Genomic loci influence patterns of structural covariance in the human brain.

Normal and pathologic neurobiological processes influence brain morphology in coordinated ways that give rise to patterns of structural covariance (PSC) across brain regions and individuals during brain aging and diseases. The genetic underpinnings of these patterns remain largely unknown. We apply a stochastic multivariate factorization method to a diverse population of 50,699 individuals (12 studies and 130 sites) and derive data-driven, multi-scale PSCs of regional brain size. PSCs were significantly correlated with 915 genomic loci in the discovery set, 617 of which are newly identified, and 72% were independently replicated. Key pathways influencing PSCs involve reelin signaling, apoptosis, neurogenesis, and appendage development, while pathways of breast cancer indicate potential interplays between brain metastasis and PSCs associated with neurodegeneration and dementia. Using support vector machines, multi-scale PSCs effectively derive imaging signatures of several brain diseases. Our results elucidate genetic and biological underpinnings that influence structural covariance patterns in the human brain.

Sirt1 Negatively Regulates Cellular Antiviral Responses by Preventing the Cytoplasmic Translocation of Interferon-Inducible Protein 16 in Human Cells.

Interferon-inducible protein 16 (IFI16) plays a critical role in antiviral innate immune responses against DNA viruses. Although the acetylation of IFI16 is crucial to its cytoplasmic translocation and downstream signal transduction, the regulation of IFI16 acetylation remains unclear. In this study, we demonstrated that the NAD-dependent deacetylase silent information regulatory 1 (Sirtuin1, Sirt1) interacted with IFI16 and decreased the acetylation of IFI16, resulting in the inhibition of IFI16 cytoplasmic localization and antiviral responses against DNA virus and viral DNA in human cells. Meantime, Sirt1 could not inhibit RNA virus-triggered signal transduction. Interestingly, even p204, the murine ortholog of human IFI16, barely interacted with Sirt1. Thus, Sirt1 could not negatively regulate the acetylation of p204 and subsequent signal transduction upon herpes simplex virus 1 (HSV-1) infection in mouse cells. Taken together, our research work showed a new mechanism by which Sirt1 manipulated IFI16-mediated host defense. Our study also demonstrated a difference in the regulation of antiviral host defense between humans and mice, which might be considered in preclinical studies for antiviral treatment. IMPORTANCE DNA viruses, such as hepatitis B virus (HBV), human papillomavirus (HPV), human cytomegalovirus (HCMV), Epstein-Barr virus (EBV), and herpes simplex virus (HSV), can cause a wide range of diseases and are considered a global threat to human health. Interferon-inducible protein 16 (IFI16) binds virus DNA and triggers antiviral innate immune responses to restrict viral infection. In this study, we identified that silent information regulatory 1 (Sirtuin1, Sirt1) interacted with IFI16 and regulated IFI16-mediated innate host defense. Therefore, the activator or inhibitor of Sirt1 may have the potential to be used as a novel strategy to treat DNA virus-associated diseases. We also found that Sirt1 barely interacted with p204, the murine ortholog of human IFI16, and could not negatively regulate innate immune responses upon HSV-1 infection in mouse cells. This difference between humans and mice in the regulation of antiviral host defense might be considered in preclinical studies for antiviral treatment.

Preference matrix guided sparse canonical correlation analysis for mining brain imaging genetic associations in Alzheimer's disease.

Investigating the relationship between genetic variation and phenotypic traits is a key issue in quantitative genetics. Specifically for Alzheimer's disease, the association between genetic markers and quantitative traits remains vague while, once identified, will provide valuable guidance for the study and development of genetics-based treatment approaches. Currently, to analyze the association of two modalities, sparse canonical correlation analysis (SCCA) is commonly used to compute one sparse linear combination of the variable features for each modality, giving a pair of linear combination vectors in total that maximizes the cross-correlation between the analyzed modalities. One drawback of the plain SCCA model is that the existing findings and knowledge cannot be integrated into the model as priors to help extract interesting correlations as well as identify biologically meaningful genetic and phenotypic markers. To bridge this gap, we introduce preference matrix guided SCCA (PM-SCCA) that not only takes priors encoded as a preference matrix but also maintains computational simplicity. A simulation study and a real-data experiment are conducted to investigate the effectiveness of the model. Both experiments demonstrate that the proposed PM-SCCA model can capture not only genotype-phenotype correlation but also relevant features effectively.

Proteomic analyses reveal plasma EFEMP1 and CXCL12 as biomarkers and determinants of neurodegeneration.

