Neurodegenerative Disease Research

One twin watches her body fail while her identical sister stays perfectly healthy. Scientists just discovered the difference lives in their gut. Two bacteria turning the brain against itself. Think about that. German researchers recruited 81 pairs of identical twins where only one twin had MS—stripping away genetic confusion to expose what really causes MS. They discovered over 50 bacterial differences between affected and unaffected twins, with Eisenbergiella tayi and Lachnoclostridium species standing out as potential MS triggers. Traditional MS Reality: ↳ 2.8 million people affected worldwide ↳ Cause labeled "multifactorial mystery" ↳ Immune suppressants manage symptoms ↳ Progressive disability often inevitable The Microbiome Discovery: ↳ Specific bacteria enriched in MS twins ↳ Transplanted gut microbes trigger disease in mice ↳ Female mice particularly susceptible ↳ Direct gut-brain-immune connection proven But here's what grabbed me: When researchers transplanted gut bacteria from MS twins into germ-free mice, the animals developed MS-like disease. Not from genetics. Not from environment. From microbes alone. The bacteria from healthy twins? Protected the mice. Even more striking: Eisenbergiella tayi, barely detectable in human samples, became dominant in sick mice. A minor player in our gut turning the brain against itself. What changes everything: ↳ MS risk potentially measurable through stool samples ↳ Targeted antibiotics or bacteriophages possible ↳ Precision probiotics to outcompete harmful strains ↳ Prevention before symptoms, not just management The Multiplication Effect: 1 microbiome test = early risk detection 10 targeted interventions = personalized prevention 100 research centers refining = MS becoming preventable At scale = autoimmune diseases decoded through gut bacteria For decades, families watched one twin deteriorate while the other stayed healthy, wondering why their identical biology diverged. Now we know: the difference might be microscopic residents in their intestines. We spent 150 years treating MS as an inevitable brain disease. Now it might be a treatable gut imbalance. Because when identical DNA produces different diseases based on gut bacteria, you realise: The code for MS isn't just written in our genes. It's growing in our gut. Follow me, Dr. Martha Boeckenfeld for innovations where microscopic discoveries transform human health. ♻️ Share if you believe the next medical revolution lives in our gut, not our pharmacy. Resource: Kleinewietfeld, M., et al. (2024). Specific gut bacteria from multiple sclerosis patients modulate human T cell function and exacerbate symptoms in a mouse model. Proceedings of the National Academy of Sciences, 121(48), e2419689122.

1 in 9 people over 65 in America live with Alzheimer’s. Bill Gates watched his father become one of them. In a recent essay, Gates opened up about the hardest part of that journey: “It was brutal watching my brilliant, loving father disappear before my eyes.” But this wasn’t just a personal story. It was a signal that something is finally changing in the fight against Alzheimer’s. Here’s what’s happening: ▶︎ 1. The diagnosis problem is getting solved. ↳ For decades, detecting Alzheimer’s meant a PET scan or spinal tap - tools most people never access. ↳ Now, the FDA has approved the first blood-based test for early detection. It’s simple, accurate, and can catch signs up to 20 years before symptoms show. ▶︎ 2. Early detection is finally useful. ↳ Until recently, the usual question was: Why get diagnosed early if there’s no treatment? ↳ But two new FDA-approved drugs - Leqembi and Kisunla - are changing that. They don’t reverse the disease, but they can slow it down if caught early enough. ▶︎ 3. This changes the innovation timeline. ↳ Blood tests don’t just help patients - they accelerate research. ↳ And faster diagnosis → faster clinical trials → more data → better drugs. So the flywheel is finally in motion. Bill Gates said that when his dad was diagnosed with Alzheimer’s, it felt like a death sentence. Today, he’s optimistic that the tide is turning - not just because of tech, but because of timing. We’re finally catching Alzheimer’s when it can still be slowed. And for healthtech founders, this shift signals something bigger. Chronic diseases like Alzheimer’s are finally becoming measurable, trackable, and actionable - decades before symptoms show. That opens new frontiers for diagnostics, real-world data platforms, clinical trial tech, and patient engagement tools. So If you’re building in healthtech, this is your moment: You’re no longer waiting for symptoms to build solutions - you’re designing for detection, prevention, and personalized intervention. And the healthtech companies that act on this shift early? They won’t just serve the system. They’ll reshape it. What chronic disease do you think is overdue for this kind of breakthrough? #entrepreneurship #startup #healthtech

