Revisiting the Role of Insulin-Like Growth Factor-I Receptor Stimulating Activity and the Apolipoprotein E in Alzheimer's Disease

Brain high-throughput multi-omics data reveal molecular heterogeneity in Alzheimer's disease

Unbiased data-driven omic approaches are revealing the molecular heterogeneity of Alzheimer disease. Here, we used machine learning approaches to integrate high-throughput transcriptomic, proteomic, metabolomic, and lipidomic profiles with clinical and neuropathological data from multiple human AD cohorts. We discovered 4 unique multimodal molecular profiles, one of them showing signs of poor cognitive function, a faster pace of disease progression, shorter survival with the disease, severe neurodegeneration and astrogliosis, and reduced levels of metabolomic profiles. We found this molecular profile to be present in multiple affected cortical regions associated with higher Braak tau scores and significant dysregulation of synapse-related genes, endocytosis, phagosome, and mTOR signaling pathways altered in AD early and late stages. AD cross-omics data integration with transcriptomic data from an SNCA mouse model revealed an overlapping signature. Furthermore, we leveraged single-nuclei RNA-seq data to identify distinct cell-types that most likely mediate molecular profiles. Lastly, we identified that the multimodal clusters uncovered cerebrospinal fluid biomarkers poised to monitor AD progression and possibly cognition. Our cross-omics analyses provide novel critical molecular insights into AD.

Identification of IGF-1 Effects on White Adipose Tissue and Hippocampus in Alzheimer's Disease Mice via Transcriptomic and Cellular Analysis

Alzheimer's disease (AD) stands as the most prevalent neurodegenerative disorder, characterized by a multitude of pathological manifestations, prominently marked by the aggregation of amyloid beta. Recent investigations have revealed a compelling association between excessive adiposity and glial activation, further correlating with cognitive impairments. Additionally, alterations in levels of insulin-like growth factor 1 (IGF-1) have been reported in individuals with metabolic conditions accompanied by memory dysfunction. Hence, our research endeavors to comprehensively explore the impact of IGF-1 on the hippocampus and adipose tissue in the context of Alzheimer's disease. To address this, we have conducted an in-depth analysis utilizing APP/PS2 transgenic mice, recognized as a well-established mouse model for Alzheimer's disease. Upon administering IGF-1 injections to the APP/PS2 mice, we observed notable alterations in their behavioral patterns, prompting us to undertake a comprehensive transcriptomic analysis of both the hippocampal and adipose tissues. Our data unveiled significant modifications in the functional profiles of these tissues. Specifically, in the hippocampus, we identified changes associated with synaptic activity and neuroinflammation. Concurrently, the adipose tissue displayed shifts in processes related to fat browning and cell death signaling. In addition to these findings, our analysis enabled the identification of a collection of long non-coding RNAs and circular RNAs that exhibited significant changes in expression subsequent to the administration of IGF-1 injections. Furthermore, we endeavored to predict the potential roles of these identified RNA molecules within the context of our study. In summary, our study offers valuable transcriptome data for hippocampal and adipose tissues within an Alzheimer's disease model and posits a significant role for IGF-1 within both the hippocampus and adipose tissue.

The Role of Insulin-like Growth Factor I in Mechanisms of Resilience and Vulnerability to Sporadic Alzheimer's Disease

Despite decades of intense research, disease-modifying therapeutic approaches for Alzheimer's disease (AD) are still very much needed. Apart from the extensively analyzed tau and amyloid pathological cascades, two promising avenues of research that may eventually identify new druggable targets for AD are based on a better understanding of the mechanisms of resilience and vulnerability to this condition. We argue that insulin-like growth factor I (IGF-I) activity in the brain provides a common substrate for the mechanisms of resilience and vulnerability to AD. We postulate that preserved brain IGF-I activity contributes to resilience to AD pathology as this growth factor intervenes in all the major pathological cascades considered to be involved in AD, including metabolic impairment, altered proteostasis, and inflammation, to name the three that are considered to be the most important ones. Conversely, disturbed IGF-I activity is found in many AD risk factors, such as old age, type 2 diabetes, imbalanced diet, sedentary life, sociality, stroke, stress, and low education, whereas the Apolipoprotein (Apo) E4 genotype and traumatic brain injury may also be influenced by brain IGF-I activity. Accordingly, IGF-I activity should be taken into consideration when analyzing these processes, while its preservation will predictably help prevent the progress of AD pathology. Thus, we need to define IGF-I activity in all these conditions and develop a means to preserve it. However, defining brain IGF-I activity cannot be solely based on humoral or tissue levels of this neurotrophic factor, and new functionally based assessments need to be developed.

