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We evaluated the efficacy of a social skills training intervention designed to improve adolescents’ social, emotional and behavioral adjustment, Social Skills Group Intervention-Adolescent (S.S.GRIN-A). Seventy-four adolescents (ages 13–16 years) and their parents were randomly assigned to either the treatment group ( N  = 40) or a wait-list control group ( N  = 34). Adolescents in the treatment and control groups were compared on global self-concept, social self-efficacy, internalizing problems, and externalizing problems pre- and post-intervention. Youth in the treatment group demonstrated enhanced global self-concept, increased social self-efficacy, and decreased internalizing problems as compared to youth in the control group. No differences in externalizing behavior were found. We discuss the effectiveness of S.S.GRIN-A as a general program designed for addressing a range of adjustment issues and social skill deficits in adolescents.

This investigation of the effects of stressful life events on rural African American women's relationship well-being, psychological functioning, and parenting included 361 married or long-term cohabiting women. Associations among stressful events, socioeconomic status, perceived racial discrimination, coping strategies, psychological functioning, relationship well-being, and parenting were tested. Stressful events were related directly to diminished relationship well-being and heightened psychological distress and indirectly to compromised parenting. The results can inform research and intervention with African American women.

Transcriptome-wide association analysis is a powerful approach to studying the genetic architecture of complex traits. A key component of this approach is to build a model to impute gene expression levels from genotypes by using samples with matched genotypes and gene expression data in a given tissue. However, it is challenging to develop robust and accurate imputation models with a limited sample size for any single tissue. Here, we first introduce a multi-task learning method to jointly impute gene expression in 44 human tissues. Compared with single-tissue methods, our approach achieved an average of 39% improvement in imputation accuracy and generated effective imputation models for an average of 120% more genes. We describe a summary-statistic-based testing framework that combines multiple single-tissue associations into a powerful metric to quantify the overall gene–trait association. We applied our method, called UTMOST (unified test for molecular signatures), to multiple genome-wide-association results and demonstrate its advantages over single-tissue strategies. UTMOST (unified test for molecular signatures) is a method for cross-tissue gene expression imputation for transcriptome-wide association analyses. Cross-tissue TWAS using UTMOST identifies new candidate genes for late-onset Alzheimer’s disease.

We present an unconventional approach to antiviral drug discovery, which is used to identify potent small molecules against rabies virus. First, we conceptualized viral capsid assembly as occurring via a host-catalyzed biochemical pathway, in contrast to the classical view of capsid formation by self-assembly. This suggested opportunities for antiviral intervention by targeting previously unappreciated catalytic host proteins, which were pursued. Second, we hypothesized these host proteins to be components of heterogeneous, labile, and dynamic multi-subunit assembly machines, not easily isolated by specific target protein-focused methods. This suggested the need to identify active compounds before knowing the precise protein target. A cell-free translation-based small molecule screen was established to recreate the hypothesized interactions involving newly synthesized capsid proteins as host assembly machine substrates. Hits from the screen were validated by efficacy against infectious rabies virus in mammalian cell culture. Used as affinity ligands, advanced analogs were shown to bind a set of proteins that effectively reconstituted drug sensitivity in the cell-free screen and included a small but discrete subfraction of cellular ATP-binding cassette family E1 (ABCE1), a host protein previously found essential for HIV capsid formation. Taken together, these studies advance an alternate view of capsid formation (as a host-catalyzed biochemical pathway), a different paradigm for drug discovery (whole pathway screening without knowledge of the target), and suggest the existence of labile assembly machines that can be rendered accessible as next-generation drug targets by the means described.