FDA clears first blood test to help diagnose Alzheimer’s disease in the US: 🧠The FDA has cleared the first blood-based diagnostic to aid Alzheimer’s diagnosis in adults over 55 with cognitive symptoms, marking a major milestone for early detection 🧠 The test, developed by Fujirebio Diagnostics, measures the ratio of two proteins in blood plasma, pTau217 and β-amyloid 1-42, that correlate with amyloid plaque buildup in the brain 🧠 It’s not a stand-alone diagnostic, but when combined with other clinical information, it can help determine whether Alzheimer’s pathology is likely present 🧠 Compared to PET scans or spinal taps, the blood test is faster, cheaper, less invasive, and far more scalable in routine practice 🧠 Clinical validation showed 91.7% of those who tested positive had amyloid confirmed by PET or CSF tests, 97.3% of those with negative results were confirmed negative. 🧠 This clearance could improve access to new Alzheimer’s treatments like Leqembi (Eisai/Biogen) and Kisunla (Eli Lilly), which are most effective when started early but remain underprescribed 🧠 Biogen has partnered with Fujirebio and Eisai Co., Ltd. with C2N Diagnostics signaling pharma betting on blood tests to boost uptake of amyloid-targeting Alzheimer’s drugs #healthtech #pharma

I've analyzed hundreds of voice samples from patients who later developed Alzheimer's. The pattern is unmistakable. Subtle changes in speech timing, word finding, and vocal tremor show up long before memory complaints. Here's what shocked me most. The 3 early voice changes that predict cognitive decline: 1/ Increased pause time between words ↳ Longer hesitations when searching for words ↳ Your brain is working harder to access vocabulary ↳ Often subtle and dismissed as "normal aging" 2/ Loss of vocal melody (prosody) ↳ Speech becomes more monotone ↳ Less emotional expression in voice ↳ Sounds "flat" compared to baseline 3/ Subtle word-finding hesitations ↳ Not obvious memory lapses ↳ More "um" and "uh" fillers ↳ Circular descriptions instead of specific words The technology to detect this exists today. But most patients never get tested until cognitive symptoms are obvious. By then, we've missed years of potential intervention. The opportunity? Early detection when lifestyle changes, social engagement, and emerging treatments could have maximum impact. Voice analysis is significantly more accessible than brain imaging. Guess which one most people can access? Bottom line: The future of dementia screening isn't expensive brain imaging. It's a brief conversation with digital technology. ⁉️ Have you noticed changes in someone's speech patterns over the years? ♻️ Repost if you believe early detection saves lives 👉 Follow me (Reza Hosseini Ghomi, MD, MSE) for insights on digital health innovation

My PhD will focus on something we still only partially understand: the molecular mechanisms linking the oral microbiome, the gut, and neurodegeneration. For years, the scientific and clinical conversation has been centred on the gut–brain axis, often overlooking a critical upstream component. The oral microbiome has largely remained at the margins of this discussion, despite growing evidence that it plays a far more central role than previously assumed. This recent review brings this into sharper focus by showing that oral dysbiosis is not confined to the oral cavity but can actively contribute to systemic and neural processes. Several periodontal pathogens are able to disseminate beyond their local environment, influencing immune regulation and promoting inflammatory cascades that extend to the brain. What is particularly striking is that these mechanisms converge on pathways we already recognise as central to neurodegenerative and neuropsychiatric disorders, including microglial activation, cytokine release, and protein misfolding processes associated with Alzheimer’s and Parkinson’s disease. This shifts the perspective from isolated associations to a more integrated biological framework. The oral microbiome is not simply an additional variable, but part of a continuous system that interacts with the gut, the immune system, and neuroendocrine pathways such as the HPA axis. These interactions form a network in which microbial ecosystems across different body sites contribute to a shared inflammatory and metabolic landscape. What becomes increasingly difficult to justify is the way we continue to approach these domains separately. Oral health, gut health, and brain health are still often treated as distinct areas, both in research and in clinical practice. Yet the biology suggests otherwise. These systems are interconnected, and their interactions may be key to understanding not only disease progression but also potential points of intervention. This is precisely where my work is directed: moving beyond descriptive associations to identify the molecular signals that link these microbial ecosystems to neuroinflammatory processes. The goal is not simply to confirm that a connection exists, but to understand how it operates, and whether it can be meaningfully targeted. If these mechanisms are clarified, oral dysbiosis may no longer be seen as a secondary feature or a coincidental finding, but as a modifiable contributor to neurodegeneration. That shift has significant implications, both for how we conceptualise these conditions and for how we approach prevention and intervention. We are still at an early stage in connecting these layers, but one conclusion is becoming increasingly clear. Brain health cannot be fully understood without considering the broader microbial systems that influence it. #parkinsondisease #oralmicrobiome #gutmicrobiome #neurodegeneration https://lnkd.in/echFjvad