Integrated DNA Methylation/RNA Profiling in Middle Temporal Gyrus of Alzheimer's Disease

Alzheimer's disease is a neurodegenerative disorder clinically defined by gradual cognitive impairment and alteration in executive function. We conducted an epigenome-wide association study (EWAS) of a clinically and neuropathologically characterized cohort of 296 brains, including Alzheimer's disease (AD) and non-demented controls (ND), exploring the relationship with the RNA expression from matched donors. We detected 5246 CpGs and 832 regions differentially methylated, finding overlap with previous EWAS but also new associations. CpGs previously identified in ANK1, MYOC, and RHBDF2 were differentially methylated, and one of our top hits (GPR56) was not previously detected. ANK1 was differentially methylated at the region level, along with APOE and RHBDF2. Only a small number of genes showed a correlation between DNA methylation and RNA expression statistically significant. Multiblock partial least-squares discriminant analysis showed several CpG sites and RNAs discriminating AD and ND (AUC = 0.908) and strongly correlated with each other. Furthermore, the CpG site cg25038311 was negatively correlated with the expression of 22 genes. Finally, with the functional epigenetic module analysis, we identified a protein-protein network characterized by inverse RNA/DNA methylation correlation and enriched for "Regulation of insulin-like growth factor transport", with IGF1 as the hub gene. Our results confirm and extend the previous EWAS, providing new information about a brain region not previously explored in AD DNA methylation studies. The relationship between DNA methylation and gene expression is not significant for most of the genes in our sample, consistently with the complexities in the gene expression regulation.

Extracellular vesicles, the emerging mirrors of brain physiopathology

Extracellular vesicles are secreted by a wide variety of cells, and their primary functions include intercellular communication, immune responses, human reproduction, and synaptic plasticity. Their molecular cargo reflects the physiological processes that their cells of origin are undergoing. Thus, many studies have suggested that extracellular vesicles could be a promising biomarker tool for many diseases, mainly due to their biological relevance and easy accessibility to a broad range of body fluids. Moreover, since their biological composition leads them to cross the blood-brain barrier bidirectionally, growing evidence points to extracellular vesicles as emerging mirrors of brain diseases processes. In this regard, this review explores the biogenesis and biological functions of extracellular vesicles, their role in different physiological and pathological processes, their potential in clinical practice, and the recent outstanding studies about the role of exosomes in major human brain diseases, such as Alzheimer's disease (AD), Parkinson's disease (PD), multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), or brain tumors.

Associations Between Insulin-Like Growth Factor-1 and Resting-State Functional Connectivity in Cognitively Unimpaired Midlife Adults

BACKGROUND

Insulin-like growth factor (IGF)-1 plays an important role in Alzheimer's disease (AD) pathogenesis and increases disease risk. However, prior research examining IGF-1 levels and brain neural network activity is mixed.

OBJECTIVE

The present study investigated the relationship between IGF-1 levels and 21 neural networks, as measured by functional magnetic resonance imaging (fMRI) in 13,235 UK Biobank participants.

METHODS

Linear mixed models were used to regress IGF-1 against the intrinsic functional connectivity (i.e., degree of network activity) for each neural network. Interactions between IGF-1 and AD risk factors such as Apolipoprotein E4 (APOE4) genotype, sex, AD family history, and age were also tested.

