Investigation of the genetic aetiology of Lewy body diseases with and without dementia.

Up to 80% of Parkinson's disease patients develop dementia, but time to dementia varies widely from motor symptom onset. Dementia with Lewy bodies presents with clinical features similar to Parkinson's disease dementia, but cognitive impairment precedes or coincides with motor onset. It remains controversial whether dementia with Lewy bodies and Parkinson's disease dementia are distinct conditions or represent part of a disease spectrum. The biological mechanisms underlying disease heterogeneity, in particular the development of dementia, remain poorly understood, but will likely be the key to understanding disease pathways and, ultimately, therapy development. Previous genome-wide association studies in Parkinson's disease and dementia with Lewy bodies/Parkinson's disease dementia have identified risk loci differentiating patients from controls. We collated data for 7804 patients of European ancestry from Tracking Parkinson's, The Oxford Discovery Cohort, and Accelerating Medicine Partnership-Parkinson's Disease Initiative. We conducted a discrete phenotype genome-wide association study comparing Lewy body diseases with and without dementia to decode disease heterogeneity by investigating the genetic drivers of dementia in Lewy body diseases. We found that risk allele rs429358 tagging APOEe4 increases the odds of developing dementia, and that rs7668531 near the MMRN1 and SNCA-AS1 genes and an intronic variant rs17442721 tagging LRRK2 G2019S on chromosome 12 are protective against dementia. These results should be validated in autopsy-confirmed cases in future studies.

Outcomes of Percutaneous Endoscopic Gastrostomy in Huntington's Disease at a Tertiary Center.

BACKGROUND: Clinically assisted nutrition and hydration via percutaneous endoscopic gastrostomy (PEG) is a therapeutic option to ameliorate the difficulties associated with enhanced catabolism, weight loss, and dysphagia in Huntington's disease (HD). OBJECTIVES: The objective is to provide insights into demographics, staging (Shoulson-Fahn), complications, weight trajectories, and survival rates in people with HD (pwHD) who underwent PEG. METHODS: This retrospective study included 705 consecutive pwHD who attended our HD clinic between July 2006 and March 2024, of whom 52 underwent PEG. A control group (n = 52), comprising pwHD without PEG, were closely matched for sex, stage, age, CAG length, and disease burden score at PEG. The study was registered as a service evaluation at the National Hospital for Neurology and Neurosurgery. RESULTS: PEG prevalence was 15.0% (n = 52/347) among manifest pwHD: 4.8% (n = 3/62) for Stage 3; 33.3% (n = 16/48) for stage 4; and 44.1% (n = 30/68) for stage 5. Commonest indications were dysphagia, weight loss, and inadequate oral intake. Complications included chest infection, tube dislodgement, and peristomal and skin infections. Modeling of weight trajectories after PEG found no difference between PEG and non-PEG groups. Mortality rate was 34.6% (n = 18/52) in the PEG and 36.5% (n = 19/52) in the non-PEG groups (P = 0.84). Treatment duration (until study endpoint or death) was 3.48 years (interquartile range = 1.71-6.02; range = 0.23-18.8), with 65.4% (n = 34/52) alive at the study endpoint. CONCLUSION: PEG in pwHD at-risk for weight loss may help slow weight loss. Prospective studies are required to strengthen PEG decision-making in pwHD. PEG survival was much longer than other dementias, highlighting the need to consider PEG independently in pwHD.

Genome-wide determinants of mortality and motor progression in Parkinson's disease.

There are 90 independent genome-wide significant genetic risk variants for Parkinson's disease (PD) but currently only five nominated loci for PD progression. The biology of PD progression is likely to be of central importance in defining mechanisms that can be used to develop new treatments. We studied 6766 PD patients, over 15,340 visits with a mean follow-up of between 4.2 and 15.7 years and carried out genome-wide survival studies for time to a motor progression endpoint, defined by reaching Hoehn and Yahr stage 3 or greater, and death (mortality). There was a robust effect of the APOE ε4 allele on mortality in PD. We also identified a locus within the TBXAS1 gene encoding thromboxane A synthase 1 associated with mortality in PD. We also report 4 independent loci associated with motor progression in or near MORN1, ASNS, PDE5A, and XPO1. Only the non-Gaucher disease causing GBA1 PD risk variant E326K, of the known PD risk variants, was associated with mortality in PD. Further work is needed to understand the links between these genomic variants and the underlying disease biology. However, these may represent new candidates for disease modification in PD.

