also supported roles for complement and immune cell traits. Although numerous lipid traits were found to be significantly related to AMD, MR-BMA suggested a driving causal role for serum sphingomyelin (marginal inclusion probability [MIP] = 0.76; model-averaged causal estimate [MACE] = 0.29). Conclusions: The results of this MR study support several putative causal factors for AMD and highlight avenues for future translational research. Funding: This project was funded by the Wellcome Trust (224643/Z/21/Z; 200990/Z/16/Z); the University of Manchester's Wellcome Institutional Strategic Support Fund (Wellcome ISSF) grant (204796/Z/16/Z); the UK National Institute for Health Research (NIHR) Academic Clinical Fellow and Clinical Lecturer Programmes; Retina UK and Fight for Sight (GR586); the Australian National Health and Medical Research Council (NHMRC) (1150144).

Atypical TDP-43 protein expression in an ALS pedigree carrying a p.Y374X truncation mutation in TARDBP.

We describe an autosomal dominant, multi-generational, amyotrophic lateral sclerosis (ALS) pedigree in which disease co-segregates with a heterozygous p.Y374X nonsense mutation within TDP-43. Mislocalization of TDP-43 and formation of insoluble TDP-43-positive neuronal cytoplasmic inclusions is the hallmark pathology in >95% of ALS patients. Neuropathological examination of the single case for which CNS tissue was available indicated typical TDP-43 pathology within lower motor neurons, but classical TDP-43-positive inclusions were absent from motor cortex. The mutated allele is transcribed and translated in patient fibroblasts and motor cortex tissue, but overall TDP-43 protein expression is reduced compared to wild-type controls. Despite absence of TDP-43-positive inclusions we confirmed deficient TDP-43 splicing function within motor cortex tissue. Furthermore, urea fractionation and mass spectrometry of motor cortex tissue carrying the mutation revealed atypical TDP-43 protein species but not typical C-terminal fragments. We conclude that the p.Y374X mutation underpins a monogenic, fully penetrant form of ALS. Reduced expression of TDP-43 combined with atypical TDP-43 protein species and absent C-terminal fragments extends the molecular phenotypes associated with TDP-43 mutations and with ALS more broadly. Future work will need to include the findings from this pedigree in dissecting the mechanisms of TDP-43-mediated toxicity.

Unbiased metabolome screen links serum urate to risk of Alzheimer's disease.

Alzheimer's disease (AD) is a progressive and fatal neurodegenerative disease caused by a combination of genetic and environmental risk factors. The serum metabolome refers to a set of small-molecules which are an important determinant of cellular health. We obtained genome-wide association study (GWAS) summary statistics for serum concentrations of 376 metabolites which were population matched with 2 GWAS studies of AD. For each metabolite we performed 2-sample MR (2SMR) using an inverse variance weighted (IVW) estimate for significance testing. After Bonferroni multiple testing correction one metabolite was causally linked to AD in both GWAS: serum urate. This result was supported by robust 2SMR measures and sensitivity analyses. We applied 2SMR to test for a causal relationship between serum urate and other neurodegenerative diseases: Parkinson disease (PD) and Amyotrophic lateral sclerosis (ALS). In ALS but not PD we identified a nominally significant link between serum urate and disease-risk, although in this case increased serum urate was protective. We conclude that serum urate is a modulator of risk for neurodegeneration. Our work has implications for the design of preventative interventions.

Multiomic analysis reveals cell-type-specific molecular determinants of COVID-19 severity.

The determinants of severe COVID-19 in healthy adults are poorly understood, which limits the opportunity for early intervention. We present a multiomic analysis using machine learning to characterize the genomic basis of COVID-19 severity. We use single-cell multiome profiling of human lungs to link genetic signals to cell-type-specific functions. We discover >1,000 risk genes across 19 cell types, which account for 77% of the SNP-based heritability for severe disease. Genetic risk is particularly focused within natural killer (NK) cells and T cells, placing the dysfunction of these cells upstream of severe disease. Mendelian randomization and single-cell profiling of human NK cells support the role of NK cells and further localize genetic risk to CD56bright NK cells, which are key cytokine producers during the innate immune response. Rare variant analysis confirms the enrichment of severe-disease-associated genetic variation within NK-cell risk genes. Our study provides insights into the pathogenesis of severe COVID-19 with potential therapeutic targets.