RESULTS

Higher IGF-1 was associated with more network activity in the right Executive Function neural network. IGF-1 interactions with APOE4 or sex implicated motor, primary/extrastriate visual, and executive function related neural networks. Neural network activity trends with increasing IGF-1 were different in different age groups. Higher IGF-1 levels relate to much more network activity in the Sensorimotor Network and Cerebellum Network in early-life participants (40-52 years old), compared with mid-life (52-59 years old) and late-life (59-70 years old) participants.

CONCLUSION

These findings suggest that sex and APOE4 genotype may modify the relationship between IGF-1 and brain network activities related to visual, motor, and cognitive processing. Additionally, IGF-1 may have an age-dependent effect on neural network connectivity.

Targeting Systemic Innate Immune Cells as a Therapeutic Avenue for Alzheimer Disease

Alzheimer disease (AD) is the first progressive neurodegenerative disease worldwide, and the disease is characterized by an accumulation of amyloid in the brain and neurovasculature that triggers cognitive decline and neuroinflammation. The innate immune system has a preponderant role in AD. The last decade, scientists focused their efforts on therapies aiming to modulate innate immunity. The latter is of great interest, since they participate to the inflammation and phagocytose the amyloid in the brain and blood vessels. We and others have developed pharmacological approaches to stimulate these cells using various ligands. These include toll-like receptor 4, macrophage colony stimulating factor, and more recently nucleotide-binding oligomerization domain-containing 2 receptors. This review will discuss the great potential to take advantage of the innate immune system to fight naturally against amyloid β accumulation and prevent its detrimental consequence on brain functions and its vascular system. SIGNIFICANCE STATEMENT: The focus on amyloid β removal from the perivascular space rather than targeting CNS plaque formation and clearance represents a new direction with a great potential. Small molecules able to act at the level of peripheral immunity would constitute a novel approach for tackling aberrant central nervous system biology, one of which we believe would have the potential of generating a lot of interest.

Hypoglycemia, Vascular Disease and Cognitive Dysfunction in Diabetes: Insights from Text Mining-Based Reconstruction and Bioinformatics Analysis of the Gene Networks

Hypoglycemia has been recognized as a risk factor for diabetic vascular complications and cognitive decline, but the molecular mechanisms of the effect of hypoglycemia on target organs are not fully understood. In this work, gene networks of hypoglycemia and cardiovascular disease, diabetic retinopathy, diabetic nephropathy, diabetic neuropathy, cognitive decline, and Alzheimer's disease were reconstructed using ANDSystem, a text-mining-based tool. The gene network of hypoglycemia included 141 genes and 2467 interactions. Enrichment analysis of Gene Ontology (GO) biological processes showed that the regulation of insulin secretion, glucose homeostasis, apoptosis, nitric oxide biosynthesis, and cell signaling are significantly enriched for hypoglycemia. Among the network hubs, INS, IL6, LEP, TNF, IL1B, EGFR, and FOS had the highest betweenness centrality, while GPR142, MBOAT4, SLC5A4, IGFBP6, PPY, G6PC1, SLC2A2, GYS2, GCGR, and AQP7 demonstrated the highest cross-talk specificity. Hypoglycemia-related genes were overrepresented in the gene networks of diabetic complications and comorbidity; moreover, 14 genes were mutual for all studied disorders. Eleven GO biological processes (glucose homeostasis, nitric oxide biosynthesis, smooth muscle cell proliferation, ERK1 and ERK2 cascade, etc.) were overrepresented in all reconstructed networks. The obtained results expand our understanding of the molecular mechanisms underlying the deteriorating effects of hypoglycemia in diabetes-associated vascular disease and cognitive dysfunction.

Targeting impaired nutrient sensing with repurposed therapeutics to prevent or treat age-related cognitive decline and dementia: A systematic review

BACKGROUND

Dementia is a debilitating syndrome that significantly impacts individuals over the age of 65 years. There are currently no disease-modifying treatments for dementia. Impairment of nutrient sensing pathways has been implicated in the pathogenesis of dementia, and may offer a novel treatment approach for dementia.

