2025-05-20 13:24:39
Diabetes Type I majorpublished
Did you know?
Did you know that one of the primary autoantigens in type 1 diabetes is a zinc transporter (ZnT8) found in pancreatic β-cells? This highlights the role of metal ions in insulin storage and suggests that trace metal imbalances could intersect with the autoimmune process of T1D, an insight which researchers are exploring in the quest for new interventions.
Type 1 diabetes is an autoimmune condition in which pancreatic β-cells are destroyed, causing insulin deficiency and hyperglycemia. It typically arises in youth and requires lifelong insulin therapy. This article provides a clinician-focused review of T1D’s causes, mechanisms, complications, diagnosis, and management, including emerging multi-omics insights.
Clinical Pharmacist and Clinical Pharmacy Master’s candidate focused on antibiotic stewardship, AI-driven pharmacy practice, and research that strengthens safe and effective medication use. Experience spans digital health research with Bloomsbury Health (London), pharmacovigilance in patient support programs, and behavioral approaches to mental health care. Published work includes studies on antibiotic use and awareness, AI applications in medicine, postpartum depression management, and patient safety reporting. Developer of an AI-based clinical decision support system designed to enhance antimicrobial stewardship and optimize therapeutic outcomes.
Microbiome Signatures identifies and validates condition-specific microbiome shifts and interventions to accelerate clinical translation. Our multidisciplinary team supports clinicians, researchers, and innovators in turning microbiome science into actionable medicine.
Clinical Pharmacist and Clinical Pharmacy Master’s candidate focused on antibiotic stewardship, AI-driven pharmacy practice, and research that strengthens safe and effective medication use. Experience spans digital health research with Bloomsbury Health (London), pharmacovigilance in patient support programs, and behavioral approaches to mental health care. Published work includes studies on antibiotic use and awareness, AI applications in medicine, postpartum depression management, and patient safety reporting. Developer of an AI-based clinical decision support system designed to enhance antimicrobial stewardship and optimize therapeutic outcomes.
Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by immune-mediated destruction of the insulin-producing β-cells in the pancreatic islets, leading to absolute insulin deficiency.[1] It typically onsets in childhood or adolescence but can occur at any age. T1D is distinguished from type 2 diabetes by its autoimmune etiology and dependence on exogenous insulin from diagnosis, whereas type 2 involves insulin resistance with relative insulin deficiency. Globally, the incidence of T1D has been rising (~3% annual increase in youth) and shows geographic variation, with the highest rates in Northern Europe and North America.[2] An estimated 8–9 million people worldwide have T1D, and prevalence is projected to climb further by 2040 [3]
T1D arises from a complex interplay of genetic predisposition and environmental triggers.[4] The strongest genetic risk factors are certain HLA class II alleles (especially the DR3-DQ2 and DR4-DQ8 haplotypes), which confer up to a 30–50 fold increased risk compared to protective genotypes.[5] Other susceptibility genes include those affecting immune regulation (e.g. PTPN22, IL2RA, CTLA4) and β-cell function. However, genetics alone is not determinative; concordance in identical twins is only ~30–50%, implying a major role for environmental factors.[6] Viral infections are implicated as possible triggers – enteroviruses (coxsackie B), rotavirus, and cytomegalovirus have been associated with islet autoimmunity in epidemiologic studies, though causation remains unproven. Dietary factors in early life have been explored (e.g. cow’s milk exposure, infant diet, vitamin D status), with mixed evidence. The gut microbiome has emerged as another factor: alterations in gut microbial composition precede islet autoimmunity in some children, suggesting a potential influence on the developing immune system (see Microbiome Signature section).
