Biology subjects

Fongang, B.

Publications and source records attributed to Fongang, B..

14 recordsLinked to original sources

bioRxiv2025

Early Metabolic Alterations in Cerebrospinal Fluid Fatty Acid Profiles Linked to Cognitive Decline and All-Cause Dementia

BackgroundWhile All-cause dementia (ACD) may often be characterized by the abnormal deposition of extracellular {beta}-amyloid (A{beta}) in the brain cortex and hyperphosphorylated tau (p-tau) as neurofibrillary tangles intracellularly, there is a need to identify early metabolic changes that may accompany these pathological changes. ObjectiveThis study evaluated the predictive value of fatty acids in cerebrospinal fluid (CSF) fractions in differentiating cognitively unimpaired (CU), mild cognitive impairment (MCI), and ACD participants. MethodsCSF fatty acid profiles were analyzed from CU (n=68), MCI (n=38), and ACD (n=37) individuals aged 77.3 {+/-} 7.7 years, sourced from the Huntington Medical Research Institutes (HMRI). Multivariable binary logistic regression identified the most effective CSF fatty acid biomarkers for distinguishing CU, MCI, and ACD groups. The top-performing CSF fatty acid biomarkers were combined with A{beta}42, tau, and the A{beta}42/tau ratio to evaluate their collective diagnostic performance. The model was adjusted for covariates, including age, sex, smoking status, hypertension, diabetes, and APOE genotype. Receiver operating characteristic (ROC) curves were generated for the top 10 CSF fatty acids ranked by area under the curve (AUC), sensitivity, and specificity, and their significance was assessed using the DeLong test. ResultsThe top 10 fatty acids in CSF fractions demonstrated superior discrimination between CU individuals and those with MCI compared to traditional markers such as A{beta}42, tau, and the A{beta}42/tau ratio. Furthermore, incorporating a panel of these fatty acid biomarkers alongside A{beta}42/tau significantly improved diagnostic accuracy. Age, sex, smoking, hypertension, APOE genotype, and diabetes did not significantly influence the models performance. ConclusionThis study suggests that changes in fatty acid metabolism occur in early ACD pathology. Thus, strategies that regulate fatty acid metabolism may prevent cognitive decline in an older population. HighlightsO_LIThis study revealed that CSF fractions fatty acids have a better discriminatory power for CU from MCI than CSF A{beta}42, tau, and A{beta}42/tau ratio. C_LIO_LIA panel of CSF fraction fatty acids combined with A{beta}42/tau remarkably improved its diagnostic performance for differential diagnosis of CU, MCI, and ACD. C_LIO_LIClinical evaluation of these fatty acids will strengthen the detection of early cognitive impairment. A prospective large cohort multicenter study of the diagnostic utility of CSF fractions fatty acids will provide robust evidence before extensive clinical usage of these fatty acids. C_LI

neuroscience↗

bioRxiv2025

Altered Gut Microbiota Mediates the Association between APOE Genotype and Amyloid-β Accumulation in Middle-Aged Adults

ImportanceThe apolipoprotein E (APOE) {varepsilon}4 allele is the strongest genetic risk factor for Alzheimers disease (AD), yet the mechanisms linking APOE to amyloid-{beta} (A{beta}) pathology remain incompletely understood. Emerging evidence suggests that the gut microbiome may modulate neurodegeneration; however, its role as a mediator in the APOE-A{beta} relationship remains unclear. ObjectiveTo evaluate whether specific microbial taxa mediate APOE-related effects on brain A{beta} burden in an established population-based study of middle-aged adults. Design, Setting, and ParticipantsThis cross-sectional study analyzed data from the Framingham Heart Study cohort. Data were collected at the third examination visit (n = 227, %Female = 58, mean age = 56.5 {+/-} 8.3), between 2016 and 2019. ExposuresGut bacterial DNA was sequenced using 16S rRNA, and amplicon sequence variants (ASVs) were agglomerated at various taxonomic levels (14 phyla, 70 families, and [~]140 genera). APOE genotypes were derived from blood DNA using PCR and restriction isotyping. Predicted microbial functional potential was based on KEGG Orthologs. Main Outcomes and MeasuresOverall and regional measures of cerebral amyloid-{beta} deposition were assessed using carbon-11 Pittsburgh (PiB) Compound-B PET scans. The global PiB deposition served as the primary outcome for "overall" amyloid burden. Regional amyloid deposition values were analyzed as secondary outcomes. ResultsA higher A{beta} burden was significantly associated with the depletion of protective genera (e.g., Faecalibacterium {beta} [95%CI],-0.35 [-0.40,-0.30]; Ruminococcus-0.25 [-0.27,-0.23]; Butyricicoccus-0.27 [-0.32,-0.22]) and the enrichment of pro-inflammatory taxa (e.g., Alistipes 0.07 [0.06, 0.08], Bacteroides 0.10 [0.07, 0.13]) and Barnesiella (0.18 [0.16, 0.20]). These associations were more pronounced in APOE {varepsilon}4 carriers, who exhibited a broader spectrum of microbial dysbiosis. Mediation analysis showed that Ruminococcus, Butyricicoccus, Clostridium, and Christensenellaceae collectively mediated [~]0.3-0.4% of the effect of APOE {varepsilon}4 on global A{beta} burden. Functional profiling revealed a reduced abundance of microbial genes involved in key metabolic pathways among individuals with higher A{beta} levels. Conclusion and RelevanceGut microbiome composition partially mediates the relationship between APOE {varepsilon}4 and cerebral amyloid burden. These findings support a gut-brain axis mechanism in AD and suggest that microbiome-targeted interventions may mitigate APOE-related risk.