AIMS

This systematic review collates all available evidence for Food and Drug Administration (FDA)-approved therapeutics that modify nutrient sensing in the context of preventing cognitive decline or improving cognition in ageing, mild cognitive impairment (MCI), and dementia populations.

METHODS

PubMed, Embase and Web of Science databases were searched using key search terms focusing on available therapeutics such as 'metformin', 'GLP1', 'insulin' and the dementias including 'Alzheimer's disease' and 'Parkinson's disease'. Articles were screened using Covidence systematic review software (Veritas Health Innovation, Melbourne, Australia). The risk of bias was assessed using the Cochrane Risk of Bias tool v 2.0 for human studies and SYRCLE's risk of bias tool for animal studies.

RESULTS

Out of 2619 articles, 114 were included describing 31 different 'modulation of nutrient sensing pathway' therapeutics, 13 of which specifically were utilized in human interventional trials for normal ageing or dementia. Growth hormone secretagogues improved cognitive outcomes in human mild cognitive impairment, and potentially normal ageing populations. In animals, all investigated therapeutic classes exhibited some cognitive benefits in dementia models. While the risk of bias was relatively low in human studies, this risk in animal studies was largely unclear.

CONCLUSIONS

Modulation of nutrient sensing pathway therapeutics, particularly growth hormone secretagogues, have the potential to improve cognitive outcomes. Overall, there is a clear lack of translation from animal models to human populations.

Impact of Genetic Risk Factors for Alzheimer's Disease on Brain Glucose Metabolism

Alzheimer's disease (AD) is a devastating neurodegenerative disease that affects more than 30 million people worldwide. Despite growing knowledge of AD pathophysiology, a complete understanding of the pathogenic mechanisms underpinning AD is lacking, and there is currently no cure for AD. Extant literature suggests that AD is a polygenic and multifactorial disease underscored by complex and dynamic pathogenic mechanisms. Despite extensive research and clinical trials, there has been a dearth of novel drugs for AD treatment on the market since memantine in 2003. This lack of therapeutic success has directed the entire research community to approach the disease from a different angle. In this review, we discuss growing evidence for the close link between altered glucose metabolism and AD pathogenesis by exploring how genetic risk factors for AD are associated with dysfunctional glucose metabolism. We also discuss modification of genes responsible for metabolic pathways implicated in AD pathology.

Exercise as Potential Therapeutic Target to Modulate Alzheimer's Disease Pathology in APOE ε4 Carriers: A Systematic Review

Alzheimer's disease (AD) is a progressive neurodegenerative disease for which no effective treatment exists at present. Previous research has found that exercise reduces the risk of AD. Since the apolipoprotein E (APOE) ε4 allele increases the risk of AD and is associated with faster disease progression than the other isoforms, we aimed to highlight the impact of exercise on AD pathology in APOE ε4 carriers. This review focuses on the effect of exercise on cognitive function, dementia risk, amyloid-β (Aβ) metabolism, lipid metabolism, neuroinflammation, neurotrophic factors and vascularization in APOE ε4 carriers. We searched the literature in the PubMed electronic database using the following search terms: physical activity, exercise, aerobic fitness, training, sport, APOE4, Alzheimer's disease, AD and dementia. By cross-referencing, additional publications were identified. Selected studies required older adults to take part in an exercise intervention or to make use of self-reported physical activity questionnaires. All included studies were written and published in English between 2000 and 2020. From these studies, we conclude that exercise is a non-pharmacological treatment option for high-risk APOE ε4 carriers to ameliorate the AD pathological processes including reducing Aβ load, protecting against hippocampal atrophy, improving cognitive function, stabilizing cholesterol levels and lowering pro-inflammatory signals. Variation in study design related to age, cognitive outcomes and the type of intervention explained the differences in study outcomes. However, exercise seems to be effective in delaying the onset of AD and may improve the quality of life of AD patients.