Gerard Schellenberg and colleagues report a genome-wide association study of late-onset Alzheimer's disease (LOAD), as part of the Alzheimer Disease Genetics Consortium. They identify common variants in MS4A4/MS4A6E , CD2AP , CD33 and EPHA1 associated with LOAD. The Alzheimer Disease Genetics Consortium (ADGC) performed a genome-wide association study of late-onset Alzheimer disease using a three-stage design consisting of a discovery stage (stage 1) and two replication stages (stages 2 and 3). Both joint analysis and meta-analysis approaches were used. We obtained genome-wide significant results at MS4A4A (rs4938933; stages 1 and 2, meta-analysis P ( P M ) = 1.7 × 10 −9 , joint analysis P ( P J ) = 1.7 × 10 −9 ; stages 1, 2 and 3, P M = 8.2 × 10 −12 ), CD2AP (rs9349407; stages 1, 2 and 3, P M = 8.6 × 10 −9 ), EPHA1 (rs11767557; stages 1, 2 and 3, P M = 6.0 × 10 −10 ) and CD33 (rs3865444; stages 1, 2 and 3, P M = 1.6 × 10 −9 ). We also replicated previous associations at CR1 (rs6701713; P M = 4.6 × 10 −10 , P J = 5.2 × 10 −11 ), CLU (rs1532278; P M = 8.3 × 10 −8 , P J = 1.9 × 10 −8 ), BIN1 (rs7561528; P M = 4.0 × 10 −14 , P J = 5.2 × 10 −14 ) and PICALM (rs561655; P M = 7.0 × 10 −11 , P J = 1.0 × 10 −10 ), but not at EXOC3L2 , to late-onset Alzheimer's disease susceptibility 1 , 2 , 3 .

Genome-wide association studies (GWAS) have identified >80 Alzheimer’s disease and related dementias (ADRD)-associated genetic loci. However, the clinical outcomes used in most previous studies belie the complex nature of underlying neuropathologies. Here we performed GWAS on 11 ADRD-related neuropathology endophenotypes with participants drawn from the following three sources: the National Alzheimer’s Coordinating Center, the Religious Orders Study and Rush Memory and Aging Project, and the Adult Changes in Thought study ( n  = 7,804 total autopsied participants). We identified seven independent significantly associated loci, of which three were new ( COL4A1 , LZTS1 and APOC2 ). Separately testing known ADRD loci, 19 loci were significantly associated with at least one neuropathology after false-discovery rate adjustment. Genetic colocalization analyses identified pleiotropic effects and quantitative trait loci. Methylation in the cerebral cortex at two sites near APOC2 was associated with cerebral amyloid angiopathy. Studies that include neuropathology endophenotypes are an important step in understanding the mechanisms underlying genetic ADRD risk. Genome-wide analyses identify common variants associated with 11 distinct neuropathology endophenotypes, providing insights into the mechanisms underlying the genetic risk of Alzheimer’s disease and related dementias.

Genetics play an important role in late-onset Alzheimer’s Disease (AD) etiology and dozens of genetic variants have been implicated in AD risk through large-scale GWAS meta-analyses. However, the precise mechanistic effects of most of these variants have yet to be determined. Deeply phenotyped cohort data can reveal physiological changes associated with genetic risk for AD across an age spectrum that may provide clues to the biology of the disease. We utilized over 2000 high-quality quantitative measurements obtained from blood of 2831 cognitively normal adult clients of a consumer-based scientific wellness company, each with CLIA-certified whole-genome sequencing data. Measurements included: clinical laboratory blood tests, targeted chip-based proteomics, and metabolomics. We performed a phenome-wide association study utilizing this diverse blood marker data and 25 known AD genetic variants and an AD-specific polygenic risk score (PGRS), adjusting for sex, age, vendor (for clinical labs), and the first four genetic principal components; sex-SNP interactions were also assessed. We observed statistically significant SNP-analyte associations for five genetic variants after correction for multiple testing (for SNPs in or near NYAP1 , ABCA7 , INPP5D , and APOE ), with effects detectable from early adulthood. The ABCA7 SNP and the APOE2 and APOE4 encoding alleles were associated with lipid variability, as seen in previous studies; in addition, six novel proteins were associated with the e2 allele. The most statistically significant finding was between the NYAP1 variant and PILRA and PILRB protein levels, supporting previous functional genomic studies in the identification of a putative causal variant within the PILRA gene. We did not observe associations between the PGRS and any analyte. Sex modified the effects of four genetic variants, with multiple interrelated immune-modulating effects associated with the PICALM variant. In post-hoc analysis, sex-stratified GWAS results from an independent AD case–control meta-analysis supported sex-specific disease effects of the PICALM variant, highlighting the importance of sex as a biological variable. Known AD genetic variation influenced lipid metabolism and immune response systems in a population of non-AD individuals, with associations observed from early adulthood onward. Further research is needed to determine whether and how these effects are implicated in early-stage biological pathways to AD. These analyses aim to complement ongoing work on the functional interpretation of AD-associated genetic variants.