Unbiased metabolome screen leads to personalized medicine strategy for amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis is a rapidly progressive neurodegenerative disease that affects 1/350 individuals in the United Kingdom. The cause of amyotrophic lateral sclerosis is unknown in the majority of cases. Two-sample Mendelian randomization enables causal inference between an exposure, such as the serum concentration of a specific metabolite, and disease risk. We obtained genome-wide association study summary statistics for serum concentrations of 566 metabolites which were population matched with a genome-wide association study of amyotrophic lateral sclerosis. For each metabolite, we performed Mendelian randomization using an inverse variance weighted estimate for significance testing. After stringent Bonferroni multiple testing correction, our unbiased screen revealed three metabolites that were significantly linked to the risk of amyotrophic lateral sclerosis: Estrone-3-sulphate and bradykinin were protective, which is consistent with literature describing a male preponderance of amyotrophic lateral sclerosis and a preventive effect of angiotensin-converting enzyme inhibitors which inhibit the breakdown of bradykinin. Serum isoleucine was positively associated with amyotrophic lateral sclerosis risk. All three metabolites were supported by robust Mendelian randomization measures and sensitivity analyses; estrone-3-sulphate and isoleucine were confirmed in a validation amyotrophic lateral sclerosis genome-wide association study. Estrone-3-sulphate is metabolized to the more active estradiol by the enzyme 17ß-hydroxysteroid dehydrogenase 1; further, Mendelian randomization demonstrated a protective effect of estradiol and rare variant analysis showed that missense variants within HSD17B1, the gene encoding 17ß-hydroxysteroid dehydrogenase 1, modify risk for amyotrophic lateral sclerosis. Finally, in a zebrafish model of C9ORF72-amyotrophic lateral sclerosis, we present evidence that estradiol is neuroprotective. Isoleucine is metabolized via methylmalonyl-CoA mutase encoded by the gene MMUT in a reaction that consumes vitamin B12. Multivariable Mendelian randomization revealed that the toxic effect of isoleucine is dependent on the depletion of vitamin B12; consistent with this, rare variants which reduce the function of MMUT are protective against amyotrophic lateral sclerosis. We propose that amyotrophic lateral sclerosis patients and family members with high serum isoleucine levels should be offered supplementation with vitamin B12.

A review of Mendelian randomization in amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis is a relatively common and rapidly progressive neurodegenerative disease that, in the majority of cases, is thought to be determined by a complex gene-environment interaction. Exponential growth in the number of performed genome-wide association studies combined with the advent of Mendelian randomization is opening significant new opportunities to identify environmental exposures that increase or decrease the risk of amyotrophic lateral sclerosis. Each of these discoveries has the potential to shape new therapeutic interventions. However, to do so, rigorous methodological standards must be applied in the performance of Mendelian randomization. We have reviewed Mendelian randomization studies performed in amyotrophic lateral sclerosis to date. We identified 20 Mendelian randomization studies, including evaluation of physical exercise, adiposity, cognitive performance, immune function, blood lipids, sleep behaviours, educational attainment, alcohol consumption, smoking and type 2 diabetes mellitus. We have evaluated each study using gold standard methodology supported by the Mendelian randomization literature and the STROBE-Mendelian randomization checklist. Where discrepancies exist between Mendelian randomization studies, we suggest the underlying reasons. A number of studies conclude that there is a causal link between blood lipids and risk of amyotrophic lateral sclerosis; replication across different datasets and even different populations adds confidence. For other putative risk factors, such as smoking and immune function, Mendelian randomization studies have provided cause for doubt. We highlight the use of positive control analyses in choosing exposure single nucleotide polymorphisms (SNPs) to make up the Mendelian randomization instrument, use of SNP clumping to avoid false positive results due to SNPs in linkage and the importance of multiple testing correction. We discuss the implications of survival bias for study of late age of onset diseases such as amyotrophic lateral sclerosis and make recommendations to mitigate this potentially important confounder. For Mendelian randomization to be useful to the amyotrophic lateral sclerosis field, high methodological standards must be applied to ensure reproducibility. Mendelian randomization is already an impactful tool, but poor-quality studies will lead to incorrect interpretations by a field that includes non-statisticians, wasted resources and missed opportunities.

Higher admission activated partial thromboplastin time, neutrophil-lymphocyte ratio, serum sodium, and anticoagulant use predict in-hospital COVID-19 mortality in people with Diabetes: Findings from Two University Hospitals in the U.K.