Type 1 diabetes develops through an interplay of genetic predisposition and environmental triggers.[7] The highest genetic risk is conferred by HLA class II alleles, particularly DR3-DQ2 and DR4-DQ8 haplotypes, which can increase risk up to 30–50 fold over protective genotypes.[8] However, monozygotic twin concordance is only ~30–50%, underscoring the importance of non-genetic factors.[9]
Environmental contributors include viral infections (e.g., coxsackie B, rotavirus), perinatal factors (maternal age, delivery mode), early-life diet, vitamin D status, and altered gut microbiota composition. Additionally, immune checkpoint inhibitors used in cancer therapy can rarely trigger autoimmune diabetes by promoting T-cell-mediated β-cell destruction. These diverse triggers underscore the multifactorial and heterogeneous nature of T1D etiology.[10]
Autoimmune trigger → T-cell–mediated β-cell destruction → Insulin deficiency → Hyperglycemia → Metabolic decompensation → Exogenous insulin dependence.[11][12]
The immune system targets specific β-cell autoantigens such as insulin, GAD65, IA-2, and ZnT8 (a zinc transporter essential for insulin granule function), triggering a T-cell–dominated response. CD4⁺ and CD8⁺ lymphocytes infiltrate the islets (insulitis), leading to progressive β-cell apoptosis.[13]
The disease unfolds in stages: Stage 1 features multiple islet autoantibodies with normal glycemia; Stage 2 shows dysglycemia without symptoms; Stage 3 manifests as hyperglycemia or ketoacidosis. As β-cell mass declines past a functional threshold, insulin becomes essential. A transient “honeymoon phase” with partial β-cell recovery may follow diagnosis but is usually brief.[14]
Cytokine-driven inflammation (IFN-γ, IL-1β, TNF-α), oxidative and ER stress, and metabolic derangements from insulin deficiency (e.g., lipolysis, ketogenesis) all accelerate β-cell injury. Environmental modulators—like gut-derived LPS or microbial metabolites—may amplify or mitigate immune responses, though their roles remain under investigation.[15]
Persistent hyperglycemia in type 1 diabetes causes widespread tissue injury, leading to microvascular and macrovascular complications, autoimmune comorbidities, and acute metabolic crises, all of which drive morbidity and mortality.[16]
Diabetic retinopathy (retinal capillary damage leading to vision loss) develops in the majority of patients after 10–20 years of disease, making diabetes the leading cause of blindness in working-age adults. Diabetic nephropathy (kidney glomerular damage) manifests as proteinuria and can progress to end-stage renal disease – T1D is a top cause of kidney failure worldwide. Diabetic neuropathy affects peripheral nerves (causing loss of sensation, pain, and predisposing to foot ulcers and amputations) and autonomic nerves (leading to gastroparesis, orthostatic hypotension, etc.) [17]
Accelerated atherosclerosis can cause premature coronary artery disease, stroke, and peripheral arterial disease. Although younger T1D patients have fewer cardiovascular risk factors than type 2 diabetics, long-duration T1D substantially raises the risk of myocardial infarction and reduces life expectancy. Beyond vasculopathy, chronic hyperglycemia and insulin deficiency have other systemic effects: bone mineral density may be reduced (increasing fracture risk), the immune system is impaired (leading to higher infection risk when glycemia is poor), and growth/puberty can be delayed in adolescents with poorly controlled T1D.[18]
T1D frequently coexists with autoimmune thyroid diseases (Hashimoto thyroiditis, Graves disease), celiac disease, pernicious anemia, vitiligo, and Addison disease. These comorbidities reflect a shared autoimmune predisposition, necessitating routine thyroid and celiac screening. Psychosocial issues like depression and diabetes-related burnout are also common and can negatively impact glycemic control and overall outcomes.[19]
Lifelong insulin replacement is essential in T1D. Most patients use multiple daily injections (MDI) of basal and prandial insulins or insulin pumps for continuous subcutaneous infusion. Basal insulins (e.g., glargine, degludec) provide background coverage, while rapid-acting analogs (e.g., lispro, aspart) are used at meals. Dose adjustments rely on glucose self-monitoring, CGM data, dietary intake, and physical activity patterns..
Yes. Pramlintide, an amylin analog, may be co-administered with mealtime insulin to blunt postprandial spikes. SGLT2 inhibitors like empagliflozin have been studied but are not widely recommended due to euglycemic DKA risk. Cardiovascular risk is mitigated with statins, ACE inhibitors/ARBs for hypertension or albuminuria, and aspirin in select older patients. Immunotherapy (e.g., teplizumab) may delay disease in high-risk individuals.[20]
Residual β-cell function in the honeymoon phase lowers insulin needs—over-insulinization must be avoided. Children may require diluted insulin; elderly patients often benefit from higher glucose targets to prevent hypoglycemia. CGM and HbA1c (target <7%) guide therapy, and ketone testing is recommended during illness or severe hyperglycemia.
Closed-loop insulin pumps and CGMs are widely used, improving time-in-range and reducing hypoglycemia. Education on carbohydrate counting, dose adjustments, and sick-day protocols is critical.
