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Personalized medicine promises individualized disease prediction and treatment. The convergence of machine learning (ML) and available multimodal data is key moving forward. We build upon previous work to deliver multimodal predictions of Parkinson’s disease (PD) risk and systematically develop a model using GenoML, an automated ML package, to make improved multi-omic predictions of PD, validated in an external cohort. We investigated top features, constructed hypothesis-free disease-relevant networks, and investigated drug–gene interactions. We performed automated ML on multimodal data from the Parkinson’s progression marker initiative (PPMI). After selecting the best performing algorithm, all PPMI data was used to tune the selected model. The model was validated in the Parkinson’s Disease Biomarker Program (PDBP) dataset. Our initial model showed an area under the curve (AUC) of 89.72% for the diagnosis of PD. The tuned model was then tested for validation on external data (PDBP, AUC 85.03%). Optimizing thresholds for classification increased the diagnosis prediction accuracy and other metrics. Finally, networks were built to identify gene communities specific to PD. Combining data modalities outperforms the single biomarker paradigm. UPSIT and PRS contributed most to the predictive power of the model, but the accuracy of these are supplemented by many smaller effect transcripts and risk SNPs. Our model is best suited to identifying large groups of individuals to monitor within a health registry or biobank to prioritize for further testing. This approach allows complex predictive models to be reproducible and accessible to the community, with the package, code, and results publicly available.

Despite evidence of a genetic role in stroke, the identification of common genetic risk factors for this devastating disorder remains problematic. We aimed to identify any common genetic variability exerting a moderate to large effect on risk of ischaemic stroke, and to generate publicly available genome-wide genotype data to facilitate others doing the same. We applied a genome-wide high-density single-nucleotide-polymorphism (SNP) genotyping approach to a cohort of samples with and without ischaemic stroke (n=278 and 275, respectively), and did an association analysis adjusted for known confounders in a final cohort of 249 cases and 268 controls. More than 400 000 unique SNPs were assayed. We produced more than 200 million genotypes in 553 unique participants. The raw genotypes of all the controls have been posted publicly in a previous study of Parkinson's disease. From this effort, results of genotype and allele association tests have been publicly posted for 88% of stroke patients who provided proper consent for public release. Preliminary analysis of these data did not reveal any single locus conferring a large effect on risk for ischaemic stroke. The data generated here comprise the first phase of a genome-wide association analysis in patients with stroke. Release of phase I results generated in these publicly available samples from each consenting individual makes this dataset a valuable resource for data-mining and augmentation.

In the current study we undertook a series of experiments to test the hypothesis that a monogenic cause of disease may be detectable within a cohort of Finnish young onset Parkinson's disease patients. In the first instance we performed standard genome wide association analyses, and subsequent risk profile analysis. In addition we performed a series of analyses that involved testing measures of global relatedness within the cases compared to controls, searching for excess homozygosity in the cases, and examining the cases for signs of excess local genomic relatedness using a sliding window approach. This work suggested that the previously identified common, low risk alleles, and the risk models associated with these alleles, were generalizable to the Finnish Parkinson's disease population. However, we found no evidence that would suggest a single common high penetrance mutation exists in this cohort of young onset patients.

Hyperphosphorylation of the microtubule binding protein Tau is a feature of a number of neurodegenerative diseases, including Alzheimer's disease. Tau is hyperphosphorylated in the hippocampus of dab1-null mice in a strain-dependent manner; however, it has not been clear if the Tau phosphorylation phenotype is a secondary effect of the morbidity of these mutants. The dab1 gene encodes a docking protein that is required for normal brain lamination and dendritogenesis as part of the Reelin signaling pathway. We show that dab1 gene inactivation after brain development leads to Tau hyperphosphorylation in anatomically normal mice. Genomic regions that regulate the phospho Tau phenotype in dab1 mutants have previously been identified. Using a microarray gene expression comparison between dab1-mutants from the high-phospho Tau expressing and low-phospho Tau expressing strains, we identified Stk25 as a differentially expressed modifier of dab1-mutant phenotypes. Stk25 knockdown reduces Tau phosphorylation in embryonic neurons. Furthermore, Stk25 regulates neuronal polarization and Golgi morphology in an antagonistic manner to Dab1. This work provides insights into the complex regulation of neuronal behavior during brain development and provides insights into the molecular cascades that regulate Tau phosphorylation.