neuroscience↗

bioRxiv2025

Adherence to Lifes Essential 8 Enhances Gut Microbiota Diversity and Cognitive Performance

Emerging evidence suggests a complex interplay among cardiovascular health, gut microbiome composition, and cognitive function. Lifes Essential 8 (LE8), developed by the American Heart Association, includes vital metrics of cardiovascular health, such as diet, physical activity, nicotine exposure, sleep health, body mass index (BMI), blood glucose, blood lipids, and blood pressure. In this study, we analyzed data from 781 participants in the Framingham Heart Study (FHS) to explore the relationship between LE8 adherence, gut microbiota, and cognitive performance. Participants with greater adherence to LE8 demonstrated significantly increased gut microbial diversity (-diversity: Chao1, p = 0.0014; Shannon, p = 0.0071) and distinct microbial compositions ({beta}-diversity: PERMANOVA p = 1e-4). Higher adherence to LE8 was related to an increased abundance of genera Barnesiella and Ruminococcus, while a reduced abundance of Clostridium was associated with higher LE8 adherence. Greater gut microbial diversity (-diversity: Chao1, p = 0.0012; Shannon, p = 0.0066), and beneficial genera like Oscillospira correlated with better global cognitive scores (GCS). Taxonomic overlap analyses revealed microbial taxa that simultaneously influence both LE8 adherence and cognitive outcomes. Mediation analyses indicated that specific taxa, including Barnesiella and Lentisphaerae, mediated the link between LE8 adherence and cognitive performance. These taxa may serve as key modulators in the gut-brain axis, connecting cardiovascular and brain health. Conversely, higher Clostridium abundance was associated with poorer cognitive performance. This study highlights the significance of comprehensive cardiovascular health metrics in shaping gut microbiota and enhancing cognitive resilience. Our findings underscore the therapeutic potential of targeting gut microbiota to mitigate cognitive decline, warranting further exploration through longitudinal and metagenomic studies.

neuroscience↗

bioRxiv2024

Differential Patterns of Gut and Oral Microbiomes in Hispanic Individuals with Cognitive Impairment

Alzheimers disease and related dementias (ADRD) have been associated with alterations in both oral and gut microbiomes. While extensive research has focused on the role of gut dysbiosis in ADRD, the contribution of the oral microbiome remains relatively understudied. Furthermore, the potential synergistic interactions between oral and gut microbiomes in ADRD pathology are largely unexplored. This study aims to evaluate distinct patterns and potential synergistic effects of oral and gut microbiomes in a cohort of predominantly Hispanic individuals with cognitive impairment (CI) and without cognitive impairment (NC). We conducted 16S rRNA gene sequencing on stool and saliva samples from 32 participants (17 CI, 15 NC; 62.5% female, mean age = 70.4 {+/-} 6.2 years) recruited in San Antonio, Texas, USA. Correlation analysis through MaAslin2 assessed the relationship between participants clinical measurements (e.g., fasting glucose and blood cholesterol) and their gut and saliva microbial contents. Differential abundance analysis evaluated taxa with significant differences between CI and NC groups, and alpha and beta diversity metrics assessed within-sample and group compositional differences. Our analyses revealed no significant differences between NC and CI groups in fasting glucose or blood cholesterol levels. However, a clear association was observed between gut microbiome composition and levels of fasting glucose and blood cholesterol. While alpha and beta diversity metrics showed no significant differences between CI and NC groups, differential abundance analysis revealed an increased presence of oral genera such as Dialister, Fretibacterium, and Mycoplasma in CI participants. Conversely, CI individuals exhibited a decreased abundance of gut genera, including Shuttleworthia, Holdemania, and Subdoligranulum, which are known for their anti-inflammatory properties. No evidence was found for synergistic contributions between oral and gut microbiomes in the context of ADRD. Our findings suggest that similar to the gut microbiome, the oral microbiome undergoes significant modifications as individuals transition from NC to CI. Notably, the identified oral microbes have been previously associated with periodontal diseases and gingivitis. These results underscore the necessity for further investigations with larger sample sizes to validate our findings and elucidate the complex interplay between oral and gut microbiomes in ADRD pathogenesis.