Towards cascading genetic risk in Alzheimer's disease.

Alzheimer's disease typically progresses in stages, which have been defined by the presence of disease-specific biomarkers: Amyloid (A), Tau (T) and neurodegeneration (N). This progression of biomarkers has been condensed into the ATN framework, where each of the biomarkers can be either positive (+) or negative (-). Over the past decades genome wide association studies have implicated about 90 different loci involved with the development of late onset Alzheimer's disease. Here we investigate whether genetic risk for Alzheimer's disease contributes equally to the progression in different disease stages or whether it exhibits a stage-dependent effect. Amyloid (A) and tau (T) status was defined using a combination of available PET and CSF biomarkers in the Alzheimer's Disease Neuroimaging Initiative cohort. In 312 participants with biomarker-confirmed A-T- status, we employed Cox proportional hazards models to estimate the contribution of APOE and polygenic risk scores (beyond APOE) to convert to A+T- status (65 conversions). Furthermore, we repeated the analysis in 290 participants with A+T- status and investigated the genetic contribution to conversion to A+T+ (45 conversions). Both survival analyses were adjusted for age, sex, and years of education. For progression from A-T- to A+T-, APOE-e4 burden showed significant effect (HR=2.88; 95% CI: 1.70-4.89; P<0.001), while polygenic risk did not (HR=1.09; 95% CI: 0.84-1.42; P=0.53). Conversely, for the transition from A+T- to A+T+, the APOE-e4 burden contribution was reduced (HR=1.62 95% CI: 1.05-2.51; P=0.031), while the polygenic risk showed an increased contribution (HR=1.73; 95% CI:1.27-2.36; P<0.001). The marginal APOE effect was driven by e4 homozygotes (HR=2.58; 95% CI: 1.05-6.35; P=0.039) as opposed to e4 heterozygotes (HR=1.74; 95% CI: 0.87-3.49; P=0.12). The genetic risk for late-onset Alzheimer's disease unfolds in a disease stage-dependent fashion. A better understanding of the interplay between disease stage and genetic risk can lead to a more mechanistic understanding of transition between ATN stages, a better understanding of the molecular processes leading to Alzheimer's disease as well as opening therapeutic windows for targeted interventions.

MAPT H2 haplotype and risk of Pick's disease in the Pick's disease International Consortium: a genetic association study.