🚨 New preprint out! 🚨 “Translating the Transcriptome: A Connectomics Approach for Gene-Network Mapping and Clinical Application” 🔗 https://lnkd.in/edC4Twm2 🧵 A short thread: Genes shape brain networks—but do genes linked to the same disorder converge on shared circuits? Clemens Neudorfer presents Gene-Network Mapping: a framework combining spatial transcriptomics with functional connectomics to uncover the molecular architecture of brain networks. Using the Allen Human Brain Atlas + normative functional connectivity, we generated gene-network maps for >20,000 genes. These maps capture distributed connectivity patterns linked to each gene’s expression. Think of it as a “connectome fingerprint” for every gene. Aggregating across genes tied to the same disorder, we built disease-network maps. Example: Parkinsonism genes—though diverse in pathways—converged on the nigrostriatal system & extended basal ganglia-thalamocerebellar circuits. Dystonia genes converged on cerebellum & basal ganglia. Validation: ✅ Maps aligned with pharmacological MRI & PET data (neurotransmitter systems). ✅ Converged with networks from brain lesions causing the same symptoms (Lesion Network Mapping). Genetic & lesional causes of movement disorders mapped to the same circuits. Clinical translation: In cohorts of DBS patients (Parkinson’s, dystonia, OCD), symptom improvement correlated with how well stimulation engaged the gene-derived disease network. Better DBS outcomes = closer match to genetic networks. This suggests gene-network mapping could: • Bridge genetics & connectomics • Provide mechanistic insight into disease networks • Guide neuromodulation & precision medicine • Open doors for drug discovery & gene therapy targeting In short: We introduce a framework that links genes → networks → clinical interventions. A step toward network-informed, gene-guided brain therapeutics. 🙌 Huge congratulations to Clemens Neudorfer – this has been his oevre magnum for the last 3-4 years – and thanks to our fantastic team of collaborators across multiple centers worldwide.

Do you know this story, and why it might also hold the key to curing Parkinson’s? In World War II, engineers studied returning planes riddled with bullet holes. At first, they thought reinforcing the damaged areas would save more aircraft. But statistician Abraham Wald realized the opposite - the planes that made it back told us only about tolerated injuries. The missing data were the planes that didn’t return. Protection needed to go where the bullets weren’t. Post-mortem brain omics in Parkinson’s disease carry a similar trap. They reflect the neurons resilient enough to survive, not the ones already lost. If we only study the “bullet holes” left in the surviving cells, we miss the real vulnerabilities. That’s why context matters. To build the right hypotheses, we need orthogonal perspectives: genetics, living peripheral tissues, and longitudinal multi-omic samples during disease progression - data we increasingly have thanks to The Michael J. Fox Foundation for Parkinson's Research When we brought these perspectives together, one theme was unmistakable: deficient mitophagy. Faulty recycling of damaged mitochondria as the central problem in PD. At Vincere Biosciences we've engineered molecules to restore this process and we're preparing for human clinical trials. I can't wait to see these data-driven predictions translated into relief for millions of patients!