neuroscience↗

bioRxiv2024

Quinolinic acid links kidney injury to brain toxicity

Kidney dysfunction often leads to neurological impairment, yet the complex kidney-brain relationship remains elusive. We employed spatial and bulk metabolomics to investigate a mouse model of rapid kidney failure induced by mouse double minute 2 (Mdm2) conditional deletion in the kidney tubules to interrogate kidney and brain metabolism. Pathway enrichment analysis of focused plasma metabolomics panel pinpointed tryptophan metabolism as the most altered pathway with kidney failure. Spatial metabolomics showed toxic tryptophan metabolites in the kidneys and brains, revealing a novel connection between advanced kidney disease and accelerated kynurenine degradation. In particular, the excitotoxic metabolite quinolinic acid was localized in ependymal cells adjacent to the ventricle in the setting of kidney failure. These findings were associated with brain inflammation and cell death. A separate mouse model of acute kidney injury also had an increase in circulating toxic tryptophan metabolites along with altered brain inflammation. Patients with advanced CKD similarly demonstrated elevated plasma kynurenine metabolites and quinolinic acid was uniquely correlated with fatigue and reduced quality of life in humans. Overall, our study identifies the kynurenine pathway as a bridge between kidney decline, systemic inflammation, and brain toxicity, offering potential avenues for diagnosis and treatment of neurological issues in kidney disease.

molecular biology↗

bioRxiv2024

Nanopore-based DNA long-read sequencing analysis of the aged human brain

Studies in laboratory models and postmortem human brain tissue from patients with Alzheimers disease have revealed disruption of basic cellular processes such as DNA repair and epigenetic control as drivers of neurodegeneration. While genomic alterations in regions of the genome that are rich in repetitive sequences, often termed "dark regions," are difficult to resolve using traditional sequencing approaches, long-read technologies offer promising new avenues to explore previously inaccessible regions of the genome. In the current study, we leverage nanopore-based long-read whole-genome sequencing of DNA extracted from postmortem human frontal cortex at early and late stages of Alzheimers disease, as well as age-matched controls, to analyze retrotransposon insertion events, non-allelic homologous recombination (NAHR), structural variants and DNA methylation within retrotransposon loci and other repetitive/dark regions of the human genome. Interestingly, we find that retrotransposon insertion events and repetitive element-associated NAHR are particularly enriched within centromeric and pericentromeric regions of DNA in the aged human brain, and that ribosomal DNA (rDNA) is subject to a high degree of NAHR compared to other regions of the genome. We detect a trending increase in potential somatic retrotransposition events of the small interfering nuclear element (SINE) AluY in late-stage Alzheimers disease, and differential changes in methylation within repetitive elements and retrotransposons according to disease stage. Taken together, our analysis provides the first long-read DNA sequencing-based analysis of retrotransposon sequences, NAHR, structural variants, and DNA methylation in the aged brain, and points toward transposable elements, centromeric/pericentromeric regions and rDNA as hotspots for genomic variation.

genomics↗

bioRxiv2022

A meta-analysis of genome-wide association studies identifies new genetic loci associated with all-cause and vascular dementia

Dementia is multifactorial with Alzheimer (AD) and vascular (VaD) pathologies making the largest contributions. Genome-wide association studies (GWAS) have identified over 70 genetic risk loci for AD but the genomic determinants of other dementias, including VaD remain understudied. We hypothesize that common forms of dementia will share genetic risk factors and conducted the largest GWAS to date of "all-cause dementia" (ACD) and examined the genetic overlap with VaD. Our dataset includes 809,299 individuals from European, African, Asian, and Hispanic ancestries with 46,902 and 8,702 cases of ACD and VaD, respectively. We replicated known AD loci at genome-wide significance for both ACD and VaD and conducted bioinformatic analyses to prioritize genes that are likely functionally relevant, and shared with closely related traits and risk factors. For ACD, novel loci identified were associated with energy transport (SEMA4D), neuronal excitability (ANO3), amyloid deposition in the brain (RBFOX1), and MRI markers of small vessel disease (HBEGF). Novel VaD loci were associated with hypertension, diabetes, and neuron maintenance (SPRY2, FOXA2, AJAP1, and PSMA3). Our study identified genetic risks underlying all-cause dementia, demonstrating overlap with neurodegenerative processes, vascular risk factors (Type-II diabetes, blood pressure, lipid) and cerebral small vessel disease. These novel insights could lead to new prevention and treatment strategies for all dementias.