BACKGROUND: Pick's disease is a rare and predominantly sporadic form of frontotemporal dementia that is classified as a primary tauopathy. Pick's disease is pathologically defined by the presence in the frontal and temporal lobes of Pick bodies, composed of hyperphosphorylated, three-repeat tau protein, encoded by the MAPT gene. MAPT has two distinct haplotypes, H1 and H2; the MAPT H1 haplotype is the major genetic risk factor for four-repeat tauopathies (eg, progressive supranuclear palsy and corticobasal degeneration), and the MAPT H2 haplotype is protective for these disorders. The primary aim of this study was to evaluate the association of MAPT H2 with Pick's disease risk, age at onset, and disease duration. METHODS: In this genetic association study, we used data from the Pick's disease International Consortium, which we established to enable collection of data from individuals with pathologically confirmed Pick's disease worldwide. For this analysis, we collected brain samples from individuals with pathologically confirmed Pick's disease from 35 sites (brainbanks and hospitals) in North America, Europe, and Australia between Jan 1, 2020, and Jan 31, 2023. Neurologically healthy controls were recruited from the Mayo Clinic (FL, USA, or MN, USA between March 1, 1998, and Sept 1, 2019). For the primary analysis, individuals were directly genotyped for the MAPT H1-H2 haplotype-defining variant rs8070723. In a secondary analysis, we genotyped and constructed the six-variant-defined (rs1467967-rs242557-rs3785883-rs2471738-rs8070723-rs7521) MAPT H1 subhaplotypes. Associations of MAPT variants and MAPT haplotypes with Pick's disease risk, age at onset, and disease duration were examined using logistic and linear regression models; odds ratios (ORs) and ß coefficients were estimated and correspond to each additional minor allele or each additional copy of the given haplotype. FINDINGS: We obtained brain samples from 338 people with pathologically confirmed Pick's disease (205 [61%] male and 133 [39%] female; 338 [100%] White) and 1312 neurologically healthy controls (611 [47%] male and 701 [53%] female; 1312 [100%] White). The MAPT H2 haplotype was associated with increased risk of Pick's disease compared with the H1 haplotype (OR 1·35 [95% CI 1·12 to 1·64], p=0·0021). MAPT H2 was not associated with age at onset (ß -0·54 [95% CI -1·94 to 0·87], p=0·45) or disease duration (ß 0·05 [-0·06 to 0·16], p=0·35). Although not significant after correcting for multiple testing, associations were observed at p less than 0·05: with risk of Pick's disease for the H1f subhaplotype (OR 0·11 [0·01 to 0·99], p=0·049); with age at onset for H1b (ß 2·66 [0·63 to 4·70], p=0·011), H1i (ß -3·66 [-6·83 to -0·48], p=0·025), and H1u (ß -5·25 [-10·42 to -0·07], p=0·048); and with disease duration for H1x (ß -0·57 [-1·07 to -0·07], p=0·026). INTERPRETATION: The Pick's disease International Consortium provides an opportunity to do large studies to enhance our understanding of the pathobiology of Pick's disease. This study shows that, in contrast to the decreased risk of four-repeat tauopathies, the MAPT H2 haplotype is associated with an increased risk of Pick's disease in people of European ancestry. This finding could inform development of isoform-related therapeutics for tauopathies. FUNDING: Wellcome Trust, Rotha Abraham Trust, Brain Research UK, the Dolby Fund, Dementia Research Institute (Medical Research Council), US National Institutes of Health, and the Mayo Clinic Foundation.

Investigation of the genetic aetiology of Lewy body diseases with and without dementia.

Up to 80% of Parkinson's disease patients develop dementia, but time to dementia varies widely from motor symptom onset. Dementia with Lewy bodies presents with clinical features similar to Parkinson's disease dementia, but cognitive impairment precedes or coincides with motor onset. It remains controversial whether dementia with Lewy bodies and Parkinson's disease dementia are distinct conditions or represent part of a disease spectrum. The biological mechanisms underlying disease heterogeneity, in particular the development of dementia, remain poorly understood, but will likely be key to understanding disease pathways and ultimately therapy development. Previous genome-wide association studies in Parkinson's disease and dementia with Lewy bodies/Parkinson's disease dementia have identified risk loci differentiating patients from controls. We collated data for 7,804 patients of European ancestry from Tracking Parkinson's (PRoBaND), The Oxford Discovery Cohort, and AMP-PD. We conducted a discrete phenotype genome-wide association studies comparing Lewy body diseases with and without dementia to decode disease heterogeneity by investigating the genetic drivers of dementia in Lewy body diseases. We found that risk alleles rs429358 tagging APOEe4 and rs7668531 near the MMRN1 and SNCA-AS1 genes, increase the odds of developing dementia and that an intronic variant rs17442721 tagging LRRK2 G2019S, on chromosome 12 is protective against dementia. These results should be validated in autopsy confirmed cases in future studies.

Genome-wide Analysis of Motor Progression in Parkinson Disease.