Background Elucidating the genetic determinants influencing Alzheimer's disease (AD) progression is crucial for the rational design of new targeted and efficacious therapeutic interventions. Method We conducted a genome‐wide study utilizing data from 382 participants with amyloid beta status, genetic profiles, and longitudinal clinical assessments, sourced from the Alzheimer's Disease Neuroimaging Initiative and the Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing. Mixed effects models were employed to evaluate the rate of change in Mini‐Mental State Examination scores as a quantitative measure of disease progression Results Variants on chromosome 22q12.1 mapped to ZNRF3, MN1, PIPNB genes reached genome‐wide significance and together with nominally significant loci (p <5×10−6) highlighted a role for neuronal resilience (both excitatory and inhibitory neurones) and anti‐viral immune responses. The APOE locus was not significantly associated with the rate of progression. Among the known AD risk genes, the OAS locus achieved nominal significance suggesting the interferon pathway has a role in determining rates of progression. Conclusion The absence of a significant association between APOE and AD progression suggests that alternative pathological pathways, beyond amyloid beta, may represent viable targets for impeding disease advancement. These pathways appear to involve neuronal resilience and immune system modulation.

INTRODUCTION Assessing treatments for Alzheimer's disease (AD) relies on reliable tools for measuring AD progression. In this analysis, we evaluate the sensitivity of clinical progression measures in AD within randomized controlled trials (RCTs) with confirmed positive amyloid (Aβ+) status prior to trial enrollment. METHODS Excluding trials targeting non‐cognitive symptoms, we conducted meta‐analyses on progression measures from 25 selected RCTs using R version 4.2.0, along with the metafor and emmeans libraries. RESULTS The Functional Activities Questionnaire (FAQ) demonstrated the greatest sensitivity over 12 weeks. Other cognitive measures demonstrated lower sensitivity. The integrated Alzheimer's Disease Rating Scale (iADRS) and Clinical Dementia Rating‐Sum of Boxes (CDR‐SB) seemed more effective than their individual cognitive components. Neuropsychiatric measures were the least sensitive in measuring progression. DISCUSSION Functional measures generally outperformed other measure categories. Purely cognitive domain‐based measures were suboptimal for tracking early AD progression. Ideally, future measures should incorporate both cognitive and functional components to enhance sensitivity. Highlights Concerns remain regarding the limitations of current outcome measures used in AD clinical trials, particularly their sensitivity in the early and preclinical stages of the disease, which hampers their reliability as indicators of AD progression. The Functional Activities Questionnaire (FAQ) demonstrated the most substantial weighted mean change over 12 weeks, followed by the Mini‐Mental State Examination (MMSE). Functional measures outperformed other measure categories. Composite scores of integrated Alzheimer's Disease Rating Scale and Clinical Dementia Rating‐Sum of Boxes are more sensitive to change than their individual cognitive components, possibly driven by the functional components of the score. Neuropsychiatric measures analyzed in this study appeared to be the least sensitive in measuring progression.

The human genome expresses thousands of natural antisense transcripts (NAT) that can regulate epigenetic state, transcription, RNA stability or translation of their overlapping genes 1 , 2 . Here we describe MAPT-AS1, a brain-enriched NAT that is conserved in primates and contains an embedded mammalian-wide interspersed repeat (MIR), which represses tau translation by competing for ribosomal RNA pairing with the MAPT mRNA internal ribosome entry site 3 . MAPT encodes tau, a neuronal intrinsically disordered protein (IDP) that stabilizes axonal microtubules. Hyperphosphorylated, aggregation-prone tau forms the hallmark inclusions of tauopathies 4 . Mutations in MAPT cause familial frontotemporal dementia, and common variations forming the MAPT H1 haplotype are a significant risk factor in many tauopathies 5 and Parkinson’s disease. Notably, expression of MAPT-AS1 or minimal essential sequences from MAPT-AS1 (including MIR) reduces—whereas silencing MAPT-AS1 expression increases—neuronal tau levels, and correlate with tau pathology in human brain. Moreover, we identified many additional NATs with embedded MIRs (MIR-NATs), which are overrepresented at coding genes linked to neurodegeneration and/or encoding IDPs, and confirmed MIR-NAT-mediated translational control of one such gene, PLCG1 . These results demonstrate a key role for MAPT-AS1 in tauopathies and reveal a potentially broad contribution of MIR-NATs to the tightly controlled translation of IDPs 6 , with particular relevance for proteostasis in neurodegeneration. The natural antisense transcript MAPT-AS1 interferes with translation of mRNA transcript into tau protein in the brain and may represent a general mechanism for controlling levels of intrinsically disordered proteins, with particular relevance for neurodegeneration.