Using machine intelligence to uncover Alzheimer’s disease progression heterogeneity

Aim: Research suggests that Alzheimer’s disease (AD) is heterogeneous with numerous subtypes. Through a proprietary interactive ML system, several underlying biological mechanisms associated with AD pathology were uncovered. This paper is an introduction to emerging analytic efforts that can more precisely elucidate the heterogeneity of AD. Methods: A public AD data set (GSE84422) consisting of transcriptomic data of postmortem brain samples from healthy controls (n = 121) and AD (n = 380) subjects was analyzed. Data were processed by an artificial intelligence platform designed to discover potential drug repurposing candidates, followed by an interactive augmented intelligence program. Results: Using perspective analytics, six perspective classes were identified: Class I is defined by TUBB1, ASB4, and PDE5A; Class II by NRG2 and ZNF3; Class III by IGF1, ASB4, and GTSE1; Class IV is defined by cDNA FLJ39269, ITGA1, and CPM; Class V is defined by PDE5A, PSEN1, and NDUFS8; and Class VI is defined by DCAF17, cDNA FLJ75819, and SLC33A1. It is hypothesized that these classes represent biological mechanisms that may act alone or in any combination to manifest an Alzheimer’s pathology. Conclusions: Using a limited transcriptomic public database, six different classes that drive AD were uncovered, supporting the premise that AD is a heterogeneously complex disorder. The perspective classes highlighted genetic pathways associated with vasculogenesis, cellular signaling and differentiation, metabolic function, mitochondrial function, nitric oxide, and metal ion metabolism. The interplay among these genetic factors reveals a more profound underlying complexity of AD that may be responsible for the confluence of several biological factors. These results are not exhaustive; instead, they demonstrate that even within a relatively small study sample, next-generation machine intelligence can uncover multiple genetically driven subtypes. The models and the underlying hypotheses generated using novel analytic methods may translate into potential treatment pathways.

Blood-based Biomarkers of Alzheimer's Disease: The Long and Winding Road

BACKGROUND

Blood-based biomarkers can be very useful in formulating new diagnostic and treatment proposals in the field of dementia, especially in Alzheimer's disease (AD). However, due to the influence of several factors on the reproducibility and reliability of these markers, their clinical use is still very uncertain. Thus, up-to-date knowledge about the main blood biomarkers that are currently being studied is extremely important in order to discover clinically useful and applicable tools, which could also be used as novel pharmacological strategies for the AD treatment.

METHODS

A narrative review was performed based on the current candidates of blood-based biomarkers for AD to show the main results from different studies, focusing on their clinical applicability and association with AD pathogenesis.

OBJECTIVE

The aim of this paper was to carry out a literature review on the major blood-based biomarkers for AD, connecting them with the pathophysiology of the disease.

RESULTS

Recent advances in the search of blood-based AD biomarkers were summarized in this review. The biomarkers were classified according to the topics related to the main hallmarks of the disease such as inflammation, amyloid, and tau deposition, synaptic degeneration and oxidative stress. Moreover, molecules involved in the regulation of proteins related to these hallmarks were described, such as non-coding RNAs, neurotrophins, growth factors and metabolites. Cells or cellular components with the potential to be considered as blood-based AD biomarkers were described in a separate topic.

CONCLUSION

A series of limitations undermine new discoveries on blood-based AD biomarkers. The lack of reproducibility of findings due to the small size and heterogeneity of the study population, different analytical methods and other assay conditions make longitudinal studies necessary in this field to validate these structures, especially when considering a clinical evaluation that includes a broad panel of these potential and promising blood-based biomarkers.

The Other Side of Alzheimer's Disease: Influence of Metabolic Disorder Features for Novel Diagnostic Biomarkers

Nowadays, the amyloid cascade hypothesis is the dominant model to explain Alzheimer's disease (AD) pathogenesis. By this hypothesis, the inherited genetic form of AD is discriminated from the sporadic form of AD (SAD) that accounts for 85-90% of total patients. The cause of SAD is still unclear, but several studies have shed light on the involvement of environmental factors and multiple susceptibility genes, such as Apolipoprotein E and other genetic risk factors, which are key mediators in different metabolic pathways (e.g., glucose metabolism, lipid metabolism, energetic metabolism, and inflammation). Furthermore, growing clinical evidence in AD patients highlighted the presence of affected systemic organs and blood similarly to the brain. Collectively, these findings revise the canonical understating of AD pathogenesis and suggest that AD has metabolic disorder features. This review will focus on AD as a metabolic disorder and highlight the contribution of this novel understanding on the identification of new biomarkers for improving an early AD diagnosis.