Background and Objectives: The genetic basis of Parkinson disease (PD) motor progression is largely unknown. Previous studies of the genetics of PD progression have included small cohorts and shown a limited overlap with genetic PD risk factors from case-control studies. Here, we have studied genomic variation associated with PD motor severity and early-stage progression in large longitudinal cohorts to help to define the biology of PD progression and potential new drug targets. Methods: We performed a GWAS meta-analysis of early PD motor severity and progression up to 3 years from study entry. We used linear mixed-effect models with additive effects, corrected for age at diagnosis, sex, and the first 5 genetic principal components to assess variability in axial, limb, and total Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) III scores. Results: We included 3,572 unrelated European ancestry patients with PD from 5 observational cohorts and 1 drug trial. The average AAO was 62.6 years (SD = 9.83), and 63% of participants were male. We found an average increase in the total MDS-UPDRS III score of 2.3 points/year. We identified an association between PD axial motor progression and variation at the GJA5 locus at 1q12 (ß = -0.25, SE = 0.04, p = 3.4e-10). Exploration of the regulation of gene expression in the region (cis-expression quantitative trait loci [eQTL] analysis) showed that the lead variant was associated with expression of ACP6, a lysophosphatidic acid phosphatase that regulates mitochondrial lipid biosynthesis (cis-eQTL p-values in blood and brain RNA expression data sets: <10-14 in eQTLGen and 10-7 in PsychEncode). Discussion: Our study highlights the potential role of mitochondrial lipid homeostasis in the progression of PD, which may be important in establishing new drug targets that might modify disease progression.

Genetic meta-analysis of levodopa induced dyskinesia in Parkinson's disease.

The genetic basis of levodopa-induced-dyskinesia (LiD) is poorly understood, and there have been few well-powered genome-wide studies. We performed a genome-wide survival meta-analyses to study the effect of genetic variation on the development of LiD in five separate longitudinal cohorts, and meta-analysed the results. We included 2784 PD patients, of whom 14.6% developed LiD. We found female sex (HR = 1.35, SE = 0.11, P = 0.007) and younger age at onset (HR = 1.8, SE = 0.14, P = 2 × 10-5) increased the probability of developing LiD. We identified three genetic loci significantly associated with time-to-LiD onset. rs72673189 on chromosome 1 (HR = 2.77, SE = 0.18, P = 1.53 × 10-8) located at the LRP8 locus, rs189093213 on chromosome 4 (HR = 3.06, SE = 0.19, P = 2.81 × 10-9) in the non-coding RNA LINC02353 locus, and rs180924818 on chromosome 16 (HR = 3.13, SE = 0.20, P = 6.27 × 10-9) in the XYLT1 locus. Based on a functional annotation analysis on chromosome 1, we determined that changes in DNAJB4 gene expression, close to LRP8, are an additional potential cause of increased susceptibility to LiD. Baseline anxiety status was significantly associated with LiD (OR = 1.14, SE = 0.03, P = 7.4 × 10-5). Finally, we performed a candidate variant analysis of previously reported loci, and found that genetic variability in ANKK1 (rs1800497, HR = 1.27, SE = 0.09, P = 8.89 × 10-3) and BDNF (rs6265, HR = 1.21, SE = 0.10, P = 4.95 × 10-2) loci were significantly associated with time to LiD in our large meta-analysis.

Genetic meta-analysis of levodopa induced dyskinesia in Parkinson's disease.

