BIN1
- Known as:
- BIN1
- Catalog number:
- Y214053
- Product Quantity:
- 200ul
- Category:
- -
- Supplier:
- ABM
- Gene target:
- BIN1
Related genes to: BIN1
- Gene:
- BIN1 NIH gene
- Name:
- bridging integrator 1
- Previous symbol:
- AMPHL
- Synonyms:
- SH3P9, AMPH2
- Chromosome:
- 2q14.3
- Locus Type:
- gene with protein product
- Date approved:
- 2000-05-19
- Date modifiied:
- 2019-04-23
Related products to: BIN1
Related articles to: BIN1
- Alzheimer's disease (AD) is characterized by extracellular β-amyloid (Aβ) plaques and intracellular hyperphosphorylated tau neurofibrillary tangles, with tau pathology correlating more strongly than amyloid pathology with cognitive decline and neuronal loss. While traditional genome-wide association studies (GWAS) have identified loci associated with tau-related phenotypes in cerebrospinal fluid, these approaches cannot capture the regional brain patterns of tau deposition that may underlie disease heterogeneity. Recent GWAS incorporating tau-PET imaging have begun to address this gap, identifying novel genetic variants associated with tau-PET signal through chromatin modification, microtubule dynamics, and immune regulation. Some of these mechanisms may operate at least partly independently of established amyloid-related pathways. This narrative review synthesizes the peer-reviewed evidence from genome-wide and candidate-gene association studies of tau-PET in AD, classifying findings by biological mechanism to characterize the reported genetic determinants of regional tau-PET signal, to grade the strength of the evidence behind each, and to consider their clinical applications. Throughout, the phenotype under analysis is tracer uptake and not directly measured neuropathological tau, and each locus is interpreted with that constraint in view. Transcriptional regulators such as and have been associated with tau-PET signals, although both findings rest on a single, unreplicated analysis. Common variants showed only nominal associations, whereas the - locus, which influences microtubule dynamics and oxidative stress, reached genome-wide significance and is the only locus to date that has been formally replicated in independent cohorts. is notable because it offers a plausible mechanism linking oxidative stress to tau aggregation. Genes controlling tau phosphorylation, such as and , have also been implicated, although the association was reported without a replication sample and the association was nominal ( = 0.048) in a candidate-gene analysis of 146 participants. Immune- and trafficking-related loci, including , , and , suggest contributions of neuroinflammation and endosomal transport to regional tau accumulation. Lastly, ε4 is the most frequently reported predictor of tau-PET burden across brain regions, but its effect attenuates in population-based, predominantly cognitively unimpaired cohorts, indicating that it may be substantially amyloid-conditional, not amyloid-independent. Across these studies the genetic architecture of tau-PET signal appears at least partly separable from that of clinically diagnosed AD, although this remains preliminary: no formal genetic correlation has been estimated, the contributing cohorts overlap substantially, and the samples are small enough that a null result carries little weight. The evidence supports continued study of tau-PET as an endophenotype, and it also indicates that the therapeutic implications of these loci are less direct than these studies generally claim. - Source: PubMed
Publication date: 2026/09/08
Gujral JaskeeratGandhi Om HBhogale TejasAmanullah Amir ASrivastava AshilSingh Shashi BWerner Thomas JHøilund-Carlsen Poul FlemmingAlavi Abass - Genome-wide association studies (GWAS) have identified many loci that contribute to the risk of neurodegenerative diseases. However, a persistent challenge in interpretation of GWAS is to break loci down to specific genes, variants, and cell types, and thus nominate disease mechanisms. Here, we used iPSC-derived cells containing population-level variation to examine GWAS loci across NDDs including Alzheimer's disease, Parkinson's disease and Lewy body dementia. We differentiated a set of 135 iPSC donor lines into two cell types relevant to neurodegeneration, neurons and microglia, and completed single cell gene expression and chromatin accessibility profiling. Meta-analysis of these data with published human brain snRNAseq for QTL mapping identified multiple loci associated with NDDs that are restricted to either neurons or microglia. Colocalization of GWAS and these QTL supports microglia as having a strong contribution to disease risk. We tested peaks nominated at the locus for enhancer activity using a perturb-seq-based method in microglia. Our results show one of the nominated peaks controls expression in microglia but also modifies expression of other genes at the locus. These results support the hypothesis that common variants affecting gene expression specifically in microglia can contribute directly to NDD risk rather than functioning solely as a secondary response to neurodegeneration. These data also show that iPSC-derived cells are a useful model to experimentally dissect GWAS loci that colocalize with QTL. - Source: PubMed