New Study Maps Shared and Unique Molecular Signatures Across Alzheimer’s, Parkinson’s, and Frontotemporal Dementia Here we performed the largest plasma proteomics study to date across three major neurodegenerative diseases: Alzheimer’s disease (AD), Parkinson’s disease (PD), and frontotemporal dementia (FTD). The study identifies both shared and disease-specific molecular signatures and is published in Nature Medicine (https://lnkd.in/gx_fvQqv). These findings reveal key biological pathways involved in each disease and offer new directions for biomarker and therapeutic development. In this comprehensive study, researchers from the Cruchaga Lab analyzed plasma samples from over 10,500 individuals, collected across 23 sites as part of the Global Neurodegeneration Proteomics Consortium (GNPC). Using the SomaScan v4.1 platform, the researchers identified 5,187 proteins significantly altered in AD, 3,748 in PD, and 2,380 in FTD. Notably, 996 proteins were shared across all three diseases, while many others showed distinct signatures. Our goal was to map the proteomic landscape across multiple neurodegenerative diseases in the same dataset. By studying these diseases side by side, we were able to identify both converging biological processes and unique disease pathways. Pathway analysis revealed that shared proteins were involved in inflammation, complement activation, and vesicle trafficking, which are mechanisms common to neurodegeneration. In contrast, AD-specific proteins were enriched in metabolic and immune-related pathways, PD-specific proteins were linked to neuronal signaling and vascular processes, and FTD-specific proteins mapped to extracellular matrix remodeling and Wnt signaling. We found that each disease has a unique proteomic fingerprint in plasma. These differences could be leveraged to improve diagnostic specificity and better understand disease mechanisms. We also developed machine learning–based biomarker panels for each disease, achieving strong prediction accuracy with disease-specific predictive models. Importantly, the study included rigorous site-level sensitivity analyses and orthogonal validation using external datasets, including UK Biobank and additional data from Knight-ADRC and Stanford-ADRC cohorts. All preprocessed plasma proteomic data from this study is publicly available at the GNPC website (www.neuroproteome.org). The code used for data analysis and figures generation is available on GitHub. Even these are already breakthrough findings, they only constitute the tip of the iceberg, as many more findings are expected, including, but not limited, to the identification of actionable disease subtypes, novel causal and druggable targets, or novel predictive models not only for disease risk but also for progression, onset and healthy aging. To read the full article, go to: https://lnkd.in/gx_fvQqv

Scientists have discovered two new subtypes of multiple sclerosis with the aid of artificial intelligence, paving the way for personalised treatments and better outcomes for patients. In research involving 600 patients, led by University College London (UCL) and Queen Square Analytics, researchers looked at blood levels of a special protein called serum neurofilament light chain (sNfL). The protein can help indicate levels of nerve cell damage and signal how active the disease is. The sNfL results and scans of the patients’ brains were interpreted by a machine learning model, called SuStaIn. The results, published in medical journal Brain, revealed two distinct types of MS: early sNfL and late sNfL. In the first subtype, patients had high levels of sNfL early on in the disease, with visible damage in a part of the brain called the corpus callosum. They also developed brain lesions quickly. This type appears to be more aggressive and active, scientists said. In the second subtype, patients showed brain shrinkage in areas like the limbic cortex and deep grey matter before sNfL levels went up. This type seems to be slower, with overt damage occurring later. Researchers say the breakthrough will enable doctors to more precisely understand which patients are at higher risk of different complications, paving the way for more personalised care. Source in comments.

A very important diagnostic tool has just received FDA approval. A blood test using a ratio of two protein biomarkers, pTau-217 and beta-amyloid 1-42, for #Alzheimersdisease (AD) is a significant landmark that could alter the course of this debilitating disease. This less invasive test (just a blood draw without lumbar puncture) is ~92% accurate to positively identify an AD diagnosis while 97% accurate to rule out an AD diagnosis. These are pretty good statistics and arguably even better (certainly faster / cheaper) than current diagnostic tools like cognitive screenings and PET imaging. The most exciting part of the pTau-217 biomarker is its ability to be identified prior to symptom onset. In some cases, an elevated pTau-217 reading can signal an increased risk for AD 20 years prior to cognitive decline and other symptoms. Additionally, pTau-217 does correlate with cognitive decline in AD patients which should aid future development of therapeutics. Like cancer, I believe that early diagnosis is crucial for better AD outcomes. Once symptoms are present it’s likely already too late for therapeutics to add significant value (just look at the current mAbs treatments). There’s only so much that can be done for a brain that’s atrophied and riddled with toxic proteins… However, we do know environmental and lifestyle changes (such as exercise, good sleep, and diet) can reduce disease factors. Combining these activities with therapeutic interventions should slow disease onset / progression which has the potential to reshape the global AD burden. The era of precision neuroscience is just beginning, and these #biomarkers within the diagnostic toolkit are evidence that the future of this disease can be viewed with more optimism. The next set of liquid biomarkers (neurofilament light chain, NfL) are not far behind either as they correlate to several neurodegenerative diseases (dementia, ALS, FTD, etc). I would like to congratulate Fujirebio for their important contribution to the field and to millions of patients worldwide! #sciencesunday https://lnkd.in/e4xJZQGA