Teplizumab, an anti-CD3 antibody, is approved to delay progression in at-risk individuals. Other agents like rituximab and abatacept are under investigation. Islet or pancreas transplantation is reserved for select patients with severe hypoglycemia unawareness or concurrent kidney transplantation due to limited availability and immunosuppression requirements.[21]
The metallome (metal ions in biology), metabolome (small-molecule metabolites), and microbiome (microbial community) form an interlinked triad that can influence immune and metabolic homeostasis in T1D. Though T1D is classically an autoimmune process, one can conceptualize how disturbances in one domain ripple through the others. For instance, chronic inflammation in T1D triggers nutritional immunity responses – the host elevates hepcidin, which sequesters iron (a metallomic change), potentially leading to functional iron deficiency.[22] This shift in iron availability could impact the gut microbiome, since many gut microbes require iron; in theory, an iron-deprived environment might suppress some bacteria while favoring others that can thrive on limited iron. Conversely, the gut microbiota produce various metabolites (short-chain fatty acids, amino acid derivatives, etc.) that can enter the circulation and affect host metabolism and immunity. An example is microbial butyrate: its deficiency (a metabolomic change) in T1D could impair regulatory T-cell development in the gut, thereby influencing autoimmune propensity. Similarly, the microbiome can influence the metallome: certain gut bacteria alter the absorption of dietary metals (like producing metabolites that chelate minerals or modulate gut barrier integrity). A pertinent illustration is the role of zinc. Zinc is essential in β-cells for insulin crystallization, and the ZnT8 transporter that loads zinc into insulin granules is an autoantigen in T1D. This means a component of the metallome (zinc handling) is directly tied into the autoimmune process. If zinc homeostasis is perturbed (e.g. chronic high zinc or copper levels), it might stress β-cells or modify immune responses. Indeed, serum studies show altered levels of metals (copper, zinc, magnesium) in diabetes, suggesting systemic metallomic imbalance.[23] Meanwhile, metabolomic disturbances like hyperglycemia, elevated fatty acids, and ketones provide substrates that can change the gut microbial composition (e.g. high glucose may promote Candida or certain bacteria, high ketones might favor others). Microbes in turn produce pro-inflammatory molecules (like LPS) that worsen metabolic and immune dysfunction. Thus, T1D can be seen as a condition where immune-metabolic crosstalk is central, and that crosstalk may be modulated by metal ions and microbial metabolites. Importantly, not every aspect is relevant: e.g. there is no evidence that toxic heavy metals (lead, arsenic) play any role in typical T1D. So the integration is specific – focusing on nutritional metals (iron, zinc, copper) and metabolites (glucose, SCFAs, amino acids) that intersect with immune pathways. In summary, the metallome, metabolome, and microbiome interact in a dynamic network: immune-driven metal sequestration and metabolic changes can reshape the microbiome, and microbial metabolites or metal utilization can feed back into immune-metabolic regulation. Understanding these links in T1D may help identify new intervention points, but we must avoid overextending causality beyond what evidence supports.
“Mismetallation” refers to the inappropriate incorporation of a metal ion into biomolecules (proteins/enzymes) that usually require a different metal. This can occur in states of metal imbalance – for example, zinc deficiency might lead to manganese or copper occupying sites in enzymes meant for zinc, potentially impairing their function. In the context of T1D, there is no direct evidence that mismetallation is a significant pathological mechanism. T1D does involve perturbations in metal homeostasis (as an effect or minor contributor), but specific cases of enzymes malfunctioning due to wrong-metal insertion have not been documented in the literature for this disease. That said, T1D’s autoimmune targeting of ZnT8 underscores the importance of proper zinc handling in β-cells: ZnT8 ensures zinc is available for insulin crystallization; autoimmunity against ZnT8 may effectively create a state of zinc dysfunction within islets. It is conceivable that chronic hyperglycemia and oxidative stress in T1D could alter the redox state of metals like iron or copper, but that typically leads to generalized oxidative damage rather than specific enzyme mismetallation. Studies have shown that people with T1D often have altered serum levels of trace metals. For instance, one study found serum copper and ceruloplasmin levels were significantly higher in T1D patients than controls,[24][25] and that high copper was strongly associated with T1D risk. Another reported that T1D and type 2 patients had higher copper and lower zinc and magnesium levels, correlating with worse glycemic control.[26] These shifts might influence enzyme systems (many antioxidant enzymes use copper or zinc, such as superoxide dismutase). Yet, whether these imbalances actually cause enzymes to incorporate the “wrong” metal is unproven. For example, excess free copper could catalyze more oxidative reactions (Fenton chemistry) and deplete cellular antioxidants, but does it replace zinc in zinc-dependent proteins? There is no clear evidence of that in T1D. Similarly, no known toxin metal (like lead or cadmium) is linked to T1D development. Some T1D patients, especially with associated autoimmune gastritis or celiac disease, might develop deficiencies (e.g. iron, B12, zinc). Treating those is important for general health but doesn’t cure diabetes. Summarily, mismetallation is more a theoretical concept here – T1D is not like certain neurodegenerative diseases where metalloprotein mishandling is central. The prudent stance is that metallomic disturbances in T1D are secondary: e.g. hyperglycemia fosters oxidative stress which can alter metal ion distribution and binding (like more copper being bound to ceruloplasmin[27]), and inflammation can sequester iron. These may contribute to complication pathology (oxidative tissue injury) but not via a specific enzyme metal swap mechanism as far as evidence shows. In conclusion, aside from the unique ZnT8 autoimmune aspect, there is no known mismetallation pathology in T1D – any discussion of metals is mainly about imbalance (excess or deficiency) rather than enzymes grabbing the wrong cofactor.