AIMS: To create and compare survival models from admission laboratory indices in people hospitalized with coronavirus disease 2019 (COVID-19) with and without diabetes. METHODS: Retrospective observational study of patients with COVID-19 with or without diabetes admitted to Sheffield Teaching Hospitals from 29 February to 01 May 2020. Predictive variables for in-hospital mortality from COVID-19 were explored using Cox proportional hazard models. RESULTS: Out of 505 patients, 156 (30.8%) had diabetes mellitus (DM) of which 143 (91.7%) had type 2 diabetes. There were significantly higher in-hospital COVID-19 deaths in those with DM [DM COVID-19 deaths 54 (34.6%) vs. non-DM COVID-19 deaths 88 (25.2%): P < 0.05]. Activated partial thromboplastin time (APPT) > 24 s without anticoagulants (HR 6.38, 95% CI: 1.07-37.87: P = 0.04), APTT > 24 s with anticoagulants (HR 24.01, 95% CI: 3.63-159.01: P < 0.001), neutrophil-lymphocyte ratio > 8 (HR 6.18, 95% CI: 2.36-16.16: P < 0.001), and sodium > 136 mmol/L (HR 3.27, 95% CI: 1.12-9.56: P = 0.03) at admission, were only associated with in-hospital COVID-19 mortality for those with diabetes. CONCLUSIONS: At admission, elevated APTT with or without anticoagulants, neutrophil-lymphocyte ratio and serum sodium are unique factors that predict in-hospital COVID-19 mortality in patients with diabetes compared to those without. This novel finding may lead to research into haematological and biochemical mechanisms to understand why those with diabetes are more susceptible to poor outcomes when infected with Covid-19, and contribute to identification of those most at risk when admitted to hospital.

Common and rare variant analyses combined with single-cell multiomics reveal cell-type-specific molecular mechanisms of COVID-19 severity.

The determinants of severe COVID-19 in non-elderly adults are poorly understood, which limits opportunities for early intervention and treatment. Here we present novel machine learning frameworks for identifying common and rare disease-associated genetic variation, which outperform conventional approaches. By integrating single-cell multiomics profiling of human lungs to link genetic signals to cell-type-specific functions, we have discovered and validated over 1,000 risk genes underlying severe COVID-19 across 19 cell types. Identified risk genes are overexpressed in healthy lungs but relatively downregulated in severely diseased lungs. Genetic risk for severe COVID-19, within both common and rare variants, is particularly enriched in natural killer (NK) cells, which places these immune cells upstream in the pathogenesis of severe disease. Mendelian randomization indicates that failed NKG2D-mediated activation of NK cells leads to critical illness. Network analysis further links multiple pathways associated with NK cell activation, including type-I-interferon-mediated signalling, to severe COVID-19. Our rare variant model, PULSE, enables sensitive prediction of severe disease in non-elderly patients based on whole-exome sequencing; individualized predictions are accurate independent of age and sex, and are consistent across multiple populations and cohorts. Risk stratification based on exome sequencing has the potential to facilitate post-exposure prophylaxis in at-risk individuals, potentially based around augmentation of NK cell function. Overall, our study characterizes a comprehensive genetic landscape of COVID-19 severity and provides novel insights into the molecular mechanisms of severe disease, leading to new therapeutic targets and sensitive detection of at-risk individuals.

Physical exercise is a risk factor for amyotrophic lateral sclerosis: Convergent evidence from Mendelian randomisation, transcriptomics and risk genotypes.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a universally fatal neurodegenerative disease. ALS is determined by gene-environment interactions and improved understanding of these interactions may lead to effective personalised medicine. The role of physical exercise in the development of ALS is currently controversial. METHODS: First, we dissected the exercise-ALS relationship in a series of two-sample Mendelian randomisation (MR) experiments. Next we tested for enrichment of ALS genetic risk within exercise-associated transcriptome changes. Finally, we applied a validated physical activity questionnaire in a small cohort of genetically selected ALS patients. FINDINGS: We present MR evidence supporting a causal relationship between genetic liability to frequent and strenuous leisure-time exercise and ALS using a liberal instrument (multiplicative random effects IVW, p=0.01). Transcriptomic analysis revealed that genes with altered expression in response to acute exercise are enriched with known ALS risk genes (permutation test, p=0.013) including C9ORF72, and with ALS-associated rare variants of uncertain significance. Questionnaire evidence revealed that age of onset is inversely proportional to historical physical activity for C9ORF72-ALS (Cox proportional hazards model, Wald test p=0.007, likelihood ratio test p=0.01, concordance=74%) but not for non-C9ORF72-ALS. Variability in average physical activity was lower in C9ORF72-ALS compared to both non-C9ORF72-ALS (F-test, p=0.002) and neurologically normal controls (F-test, p=0.049) which is consistent with a homogeneous effect of physical activity in all C9ORF72-ALS patients. INTERPRETATION: Our MR approach suggests a positive causal relationship between ALS and physical exercise. Exercise is likely to cause motor neuron injury only in patients with a risk-genotype. Consistent with this we have shown that ALS risk genes are activated in response to exercise. In particular, we propose that G4C2-repeat expansion of C9ORF72 predisposes to exercise-induced ALS. FUNDING: We acknowledge support from the Wellcome Trust (JCK, 216596/Z/19/Z), NIHR (PJS, NF-SI-0617-10077; IS-BRC-1215-20017) and NIH (MPS, CEGS 5P50HG00773504, 1P50HL083800, 1R01HL101388, 1R01-HL122939, S10OD025212, P30DK116074, and UM1HG009442).