INTRODUCTION Late‐onset Alzheimer's disease (LOAD) has a strong genetic component. Participants in Long‐Life Family Study (LLFS) exhibit delayed onset of dementia, offering a unique opportunity to investigate LOAD genetics. METHODS We conducted a whole genome sequence analysis of 3475 LLFS members. Genetic associations were examined in six independent studies (N = 14,260) with a wide range of LOAD risk. Association analysis in a sub‐sample of the LLFS cohort (N = 1739) evaluated the association of LOAD variants with beta amyloid (Aβ) levels. RESULTS We identified several single nucleotide polymorphisms (SNPs) in tight linkage disequilibrium within the MTUS2 gene associated with LOAD (rs73154407, p = 7.6 × 10−9). Association of MTUS2 variants with LOAD was observed in the five independent studies and was significantly stronger within high levels of Aβ42/40 ratio compared to lower amyloid. DISCUSSION MTUS2 encodes a microtubule associated protein implicated in the development and function of the nervous system, making it a plausible candidate to investigate LOAD biology. Highlights Long‐Life Family Study (LLFS) families may harbor late onset Alzheimer's dementia (LOAD) variants. LLFS whole genome sequence analysis identified MTUS2 gene variants associated with LOAD. The observed LLFS variants generalized to cohorts with wide range of LOAD risk. The association of MTUS2 with LOAD was stronger within high levels of beta amyloid. Our results provide evidence for MTUS2 gene as a novel LOAD candidate locus.

CpG‐related single nucleotide polymorphisms (CGS) have the potential to perturb DNA methylation; however, their effects on Alzheimer disease (AD) risk have not been evaluated systematically. We conducted a genome‐wide association study using a sliding‐window approach to measure the combined effects of CGSes on AD risk in a discovery sample of 24 European ancestry cohorts (12,181 cases, 12,601 controls) from the Alzheimer's Disease Genetics Consortium (ADGC) and replication sample of seven European ancestry cohorts (7,554 cases, 27,382 controls) from the International Genomics of Alzheimer's Project (IGAP). The potential functional relevance of significant associations was evaluated by analysis of methylation and expression levels in brain tissue of the Religious Orders Study and the Rush Memory and Aging Project (ROSMAP), and in whole blood of Framingham Heart Study participants (FHS). Genome‐wide significant (p < 5 × 10−8) associations were identified with 171 1.0 kb‐length windows spanning 932 kb in the APOE region (top p < 2.2 × 10−308), five windows at BIN1 (top p = 1.3 × 10−13), two windows at MS4A6A (top p = 2.7 × 10−10), two windows near MS4A4A (top p = 6.4 × 10−10), and one window at PICALM (p = 6.3 × 10‐9). The total number of CGS‐derived CpG dinucleotides in the window near MS4A4A was associated with AD risk (p = 2.67 × 10−10), brain DNA methylation (p = 2.15 × 10−10), and gene expression in brain (p = 0.03) and blood (p = 2.53 × 10−4). Pathway analysis of the genes responsive to changes in the methylation quantitative trait locus signal at MS4A4A (cg14750746) showed an enrichment of methyltransferase functions. We confirm the importance of CGS in AD and the potential for creating a functional CpG dosage‐derived genetic score to predict AD risk. CpG‐related single nucleotide polymorphisms (CGS) have the potential to perturb DNA methylation. We conducted a genome‐wide sliding window screen to assess the combined effects of multiple CGSes on the risk of Alzheimer disease (AD) in 12,181 cases, and 12,601 controls during discovery and top windows were followed with replication and functional analysis. We found that the CGSes in MS4 region has a dosage effect on AD risk, DNA methylation, and gene expression in human blood and brain.