Nutritional immunity is the host’s defense strategy of limiting microbial access to certain nutrients, notably metal ions, during infection or inflammation. Key examples are the sequestration of iron through elevated hepcidin (trapping iron in ferritin and reducing serum iron) and the withholding of zinc and manganese by proteins like calprotectin. By doing so, the body attempts to starve invading pathogens of essential metals. In T1D, which is an autoimmune disease rather than an active infection, nutritional immunity is not a prominent driver of pathogenesis; however, aspects of it can be observed as part of the chronic inflammatory state. Chronic low-grade inflammation in T1D (especially if glycemic control is suboptimal) can lead to increased hepcidin production.[28]Hepcidin, produced by the liver in response to inflammatory signals (e.g. IL-6), causes iron to be locked in macrophages and decreases gut iron absorption. Pediatric studies in T1D have found higher hepcidin levels in children with functional iron deficiency (low transferrin saturation despite normal ferritin) compared to those without – suggesting that the inflammation of T1D may indeed invoke a nutritional immunity response that results in iron-restricted erythropoiesis.[29] Clinically, this means some T1D patients can have anemia of chronic disease-like pictures (normal ferritin, low serum iron, low transferrin saturation) due to hepcidin elevation. Whether this is adaptive (perhaps protecting against infections in a patient with high blood sugar, which predisposes to infection) or maladaptive is unclear, but it mirrors the nutritional immunity concept. There’s less data on zinc-sequestration in T1D, but it’s known that during infection/inflammation, zinc is redistributed (serum zinc can drop as it is taken up by the liver and immune cells). T1D patients with poor control have higher IL-6 and acute-phase responses, possibly leading to lower serum zinc and altered zinc transporter expression. The protein calprotectin (released by neutrophils) binds zinc and manganese in tissue fluids during inflammation; elevated calprotectin has been noted in the stool of infants who later develop T1D, hinting at gut inflammation preceding disease, which could alter local metal availability for microbes. However, these findings are preliminary. If nutritional immunity mechanisms are active in T1D, the gut microbiota may be affected. For example, iron sequestration via hepcidin could suppress the growth of commensals or pathogens that depend on free iron, potentially shifting the microbiome composition. Some hypothesize that an iron-poor environment might favor organisms that scavenge iron more aggressively (like certain Bacteroides or fungi). Similarly, changes in zinc availability could influence the microbiome, since many gut bacteria need zinc for enzymes. These effects could conceivably tie into the dysbiosis observed in T1D (for instance, low-grade gut inflammation could create a metal-ion milieu that favors pro-inflammatory bacteria). That said, direct evidence linking nutritional immunity to T1D microbiome or autoimmunity is limited. It is more a plausible hypothesis drawn from general principles of inflammation. Understanding nutritional immunity in T1D might inform adjunct treatments – for example, if high hepcidin is contributing to anemia and fatigue in a T1D patient, one might consider hepcidin-lowering strategies or judicious iron supplementation (recognizing that giving iron when inflammation is high may not correct anemia and could feed pathogens). In the big picture, nutritional immunity reflects how the immune system’s fight against perceived threats can alter metal distribution. In T1D, the “threat” is misdirected (the host’s own β-cells), but the inflammatory response still triggers these ancient defensive programs. Thus, T1D patients often exist in a mild state of nutritional immunity activation, with subtle functional iron deficiency and shifts in other micronutrients. This underscores the importance of monitoring and managing nutrient levels (iron, zinc, vitamin D, etc.) as part of comprehensive T1D care, even though modulating nutritional immunity is not a primary treatment target. In conclusion, nutritional immunity plays a secondary, contextual role in T1D – it is a consequence of inflammation that can influence infection susceptibility and nutritional status, rather than a causative mechanism of the autoimmune process.