Phycocyanin alleviates ICV-STZ induced cognitive and molecular deficits via PI3-Kinase dependent pathway

In this study, the effect of Phycocyanin (Pc) to ameliorate the cognitive dysfunction in experimental model of Alzheimer's disease (AD) was evaluated. Intracerebroventricular (ICV) induction of Streptozotocin (STZ) (3 mg/kg) was done bilaterally twice in rats on alternative days. Rats were injected with Pc (50, 100 mg/kg; i. p.) for 28 days daily for behavioural and cholinergic activity assessment. As the effect was only significant at 100 mg/kg, later molecular experiments were performed using the same only. STZ induction led to increased activity of hippocampal cholinesterases and BAX and decreased activity of BCL-2 and ChAT. It enhanced TNF-α, and NF-κB in rat's brain and reduced BDNF and IGF-1 levels. Dysfunctional insulin signaling and decreased gene expressions of PI3-K, AKT was also observed. However, Pc treatment significantly prevented STZ-induced increased activity of hippocampal cholinesterases and BAX as well as increased the levels of BCL-2 and ChAT. Neuroinflammation was significantly attenuated and BDNF and IGF-1 levels were upregulated. Further, Pc also alleviated dysfunctional insulin signaling as evidenced by increased gene expression of IRS-1, PI3-K, AKT. In conclusion, our study demonstrated the immense potential of Pc in attenuating STZ-induced cognitive decline and it may be further explored as a therapeutic agent in managing AD.

Amyloid-β oligomers in cellular models of Alzheimer's disease

Amyloid-β (Aβ) dysmetabolism is tightly associated with pathological processes in Alzheimer's disease (AD). Currently, it is thought that, in addition to Aβ fibrils that give rise to plaque formation, Aβ aggregates into non-fibrillar soluble oligomers (AβOs). Soluble AβOs have been extensively studied for their synaptotoxic and neurotoxic properties. In this review, we discuss physicochemical properties of AβOs and their impact on different brain cell types in AD. Additionally, we summarize three decades of studies with AβOs, providing a compelling bulk of evidence regarding cell-specific mechanisms of toxicity. Cellular models may lead us to a deeper understanding of the detrimental effects of AβOs in neurons and glial cells, putatively shedding light on the development of innovative therapies for AD.

Cerebrospinal fluid proteomics and biological heterogeneity in Alzheimer's disease: A literature review

Alzheimer's disease (AD) is the most common cause of dementia and is characterized by aggregation of amyloid and tau proteins in the brain. Results from genetic studies suggest that the pathophysiology underlying AD is complex, but studying this complexity in patients remains difficult. The cerebrospinal fluid (CSF) proteome contains a large number of proteins that can reflect ongoing biological processes. Proteomics techniques can be used to measure many proteins simultaneously in individual patients and may therefore provide an opportunity to study AD disease mechanisms. Here, we review the CSF proteomics literature to identify proteins consistently associated with AD, and perform pathway analyses on these proteins to study which biological processes may be involved in the disease.We performed a literature search of studies that investigated CSF proteomic alterations related to AD. We included original research articles when they measured at least 10 proteins in (antemortem) CSF in at least 10 individuals with AD, mild cognitive impairment (MCI) or controls. We examined if proteins were consistently related to AD, defined as consistent increase or decrease in AD vs. controls across studies. Next, we used the proteins identified as input to pathway analyses using Reactome to investigate which biological processes were enriched.In total, 29 studies were included that investigated AD-related changes to the CSF proteome, including a total of 1434 individuals with AD (of whom 47.1% had a CSF biomarker profile and 9.6% a postmortem examination consistent with AD) and 1380 controls. The studies reported 1 to 138 proteins associated with AD, of which 97 proteins were reported by two or more studies. Among proteins that were measured in more than one study, 27 (27.8%) showed consistent increases, 15 (15.5%) consistent decreases and 55 (56.7%) had contrasting results. Pathway analyses showed that AD-related proteins were enriched for hemostasis, lipoprotein and extracellular matrix pathways.These results indicate that proteomic alterations in CSF associated with AD reflect involvement of various biological pathways. The frequent occurrence of inconsistent protein level changes reported by different studies suggests that additional biological and/or (pre)analytical factors may influence the CSF proteome in AD, which should be further investigated in order to improve understanding of the biological complexity underlying AD.