genetics↗

bioRxiv2022

Cerebral Small Vessel Disease Burden is Associated with Decreased Abundance of Gut Barnesiella intestinihominis Bacterium in the Framingham Heart Study

A bidirectional communication exists between the brain and the gut, in which the gut microbiota influences cognitive function and vice-versa. Gut dysbiosis has been linked to several diseases, including Alzheimers disease and related dementias (ADRD). However, the relationship between gut dysbiosis and markers of cerebral small vessel disease (cSVD), a major contributor to ADRD, is unknown. In this cross-sectional study, we examined the connection between the gut microbiome, cognitive, and neuroimaging markers of cSVD in the Framingham Heart Study (FHS). Markers of cSVD included white matter hyperintensities (WMH), peak width of skeletonized mean diffusivity (PSMD), and executive function (EF), estimated as the difference between the trail-making tests B and A. We included 972 FHS participants with MRI scans, neurocognitive measures, and stool samples and quantified the gut microbiota composition using 16S rRNA sequencing. We used multivariable association and differential abundance analyses adjusting for age, sex, BMI, and education level to estimate the association between gut microbiota and WMH, PSMD, and EF measures. Our results suggest an increased abundance of Pseudobutyrivibrio and Ruminococcus genera was associated with lower WMH and PSMD (p-values < 0.001), as well as better executive function (p-values < 0.01). In addition, in both differential and multivariable analyses, we found that the gram-negative bacterium Barnesiella intestinihominis was strongly associated with markers indicating a higher cSVD burden. Finally, functional analyses using PICRUSt implicated various KEGG pathways, including microbial quorum sensing, AMP/GMP-activated protein kinase, phenylpyruvate, and {beta}-hydroxybutyrate production previously associated with cognitive performance and dementia. Our study provides important insights into the association between the gut microbiome and cSVD, but further studies are needed to replicate the findings.

neuroscience↗

bioRxiv2020

Analyzing and interpreting DNA double-strand break sequencing data

DNA double-strand breaks (DSBs), are a major threat to genomic stability and may lead to cancer. Several technologies to accurately detect DSBs genome-wide have been developed recently, but still lacking publicly available tools for analysis of the resulting data. Here, we present a step-by-step iSeq package (http://breakome.utmb.edu/software.html), custom designed for analysis and interpretation of DSB-sequencing data. iSeq performs barcode trimming and read counting, and identifies DSB-enriched regions by statistical test and annotate them to the desired genomic features. Applying this package, users can identify and annotate DSB-enriched regions from base pair (eg. Cas9 cleavage sites) up to megabase (eg. DNA replication stress-induced) resolution, and if possible quantify DSB frequencies per cell genome-wide by combining with qDSB-Seq. iSeq can be used for any sequencing-based DSB detection techniques. The analysis for Steps 1-19 can be performed within ~4 hours.

bioinformatics↗

bioRxiv2019

Co-evolutionary analysis accurately predicts details of interactions between the Integrator complex subunits

Solving the structure of large, multi-subunit complexes is difficult despite recent advances in cryoEM, due to remaining challenges to express and purify complex subunits. Computational approaches that predict protein-protein interactions, including Direct Coupling Analysis (DCA), represent an attractive alternative to dissect interactions within protein complexes. However, due to high computational complexity and high false positive rate they are applicable only to small proteins. Here, we present a modified DCA to predict residues and domains involved in interactions of large proteins. To reduce false positive levels and increase accuracy of prediction, we use local Gaussian averaging and predicted secondary structure elements. As a proof-of-concept, we apply our method to two Integrator subunits, INTS9 and INTS11, which form a heterodimeric structure previously solved by crystallography. We accurately predict the domains of INTS9/11 interaction. We then apply this approach to predict the interaction domains of two complexes whose structure is currently unknown: 1) The heterodimer formed by the Cleavage and Polyadenylation Specificity Factor 100-kD (CPSF100) and 73-kD (CPSF73); 2) The heterotrimer formed by INTS4/9/11. Our predictions of interactions within these two complexes are supported by experimental data, demonstrating that our modified DCA is a useful method for predicting interactions and can easily be applied to other complexes.