A sound therapeutic strategy for type 1 diabetes (T1D) must target validated elements of the disease signature, which includes:
Autoimmunity: autoreactive T cells, autoantibodies (e.g., GAD, IA-2, ZnT8)
Metabolomic disturbances: hyperglycemia, oxidative stress, dyslipidemia, SCFA deficiency
Metallomic imbalance: elevated serum copper, altered zinc profiles[30]
Microbiome dysfunction: reduced SCFA-producing bacteria, increased pro-inflammatory taxa.[31]
Interventions are evaluated based on their coherence with this multi-omic model. Those that correct core dysfunctions without introducing new imbalances are considered evidence-aligned; those that contradict or destabilize the system receive a STOP signal.
| Class | Interventions | Mechanisms of Action | Status |
|---|
| Pharmaceutical | Insulin Therapy | Replaces absent endogenous insulin; restores glycemic control, suppresses ketogenesis, and reduces glucotoxicity. Fundamental for survival and prevention of acute and chronic complications. | Validated |
| Teplizumab | Anti-CD3 monoclonal antibody that modulates autoreactive T cells; delays progression from islet autoimmunity to overt diabetes in high-risk individuals.[32] | Validated (Preventive) |
| Pramlintide | Amylin analog co-secreted with insulin; slows gastric emptying, reduces glucagon, and blunts postprandial glucose excursions. | Promising Candidate |
| Trace Metal Modifiers | Tetrathiomolybdate (TM) | Chelates excess copper, reducing reactive oxygen species and improving insulin sensitivity; corrects metallomic imbalance observed in diabetic models.[33] | Promising Candidate |
| Triethylenetetramine (TETA) | Binds tissue copper, reduces fibrosis and albuminuria; mitigates diabetic kidney injury and improves endothelial function in T1D models.[34] | Promising Candidate |
| Immunomodulatory | Rituximab, Abatacept | B-cell depletion (Rituximab) and T-cell co-stimulation blockade (Abatacept); preserve β-cell function in new-onset T1D, though effects are modest and not durable.[35] | Under Investigation |
| Nutritional & Microbiome | Butyrate / SCFA Supplementation | Enhances regulatory T-cell function, restores intestinal barrier integrity, and reduces systemic inflammation. SCFA deficiency is a recurrent feature in T1D-associated dysbiosis.[36] | Under Investigation |
| Prebiotics / High-Fiber Diet | Promotes SCFA-producing bacteria (e.g., Faecalibacterium, Roseburia); may indirectly suppress pro-inflammatory immune tone and support glucose regulation.[37] | Promising Candidate |
| Probiotics | May help reestablish microbial diversity and reduce gut permeability; inconsistent results to date, with limited efficacy in modifying T1D autoimmunity or progression.[38] | Under Investigation |
Despite the search for novel adjunct therapies in type 1 diabetes (T1D), certain interventions—though theoretically appealing—may inadvertently worsen disease progression when misaligned with the underlying immunometabolic environment. In T1D, systemic inflammation, microbial dysbiosis, and nutritional immunity mechanisms create a sensitive milieu in which improper modulation can amplify β-cell stress, immune activation, or pathogen virulence. Two commonly considered strategies, broad-spectrum antibiotics and iron supplementation, illustrate the risks of applying biologically discordant interventions without alignment to the disease’s multi-omic signature.
| STOP | Microbiome / Host Impact | T1D Risk or Progression Link |
|---|
| Broad-Spectrum Antibiotics | Reduces beneficial SCFA-producing microbes (e.g., Faecalibacterium, Roseburia), disrupts gut barrier integrity, and increases LPS-driven inflammation.[39] | Associated with accelerated autoimmunity and β-cell destruction in NOD mice; worsens immunologic tolerance and gut–immune axis dysfunction in preclinical T1D models.[40] |
| Excessive Iron Supplementation | Inflammatory milieu in T1D (elevated hepcidin) inhibits iron utilization; unabsorbed iron promotes gut microbial virulence and ROS generation.[41] | May increase oxidative stress, tissue damage, and infection risk without correcting anemia, especially in patients with subclinical inflammation and dysbiosis.[42] |
The honeymoon phase refers to a period shortly after T1D diagnosis when the patient’s insulin requirements decrease and glycemic control temporarily improves. This happens because not all β-cells are destroyed at diagnosis; with the initiation of insulin therapy (and removal of glucotoxic stress), the remaining β-cells “recover” some function, producing endogenous insulin for a time. Clinically, a patient may go from needing, say, 0.7 units/kg to only 0.3 units/kg of insulin per day during the honeymoon. This phase can last from a few weeks to several months, occasionally over a year, but ultimately the autoimmune process usually progresses and endogenous insulin production wanes completely. Patients and providers must be cautious during the honeymoon – frequent insulin dose adjustments are needed to avoid hypoglycemia. The honeymoon illustrates that T1D is not an overnight on/off phenomenon; residual β-cell function lingers transiently. Some new therapies (like immunomodulators) aim to prolong the honeymoon or preserve those remaining β-cells.