INTRODUCTION: Plasma proteomic analyses of unique brain atrophy patterns may illuminate peripheral drivers of neurodegeneration and identify novel biomarkers for predicting clinically relevant outcomes. METHODS: We identified proteomic signatures associated with machine learning-derived aging- and Alzheimer's disease (AD) -related brain atrophy patterns in the Baltimore Longitudinal Study of Aging (n = 815). Using data from five cohorts, we examined whether candidate proteins were associated with AD endophenotypes and long-term dementia risk. RESULTS: Plasma proteins associated with distinct patterns of age- and AD-related atrophy were also associated with plasma/cerebrospinal fluid (CSF) AD biomarkers, cognition, AD risk, as well as mid-life (20-year) and late-life (8-year) dementia risk. EFEMP1 and CXCL12 showed the most consistent associations across cohorts and were mechanistically implicated as determinants of brain structure using genetic methods, including Mendelian randomization. DISCUSSION: Our findings reveal plasma proteomic signatures of unique aging- and AD-related brain atrophy patterns and implicate EFEMP1 and CXCL12 as important molecular drivers of neurodegeneration. HIGHLIGHTS: Plasma proteomic signatures are associated with unique patterns of brain atrophy. Brain atrophy-related proteins predict clinically relevant outcomes across cohorts. Genetic variation underlying plasma EFEMP1 and CXCL12 influences brain structure. EFEMP1 and CXCL12 may be important molecular drivers of neurodegeneration.

Brain-wide genome-wide colocalization study for integrating genetics, transcriptomics and brain morphometry in Alzheimer's disease.

Alzheimer's disease (AD) is one of the most common neurodegenerative diseases. However, the AD mechanism has not yet been fully elucidated to date, hindering the development of effective therapies. In our work, we perform a brain imaging genomics study to link genetics, single-cell gene expression data, tissue-specific gene expression data, brain imaging-derived volumetric endophenotypes, and disease diagnosis to discover potential underlying neurobiological pathways for AD. To do so, we perform brain-wide genome-wide colocalization analyses to integrate multidimensional imaging genomic biobank data. Specifically, we use (1) the individual-level imputed genotyping data and magnetic resonance imaging (MRI) data from the UK Biobank, (2) the summary statistics of the genome-wide association study (GWAS) from multiple European ancestry cohorts, and (3) the tissue-specific cis-expression quantitative trait loci (cis-eQTL) summary statistics from the GTEx project. We apply a Bayes factor colocalization framework and mediation analysis to these multi-modal imaging genomic data. As a result, we derive the brain regional level GWAS summary statistics for 145 brain regions with 482,831 single nucleotide polymorphisms (SNPs) followed by posthoc functional annotations. Our analysis yields the discovery of a potential AD causal pathway from a systems biology perspective: the SNP chr10:124165615:G>A (rs6585827) mutation upregulates the expression of BTBD16 gene in oligodendrocytes, a specialized glial cells, in the brain cortex, leading to a reduced risk of volumetric loss in the entorhinal cortex, resulting in the protective effect on AD. We substantiate our findings with multiple evidence from existing imaging, genetic and genomic studies in AD literature. Our study connects genetics, molecular and cellular signatures, regional brain morphologic endophenotypes, and AD diagnosis, providing new insights into the mechanistic understanding of the disease. Our findings can provide valuable guidance for subsequent therapeutic target identification and drug discovery in AD.

Ultraportable Flow Cytometer Based on an All-Glass Microfluidic Chip.

The flow cytometer has become a powerful and widely accepted measurement device in both biological studies and clinical diagnostics. The application of the flow cytometer in emerging point-of-care scenarios, such as instant detection in remote areas and emergency diagnosis, requires a significant reduction in physical dimension, cost, and power consumption. This requirement promotes studies to develop portable flow cytometers, mostly based on the utilization of polymer microfluidic chips. However, due to the relatively poor optical performance of polymer materials, existing microfluidic flow cytometers are incapable of accurate blood analysis, such as the four-part leukocyte differential count, which is necessary to monitor the immune system and to assess the risk of allergic inflammation or viral infection. To address this issue, an ultraportable flow cytometer based on an all-glass microfluidic chip (AG-UFCM) has been developed in this study. Compared with that of a typical commercial flow cytometer (BD FACSAria III), the volume of the AG-UFCM was reduced by 90 times (from 720 to 8 L). A two-step laser processing was employed to fabricate an all-glass microfluidic chip with a surface roughness of less than 1 nm, significantly improving the optical performance of on-chip micro-lens. The signal-to-noise ratio was enhanced by 3 dB, compared with that of polymer materials. For the first time, a four-part leukocyte differential count based on single fluorescence staining was realized using a miniaturized flow cytometer, laying a foundation for the point-of-care testing of miniaturized flow cytometers.