Importance: Forty percent of Parkinson's disease patients develop levodopa-induced-dyskinesia (LiD) within 4 years of starting levodopa. The genetic basis of LiD remains poorly understood, and there have been few well powered studies. Objective: To discover common genetic variants in the PD population that increase the probability of developing LiD. Design setting and Participants: We performed survival analyses to study the development of LiD in 5 separate longitudinal cohorts. We performed a meta-analysis to combine the results of genetic association from each study based on a fixed effects model weighting the effect sizes by the inverse of their standard error. The selection criteria was specific to each cohort. We studied individuals that were genotyped from each cohort and that passed our analysis specific inclusion criteria. Main Outcomes and Measures: We measured the time for PD patients on levodopa treatment to develop LiD as defined by reaching a score higher or equal than 2 from the MDS-UPDRS part IV, item 1, which is equivalent to a range of 26%-50% of the waking time with dyskinesia. We carried out a genome-wide analysis of the hazard ratio and the association of genome-wide SNPs with the probability of developing LiD using cox proportional hazard models (CPH). Results: This study included 2,784 PD patients of European ancestry, of whom 14.6% developed LiD. Consistent with previous studies, we found female gender (HR = 1.35, SE = 0.11, P = 0.007) and younger age at onset (HR = 1.8, SE = 0.14, P = 2 × 10 -5 ) to increase the probability of developing LiD. We identified three loci significantly associated with time-to-LiD onset. rs72673189 on chromosome 1 (HR = 2.77, SE = 0.18, P = 1.53 × 10 -8 ) located in the LRP8 locus, rs189093213 on chromosome 4 (HR = 3.06,, SE = 0.19, P = 2.81 × 10 -9 ) in the non-coding RNA LINC02353 locus, and rs180924818 on chromosome 16 (HR = 3.13, SE = 0.20, P = 6.27 × 10 -9 ) in the XYLT1 locus. Subsequent colocalization analyses on chromosome 1 identified DNAJB4 as a candidate gene associated with LiD through a change in gene expression. We computed a PRS based on our GWAS meta-analysis and found high accuracy to stratify between PD-LID and PD (AUC 83.9). We also performed a stepwise regression analysis for baseline features selection associated with LiD status. We found baseline anxiety status to be significantly associated with LiD (OR = 1.14, SE = 0.03, P = 7.4 × 10 -5 ). Finally, we performed a candidate variant analysis and found that genetic variability in ANKK1 ( rs1800497 , Beta = 0.24, SE = 0.09, P = 8.89 × 10 -3 ) and BDNF ( rs6265 , Beta = 0.19, SE = 0.10, P = 4.95 × 10 -2 ) loci were significantly associated with time to LiD in our large meta-analysis. Conclusion: In this association study, we have found three novel genetic variants associated with LiD, as well as confirming reports that variability in ANKK1 and BDNF loci were significantly associated with LiD probability. A PRS nominated from our time-to-LiD meta-analysis significantly differentiated between PD-LiD and PD. In addition, we have found female gender, young PD onset and anxiety to be significantly associated with LiD.

POPULATION FREQUENCY OF REPEAT EXPANSIONS INDICATES INCREASED DISEASE PREVALENCE ESTIMATES ACROSS DIFFERENT POPULATIONS.

Repeat expansion disorders (REDs) are a devastating group of predominantly neurological diseases. Together they are common, affecting 1 in 3,000 people worldwide with population-specific differences. However, prevalence estimates of REDs are hampered by heterogeneous clinical presentation, variable geographic distributions, and technological limitations leading to under-ascertainment. Here, leveraging whole genome sequencing data from 82,176 individuals from different populations we found an overall carrier frequency of REDs of 1 in 340 individuals. Modelling disease prevalence using genetic data, age at onset and survival, we show that REDs are up to 3-fold more prevalent than currently reported figures. While some REDs are population-specific, e.g. Huntington's disease type 2, most REDs are represented in all broad genetic ancestries, including Africans and Asians, challenging the notion that some REDs are found only in European populations. These results have worldwide implications for local and global health communities in the diagnosis and management of REDs both at local and global levels.

Creating the Pick's disease International Consortium: Association study of MAPT H2 haplotype with risk of Pick's disease.