bioinformatics↗

bioRxiv2019

Protein Co-Evolution Strategies Detect Predicted Functional Interaction Between the Serotonin 5-HT2A and 5-HT2C Receptors

Serotonin is a neurotransmitter that plays a role in regulating activities such as sleep, appetite, mood and substance abuse disorders; serotonin receptors 5-HT2AR and 5-HT2CR are active within pathways associated with substance abuse. It has been suggested that 5-HT2AR and 5-HT2CR may form a dimer that affects behavioral processes. Here we study the coevolution of residues in 5-HT2AR and 5-HT2CR to identify potential interactions between residues in both proteins. Coevolution studies can detect protein interactions, and since the thus uncovered interactions are subject to evolutionary pressure, they are likely functional. We assessed the significance of the 5-HT2AR/5-HT2CR interactions using randomized phylogenetic trees and found the interaction significant (p-value = 0.01). We also discuss how co-expression of the receptors suggests the predicted interaction is functional. Finally, we analyze how several single nucleotide polymorphisms for the 5-HT2AR and 5-HT2CR genes affect their interaction. Our findings are the first to characterize the binding interface of 5-HT2AR/5-HT2CR and indicate a correlation between this interface and location of SNPs in both proteins.

neuroscience↗

bioRxiv2017

Integrated analysis of DSB patterns reveals precisely DSB formation mechanisms following replication fork collapse

DNA double-strand breaks (DSBs) can be detected by label-based sequencing or pulsed-field gel electrophoresis (PFGE). Sequencing yields population-average DSB frequencies genome-wide, while PFGE reveals percentages of broken chromosomes. We constructed a mathematical framework to combine advantages of both: high-resolution DSB locations and their population distribution. We also use sequencing read patterns to identify replication-induced DSBs and active replication origins. We describe changes in spatiotemporal replication program upon hydroxyurea-induced replication stress. We found that one-ended DSBs, resulting from collapsed replication forks, are population-representative, while majority of two-ended DSBs (79-100%) are not. To study replication fork collapse, we used strains lacking the checkpoint protein Mec1 and the endonuclease Mus81 and quantified that 19% and 13% of hydroxyurea-induced one-ended DSBs are Mec1-and Mus81-dependent, respectively. We also clarified that Mus81-induced one-ended DSBs are Mec1-dependent.

genomics↗

bioRxiv2017

Quantitative DSB sequencing (qDSB-Seq): a method for genome-wide accurate estimation of absolute DNA double-strand break frequencies per cell

Sequencing-based methods for mapping DNA double-strand breaks (DSBs) allow measurement only of relative frequencies of DSBs between loci, which limits our understanding of the physiological relevance of detected DSBs. We propose quantitative DSB sequencing (qDSB-Seq), a method providing both DSB frequencies per cell and their precise genomic coordinates. We induced spike-in DSBs by a site-specific endonuclease and used them to quantify labeled DSBs (e.g. using i-BLESS). Utilizing qDSB-Seq, we determined numbers of DSBs induced by a radiomimetic drug and various forms of replication stress, and revealed several orders of magnitude differences in DSB frequencies. We also measured for the first time Top1-dependent absolute DSB frequencies at replication fork barriers. qDSB-Seq is compatible with various DSB labeling methods in different organisms and allows accurate comparisons of absolute DSB frequencies across samples.

genomics↗

bioRxiv2017

The High-resolution Timeline of Expression of Ribosomal Protein Genes in Yeast

The yeast ribosome is a complex molecular machine built from four rRNAs and over 70 r-proteins. Ribosome biogenesis involves ordered incorporation of ribosomal proteins, accompanied by and association and dissociation of other proteins specific to different stages of the process. By model-based analysis of temporal profiles of gene expression in a metabolically regulated system, we obtained an accurate, high-resolution estimation of the time of expression of genes coding for proteins involved in ribosome biogenesis. The ribosomal proteins are expressed in a sequence that spans approximately 25-minutes under metabolically regulated conditions. The genes coding for proteins incorporated into the mature ribosome are expressed significantly later than those that are not incorporated, but are otherwise involved in ribosome biogenesis, localization and assembly, rRNA processing and translational initiation. The relative expression time of proteins localized within specified neighborhood is significantly correlated with the distance to the centroid of the mature ribosome: protein localized closer to the center of mass of the entire complex tend to be expressed earlier than the protein localized further from the center. The timeline of gene expression also agrees with the known dependencies between recruitment of specific proteins into the mature ribosome. These findings are consistent in two independent experiments. We have further identified regulatory elements correlated with the time of regulation, including a possible dependence of expression time on the position of the RAP1 binding site within the 5UTR.

biochemistry↗