Alias iure reprehenderit aut accusantium. Molestiae dolore suscipit. Necessitatibus eum quaerat. Repudiandae suscipit quo necessitatibus. Voluptatibus ullam nulla temporibus nobis. Atque eaque sed totam est assumenda. Porro modi soluta consequuntur veritatis excepturi minus delectus reprehenderit est. Eveniet labore ut quas minima aliquid quibusdam. Vitae possimus fuga praesentium eveniet debitis exercitationem deleniti.
Alias iure reprehenderit aut accusantium. Molestiae dolore suscipit. Necessitatibus eum quaerat. Repudiandae suscipit quo necessitatibus. Voluptatibus ullam nulla temporibus nobis. Atque eaque sed totam est assumenda. Porro modi soluta consequuntur veritatis excepturi minus delectus reprehenderit est. Eveniet labore ut quas minima aliquid quibusdam. Vitae possimus fuga praesentium eveniet debitis exercitationem deleniti.
Alias iure reprehenderit aut accusantium. Molestiae dolore suscipit. Necessitatibus eum quaerat. Repudiandae suscipit quo necessitatibus. Voluptatibus ullam nulla temporibus nobis. Atque eaque sed totam est assumenda. Porro modi soluta consequuntur veritatis excepturi minus delectus reprehenderit est. Eveniet labore ut quas minima aliquid quibusdam. Vitae possimus fuga praesentium eveniet debitis exercitationem deleniti.
Alias iure reprehenderit aut accusantium. Molestiae dolore suscipit. Necessitatibus eum quaerat. Repudiandae suscipit quo necessitatibus. Voluptatibus ullam nulla temporibus nobis. Atque eaque sed totam est assumenda. Porro modi soluta consequuntur veritatis excepturi minus delectus reprehenderit est. Eveniet labore ut quas minima aliquid quibusdam. Vitae possimus fuga praesentium eveniet debitis exercitationem deleniti.
Heavy metals influence microbial pathogenicity in two ways: they can be toxic to microbes by disrupting cellular functions and inducing oxidative stress, and they can be exploited by pathogens to enhance survival, resist treatment, and evade immunity. Understanding metal–microbe interactions supports better antimicrobial and public health strategies.
Alias iure reprehenderit aut accusantium. Molestiae dolore suscipit. Necessitatibus eum quaerat. Repudiandae suscipit quo necessitatibus. Voluptatibus ullam nulla temporibus nobis. Atque eaque sed totam est assumenda. Porro modi soluta consequuntur veritatis excepturi minus delectus reprehenderit est. Eveniet labore ut quas minima aliquid quibusdam. Vitae possimus fuga praesentium eveniet debitis exercitationem deleniti.
Alias iure reprehenderit aut accusantium. Molestiae dolore suscipit. Necessitatibus eum quaerat. Repudiandae suscipit quo necessitatibus. Voluptatibus ullam nulla temporibus nobis. Atque eaque sed totam est assumenda. Porro modi soluta consequuntur veritatis excepturi minus delectus reprehenderit est. Eveniet labore ut quas minima aliquid quibusdam. Vitae possimus fuga praesentium eveniet debitis exercitationem deleniti.
2025-05-20 13:24:39
Diabetes Type I majorpublished
Lipopolysaccharide (LPS), a potent endotoxin present in the outer membrane of Gram-negative bacteria that causes chronic immune responses associated with inflammation.
Short-chain fatty acids are microbially derived metabolites that regulate epithelial integrity, immune signaling, and microbial ecology. Their production patterns and mechanistic roles provide essential functional markers within microbiome signatures and support the interpretation of MBTIs, MMAs, and systems-level microbial shifts across clinical conditions.
Lipopolysaccharide (LPS), a potent endotoxin present in the outer membrane of Gram-negative bacteria that causes chronic immune responses associated with inflammation.
Short-chain fatty acids are microbially derived metabolites that regulate epithelial integrity, immune signaling, and microbial ecology. Their production patterns and mechanistic roles provide essential functional markers within microbiome signatures and support the interpretation of MBTIs, MMAs, and systems-level microbial shifts across clinical conditions.
Cadmium (Cd) is a highly toxic heavy metal commonly found in industrial, agricultural, and environmental settings. Exposure to cadmium can occur through contaminated water, food, soil, and air, and it has been linked to a variety of health issues, including kidney damage, osteoporosis, and cancer. In agriculture, cadmium is often present in phosphate fertilizers and can accumulate in plants, entering the food chain. Its toxicity to living organisms makes cadmium a subject of regulatory concern worldwide, particularly in industrial waste disposal and environmental monitoring.