Background: Pick's disease (PiD) is a rare and predominantly sporadic form of frontotemporal dementia that is classified as a primary tauopathy. PiD is pathologically defined by argyrophilic inclusion Pick bodies and ballooned neurons in the frontal and temporal brain lobes. PiD is characterised by the presence of Pick bodies which are formed from aggregated, hyperphosphorylated, 3-repeat tau proteins, encoded by the MAPT gene. The MAPT H2 haplotype has consistently been associated with a decreased disease risk of the 4-repeat tauopathies of progressive supranuclear palsy and corticobasal degeneration, however its role in susceptibility to PiD is unclear. The primary aim of this study was to evaluate the association between MAPT H2 and risk of PiD. Methods: We established the Pick's disease International Consortium (PIC) and collected 338 (60.7% male) pathologically confirmed PiD brains from 39 sites worldwide. 1,312 neurologically healthy clinical controls were recruited from Mayo Clinic Jacksonville, FL (N=881) or Rochester, MN (N=431). For the primary analysis, subjects were directly genotyped for MAPT H1-H2 haplotype-defining variant rs8070723. In secondary analysis, we genotyped and constructed the six-variant MAPT H1 subhaplotypes (rs1467967, rs242557, rs3785883, rs2471738, rs8070723, and rs7521). Findings: Our primary analysis found that the MAPT H2 haplotype was associated with increased risk of PiD (OR: 1.35, 95% CI: 1.12-1.64 P=0.002). In secondary analysis involving H1 subhaplotypes, a protective association with PiD was observed for the H1f haplotype (0.0% vs. 1.2%, P=0.049), with a similar trend noted for H1b (OR: 0.76, 95% CI: 0.58-1.00, P=0.051). The 4-repeat tauopathy risk haplotype MAPT H1c was not associated with PiD susceptibility (OR: 0.93, 95% CI: 0.70-1.25, P=0.65). Interpretation: The PIC represents the first opportunity to perform relatively large-scale studies to enhance our understanding of the pathobiology of PiD. This study demonstrates that in contrast to its protective role in 4R tauopathies, the MAPT H2 haplotype is associated with an increased risk of PiD. This finding is critical in directing isoform-related therapeutics for tauopathies.

What does heritability of Alzheimer's disease represent?

INTRODUCTION: Both late-onset Alzheimer's disease (AD) and ageing have a strong genetic component. In each case, many associated variants have been discovered, but how much missing heritability remains to be discovered is debated. Variability in the estimation of SNP-based heritability could explain the differences in reported heritability. METHODS: We compute heritability in five large independent cohorts (N = 7,396, 1,566, 803, 12,528 and 3,963) to determine whether a consensus for the AD heritability estimate can be reached. These cohorts vary by sample size, age of cases and controls and phenotype definition. We compute heritability a) for all SNPs, b) excluding APOE region, c) excluding both APOE and genome-wide association study hit regions, and d) SNPs overlapping a microglia gene-set. RESULTS: SNP-based heritability of late onset Alzheimer's disease is between 38 and 66% when age and genetic disease architecture are correctly accounted for. The heritability estimates decrease by 12% [SD = 8%] on average when the APOE region is excluded and an additional 1% [SD = 3%] when genome-wide significant regions were removed. A microglia gene-set explains 69-84% of our estimates of SNP-based heritability using only 3% of total SNPs in all cohorts. CONCLUSION: The heritability of neurodegenerative disorders cannot be represented as a single number, because it is dependent on the ages of cases and controls. Genome-wide association studies pick up a large proportion of total AD heritability when age and genetic architecture are correctly accounted for. Around 13% of SNP-based heritability can be explained by known genetic loci and the remaining heritability likely resides around microglial related genes.

Local genetic correlations exist among neurodegenerative and neuropsychiatric diseases.

Genetic correlation ([Formula: see text]) between traits can offer valuable insight into underlying shared biological mechanisms. Neurodegenerative diseases overlap neuropathologically and often manifest comorbid neuropsychiatric symptoms. However, global [Formula: see text] analyses show minimal [Formula: see text] among neurodegenerative and neuropsychiatric diseases. Importantly, local [Formula: see text] s can exist in the absence of global relationships. To investigate this possibility, we applied LAVA, a tool for local [Formula: see text] analysis, to genome-wide association studies of 3 neurodegenerative diseases (Alzheimer's disease, Lewy body dementia and Parkinson's disease) and 3 neuropsychiatric disorders (bipolar disorder, major depressive disorder and schizophrenia). We identified several local [Formula: see text] s missed in global analyses, including between (i) all 3 neurodegenerative diseases and schizophrenia and (ii) Alzheimer's and Parkinson's disease. For those local [Formula: see text] s identified in genomic regions containing disease-implicated genes, such as SNCA, CLU and APOE, incorporation of expression quantitative trait loci identified genes that may drive genetic overlaps between diseases. Collectively, we demonstrate that complex genetic relationships exist among neurodegenerative and neuropsychiatric diseases, highlighting putative pleiotropic genomic regions and genes. These findings imply sharing of pathogenic processes and the potential existence of common therapeutic targets.