Andrew Singleton, Thomas Gasser and colleagues report results of a genome-wide association study of Parkinson's disease among individuals of European ancestry. They find genome-wide significant associations at two loci, SNCA and MAPT , and provide supporting evidence for a new risk locus on 1q32. We performed a genome-wide association study (GWAS) in 1,713 individuals of European ancestry with Parkinson's disease (PD) and 3,978 controls. After replication in 3,361 cases and 4,573 controls, we observed two strong association signals, one in the gene encoding α-synuclein ( SNCA ; rs2736990, OR = 1.23, P = 2.24 × 10 −16 ) and another at the MAPT locus (rs393152, OR = 0.77, P = 1.95 × 10 −16 ). We exchanged data with colleagues performing a GWAS in Japanese PD cases. Association to PD at SNCA was replicated in the Japanese GWAS 1 , confirming this as a major risk locus across populations. We replicated the effect of a new locus detected in the Japanese cohort ( PARK16 , rs823128, OR = 0.66, P = 7.29 × 10 −8 ) and provide supporting evidence that common variation around LRRK2 modulates risk for PD (rs1491923, OR = 1.14, P = 1.55 × 10 −5 ). These data demonstrate an unequivocal role for common genetic variants in the etiology of typical PD and suggest population-specific genetic heterogeneity in this disease.

Elucidating the genetic determinants influencing Alzheimer's disease (AD) progression is crucial for the rational design of new targeted and efficacious therapeutic interventions. We conducted a genome-wide study utilizing data from 382 participants with amyloid beta status, genetic profiles, and longitudinal clinical assessments, sourced from the Alzheimer's Disease Neuroimaging Initiative and the Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing. Mixed effects models were employed to evaluate the rate of change in Mini-Mental State Examination scores as a quantitative measure of disease progression RESULTS: Variants on chromosome 22q12.1 mapped to ZNRF3, MN1, PIPNB genes reached genome-wide significance and together with nominally significant loci (p <5×10-6) highlighted a role for neuronal resilience (both excitatory and inhibitory neurones) and anti-viral immune responses. The APOE locus was not significantly associated with the rate of progression. Among the known AD risk genes, the OAS locus achieved nominal significance suggesting the interferon pathway has a role in determining rates of progression. The absence of a significant association between APOE and AD progression suggests that alternative pathological pathways, beyond amyloid beta, may represent viable targets for impeding disease advancement. These pathways appear to involve neuronal resilience and immune system modulation.

Genetic baggage check The analysis of genome-wide patterns of variation in human populations can provide genetic evidence of patterns of human migration and adaptation across the world. Two contrasting papers in this issue illustrate the power of the method. By combining a large number of datasets, Lohmueller et al . obtain precise estimates of the number of deleterious mutations carried by each of 15 African-Americans and 20 European-Americans, resequenced across 11,000 genes. They find that individuals with a European background have more potentially damaging mutations lurking in their genomes than those with an African background. This is interpreted as a genetic legacy from the 'out-of-Africa' bottleneck that accompanied the peopling of Europe. Jakobsson et al . take a broader snapshot of human variation by examining 29 populations in the Human Genome Diversity Project. They obtain genotype data for over 500,000 markers in the human genome. Echoing the study of Americans with African and European backgrounds, these data reveal increasing linkage disequilibrium with increasing geographic distance from Africa. A report detailing genotype data for over 500,000 markers in the human genome by examining 29 populations in the Human Genome Diversity Project. Genome-wide patterns of variation across individuals provide a powerful source of data for uncovering the history of migration, range expansion, and adaptation of the human species. However, high-resolution surveys of variation in genotype, haplotype and copy number have generally focused on a small number of population groups 1 , 2 , 3 . Here we report the analysis of high-quality genotypes at 525,910 single-nucleotide polymorphisms (SNPs) and 396 copy-number-variable loci in a worldwide sample of 29 populations. Analysis of SNP genotypes yields strongly supported fine-scale inferences about population structure. Increasing linkage disequilibrium is observed with increasing geographic distance from Africa, as expected under a serial founder effect for the out-of-Africa spread of human populations. New approaches for haplotype analysis produce inferences about population structure that complement results based on unphased SNPs. Despite a difference from SNPs in the frequency spectrum of the copy-number variants (CNVs) detected—including a comparatively large number of CNVs in previously unexamined populations from Oceania and the Americas—the global distribution of CNVs largely accords with population structure analyses for SNP data sets of similar size. Our results produce new inferences about inter-population variation, support the utility of CNVs in human population-genetic research, and serve as a genomic resource for human-genetic studies in diverse worldwide populations.