Loes C. A. Rutten-Jacobs

Background: Huntington's disease (HD) is a rare neurodegenerative disease that presents with progressive psychological, cognitive and motor impairment. These diverse symptoms place a high burden on the patient, families and the healthcare systems they rely on. This study aimed to describe the epidemiology and clinical burden in individuals with HD compared with controls from the general population.Methods: This cohort study utilised data from general practitioner medical records to estimate the prevalence and incidence of HD between January 2000 and December 2018. A cohort of incident HD cases were matched 1:3 to controls from the general population, in whom common clinical diagnoses, medications and healthcare interventions were compared at the time of first recorded diagnosis and at a time close to death. Incidence rates of common diagnoses and mortality were compared with matched controls in the time following HD diagnosis.Results: Prevalence of HD increased between 2000 and 2018, whilst incidence remained stable. Prevalence of psychiatric diagnoses and symptomatic treatments were higher in HD cases than controls. A higher relative risk of psychotic disorders, depression, insomnia, dementia, weight loss, pneumonia and falls was observed in HD cases. Risk of death was >4 times higher in HD, with a median survival of ~12 years from first recorded diagnosis.Conclusions: This study demonstrates the significant and progressive clinical burden in individuals with HD up to 18 years after first recorded diagnosis.

Background: Genome-wide association studies have identified multiple loci associated with stroke. However, the specific stroke subtypes affected, and whether loci influence both ischemic and hemorrhagic stroke, remains unknown. For loci associated with stroke, we aimed to infer the combination of stroke subtypes likely to be affected, and in doing so assess the extent to which such loci have homogeneous effects across stroke subtypes. Methods: We performed Bayesian multinomial regression in 16 664 stroke cases and 32 792 controls of European ancestry to determine the most likely combination of stroke subtypes affected for loci with published genome-wide stroke associations, using model selection. Cases were subtyped under 2 commonly used stroke classification systems, TOAST (Trial of Org 10172 Acute Stroke Treatment) and causative classification of stroke. All individuals had genotypes imputed to the Haplotype Reference Consortium 1.1 Panel. Results: Sixteen loci were considered for analysis. Seven loci influenced both hemorrhagic and ischemic stroke, 3 of which influenced ischemic and hemorrhagic subtypes under both TOAST and causative classification of stroke. Under causative classification of stroke, 4 loci influenced both small vessel stroke and intracerebral hemorrhage. An EDNRA locus demonstrated opposing effects on ischemic and hemorrhagic stroke. No loci were predicted to influence all stroke subtypes in the same direction, and only one locus (12q24) was predicted to influence all ischemic stroke subtypes. Conclusions: Heterogeneity in the influence of stroke-associated loci on stroke subtypes is pervasive, reflecting differing causal pathways. However, overlap exists between hemorrhagic and ischemic stroke, which may reflect shared pathobiology predisposing to small vessel arteriopathy. Stroke is a complex, heterogeneous disorder requiring tailored analytic strategies to decipher genetic mechanisms.

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Objective To identify novel genetic associations with white matter hyperintensities (WMH). Methods We performed a genome-wide association meta-analysis of WMH volumes in 11,226 individuals, including 8,429 population-based individuals from UK Biobank and 2,797 stroke patients. Replication of novel loci was performed in an independent dataset of 1,202 individuals. In all studies, WMH were quantified using validated automated or semi-automated methods. Imputation was to either the Haplotype Reference Consortium or 1,000 Genomes Phase 3 panels. Results We identified a locus at genome-wide significance in an intron of PLEKHG1 (rs275350, β [SE] = 0.071 [0.013]; p = 1.6 × 10⁻⁸), a Rho guanine nucleotide exchange factor that is involved in reorientation of cells in the vascular endothelium. This association was validated in an independent sample (overall p value, 2.4 × 10⁻⁹). The same single nucleotide polymorphism was associated with all ischemic stroke (odds ratio [OR] [95% confidence interval (CI)] 1.07 [1.03–1.12], p = 0.00051), most strongly with the small vessel subtype (OR [95% CI] 1.09 [1.00–1.19], p = 0.044). Previous associations at 17q25 and 2p16 reached genome-wide significance in this analysis (rs3744020; β [SE] = 0.106 [0.016]; p = 1.2 × 10⁻¹¹ and rs7596872; β [SE] = 0.143 [0.021]; p = 3.4 × 10⁻¹²). All identified associations with WMH to date explained 1.16% of the trait variance in UK Biobank, equivalent to 6.4% of the narrow-sense heritability. Conclusions Genetic variation in PLEKHG1 is associated with WMH and ischemic stroke, most strongly with the small vessel subtype, suggesting it acts by promoting small vessel arteriopathy.