Deep learning-based polygenic risk analysis for Alzheimer's disease prediction.

BACKGROUND: The polygenic nature of Alzheimer's disease (AD) suggests that multiple variants jointly contribute to disease susceptibility. As an individual's genetic variants are constant throughout life, evaluating the combined effects of multiple disease-associated genetic risks enables reliable AD risk prediction. Because of the complexity of genomic data, current statistical analyses cannot comprehensively capture the polygenic risk of AD, resulting in unsatisfactory disease risk prediction. However, deep learning methods, which capture nonlinearity within high-dimensional genomic data, may enable more accurate disease risk prediction and improve our understanding of AD etiology. Accordingly, we developed deep learning neural network models for modeling AD polygenic risk. METHODS: We constructed neural network models to model AD polygenic risk and compared them with the widely used weighted polygenic risk score and lasso models. We conducted robust linear regression analysis to investigate the relationship between the AD polygenic risk derived from deep learning methods and AD endophenotypes (i.e., plasma biomarkers and individual cognitive performance). We stratified individuals by applying unsupervised clustering to the outputs from the hidden layers of the neural network model. RESULTS: The deep learning models outperform other statistical models for modeling AD risk. Moreover, the polygenic risk derived from the deep learning models enables the identification of disease-associated biological pathways and the stratification of individuals according to distinct pathological mechanisms. CONCLUSION: Our results suggest that deep learning methods are effective for modeling the genetic risks of AD and other diseases, classifying disease risks, and uncovering disease mechanisms.

Polygenic diseases, such as Alzheimer's disease (AD), are those caused by the interplay between multiple genetic risk factors. Statistical models can be used to predict disease risk based on a person's genetic profile. However, there are limitations to existing methods, while emerging methods such as deep learning may improve risk prediction. Deep learning involves computer-based software learning from patterns in data to perform a certain task, e.g. predict disease risk. Here, we test whether deep learning models can help to predict AD risk. Our models not only outperformed existing methods in modeling AD risk, they also allow us to estimate an individual's risk of AD and determine the biological processes that may be involved in AD. With further testing and optimization, deep learning may be a useful tool to help accurately predict risk of AD and other diseases.

Geographical distribution of host's specific SARS-CoV-2 mutations in the early phase of the COVID-19 pandemic.

PURPOSE: To assess, if the SARS-CoV-2 mutate in a similar pattern globally or has a specific pattern in any given population. RESULTS: We report, the insertion of TTT at 11085, which adds an extra amino acid, F to the NSP6 at amino acid position 38. The highest occurrence of TTT insertion at 11,085 position was found in UK derived samples (65.97%). The second and third highest occurrence of the mutation were found in Australia (8.3%) and USA (4.16%) derived samples, respectively. Another important discovery of this study is the C27945T mutation, which translates into the termination of ORF-8 after 17 amino acids, reveals that the SARS-CoV-2 can replicate without the intact ORF-8 protein. We found that the 97% of C27945T mutation of global occurrence, occurred in Europe and the USA derived samples. CONCLUSIONS: Two of the reported mutations (11085TTT insertion and C27945T nonsense), which seemed to reduce Type I interferon response are linked to specific geographical locations of the host and implicate region-specific mutations in the virus. The findings of this study signify that SARS-CoV-2 has the potential to adapt differently to different populations.

Association between the LRP1B and APOE loci and the development of Parkinson's disease dementia.