Association of brain microbleeds with risk factors, cognition, and MRI markers in MESA.

INTRODUCTION: Little is known about the epidemiology of brain microbleeds in racially/ethnically diverse populations. METHODS: In the Multi-Ethnic Study of Atherosclerosis, brain microbleeds were identified from 3T magnetic resonance imaging susceptibility-weighted imaging sequences using deep learning models followed by radiologist review. RESULTS: Among 1016 participants without prior stroke (25% Black, 15% Chinese, 19% Hispanic, 41% White, mean age 72), microbleed prevalence was 20% at age 60 to 64.9 and 45% at ≥85 years. Deep microbleeds were associated with older age, hypertension, higher body mass index, and atrial fibrillation, and lobar microbleeds with male sex and atrial fibrillation. Overall, microbleeds were associated with greater white matter hyperintensity volume and lower total white matter fractional anisotropy. DISCUSSION: Results suggest differing associations for lobar versus deep locations. Sensitive microbleed quantification will facilitate future longitudinal studies of their potential role as an early indicator of vascular pathology.

RNF90 negatively regulates cellular antiviral responses by targeting MITA for degradation.

Mediator of IRF3 activation (MITA, also named as STING/ERIS/MPYS/TMEM173), is essential to DNA virus- or cytosolic DNA-triggered innate immune responses. In this study, we demonstrated the negative regulatory role of RING-finger protein (RNF) 90 in innate immune responses targeting MITA. RNF90 promoted K48-linked ubiquitination of MITA and its proteasome-dependent degradation. Overexpression of RNF90 inhibited HSV-1- or cytosolic DNA-induced immune responses whereas RNF90 knockdown had the opposite effects. Moreover, RNF90-deficient bone marrow-derived dendritic cells (BMDCs), bone marrow-derived macrophages (BMMs) and mouse embryonic fibroblasts (MEFs) exhibited increased DNA virus- or cytosolic DNA-triggered signaling and RNF90 deficiency protected mice from DNA virus infection. Taken together, our findings suggested a novel function of RNF90 in innate immunity.

Heavy metal blood concentrations in association with sociocultural characteristics, anthropometry and anemia among Kenyan adolescents.

OBJECTIVES: To measure heavy metal concentrations among Kenyan youth and quantify associations with sociocultural, demographic, and health factors as well as anthropometry. METHODS: Using data from a study of semi-nomadic pastoralists in Samburu County, Kenya, we measured blood concentrations of lead (Pb), mercury (Hg), and cadmium (Cd) in 161 adolescents. We identified sociocultural, demographic and health characteristics associated with each metal and quantified the association between metals and adolescent anthropometry. RESULTS: Median blood concentrations of Pb, Cd, and Hg were 1.82 µg/dL, 0.24 µg/L and 0.16 µg/L, respectively. Place of residence (highlands vs lowlands) was a determinant of metal concentrations. Hg was inversely related to anemia, and metals were not associated with anthropometry. CONCLUSIONS: In this population of Samburu adolescents, median Pb and Cd blood concentrations were higher than other North American or European biomonitoring studies. These findings motivate further investigation into the environmental sources of metals in this community.

Egg intervention effect on linear growth no longer present after two years.

The Lulun Project, a randomized controlled trial conducted in 2015, found that one egg per day for 6 months during early complementary feeding reduced stunting by 47% and increased linear growth by 0.63 length-for-age Z (LAZ). This follow-up cohort study (Lulun Project II) aimed to test whether the growth effect remained in the egg intervention group compared with the control group after approximately 2 years. Mothers or caregivers from the Lulun Project were recontacted and recruited for this study. Enumerators collected data on socio-economic and demographic factors, 24-hr frequency of dietary intakes, morbidities, and anthropometric measures of height, weight, and head circumference using World Health Organization protocols. Statistical analyses followed the same analytical plan as Lulun Project, applying generalized linear models and regression modelling to test group differences in height-for-age z (HAZ) from LAZ at Lulun Project endline, and structural equation modelling for mediation. One hundred thirty-five mother-child dyads were included in Lulun II, with 11% losses to follow-up from endline Lulun Project. Growth faltering across all children was evident with HAZ -2.07 ± 0.91 and a stunting prevelance of 50%. Regression modelling showed no difference between egg and control groups for the HAZ outcome and other anthropometric outcomes, and significant declines in HAZ from endline Lulun Project in the egg intervention are compared with control groups. Current dietary egg intake, however, was associated with reduced growth faltering in HAZ from Lulun Project endline to Lulun Project II, independent of group assignment and through mediation, explaining 8.8% of the total effect. Findings suggest the need for a longer intervention period and ongoing nutrition support to young children during early childhood.