Objective To explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts. Methods We performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n = 20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI. Results The mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, p = 1.77 × 10⁻⁸; and LINC00539/ZDHHC20, p = 5.82 × 10⁻⁹. Both have been associated with blood pressure (BP)–related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits (p value for BI, p_[BI] = 9.38 × 10⁻²⁵; p_[SSBI] = 5.23 × 10⁻¹⁴ for hypertension), smoking (p_[BI] = 4.4 × 10⁻¹⁰; p_[SSBI] = 1.2 × 10⁻⁴), diabetes (p_[BI] = 1.7 × 10⁻⁸; p_[SSBI] = 2.8 × 10⁻³), previous cardiovascular disease (p_[BI] = 1.0 × 10⁻¹⁸; p_[SSBI] = 2.3 × 10⁻⁷), stroke (p_[BI] = 3.9 × 10⁻⁶⁹; p_[SSBI] = 3.2 × 10⁻²⁴), and MRI-defined white matter hyperintensity burden (p_[BI] = 1.43 × 10⁻¹⁵⁷; p_[SSBI] = 3.16 × 10⁻¹⁰⁶), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI (p ≤ 0.0022), without indication of directional pleiotropy. Conclusion In this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI.

Cerebral small‐vessel disease (cSVD) is a common cause of stroke, functional decline, vascular cognitive impairment, and dementia. Pathological processes in the brain's microcirculation are tightly interwoven with pathology in the brain parenchyma, and this interaction has been conceptualized as the neurovascular unit (NVU). Despite intensive research efforts to decipher the NVU's structure and function to date, molecular mechanisms underlying cSVD remain poorly understood, which hampers the development of cSVD‐specific therapies. Important steps forward in understanding the disease mechanisms underlying cSVD have been made using genetic approaches in studies of both monogenic and sporadic SVD. We provide an overview of the NVU's structure and function, the implications for cSVD, and the underlying molecular mechanisms of dysfunction that have emerged from recent genetic studies of both monogenic and sporadic diseases of the small cerebral vasculature.

Objective: To evaluate the associations of a polygenic risk score and healthy lifestyle with incident stroke.Design: Prospective population based cohort study.Setting: UK Biobank Study, UK.Participants: 306 473 men and women, aged 40-73 years, recruited between 2006 and 2010.Main outcome measure: Hazard ratios for a first stroke, estimated using Cox regression. A polygenic risk score of 90 single nucleotide polymorphisms previously associated with stroke was constructed at P−5to test for an association with incident stroke. Adherence to a healthy lifestyle was determined on the basis of four factors: non-smoker, healthy diet, body mass index 2, and regular physical exercise.Results: During a median follow-up of 7.1 years (2 138 443 person years), 2077 incident strokes (1541 ischaemic stroke, 287 intracerebral haemorrhage, and 249 subarachnoid haemorrhage) were ascertained. The risk of incident stroke was 35% higher among those at high genetic risk (top third of polygenic score) compared with those at low genetic risk (bottom third): hazard ratio 1.35 (95% confidence interval 1.21 to 1.50), P=3.9×10⁻⁸. Unfavourable lifestyle (0 or 1 healthy lifestyle factors) was associated with a 66% increased risk of stroke compared with a favourable lifestyle (3 or 4 healthy lifestyle factors): 1.66 (1.45 to 1.89), P=1.19×10⁻¹³. The association with lifestyle was independent of genetic risk stratums.Conclusion: In this cohort study, genetic and lifestyle factors were independently associated with incident stroke. These results emphasise the benefit of entire populations adhering to a healthy lifestyle, independent of genetic risk.

Background: Genome-wide association studies have identified multiple loci associated with stroke. However, the specific stroke subtypes affected, and whether loci influence both ischaemic and haemorrhagic stroke, remains unknown. For loci associated with stroke, we aimed to infer the combination of stroke subtypes likely to be affected, and in doing so assess the extent to which such loci have homogeneous effects across stroke subtypes. Methods: We performed Bayesian multinomial regression in 16,664 stroke cases and 32,792 controls of European ancestry to determine the most likely combination of stroke subtypes affected for loci with published genome-wide stroke associations, using model selection. Cases were subtyped under two commonly used stroke classification systems, Trial of Org 10172 Acute Stroke Treatment (TOAST) and Causative Classification of Stroke (CCS). All individuals had genotypes imputed to the Haplotype Reference Consortium 1.1 Panel. Results: Sixteen loci were considered for analysis. Seven loci influenced both haemorrhagic and ischaemic stroke, three of which influenced ischaemic and haemorrhagic subtypes under both TOAST and CCS. Under CCS, 4 loci influenced both small vessel stroke and intracerebral haemorrhage. An EDNRA locus demonstrated opposing effects on ischaemic and haemorrhagic stroke. No loci were predicted to influence all stroke subtypes in the same direction and only one locus (12q24) was predicted to influence all ischaemic stroke subtypes. Conclusions: Heterogeneity in the influence of stroke-associated loci on stroke subtypes is pervasive, reflecting differing causal pathways. However, overlap exists between haemorrhagic and ischaemic stroke, which may reflect shared pathobiology predisposing to small vessel arteriopathy. Stroke is a complex, heterogeneous disorder requiring tailored analytic strategies to decipher genetic mechanisms.