Parkinson's disease is one of the most common age-related neurodegenerative disorders. Although predominantly a motor disorder, cognitive impairment and dementia are important features of Parkinson's disease, particularly in the later stages of the disease. However, the rate of cognitive decline varies among Parkinson's disease patients, and the genetic basis for this heterogeneity is incompletely understood. To explore the genetic factors associated with rate of progression to Parkinson's disease dementia, we performed a genome-wide survival meta-analysis of 3923 clinically diagnosed Parkinson's disease cases of European ancestry from four longitudinal cohorts. In total, 6.7% of individuals with Parkinson's disease developed dementia during study follow-up, on average 4.4 ± 2.4 years from disease diagnosis. We have identified the APOE ε4 allele as a major risk factor for the conversion to Parkinson's disease dementia [hazard ratio = 2.41 (1.94-3.00), P = 2.32 × 10-15], as well as a new locus within the ApoE and APP receptor LRP1B gene [hazard ratio = 3.23 (2.17-4.81), P = 7.07 × 10-09]. In a candidate gene analysis, GBA variants were also identified to be associated with higher risk of progression to dementia [hazard ratio = 2.02 (1.21-3.32), P = 0.007]. CSF biomarker analysis also implicated the amyloid pathway in Parkinson's disease dementia, with significantly reduced levels of amyloid ß42 (P = 0.0012) in Parkinson's disease dementia compared to Parkinson's disease without dementia. These results identify a new candidate gene associated with faster conversion to dementia in Parkinson's disease and suggest that amyloid-targeting therapy may have a role in preventing Parkinson's disease dementia.

Measuring heritable contributions to Alzheimer's disease: polygenic risk score analysis with twins.

The heritability of Alzheimer's disease estimated from twin studies is greater than the heritability derived from genome-based studies, for reasons that remain unclear. We apply both approaches to the same twin sample, considering both Alzheimer's disease polygenic risk scores and heritability from twin models, to provide insight into the role of measured genetic variants and to quantify uncaptured genetic risk. A population-based heritability and polygenic association study of Alzheimer's disease was conducted between 1986 and 2016 and is the first study to incorporate polygenic risk scores into biometrical twin models of Alzheimer's disease. The sample included 1586 twins drawn from the Swedish Twin Registry which were nested within 1137 twin pairs (449 complete pairs and 688 incomplete pairs) with clinically based diagnoses and registry follow-up (M age = 85.28, SD = 7.02; 44% male; 431 cases and 1155 controls). We report contributions of polygenic risk scores at P < 1 × 10-5, considering a full polygenic risk score (PRS), PRS without the APOE region (PRS.no.APOE) and PRS.no.APOE plus directly measured APOE alleles. Biometric twin models estimated the contribution of environmental influences and measured (PRS) and unmeasured genes to Alzheimer's disease risk. The full PRS and PRS.no.APOE contributed 10.1 and 2.4% to Alzheimer's disease risk, respectively. When APOE ɛ4 alleles were added to the model with the PRS.no.APOE, the total contribution was 11.4% to Alzheimer's disease risk, where APOE ɛ4 explained 9.3% and PRS.no.APOE dropped from 2.4 to 2.1%. The total genetic contribution to Alzheimer's disease risk, measured and unmeasured, was 71% while environmental influences unique to each twin accounted for 29% of the risk. The APOE region accounts for much of the measurable genetic contribution to Alzheimer's disease, with a smaller contribution from other measured polygenic influences. Importantly, substantial background genetic influences remain to be understood.

An IL1RL1 genetic variant lowers soluble ST2 levels and the risk effects of APOE-ε4 in female patients with Alzheimer's disease.

Changes in the levels of circulating proteins are associated with Alzheimer's disease (AD), whereas their pathogenic roles in AD are unclear. Here, we identified soluble ST2 (sST2), a decoy receptor of interleukin-33-ST2 signaling, as a new disease-causing factor in AD. Increased circulating sST2 level is associated with more severe pathological changes in female individuals with AD. Genome-wide association analysis and CRISPR-Cas9 genome editing identified rs1921622 , a genetic variant in an enhancer element of IL1RL1, which downregulates gene and protein levels of sST2. Mendelian randomization analysis using genetic variants, including rs1921622 , demonstrated that decreased sST2 levels lower AD risk and related endophenotypes in females carrying the Apolipoprotein E (APOE)-ε4 genotype; the association is stronger in Chinese than in European-descent populations. Human and mouse transcriptome and immunohistochemical studies showed that rs1921622 /sST2 regulates amyloid-beta (Aß) pathology through the modulation of microglial activation and Aß clearance. These findings demonstrate how sST2 level is modulated by a genetic variation and plays a disease-causing role in females with AD.