Introduction: Several microRNAs (miRNAs) have been implicated in Alzheimer's disease pathogenesis, but the evidence from individual case-control studies remains inconclusive. Methods: A systematic literature review was performed, followed by standardized multistage data extraction, quality control, and meta-analyses on eligible data for brain, blood, and cerebrospinal fluid specimens. Results were compared with miRNAs reported in the abstracts of eligible studies or recent qualitative reviews to assess novelty. Results: Data from 147 independent data sets across 107 publications were quantitatively assessed in 461 meta-analyses. Twenty-five, five, and 32 miRNAs showed studywide significant differential expression (a , 1$08 ! 10 24 ) in brain, cerebrospinal fluid, and blood-derived specimens, respectively, with 5 miRNAs showing differential expression in both brain and blood. Of these 57 miRNAs, 13 had not been reported in the abstracts of previous original or review articles. Discussion: Our systematic assessment of differential miRNA expression is the first of its kind in Alzheimer's disease and highlights several miRNAs of potential relevance.

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Objective: MicroRNA (miRNA)-mediated (dys)regulation of gene expression has been implicated in Parkinson's disease (PD), although results of miRNA expression studies remain inconclusive. We aimed to identify miRNAs that show consistent differential expression across all published expression studies in PD. Methods: We performed a systematic literature search on miRNA expression studies in PD and extracted data from eligible publications. After stratification for brain, blood, and cerebrospinal fluid (CSF)-derived specimen, we performed meta-analyses across miRNAs assessed in three or more independent data sets. Meta-analyses were performed using effect-size-and p-value-based methods, as applicable. Results: After screening 599 publications, we identified 47 data sets eligible for meta-analysis. On these, we performed 160 meta-analyses on miRNAs quantified in brain (n = 125), blood (n = 31), or CSF (n = 4). Twenty-one meta-analyses were performed using effect sizes. We identified 13 significantly (Bonferroni-adjusted α = 3.13 × 10 -4 ) differentially expressed miRNAs in brain (n = 3) and blood (n = 10) with consistent effect directions across studies. The most compelling findings were with hsa-miR-132-3p (p = 6.37 × 10 -5 ), hsa-miR-497-5p (p = 1.35 × 10 -4 ), and hsa-miR-133b (p = 1.90 × 10 -4 ) in brain and with hsa-miR-221-3p (p = 4.49 × 10 -35 ), hsa-miR-214-3p (p = 2.00 × 10 -34 ), and hsa-miR-29c-3p (p = 3.00 × 10 -12 ) in blood. No significant signals were found in CSF. Analyses of genome-wide association study data for target genes of brain miRNAs showed significant association (α = 9.40 × 10 -5 ) of genetic variants in nine loci. Interpretation: We identified several miRNAs that showed highly significant differential expression in PD. Future studies may assess the possible role of the identified brain miRNAs in pathogenesis and disease progression as well as the potential of the top blood miRNAs as biomarkers for diagnosis, progression, or prediction of PD. ANN NEUROL 2019;85:835-851 P arkinson's disease (PD) is the second-most common neurodegenerative disease affecting 1% of people over the age of 60. The increasing incidence of PD in industrialized, aging populations constitutes a growing socioeconomic burden. 1 Idiopathic PD results from a combination of multiple genetic 2-4 and environmental/lifestyle factors. 5,6 However, the currently known risk factors only explain a small fraction of the phenotypic variance of PD. Likewise, PD View this article online at wileyonlinelibrary.com.

ObjectiveMicroRNA-mediated (dys)regulation of gene expression has been implicated in Parkinson’s disease (PD), although results of microRNA expression studies remain inconclusive. We aimed to identify microRNAs that show consistent differential expression across all published expression studies in PD.MethodsWe performed a systematic literature search on microRNA expression studies in PD and extracted data from eligible publications. After stratification for brain, blood, and cerebrospinal fluid (CSF)-derived specimen we performed meta-analyses across microRNAs assessed in three or more independent datasets. Meta-analyses were performed using effect-size and p-value based methods, as applicable.ResultsAfter screening 599 publications we identified 47 datasets eligible for meta-analysis. On these, we performed 160 meta-analyses on microRNAs quantified in brain (n=125), blood (n=31), or CSF samples (n=4). Twenty-one meta-analyses were performed using effect sizes. We identified 13 significantly (Bonferroni-adjusted α=3.13×10-4) differentially expressed microRNAs in brain (n=3) and blood (n=10) with consistent effect directions across studies. The most compelling findings were with hsa-miR-132-3p (p=6.37×10-5), hsa-miR-497-5p (p=1.35×10-4), and hsa-miR-133b (p=1.90×10-4) in brain, and with hsa-miR-221-3p (p=4.49×10-35), hsa-miR-214-3p (p=2.00×10-34), and hsa-miR-29c-3p (p=3.00×10-12) in blood. No significant signals were found in CSF. Analyses of GWAS data for target genes of brain microRNAs showed significant association (α=9.40×10-5) of genetic variants in nine loci.InterpretationWe identified several microRNAs that showed highly significant differential expression in PD. Future studies may assess the possible role of the identified brain miRNAs in pathogenesis and disease progression as well as the potential of the top blood microRNAs as biomarkers for diagnosis, progression or prediction of PD.

