Interaction-integrated linear mixed model reveals 3D-genetic basis underlying Autism.

Genetic interactions play critical roles in genotype-phenotype associations. We developed a novel interaction-integrated linear mixed model (ILMM) that integrates a priori knowledge into linear mixed models. ILMM enables statistical integration of genetic interactions upfront and overcomes the problems of searching for combinations. To demonstrate its utility, with 3D genomic interactions (assessed by Hi-C experiments) as a priori, we applied ILMM to whole-genome sequencing data for Autism Spectrum Disorders (ASD) and brain transcriptome data, revealing the 3D-genetic basis of ASD and 3D-expression quantitative loci (3D-eQTLs) for brain tissues. Notably, we reported a potential mechanism involving distal regulation between FOXP2 and DNMT3A, conferring the risk of ASD.

Detecting depression in persons living in long-term care: a systematic review and meta-analysis of diagnostic test accuracy studies.

OBJECTIVE: Depressive disorders are common in long-term care (LTC), however, there is no one process used to detect depressive disorders in this setting. Our goal was to describe the diagnostic accuracy of depression detection tools used in LTC settings. METHODS: We conducted a systematic review and meta-analysis of diagnostic accuracy measures. The databases PubMed, EMBASE, PsycINFO and CINAHL were searched from inception to 10 September 2021. Studies involving persons living in LTC, assisted living residences or facilities, comparing diagnostic accuracy of depression tools with a reference standard, were included. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool was used to assess risk of bias. RESULTS: We identified 8,463 citations, of which 20 studies were included in qualitative synthesis and 19 in meta-analysis. We identified 23 depression detection tools (including different versions) that were validated against a reference standard. At a cut-off point of 6 on the Geriatric Depression Scale-15 (GDS-15), the pooled sensitivity was 73.6% (95% confidence interval (CI) 43.9%-76.5%), specificity was 76.5% (95% CI 62.9%-86.7%), and an area under the curve was 0.83. There was significant heterogeneity in these analyses. There was insufficient data to conduct meta-analysis of other screening tools. The Nursing Homes Short Depression Inventory (NH-SDI) had a sensitivity ranging from 40.0% to 98.0%. The 4-item Cornell Scale for Depression in Dementia (CSDD) had the highest sensitivity (67.0%-90.0%) for persons in LTC living with dementia. CONCLUSIONS: There are 23 tools validated for detection of depressive disorders in LTC, with the GDS-15 being the most studied. Tools developed specifically for use in LTC settings include the NH-SDI and CSDD-4, which provide briefer options to screen for depression. However, more studies of both are needed to examine tool accuracy using meta-analyses.

Silent brain infarctions and cognition decline: systematic review and meta-analysis.

BACKGROUND: Silent brain infarction (SBI) may be associated with cognitive decline in the general population. We systematically reviewed prior literature on: (1) SBI and cognition cross-sectionally; (2) baseline SBI and future cognitive decline and risk for cognitive disorders including dementia, and (3) incident SBI and the emergence of cognitive decline or cognitive disorders. METHODS: The MEDLINE and EMBASE databases were searched for relevant studies. Data were independently extracted by two reviewers. Quality was assessed using the Newcastle Ottawa Scale. Data were pooled using a random effects model when more than two comparable estimates were found. RESULTS: Thirty relevant studies were identified: 17 had a cross-sectional design, 10 evaluated the association of baseline SBI with future cognitive decline, and 5 evaluated the association of incident SBI with cognitive decline. Most cross-sectional studies reported lower cognitive performance in persons with SBI. The pooled risk for incident dementia in persons with SBI was 1.48 (95% CI 1.12-1.97), but there was significant heterogeneity (p = 0.009); removing one outlier eliminated the heterogeneity (p = 0.53), giving a lower but still significant estimate (hazard ratio 1.27, 95% CI 1.06-1.51). The pooled risk for incident MCI was not increased in persons with SBI (hazard ratio 0.83, 95% CI 0.40 to 1.72), but there was significant heterogeneity (p < 0.001). The appearance of new SBI was associated with steeper rate of cognitive decline and the appearance of dementia. CONCLUSIONS: SBI are associated with worse cognition and increased risk for dementia. More standardization of cognitive assessment methods would facilitate future cross-study comparisons.

Detection of anxiety symptoms in persons with dementia: A systematic review.

INTRODUCTION: Anxiety is a common symptom for those experiencing dementia and is associated with worse outcomes. The aim of the study was to examine which anxiety tools have been validated compared with a gold standard diagnostic criterion in persons with dementia. METHODS: We completed a systematic review of the literature, which was registered a priori with PROSPERO (CRD42016042123). Three databases were searched, MEDLINE, EMBASE, and PsycINFO, as well as the gray literature. Abstracts and full text were searched in duplicate for inclusion. Risk of bias was assessed in duplicate. RESULTS: We identified 9626 citations from all sources after duplicates were removed. Many excluded studies used tools for anxiety, for which no diagnostic accuracy study was identified. Four articles were included in the final synthesis. Included articles had between 32 to 101 participants with mild to moderate dementia. The gold standard criteria focused on either generalized anxiety or all anxiety subtypes. The prevalence of anxiety was between 27.7% and 63.4%. Three tools were examined, the Geriatric Anxiety Inventory, Penn State Worry Questionnaire, and the Rating Anxiety in Dementia (RAID) scale. Sensitivity varied but was the highest in the RAID at 90% and lowest in the self-rated version of the Geriatric Anxiety Inventory (58%). DISCUSSION: Given how burdensome the symptoms of anxiety are to persons with dementia, valid tools are needed to help identify symptoms. We identified three validated tools, but further validation of these and other tools are needed. Practitioners should consider the use of tools with high sensitivity such as the RAID in persons with dementia.