The insulin-like growth factor-I receptor stimulating activity (IRSA) in health and disease

Determination of true IGF-I bioactivity in serum and other biological fluids is still a substantial challenge. The IGF-IR Kinase Receptor Activation assay (IGF-IR KIRA assay) is a novel tool to asses IGF-IR stimulating activity (IRSA) and has opened a new era in studying the IGF system. In this paper we discuss many studies showing that measuring IRSA by the IGF-IR KIRA assay often provides fundamentally different information about the IGF system than the commonly used total IGF-I immunoassays. With the IGF-IR KIRA assay phosphorylation of tyrosine residues of the IGF-IR is used as read out to quantify IRSA in unknown (serum) samples. The IGF-IR KIRA assay gives information about net overall effects of circulating IGF-I, IGF-II, IGFBPs and IGFBP-proteases on IGF-IR activation and seems especially superior to immunoreactive total IGF-I in monitoring therapeutic interventions. Although the IRSA as measured by the IGF-IR KIRA assay probably more closely reflects true bioactive IGF-I than measurements of total IGF-I in serum, the IGF-IR KIRA assay in its current form does not give information about all the post-receptor intracellular events mediated by the IGF-IR. Interestingly, in several conditions in health and disease IRSA measured by the IGF-IR KIRA assay is considerably higher in interstitial fluid and ascites than in serum. This suggests that both the paracrine (local) and endocrine (circulating) IRSA should be measured to get a complete picture about the role of the IGF system in health and disease.

Circulating IGFBP-2: a novel biomarker for incident dementia

OBJECTIVE

To determine the association between plasma insulin-like growth factor binding protein 2 (IGFBP-2) and cognitive outcomes.

METHODS

We measured plasma IGFBP-2 levels in 1596 (53% women, mean age 68.7 [SD 5.7] years) dementia-free Framingham Offspring cohort participants between 1998 and 2001. Multivariable Cox proportional hazards models related plasma IGFBP-2 to subsequent risk of incident dementia and Alzheimer's disease. MRI brain measures and cognitive performance were included as secondary outcomes.

RESULTS

During a median follow-up of 11.8 (Q1, Q3: 7.1, 13.3) years, 131 participants developed incident dementia, of whom 98 were diagnosed with Alzheimer's disease. The highest tertile of IGFBP-2, compared to the lowest tertile, was associated with an increased risk of incident all-cause dementia (hazard ratio [HR] 2.89, 95% CI 1.63-5.13) and Alzheimer's disease (HR 3.63, 95% CI 1.76-7.50) in multivariable analysis. Higher circulating IGFBP2 levels were also cross-sectionally associated with poorer performance on tests of abstract reasoning but not with MRI-based outcomes. After adding plasma IGFBP-2 levels to a conventional dementia prediction model, 32% of individuals with dementia were correctly assigned a higher predicted risk, while 8% of individuals without dementia were correctly assigned a lower predicted risk (overall net reclassification improvement index, 0.40, 95% CI 0.22-0.59).

INTERPRETATION

Elevated circulating IGFBP-2 levels were associated with an increased risk of both all-cause dementia and Alzheimer's disease. Addition of IGFBP2 plasma levels to a model of traditional risk factors significantly improved dementia risk classification. Manipulation of insulin-like growth factor signaling via IGFBP-2 may be a promising therapeutic target for dementia.