Calprotectin is a neutrophil-derived protein complex measured in stool to detect intestinal inflammation. It helps distinguish IBD from functional bowel disorders and reflects mucosal immune activity that can reshape microbiome composition through antimicrobial metal sequestration.
Hepcidin is a liver peptide hormone that controls systemic iron by binding ferroportin and limiting iron export. Inflammation and microbial signals can increase hepcidin, promoting iron restriction and anemia of inflammation. Hepcidin is clinically useful for microbiome-informed evaluation of iron disorders.
Short-chain fatty acids are microbially derived metabolites that regulate epithelial integrity, immune signaling, and microbial ecology. Their production patterns and mechanistic roles provide essential functional markers within microbiome signatures and support the interpretation of MBTIs, MMAs, and systems-level microbial shifts across clinical conditions.
Chelation is a biochemical and pharmacological process in which small-molecule chelating agents bind to metal ions with high affinity to sequester, redistribute, or remove metallic elements from biological systems.
Short-chain fatty acids are microbially derived metabolites that regulate epithelial integrity, immune signaling, and microbial ecology. Their production patterns and mechanistic roles provide essential functional markers within microbiome signatures and support the interpretation of MBTIs, MMAs, and systems-level microbial shifts across clinical conditions.
Lipopolysaccharide (LPS), a potent endotoxin present in the outer membrane of Gram-negative bacteria that causes chronic immune responses associated with inflammation.
Heavy metals influence microbial pathogenicity in two ways: they can be toxic to microbes by disrupting cellular functions and inducing oxidative stress, and they can be exploited by pathogens to enhance survival, resist treatment, and evade immunity. Understanding metal–microbe interactions supports better antimicrobial and public health strategies.
Xie J, Li W, Li X, Zhang X, Liu J, Liu Z, Jing S, Shao H.
Global, regional, and national epidemiology of type 1 diabetes in children from 1990 to 2021: trend and health inequality analyses based on the Global Burden of Disease Study 2021.Diabetology & Metabolic Syndrome. 2025
Read ReviewXie J, Li W, Li X, Zhang X, Liu J, Liu Z, Jing S, Shao H.
Global, regional, and national epidemiology of type 1 diabetes in children from 1990 to 2021: trend and health inequality analyses based on the Global Burden of Disease Study 2021.Diabetology & Metabolic Syndrome. 2025
Read ReviewXie J, Li W, Li X, Zhang X, Liu J, Liu Z, Jing S, Shao H.
Global, regional, and national epidemiology of type 1 diabetes in children from 1990 to 2021: trend and health inequality analyses based on the Global Burden of Disease Study 2021.Diabetology & Metabolic Syndrome. 2025
Read ReviewXie J, Li W, Li X, Zhang X, Liu J, Liu Z, Jing S, Shao H.
Global, regional, and national epidemiology of type 1 diabetes in children from 1990 to 2021: trend and health inequality analyses based on the Global Burden of Disease Study 2021.Diabetology & Metabolic Syndrome. 2025
Read ReviewXie J, Li W, Li X, Zhang X, Liu J, Liu Z, Jing S, Shao H.
Global, regional, and national epidemiology of type 1 diabetes in children from 1990 to 2021: trend and health inequality analyses based on the Global Burden of Disease Study 2021.Diabetology & Metabolic Syndrome. 2025
Read ReviewXie J, Li W, Li X, Zhang X, Liu J, Liu Z, Jing S, Shao H.
Global, regional, and national epidemiology of type 1 diabetes in children from 1990 to 2021: trend and health inequality analyses based on the Global Burden of Disease Study 2021.Diabetology & Metabolic Syndrome. 2025
Read ReviewXie J, Li W, Li X, Zhang X, Liu J, Liu Z, Jing S, Shao H.
Global, regional, and national epidemiology of type 1 diabetes in children from 1990 to 2021: trend and health inequality analyses based on the Global Burden of Disease Study 2021.Diabetology & Metabolic Syndrome. 2025
Read ReviewXie J, Li W, Li X, Zhang X, Liu J, Liu Z, Jing S, Shao H.
Global, regional, and national epidemiology of type 1 diabetes in children from 1990 to 2021: trend and health inequality analyses based on the Global Burden of Disease Study 2021.Diabetology & Metabolic Syndrome. 2025
Read ReviewXie J, Li W, Li X, Zhang X, Liu J, Liu Z, Jing S, Shao H.
Global, regional, and national epidemiology of type 1 diabetes in children from 1990 to 2021: trend and health inequality analyses based on the Global Burden of Disease Study 2021.Diabetology & Metabolic Syndrome. 2025
Read ReviewYuan X, Wang R, Han B, et al.