A small number of de novo assembled human genomes have been reported to date, and few have been complemented with population-based genetic variation, which is particularly important for North Africa, a region underrepresented in current genome-wide references. Here, we combine long- and short-read whole-genome sequencing data with recent assembly approaches into a de novo assembly of an Egyptian genome. The assembly demonstrates well-balanced quality metrics and is complemented with variant phasing via linked reads into haploblocks, which we associate with gene expression changes in blood. To construct an Egyptian genome reference, we identify genome-wide genetic variation within a cohort of 110 Egyptian individuals. We show that differences in allele frequencies and linkage disequilibrium between Egyptians and Europeans may compromise the transferability of European ancestry-based genetic disease risk and polygenic scores, substantiating the need for multi-ethnic genome references. Thus, the Egyptian genome reference will be a valuable resource for precision medicine.

The pathogenesis of T-cell large granular lymphocytic leukemia (T-LGL) is poorly understood, as STAT3 mutations are the only known frequent genetic lesions. Here, we identified non-synonymous alterations in the TNFAIP3 tumor suppressor gene in 3 of 39 T-LGL. In two cases these were somatic mutations, in one case the somatic origin was likely. A further case harbored a SNP that is a known risk allele for autoimmune diseases and B cell lymphomas. Thus, TNFAIP3 mutations represent recurrent genetic lesions in T-LGL that affect about 8% of cases, likely contributing to deregulated NF-jB activity in this leukemia.

We present a mathematical model and exact algorithm for optimally aligning protein structures using the DALI scoring model. This scoring model is based on comparing the interresidue distance matrices of proteins and is used in the popular DALI software tool, a heuristic method for protein structure alignment. Our model and algorithm extend an integer linear programming approach that has been previously applied for the related, but simpler, contact map overlap problem. To this end, we introduce a novel type of constraint that handles negative score values and relax it in a Lagrangian fashion. The new algorithm, which we call DALIX, is applicable to any distance matrix-based scoring scheme. We also review options that allow to consider fewer pairs of interresidue distances explicitly because their large number hinders the optimization process. Using four known data sets of varying structural similarity, we compute many provably score-optimal DALI alignments. This allowed, for the first time, to evaluate the DALI heuristic in sound mathematical terms. The results indicate that DALI usually computes optimal or close to optimal alignments. However, we detect a subset of small proteins for which DALI fails to generate any significant alignment, although such alignments do exist.

Introduction Genome‐wide association studies have led to numerous genetic loci associated with Alzheimer's disease (AD). Whole‐genome sequencing (WGS) now permits genome‐wide analyses to identify rare variants contributing to AD risk. Methods We performed single‐variant and spatial clustering–based testing on rare variants (minor allele frequency [MAF] ≤1%) in a family‐based WGS‐based association study of 2247 subjects from 605 multiplex AD families, followed by replication in 1669 unrelated individuals. Results We identified 13 new AD candidate loci that yielded consistent rare‐variant signals in discovery and replication cohorts (4 from single‐variant, 9 from spatial‐clustering), implicating these genes: FNBP1L, SEL1L, LINC00298, PRKCH, C15ORF41, C2CD3, KIF2A, APC, LHX9, NALCN, CTNNA2, SYTL3, and CLSTN2. Discussion Downstream analyses of these novel loci highlight synaptic function, in contrast to common AD‐associated variants, which implicate innate immunity and amyloid processing. These loci have not been associated previously with AD, emphasizing the ability of WGS to identify AD‐associated rare variants, particularly outside of the exome.