Publication date: 2026/09/17
Reed XylenaAcri Dominic JBeilina AlexandraDing JinhuiSaez-Atienzar SaraKaileh MaryBromberek SarahHu FangleLerner GrigoriyRamos Daniel MSolaiman SultanaPortley MakaylaWeller Cory AWhitaker D ThadEhrlich Debra JFerrucci LuigiScholz Sonja WGibbs J RaphaelCookson Mark R - Right ventricular pressure overload (RVPO) is a critical pathophysiological feature of numerous pediatric cardiovascular diseases. Transverse tubules (T-tubules) form the foundation for efficient excitation-contraction coupling in mature cardiomyocytes. We hypothesized that RVPO impairs T-tubule maturation through the regulatory protein bridging integrator 1 (BIN1). In right ventricular samples from children with tetralogy of Fallot, characterized by RVPO, and in a neonatal rat RVPO model induced by pulmonary artery banding (PAB), T-tubule maturation was disrupted. RNA-seq revealed significant downregulation of T-tubule-associated genes, with Bin1 among the most suppressed. Bin1 overexpression restored T-tubule maturation in PAB rats. ATAC-seq showed reduced chromatin accessibility at Bin1 loci; motif analysis identified Mef2d (myocyte enhancer factor 2D) as the top enriched transcription factor. Mef2d knockdown rescued Bin1 expression and T-tubule maturation, and mutation of the Mef2d binding sites within the Bin1 promoter abolished the inhibitory effect of Mef2d on Bin1 promoter activity. This study delineates a phenomenon and a mechanism of cardiomyocyte maturation under pathological stress. The findings not only advance our understanding of this most pivotal event in postnatal cardiac development but also unveil a potential therapeutic direction for pediatric cardiovascular diseases associated with RVPO. - Source: PubMed
Publication date: 2026/09/22
Hu YuqingXue YitingChen XudongKong LinghuiLi DebaoWang ZhengZheng SixieShe SiqiLi HaoSun SijuanChen HaoChen LijunRuan PeisenWang KaiYe Lincai - BackgroundAlzheimer's disease (AD) is a neurodegenerative disorder characterized by cognitive decline, memory impairment, and functional deterioration. Its complex pathogenesis involves amyloid plaques, tau tangles, neuroinflammation, synaptic dysfunction, and interacting genetic, environmental, and lifestyle factors. Transcriptomic and metabolomic studies have revealed molecular disruptions relevant to AD, supporting integrative approaches for biomarker discovery.ObjectiveTo integrate genetically imputed whole-blood transcriptomics and measured plasma metabolomics to predict cognitive performance, assessed using the PACC3 score, and identify influential genes and metabolites associated with cognition.MethodsA machine learning model integrated transcriptomic and metabolomic data from 1046 participants in the Wisconsin Registry for Alzheimer's Prevention (WRAP). Performance was evaluated in a WRAP holdout test set and independently validated in 85 participants from the Wisconsin Alzheimer's Disease Research Center (ADRC). Feature importance was used to identify molecular contributors to prediction.ResultsThe model achieved a normalized root mean squared error of 0.707 and an R of 0.338 in the WRAP holdout dataset (p = 5.93 × 10), and corresponding values of 0.915 and 0.061 in ADRC (p = 4.71 × 10). Higher imputed expression of RIPK1, IL6ST, and BIN1 was associated with poorer cognitive performance, whereas UGP2, NDUFB5, and TMOD2 were associated with better performance. Predictive metabolites included benzoate, 3-phenylpropionate, imidazolelactate, hexanoylcarnitine, and propionate-related metabolites.ConclusionsMulti-omics integration identified candidate biomarkers reflecting inflammatory signaling, mitochondrial dysfunction, and lipid metabolism. Together, these findings demonstrate complementary biological information captured across both omics layers. These convergent signals support improved molecular characterization of AD and biomarker prioritization for future mechanistic and translational studies. - Source: PubMed
Publication date: 2026/09/18
Choi Jerome JEngelman Corinne DLu Tianyuan - Early detection of Alzheimer's disease (AD) requires models that combine brain structure changes with genetic risk, but existing methods struggle to align these different data types. - Source: PubMed
Publication date: 2026/08/24
Zhao KunDai SiyuanZhang YingyingLiu GuodongGu PengfeiLin ChenghuaThompson Paul MLeow AlexHuang HengHe LifangZhan LiangTang Haoteng