Functional and metabolic alterations of gut microbiota in children with new-onset type 1 diabetesNat Commun. 2022
Read ReviewWilliams CL, Long AE.
What has zinc transporter 8 autoimmunity taught us about type 1 diabetes?Diabetologia. 2019
Read ReviewYuan X, Wang R, Han B, et al.
Functional and metabolic alterations of gut microbiota in children with new-onset type 1 diabetesNat Commun. 2022
Read ReviewWilliams CL, Long AE.
What has zinc transporter 8 autoimmunity taught us about type 1 diabetes?Diabetologia. 2019
Read ReviewYuan X, Wang R, Han B, et al.
Functional and metabolic alterations of gut microbiota in children with new-onset type 1 diabetesNat Commun. 2022
Read ReviewYuan X, Wang R, Han B, et al.
Functional and metabolic alterations of gut microbiota in children with new-onset type 1 diabetesNat Commun. 2022
Read ReviewYuan X, Wang R, Han B, et al.
Functional and metabolic alterations of gut microbiota in children with new-onset type 1 diabetesNat Commun. 2022
Read ReviewYuan X, Wang R, Han B, et al.
Functional and metabolic alterations of gut microbiota in children with new-onset type 1 diabetesNat Commun. 2022
Read ReviewYuan X, Wang R, Han B, et al.
Functional and metabolic alterations of gut microbiota in children with new-onset type 1 diabetesNat Commun. 2022
Read ReviewYuan X, Wang R, Han B, et al.
Functional and metabolic alterations of gut microbiota in children with new-onset type 1 diabetesNat Commun. 2022
Read ReviewXie J, Li W, Li X, Zhang X, Liu J, Liu Z, Jing S, Shao H.
Global, regional, and national epidemiology of type 1 diabetes in children from 1990 to 2021: trend and health inequality analyses based on the Global Burden of Disease Study 2021.Diabetology & Metabolic Syndrome. 2025
Read ReviewXie J, Li W, Li X, Zhang X, Liu J, Liu Z, Jing S, Shao H.
Global, regional, and national epidemiology of type 1 diabetes in children from 1990 to 2021: trend and health inequality analyses based on the Global Burden of Disease Study 2021.Diabetology & Metabolic Syndrome. 2025
Read ReviewVreugdenhil M, Akkermans MD, van Swelm RPL, et al.
Serum hepcidin concentrations in relation to iron status in children with type 1 diabetesPediatr Hematol Oncol. 2021
Read ReviewYuan X, Wang R, Han B, et al.
Functional and metabolic alterations of gut microbiota in children with new-onset type 1 diabetesNat Commun. 2022
Read ReviewVreugdenhil M, Akkermans MD, van Swelm RPL, et al.
Serum hepcidin concentrations in relation to iron status in children with type 1 diabetesPediatr Hematol Oncol. 2021
Read ReviewVreugdenhil M, Akkermans MD, van Swelm RPL, et al.
Serum hepcidin concentrations in relation to iron status in children with type 1 diabetesPediatr Hematol Oncol. 2021
Read ReviewYuan X, Wang R, Han B, et al.
Functional and metabolic alterations of gut microbiota in children with new-onset type 1 diabetesNat Commun. 2022
Read ReviewXie J, Li W, Li X, Zhang X, Liu J, Liu Z, Jing S, Shao H.
Global, regional, and national epidemiology of type 1 diabetes in children from 1990 to 2021: trend and health inequality analyses based on the Global Burden of Disease Study 2021.Diabetology & Metabolic Syndrome. 2025
Read ReviewXie J, Li W, Li X, Zhang X, Liu J, Liu Z, Jing S, Shao H.
Global, regional, and national epidemiology of type 1 diabetes in children from 1990 to 2021: trend and health inequality analyses based on the Global Burden of Disease Study 2021.Diabetology & Metabolic Syndrome. 2025
Read ReviewYuan X, Wang R, Han B, et al.
Functional and metabolic alterations of gut microbiota in children with new-onset type 1 diabetesNat Commun. 2022
Read ReviewYuan X, Wang R, Han B, et al.
Functional and metabolic alterations of gut microbiota in children with new-onset type 1 diabetesNat Commun. 2022
Read ReviewYuan X, Wang R, Han B, et al.
Functional and metabolic alterations of gut microbiota in children with new-onset type 1 diabetesNat Commun. 2022
Read ReviewYuan X, Wang R, Han B, et al.
Functional and metabolic alterations of gut microbiota in children with new-onset type 1 diabetesNat Commun. 2022
Read ReviewYuan X, Wang R, Han B, et al.
Functional and metabolic alterations of gut microbiota in children with new-onset type 1 diabetesNat Commun. 2022
Read Review